Version 4.0 | Updated October 2025
Formatting revised December 2025
Access the Interactive Data Dashboards
The Iowa Nutrient Reduction Strategy (INRS) is a science- and technology-based approach to assess and reduce nutrients delivered to Iowa waterways and the Gulf of America (Gulf of Mexico). The Strategy outlines opportunities for reducing nutrients in surface water from both point sources, such as municipal wastewater treatment plants and industrial facilities, and nonpoint sources, including agricultural operations and urban areas, in a scientific, reasonable, and cost-effective manner. The Iowa Nutrient Reduction Strategy was developed in response to recommendations provided by the United States Environmental Protection Agency (EPA) in its March 16, 2011 memo, “Working in Partnership with States to Address Phosphorus and Nitrogen Pollution through Use of a Framework for State Nutrient Reduction.” Ongoing action for nutrient load reductions is further supported by the recent EPA recommendations, “Renewed Call to Action to Reduce Nutrient Pollution and Support for Incremental Actions to Protect Water Quality and Public Health,” released September 22, 2016, and “Accelerating Nutrient Pollution Reductions in the Nation’s Waters,” released April 5, 2022.
This page presents an analysis of changes for each indicator of the Iowa Nutrient Reduction Strategy Logic Model to facilitate reporting.
From 2014 to 2020, a comprehensive progress report was released annually by the Iowa Department of Agriculture and Land Stewardship, the Iowa Department of Natural Resources, and Iowa State University. The process of reporting nutrient reduction efforts transitioned in 2021 to a revised approach by publishing data and findings in a set of web-based dashboards.
This page presents screen reader-friendly versions of the text and tables in the web-based dashboards. Version 4.0 summarizes all data for the 2023 INRS tracking period.
Tracking Inputs for the Iowa Nutrient Reduction Strategy
Introduction to INRS Inputs
Tracking efforts of the Iowa Nutrient Reduction Strategy (INRS) – the amount of funding, outreach, practice implementation, and changes in water quality – are completed to summarize changes made to advance the INRS goal of reducing nitrogen and phosphorus loading by 45% from the 1980-96 baseline period. The dashboards serve as a comprehensive reporting tool to report ongoing efforts from multiple entities collectively working to advance the adoption of conservation practices to improve water quality. The INRS Logic Model provides a structure to evaluate the progression of changes in resources, practice adoption, and impacts of practice adoption over time. Materials for reporting on INRS efforts – funding, outreach, practice implementation, and changes in water quality – are collected annually, and dashboards are updated after data is collected, aggregated, and processed.
Each of the four indicators of the INRS logic model is described below:
- Inputs indicator summarizes staff, funding, agency resources, and NGO sector resources;
- Human indicator summarizes partner organizations, farmer knowledge and attitude, point source communities, and management knowledge and attitude;
- Land indicator summarizes land use changes, practice adoption, and point source implementation; and
- Water indicator summarizes annual statewide nutrient loads by year and modeled load reduction
Inputs are necessary to expand Iowa's capacity for encouraging and realizing changes in human behavior and for promoting and incentivizing conservation practice implementation to improve water quality. Targeting inputs toward specific INRS facets may be required to support the goals set forth by the INRS. Due to data availability, this dashboard aims to provide an overview of reported statewide funding and staff resources supporting or complementary to the INRS.
Estimates of investment encompass public and non-governmental organizations' (NGO) funding summarized through reports voluntarily submitted by Water Resources Coordinating Council (WRCC) and (historically) Watershed Planning Advisory Council (WPAC) member organizations, and other partner organizations. Most public programs described in this dashboard are considered base programs (described briefly below) and have generally existed for decades. In addition, these estimates include the farmer and landowner contribution to the implementation of cover crops, terraces, water and sediment control basins (WASCOBs), and grade stabilization structures based on landowner costs to install the practice(s). These estimates do not account for the investments made by private entities, farmers, or landowners for practices financed independently of public sector programs.
A growing number of private sector funds are available to facilitate conservation and best management practice adoption on private lands. Many of these efforts operate independently of the INRS and cannot be reliably quantified through existing reporting mechanisms. However, the lack of trackability does not diminish their importance.
Continued Research on Nutrient Reduction
Continuation of research in the physical and social sciences is necessary to better understand the processes driving nutrient losses in Iowa and how conservation measures can alleviate nutrient losses. The Iowa Nutrient Research Center (INRC) has continued to be a dedicated source of research funding for nutrients since its founding in 2013. The INRC fosters innovative research, led by Iowa researchers at Regents institutions, on land management, edge-of-field practices, nutrient management, or multi-objective research.
More information regarding projects funded at Regents Institutions through the INRC may be found on the INRC website.
INRC Projects relate to Nutrient Management, Land Use, Edge-of-Field Practices, and Multi-Objective. These project themes include:
- Nutrient Management: Agronomic activities related to the timing, source, rate, and placement of fertilizers based on crop and replacement needs depending on the cropping rotation.
- Land Use: How cropping, livestock management, and wildlife habitat intersect for a farm operation and environmental benefits.
- Edge-of-Field Practices: Best Management Practices designed with water quality benefits as a primary benefit.
- Multi-Objective: Research into Iowa's agroeconomic system and components that influence water quality.
INRS Priority Watersheds
Nine priority watersheds (hydrologic unit code 8 (HUC8) basins) across Iowa were identified by the Water Resources Coordinating Council in 2013 as areas in which to conduct outreach and focus targeted conservation and water quality efforts. Current demonstration project information for nonpoint source efforts is available on the Clean Water Iowa website.
| Priority Watershed Name | Watershed ID (as HUC-8 Watershed) | Watershed Location within Iowa |
|---|---|---|
| North Raccoon River | 07100006 | Located in west-central Iowa, the river originates near Marathon, Iowa before flowing into the Des Moines River in Des Moines. |
| Boone River | 07100005 | Located in north-central Iowa, the river originates near Hutchins and flows into the Des Moines River south of Webster City. |
| Middle Cedar River | 07080205 | Located in east-central Iowa, the watershed originates at the confluence of three rivers (the Cedar River, Shell Rock River, and the West Fork Cedar River) and is designated another watershed immediately south of Cedar Rapids. |
| Turkey River | 07060004 | Located in northeast Iowa, the river originates near Saratoga and flows into the Mississippi River east of Millville. |
| South Skunk River | 07080105 | Located in central Iowa, the river originates near Hamilton and flows into the Lower Skunk River Watershed north of Richland. |
| Lower Skunk River | 07080107 | Located in southeast Iowa, the Lower Skunk River watershed receives flow from the South Skunk River and North Skunk Rivers north of Richland and flows into the Mississippi River south of Burlington. |
| Floyd River | 10230002 | Located in northwest Iowa, the river originates near Sanborn and flows into the Missouri River in Sioux City. |
| West Nishnabotna River | 10240002 | Located in southeast Iowa, the river originates north of Manning before becoming a larger watershed north of Hamburg. |
| East Nishnabotna River | 10240003 | Located in southeast Iowa, the river originates east of Manning before becoming a larger watershed north of Hamburg. |
Data Sources for INRS Inputs
Funding and staffing levels have been voluntarily reported since 2015 by members of the Water Resources Coordinating Council (WRCC) and, historically, by the Watershed Planning Advisory Council (WPAC). Respondents provide information about the number of full-time employee equivalents, by job category, dedicated to implementation of the Iowa Nutrient Reduction Strategy. Information about funding sources is also submitted. A common template is used for reporting to standardize responses across organizations. Where data are unavailable, public records are utilized for public investments for appropriations and expenditures.
Information is collated for all submitted reports to summarize funding, staff, outreach efforts, practice implementation, and monitoring efforts, and reported efforts are reviewed to minimize duplication. For example, a grant disbursed by one organization and awarded to another may be reported by both organizations, but double-counting was minimized by obtaining specific information about different funding sources.
Reports submitted by partners may be downloaded as supplemental materials of the INRS web page. The 2023 report is available as an Excel (.xlsx) file.
INRS Funding by Partner Organizations from 2012 to 2023
Investments by the four primary investment categories - public cost-share programs, estimated farmer and landowner investment, non-governmental organizations (NGOs), and land rental as Conservation Reserve Program (CRP) payments - are summarized in the table below.
Partner funds became available for reporting in the current Iowa Nutrient Reduction Strategy methodology in 2016 for reporting purposes. Non-governmental organization investments occurred prior to this time, but data are not available. Estimated farmer and landowner investment includes implementation of cover crops, terraces, water and sediment control basins, ponds, grade stabilization structures, and sediment basins that utilized a public sector program.
| Year | Public Cost-Share Programs | Estimated Farmer and Landowner Investment | Non-Governmental Organizations | CRP - Rental Payments | Total |
|---|---|---|---|---|---|
2012 | 91,233,895 | 14,601,078 | N/A | 212,942,766 | 318,777,739 |
2013 | 107,516,595 | 16,986,070 | N/A | 216,365,107 | 340,867,772 |
2014 | 98,161,485 | 21,908,328 | N/A | 214,402,613 | 334,472,426 |
2015 | 121,613,279 | 22,334,899 | N/A | 221,360,787 | 365,308,965 |
2016 | 114,147,810 | 20,500,167 | 2,759,434 | 243,650,296 | 381,057,707 |
2017 | 136,948,822 | 23,573,742 | 3,146,103 | 318,308,819 | 481,977,485 |
2018 | 161,959,229 | 36,074,673 | 3,659,943 | 360,771,362 | 562,465,206 |
2019 | 162,502,195 | 25,583,711 | 3,279,533 | 387,472,169 | 578,837,608 |
2020 | 157,599,332 | 39,004,545 | 3,557,452 | 387,472,174 | 587,633,503 |
2021 | 201,819,299 | 44,116,890 | 2,971,140 | 382,490,928 | 631,398,257 |
2022 | 200,956,779 | 40,229,901 | 2,342,915 | 382,381,806 | 625,911,402 |
| 2023 | 201,956,779 | 28,564,317 | 2,544,702 | 403,663,000 | 636,738,798 |
Total Investment 2012-2023 | 1,752,415,499 | 333,478,320 | 24,271,223 | 3,731,281,827 | 5,841,446,868 |
State and Federal Funding in Support of INRS by Program
Program funding is reported as state appropriations by fiscal year, with the exception of Clean Water State Revolving Funds, which are reported as loans originating per state fiscal year. Farm Service Agency (FSA) expenditures are obtained from the CRP Enrollment and Rental Payments by State, 1986-2023 report. Natural Resources Conservation Service (NRCS) expenditures come from annual At-A-Glance reports by federal fiscal year. Detailed funding information can be found in Appendix A (available at the end of this document).
Full-Time Employees (FTEs) Reported for Iowa Nutrient Reduction Strategy Inputs
The table below summarizes FTEs by category, as reported by partners. Changes in tracking staff have been reported by several organizations since 2019 and are known to impact FTEs reported, both as total FTEs and within the reporting categories "On-the-ground implementation Staff" and "Infrastructure Staff."
| Year | Infrastructure Staff | On-the-ground implementation Staff | Other Staff | Research Staff | Total FTE |
|---|---|---|---|---|---|
| 2016 | 144.01 | 102.11 | 17.25 | 17.25 | 280.62 |
| 2017 | 184.15 | 442.6 | 22.6 | 17.9 | 667.25 |
| 2018 | 189.05 | 406.6 | 27.8 | 21.2 | 644.65 |
| 2019 | 179.19 | 466.31 | 55.39 | 20.31 | 721.2 |
| 2020 | 140.64 | 557.71 | 55.7 | 35.49 | 789.54 |
| 2021 | 143.64 | 575.61 | 57.3 | 49.47 | 826.02 |
| 2022 | 140.89 | 550.61 | 58.3 | 49.22 | 799.02 |
| 2023 | 140.64 | 562.11 | 64.9 | 73.5 | 841.15 |
Changes in Funding
State conservation programs have evolved from 2012 to 2023, with funding for longstanding conservation programs independent of the Iowa Nutrient Reduction Strategy (INRS) continuing to receive increased funding. The Water Quality Initiative was first established in 2014 to directly support the INRS. Additional funding became available in 2018 with the establishment of the Water Quality Infrastructure Fund, funded by Senate File 512.
Changes in federal conservation program expenditures have largely increased from the beginning of the INRS. These programs provide financial support for implementation of nonpoint source conservation practices or, through the Conservation Reserve Program (CRP), for reservation of sensitive land. Expenditures through CRP in Iowa have increased, driven by an average rental rate per acre increase from $132 to $238 from 2012 to 2023. CRP enrollment has also prioritized continuous sign-up acres that are often sited to buffer runoff from adjacent cropped land. Conservation practice implementation programs administered by the Natural Resources Conservation Service are funded through the Farm Bill. Program offerings and funding for each program have evolved over the past decade.
Conventional programs have provided strong funding support for projects in Iowa; Iowa entities have also been competitive and demonstrated innovative conservation delivery concepts to receive grant funding through the Regional Conservation Partnership Program (RCPP).
Tracking the Human Dimension
Overview of the Human Indicator
The Human indicator summarizes knowledge, attitudes, and behavior related to water quality and nutrient reduction. Changes in management and conservation practices reflect the outreach, training, and educational events aimed at increasing knowledge among communities, farmers, landowners, the public, and conservation professionals. The outreach impacts have been assessed using farmer surveys to gauge farmers’ knowledge, attitudes and awareness related to water quality and nutrient reduction.
Outreach activities regarding water quality and management practices are summarized in the following panels of this dashboard. These efforts primarily capture outreach regarding nonpoint sources and the extensive network that supports educational opportunities across the state.
While point source activities directly engage fewer people, outreach amongst publicly owned treatment works (POTWs) continues through education for plant operators by organizations such as the Iowa Water Environment Association and direct contact with permitting agencies. Individual contacts amongst DNR, municipalities, and consultants who assist with plant operations and ensure regulatory compliance standards are not tracked; however, the development of phase one and phase two assessments for major POTWs as required by the INRS requires significant time and dedicated funding to ensure community and commercial needs are economically met. More importantly, urban and rural partnerships continue to be explored across the state through the creation of Nutrient Reduction Exchanges (NREs) by pilot cities in consultation with the DNR. Nonpoint conservation practice benefits are assessed by the Nutrient Tracking Tool, validated, and then registered via the Regulatory In-Lieu Fee and Bank Information Tracking System (RIBITS) database to foster nutrient trading within a watershed.
Changes in Public Education and Outreach
INRS partners remain engaged in outreach, with 731 events reported for the 2023 reporting period that reached an estimated 35,085 attendees*. These events ranged from general public programs such as fairs and educational program visits to schools to educational opportunities for professionals such as workshops and conferences. Program delivery modes have evolved over the past several years with the widespread adoption of virtual programming. The extent of virtual program development by INRS partners varies and includes webinars for general audiences to virtual field days that facilitate virtual attendance of programming conducted in the field.
The geographic distribution of events continues to be evaluated with county-level data summarized for the number of events and attendance. For example, counties with an event center will likely host larger programs that draw attendees from multiple counties or statewide. In contrast, rural counties may host more programs focused on local issues for farmers and landowner audiences. The total number and attendance of partner-reported events are summarized by county and event type in the top right panel.
These events, which provide information to make informed decisions about conservation practices and educate attendees about water quality issues, were self-reported by INRS partner organizations, and include five general categories:
- Conferences – Multi-session events to facilitate knowledge-sharing, networking, and partnering.
- Community Outreach – Includes fairs, tours, and other community events.
- Field days – Often serve to educate farmers, landowners, and agribusiness representatives through direct demonstration.
- Workshops – Entail training in a particular skill or topic area related to nutrients and water quality.
- Youth – Focuses on spreading understanding about natural resources and watershed issues through K-12 educational programming.
- Supplemental – A training that included content related to water quality, but water quality was not the primary focus of the event.
*Because nutrient management and water quality were not the primary focus of events or activities classified as "Supplemental", supplemental events are excluded from the statewide total reported above.
| Year | Community Outreach - Attendance | Community Outreach - No. Events | Conference - Attendance | Conference - No. Events | Field Day - Attendance | Field Day - No. Events | Supplemental - Attendance | Supplemental - No. Events | Workshop - Attendance | Workshop - No. Events | Youth - Attendance | Youth - No. Events | Total - Attendance | Total - No. Events |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2016 | 9,702 | 61 | 1,757 | 11 | 9,523 | 114 | 9,218 | 226 | 2,864 | 133 | 6,152 | 68 | 39,216 | 613 |
| 2017 | 21,331 | 161 | 4,763 | 18 | 9,849 | 145 | 9,212 | 277 | 3,031 | 120 | 18,551 | 125 | 66,737 | 846 |
| 2018 | 9,323 | 202 | 3,704 | 20 | 4,861 | 138 | 8,864 | 372 | 2,125 | 82 | 28,710 | 195 | 57,587 | 1,009 |
| 2019 | 13,286 | 161 | 2,155 | 16 | 7,798 | 158 | 22,589 | 1,019 | 2,111 | 69 | 28,205 | 195 | 76,144 | 1,618 |
| 2020 | 7,344 | 130 | 1,383 | 17 | 6,733 | 140 | 23,412 | 1,539 | 2,594 | 75 | 27,036 | 208 | 68,502 | 2,109 |
| 2021 | 6,507 | 84 | 2,283 | 12 | 7,064 | 94 | 14,430 | 610 | 2,146 | 69 | 21,181 | 323 | 53,611 | 1,192 |
| 2022 | 9,063 | 305 | 2,429 | 13 | 7,192 | 128 | 27,881 | 2,743 | 4,225 | 155 | 22,811 | 237 | 73,601 | 3,581 |
| 2023 | 6,323 | 270 | 2,577 | 15 | 7,325 | 117 | 22,356 | 1,798 | 3,882 | 172 | 14,978 | 157 | 57,441 | 2,529 |
A summary of programs by county can be found in Appendix B (available at the end of this document) or in the tracking period data summary (.csv on an external site).
The Nutrient Reduction Strategy Farmer Survey
Completed over five years, the NRS Farmer Survey was designed to assess farmer knowledge, attitude, and behavior related to water quality and to gain insight into practices that are favorably received or barriers to BMP adoption. With surveys completed by respondents over multiple years, results from five of the six HUC6 watersheds in Iowa have been published and are summarized in this report. Surveys were completed within the larger HUC6 watersheds and priority HUC8 watersheds across the state.
Reports may be found in the INRS webpage supplemental documents or through the Iowa State University Extension Outreach Store (search for Iowa Farmers and the Iowa Nutrient Reduction Strategy).
Each watershed was surveyed in the years summarized in the table below. Data summarized in the tables below reflect the respondents' answerin the first year of the survey.
| INRS Farmer Survey Basin (by HUC-6 Watershed) | HUC6 ID | Years Surveyed | INRS Priority Watershed (HUC-8) within the Basin | HUC8 ID |
|---|---|---|---|---|
| Des Moines | 071000 | 2017 and 2018 | North Raccoon | 07100006 |
| Des Moines | 071000 | 2017 and 2018 | Boone | 07100005 |
| Iowa | 070802 | 2015 and 2019 | Middle Cedar | 07080205 |
| Upper Mississippi-Maquoketa-Plum | 070400 | 2016 and 2017 | Turkey | 07060004 |
| Upper Mississippi-Skunk-Wapsipinicon | 070801 | 2019 | South Skunk | 07080105 |
| Upper Mississippi-Skunk-Wapsipinicon | 070801 | 2019 | Lower Skunk | 07080107 |
| Missouri-Little Sioux | 102300 | 2015 and 2016 | Floyd | 10230002 |
| Missouri-Nishnabotna | 102400 | 2018 and 2019 | West Nishnabotna | 10240002 |
| Missouri-Nishnabotna | 102400 | 2018 and 2019 | East Nishnabotna | 10240003 |
Selected results from the Iowa Nutrient Reduction Strategy Farmer Survey are summarized below. The INRS Farmer Survey tracked farmers’ knowledge, attitudes, and behavior related to nutrient reduction beginning in 2015 with the final survey completed in 2019. Responses are aggregated in the tables below by topic area from the survey and by the basin in which the farmer operates.
| Question | Des Moines | Missouri-Little Sioux | Missouri-Nishnabotna | Upper Mississippi-Maquoketa-Plum | Upper Mississippi-Skunk-Wapsipinicon |
|---|---|---|---|---|---|
| I am already doing all that I can to reduce nutrient loss from my farm into waterways | 40.6 | 49.6 | 45.4 | 48.7 | 43.6 |
| I don’t know how well my farm operation is doing in terms of keeping nutrients out of waterways | 21.3 | 20.1 | 21.6 | 18.1 | 20.1 |
| The nutrient management practices I use are sufficient to prevent loss of nutrients into waterways | 58.9 | 61.4 | 57.1 | 65.7 | 58.9 |
| Question | Des Moines | Missouri-Little Sioux | Missouri-Nishnabotna | Upper Mississippi-Maquoketa-Plum | Upper Mississippi-Skunk-Wapsipinicon |
|---|---|---|---|---|---|
| Helping to meet the Nutrient Reduction Strategy’s goals is a high priority for me | 49.1 | 53.5 | 52.8 | 54.3 | 50.9 |
| I am concerned about agriculture’s impacts on Iowa’s water quality | 81.8 | 84 | 82.9 | 80.7 | 81.8 |
| I am concerned about Iowa’s contribution to water quality problems (e.g., hypoxia) in the Gulf of Mexico | 57.2 | 59.9 | 58.7 | 62.2 | 61.1 |
| I would be willing to have someone help me evaluate how my farm operation is doing in terms of keeping nutrients out of waterways | 47.7 | 44.8 | 48.3 | 54.1 | 44.5 |
| I would like to improve conservation practices on the land I farm to help meet the Nutrient Reduction Strategy’s goals | 74.3 | 76.6 | 78.2 | 76.7 | 77.2 |
| Iowa farmers should do more to reduce nutrient and sediment run-off into waterways | 70.9 | 74.6 | 74.8 | 75.4 | 75.4 |
| Nutrients from Iowa farms contribute to water quality problems (e.g., hypoxia) in the Gulf of Mexico | 43.9 | 44.1 | 44.8 | 47.4 | 53.5 |
| Question | Des Moines | Missouri-Little Sioux | Missouri-Nishnabotna | Upper Mississippi-Maquoketa-Plum | Upper Mississippi-Skunk-Wapsipinicon |
|---|---|---|---|---|---|
| Farmers need help learning how to reduce nutrient loss more effectively | 65.3 | 64.4 | 64.9 | 64.6 | 64.2 |
| I don’t know how to further reduce nutrient losses from my farm | 13.6 | 19.1 | 18.2 | 18.9 | 16.9 |
| Many farmers are not aware that nutrients from agriculture can impact water quality | 22.1 | 21.2 | 19.8 | 22.2 | 17.6 |
| Many farmers don’t know how to further reduce nutrient losses from their farms | 33.7 | 36.1 | 38.2 | 37 | 34 |
| Question | Des Moines | Missouri-Little Sioux | Missouri-Nishnabotna | Upper Mississippi-Maquoketa-Plum | Upper Mississippi-Skunk-Wapsipinicon |
|---|---|---|---|---|---|
| I can’t afford to implement more conservation practices | 39.4 | 30.7 | 41.7 | 34.4 | 39.3 |
| Many conservation practices have negative impacts on yields | 29.3 | 19.9 | 18.1 | 21.3 | 22.8 |
| Many farmers don’t have the economic resources to adopt sufficient conservation practices | 48 | 36.1 | 47.9 | 41 | 52.6 |
| Pressure to make profit margins makes it difficult to afford conservation practices | 69.3 | 65.2 | 73.1 | 63.1 | 74.3 |
| There is not enough cost-share and other support available from government agencies | 51.9 | 52.2 | 58 | 47.6 | 52.6 |
The source(s) from which farmers who completed the Iowa Nutrient Reduction Strategy Farmer Survey learned about the strategy is summarized in the table below by the basin in which the farmer operates.
| Knowledge Source | Des Moines | Missouri-Little Sioux | Missouri-Nishnabotna | Upper Mississippi-Maquoketa-Plum | Upper Mississippi-Skunk-Wapsipinicon |
|---|---|---|---|---|---|
| The farm press | 85.8 | 79.7 | 77.1 | 81.9 | 80.7 |
| NRCS or SWCD | 64.4 | 63.5 | 63.8 | 67.8 | 65.3 |
| Iowa State University Extension and Outreach | 59.3 | 63.1 | 53.9 | 52.5 | 61.6 |
| Commodity or farm organization | 59.5 | 50.4 | 46.3 | 53 | 55.2 |
| The popular press | 55.8 | 49.1 | 46.7 | 52.6 | 50.1 |
| Government agency | 52.5 | 48.4 | 44.8 | 45 | 47 |
| Other farmers | 45.3 | 42.3 | 41.1 | 44.2 | 42.4 |
| Agricultural retailer | 31.5 | 31.4 | 26.8 | 26.4 | 27.6 |
| Crop advisor or agronomist | 21.8 | 21.8 | 14.6 | 17.2 | 17 |
| Seed company rep. | 19.1 | 19.1 | 13.7 | 17.3 | 14.1 |
The source(s) from which farmers who completed the Iowa Nutrient Reduction Strategy Farmer Survey learned about nutrient management is summarized in the table below by the basin in which the farmer operates.
| Knowledge Source | Des Moines | Missouri-Little Sioux | Missouri-Nishnabotna | Upper Mississippi-Maquoketa-Plum | Upper Mississippi-Skunk-Wapsipinicon |
|---|---|---|---|---|---|
| NRCS or County Soil and Water Conservation District | 23.7 | 32.9 | 27.4 | 32.3 | 25.8 |
| Iowa State University Extension (e.g., field days, workshops, publications, videos) | 19.8 | 25.8 | 19 | 18.1 | 18.5 |
| Landlord/farm management firm | 17.7 | 18.1 | 16.2 | 14.3 | 15.7 |
| Independent/private crop adviser/agronomist | 14.7 | 15.4 | 13.9 | 11.2 | 11.4 |
| Iowa Water Quality Initiative (WQI) | 9.8 | 12.6 | 11.7 | 13.4 | 10.9 |
| Custom operator/applicator | 8.6 | 7.1 | 8.6 | 8.3 | 8.7 |
| Iowa Soybean Association | 9.9 | 8.3 | 8 | 7.8 | 7.7 |
| Practical Farmers of Iowa | 4.8 | 3.1 | 6.5 | 5 | 7.1 |
| Iowa Learning Farms | 4.6 | 4.6 | 5.1 | 4.2 | 5 |
Tracking Nonpoint Source Nutrient Reduction Practices - Agricultural Conservation Practices
Agricultural Land Use in Iowa Over Time
Iowa’s total land area is 35.7 million acres. Based on data from the United States Department of Agriculture (USDA) Census of Agriculture, nearly 90% of Iowa’s total area is dedicated to agricultural uses, with total annual agricultural land use averaging over 31 million acres since 1982. Land area dedicated to field crops — corn, soybeans, and other annual and perennial crops — has remained relatively steady since the 1980s, averaging just below 27 million acres annually. Total acres enrolled in the USDA Conservation Reserve Program (CRP), which aims primarily to convert environmentally sensitive land from crops to perennial cover, has fluctuated between approximately 1.5 and two million acres in Iowa since the start of the program in 1986.
| Crop | 1978 | 1982 | 1987 | 1992 | 1993 | 1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Corn | 13,376,066 | 13,416,695 | 10,352,369 | 12,773,585 | 11,000,000 | 12,600,000 | 11,600,000 | 12,400,000 | 11,930,542 | 12,200,000 | 11,800,000 | 12,000,000 | 11,400,000 | 11,761,392 | 11,900,000 | 12,400,000 | 12,500,000 | 12,350,000 | 13,842,282 | 12,800,000 | 13,300,000 | 13,050,000 | 13,733,504 | 13,949,340 | 13,301,684 | 13,395,654 | 13,218,939 | 13,585,138 | 13,024,474 | 12,891,944 | 13,230,249 | 13,437,745 | 12,746,732 | 12,760,379 | 12,920,948 |
| Hay | 2,317,391 | 2,035,033 | 1,968,207 | 1,762,425 | N/A | N/A | N/A | N/A | 1,575,777 | N/A | N/A | N/A | N/A | 1,533,027 | N/A | N/A | 1,635,000 | 1,555,000 | 1,125,565 | 1,615,000 | 1,265,000 | 1,240,000 | 1,200,000 | 996,316 | 1,220,000 | 1,220,000 | 1,240,000 | 1,010,000 | 1,069,770 | 985,000 | 1,115,000 | 1,225,000 | 1,335,000 | 1,285,000 | 1,070,000 |
| Oats | 871,460 | 811,716 | 544,907 | 367,517 | 225,000 | 430,000 | 225,000 | 190,000 | 214,485 | 185,000 | 175,000 | 180,000 | 130,000 | 143,513 | 130,000 | 140,000 | 125,000 | 110,000 | 66,651 | 75,000 | 95,000 | 75,000 | 113,308 | 125,084 | 142,288 | 134,567 | 121,230 | 111,051 | 97,071 | 124,584 | 150,014 | 145,488 | 109,195 | 82,096 | 93,789 |
| Pasture | 5,764,822 | N/A | N/A | N/A | N/A | N/A | N/A | N/A | 4,256,172 | N/A | N/A | N/A | N/A | 3,639,397 | N/A | N/A | N/A | N/A | 3,144,321 | N/A | N/A | N/A | N/A | 2,478,116 | N/A | N/A | N/A | N/A | 2,360,349 | N/A | N/A | N/A | N/A | 2,245,926 | N/A |
| Soybeans | 7,475,989 | 8,044,305 | 7,903,395 | 8,243,067 | 8,300,000 | 8,770,000 | 9,260,000 | 9,450,000 | 10,258,681 | 10,350,000 | 10,750,000 | 10,680,000 | 10,920,000 | 10,418,621 | 10,550,000 | 10,150,000 | 10,000,000 | 10,100,000 | 8,612,810 | 9,670,000 | 9,530,000 | 9,730,000 | 9,220,549 | 9,202,421 | 9,176,296 | 9,716,200 | 9,720,864 | 9,390,645 | 9,841,356 | 9,877,682 | 9,064,273 | 9,284,555 | 10,048,021 | 10,020,539 | 9,869,220 |
| Wheat | 31,863 | 98,688 | 31,047 | N/A | 25,000 | 45,000 | 35,000 | 40,000 | 22,758 | 32,000 | 31,000 | 18,000 | 18,000 | 18,317 | 21,000 | 24,000 | 15,000 | 18,000 | 29,512 | 30,000 | 22,000 | 10,000 | 18,870 | 14,232 | 26,202 | 17,213 | 17,379 | 21,160 | 14,356 | 14,099 | 12,222 | 11,586 | 17,266 | 18,740 | 21,326 |
Records from the USDA Census of Agriculture, the USDA National Agriculture Statistics Service (NASS), and the USDA Farm Service Agency (FSA) were compiled to estimate historical and recent crop acreages from 1992 to the current reporting period. Acreages prior to 1992 were tabulated from digitized documents in the USDA Census of Agriculture Historical Archive. Crop acres from the Census of Agriculture and National Agriculture Statistics Service were used for annual values from 1993 to 2010. For both periods, harvested acres were used when available; planted acres were used as an alternative value when harvested acres were not available. NASS survey values were used for years when the Census did not occur. For annual crop acres since 2011, planted crop acres were aggregated from Farm Service Agency crop acreage reports and reflect the annual crop acreage values provided in NASS (in lieu of combined records from archival, NASS, and FSA databases).
Acres enrolled in the Conservation Reserve Program in Iowa were obtained from the FSA crop acreage reports and aggregated by year.
| Year | 1987 | 1988 | 1989 | 1990 | 1991 | 1992 | 1993 | 1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Acres | 1,239,129 | 1,472,786 | 1,760,059 | 1,951,061 | 1,987,847 | 2,087,172 | 2,203,794 | 2,203,794 | 2,199,360 | 2,176,232 | 1,757,681 | 1,503,604 | 1,484,118 | 1,599,464 | 1,802,931 | 1,865,730 | 1,882,650 | 1,894,501 | 1,917,480 | 1,958,883 | 1,970,486 | 1,809,633 | 1,703,941 | 1,637,130 | 1,662,373 | 1,644,429 | 1,525,012 | 1,457,518 | 1,484,376 | 1,688,975 | 1,786,530 | 1,800,061 | 1,745,860 | 1,705,188 | 1,662,521 | 1,693,946 | 1,688,112 |
Acres enrolled in the Conservation Reserve Program in Iowa were obtained from the FSA crop acreage reports and aggregated by year.
Iowa Cover Crops
During the baseline and benchmark time periods —1980-96 and 2006-10 — there were no or very few acres of cover crops in Iowa. The USDA Census of Agriculture reported that 1.28 million acres of cover crops were planted in Iowa in the fall of 2022, and the Survey of Agricultural Retailers estimated 3.7 million acres. Based on county-level data from the 2022 USDA Census of Agriculture, counties in the eastern region of the state tend to have higher rates of cover crop use than those in other parts of Iowa.
Of these statewide estimates, public conservation programs accounted for more than 1.1 million acres in 2022. It should be noted that these publicly funded cover crop acres – including state and federal cost share programs as well as the crop insurance discount program - represent only a portion of Iowa’s total cover crop acres; annual publicly funded acres do not represent a total statewide estimate of Iowa cover crops.
| Data Source | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| United States Department of Agriculture - Census of Agriculture | N/A | N/A | N/A | 379,614 | N/A | N/A | N/A | N/A | 973,112 | N/A | N/A | N/A | N/A | 1,282,608 |
| Survey of Agricultural Retailers | N/A | N/A | N/A | N/A | N/A | N/A | N/A | 1,597,614 | 2,015,688 | 2,179,304 | 3,107,063 | 2,768,754 | 3,769,373 | 3,841,525 |
| Portion Funded by Public Conservation Programs | 18,702 | 30,987 | 69,955 | 211,235 | 161,160 | 275,965 | 324,097 | 381,352 | 465,713 | 359,628 | 617,681 | 709,318 | 818,952 | 806,053 |
Cover crop acres are reported by the crop year with which they are associated (i.e., cover crop acres reported as "2023" were planted in 2022, benefitting the 2023 cash crop).
A summary of cover crop distribution in Iowa, summarized in Appendix C, was created using the USDA Census of Agriculture county-level acres planted in the fall of 2022. County values were assigned proportionally to Iowa HUC8 watersheds based on the percentage of county land area that intersects each watershed.
The types of cover crop species planted from 2017-2023 are summarized in the table below. Annual distribution of cover crop species was determined using data from the Iowa Nutrient Research and Education Council Survey of Agricultural Retailers.
| Year | Rye Cover Crop | Oat Cover Crop | Mix of Cover Crop Species | Other Cover Crop |
|---|---|---|---|---|
| 2017 | 69.4% | 9.1% | N/A | 21.5% |
| 2018 | 82.8% | 9.8% | N/A | 7.4% |
| 2019 | 81.3% | 2.8% | 11.2% | 4.8% |
| 2020 | 90.9% | 1.3% | 6.7% | 1.1% |
| 2021 | 80.8% | 5.5% | 12.3% | 1.5% |
| 2022 | 81.8% | 4.4% | 8.5% | 5.3% |
| 2023 | 86.6% | 6.1% | 5.5% | 1.7% |
The use of cover crop mixes was not included in the INREC Ag Retailer Survey in 2017 and 2018.
Data Sources - Iowa Cover Crops
There are currently three data sources utilized for tracking the rate of cover crop adoption in Iowa. First, the Survey of Agricultural Retailers, conducted by the Iowa Nutrient Research and Education Council, has estimated annual statewide cover crop acres since 2017 (capturing the cover crops planted in the fall of the prior year). Second, the USDA Census of Agriculture, which is conducted every five years, provides county-level cover crop acres for fall 2012, 2017, and 2022, allowing for aggregated statewide totals for those years (corresponding to the 2013, 2018, and 2023 crop years). Third, state and federal conservation programs (whereby government cost-share is given to farmers and landowners) provide spatially explicit records of publicly funded cover crop acres. All state programs recorded by the Iowa Department of Agriculture and Land Stewardship were included in this analysis of cost-share acres, as well as acres under the federal Environmental Quality Incentive Program and Conservation Stewardship Program.
Iowa Tillage Practices
In the last few decades, the use of no-till and conservation tillage in Iowa has increased dramatically. Conservation tillage represents a range of reduced tillage practices that leave at least 30% of crop residue on the soil surface following harvest and planting. No-till further minimizes soil disturbance by leaving most of the crop residue on the surface.
During the INRS baseline period from 1980-1996, no-till was used on an average of two million acres. In 2012, the United States Department of Agriculture (USDA) Census of Agriculture estimated 6.9 million acres of no-till. Since 2012, no-till acres have increased to a peak of 8-10 million acres, as estimated by the Iowa Nutrient Research and Education Council (INREC) Survey of Agricultural Retailers and the Census of Agriculture. No-till practices account for a higher portion of row crop acres in the rolling landscapes of western Iowa, for example, the Loess Hills region and some southern and northeastern watersheds.
Conservation tillage was practiced on 5.2 million acres during the baseline period, on average, and on an estimated 8.8 million acres in 2012. Since then, conservation tillage has generally increased, with estimates from the Survey of Agricultural Retailers and Census of Agriculture data suggesting use of conservation tillage on anywhere from 5 to 11 million acres annually.
The increased use of no-till and conservation tillage in row crop operations since the 1980s is paired with a decrease in the use of conventional tillage. Conventional tillage was used on an estimated 12 million acres during the baseline period, and this practice has been used on fewer acres since that period, although there are annual fluctuations.
| Practice Name And Data Source | 1980-1996 Average Annual | 2006-2010 Average Annual | 2012 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 |
|---|---|---|---|---|---|---|---|---|---|---|
| No-Till (INRS - Derived from Conservation Technology Information Center data) | 1,968,882 | 6,154,727 | N/A | N/A | N/A | N/A | N/A | N/A | N/A | N/A |
| Conservation Tillage (INRS - Derived from Conservation Technology Information Center data) | 5,190,170 | 6,064,720 | N/A | N/A | N/A | N/A | N/A | N/A | N/A | N/A |
| Conventional Tillage (INRS - Derived from Conservation Technology Information Center data) | 12,042,585 | 8,288,043 | N/A | N/A | N/A | N/A | N/A | N/A | N/A | N/A |
| No-Till (Census of Agriculture) | N/A | N/A | 6,950,836 | 8,196,199 | N/A | N/A | N/A | N/A | 8,452,461 | N/A |
| Conservation Tillage (Census of Agriculture) | N/A | N/A | 8,760,348 | 10,132,599 | N/A | N/A | N/A | N/A | 9,289,863 | N/A |
| Conventional Tillage (Census of Agriculture) | N/A | N/A | 7,882,556 | 5,018,129 | N/A | N/A | N/A | N/A | 4,941,144 | N/A |
| No-Till (Survey of Agricultural Retailers) | N/A | N/A | N/A | 7,707,695 | 6,972,434 | 8,153,502 | 8,589,242 | 9,461,121 | 10,165,201 | 9,081,676 |
| Conservation Tillage (Survey of Agricultural Retailers) | N/A | N/A | N/A | 11,611,286 | 10,247,229 | 9,475,381 | 4,935,493 | 5,253,814 | 6,551,661 | 5,150,980 |
| Conventional Tillage (Survey of Agricultural Retailers) | N/A | N/A | N/A | 3,676,146 | 5,749,278 | 5,294,807 | 9,822,998 | 8,259,545 | 6,016,376 | 8,422,482 |
A summary of tillage practice distribution in Iowa, summarized in Appendix C, was created using the USDA Census of Agriculture county-level acres planted in the fall of 2022. County values were assigned proportionally to Iowa HUC8 watersheds based on the percentage of county land area that intersects each watershed.
Data Sources - Iowa Tillage Practices
Tillage acres were estimated using three data sources. First, the 1980-96 baseline period (displayed here as 1996) and the 2006-10 benchmark period (displayed here as 2010) are derived from the Crop Management Residue Survey, conducted by the Conservation Technology Information Center for Iowa from 1982 to 2011. Methods for using these findings to determine average annual acreages are described in the Iowa Nutrient Reduction Strategy Nonpoint Source Science Assessment and the corresponding Iowa Nutrient Reduction Strategy baseline study, both of which can be found at the Iowa Nutrient Reduction Strategy website.
Statewide acreages for the 2012, 2017, and 2022 crop years were estimated using the USDA Census of Agriculture, which provides county-level data for no-till, conservation tillage, and conventional tillage practice implementation.
Annual statewide acreages of tillage practices in corn and soybean fields are estimated by the INREC Survey of Agricultural Retailers for the 2017 to 2023 crop years.
Nutrient Management in Iowa - Nitrogen Rates and Phosphorus Application
During the 1980-96 baseline period, corn-soybean rotations received an estimated average of 149 pounds of commercial and manure nitrogen; continuous corn rotations received 199 pounds per acre. This figure was estimated using a similar methodology for the 2006-10 benchmark period at 151 pounds per acre for corn-soybean rotations and 201 pounds for continuous corn. These estimates were derived from the state fertilizer sales data, which is publicly available from the Iowa Department of Agriculture and Land Stewardship (IDALS), and the USDA Census of Agriculture’s reported animal units in Iowa.
The Iowa Nutrient Research and Education Council designed a Survey of Agricultural Retailers to estimate the extent of in-field practice use, including commercial fertilizer application practices, and has been completing the survey since 2017. The annual survey has found that in corn-soybean rotations, corn acres received, on average, between 170 and 183 pounds per acre during the 2017-23 period. On average, continuous corn rotations received between 186 and 209 pounds per acre during that time.
| Category (Pounds of Nitrogen Per Acre) | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 |
|---|---|---|---|---|---|---|---|
| <100 | 0.0% | 0.0% | 1.3% | 0.0% | 0.0% | 0.0% | 6.0% |
| 100-125 | 0.0% | 0.3% | 0.0% | 0.0% | 0.0% | 0.0% | 5.0% |
| 126-150 | 1.5% | 2.3% | 3.6% | 0.0% | 5.7% | 4.1% | 5.0% |
| 151-175 | 8.9% | 8.6% | 5.7% | 4.5% | 7.8% | 17.8% | 10.0% |
| 176-200 | 54.2% | 38.7% | 48.5% | 32.5% | 47.1% | 50.1% | 41.0% |
| 201-225 | 18.7% | 33.2% | 29.2% | 31.6% | 33.8% | 19.2% | 21.0% |
| 226-250 | 15.3% | 11.2% | 11.0% | 27.6% | 5.6% | 7.5% | 11.0% |
| >250 | 1.4% | 5.6% | 0.8% | 3.8% | 0.0% | 1.3% | 1.0% |
| Category (Pounds of Nitrogen Per Acre) | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 |
|---|---|---|---|---|---|---|---|
| <100 | 0.1% | 0.2% | 0.5% | 0.1% | 0.2% | 0.6% | 2.0% |
| 100-125 | 1.9% | 1.5% | 0.4% | 0.8% | 2.3% | 2.6% | 2.0% |
| 126-150 | 22.3% | 19.0% | 10.8% | 8.6% | 20.7% | 15.0% | 21.0% |
| 151-175 | 36.8% | 29.2% | 32.9% | 26.8% | 32.3% | 35.6% | 30.0% |
| 176-200 | 31.8% | 37.1% | 39.7% | 37.7% | 33.1% | 36.7% | 36.0% |
| 201-225 | 5.2% | 10.1% | 11.9% | 17.2% | 9.5% | 7.8% | 5.0% |
| 226-250 | 0.8% | 2.8% | 3.5% | 5.5% | 1.5% | 1.7% | 3.0% |
| >250 | 1.2% | 0.1% | 0.3% | 3.2% | 0.4% | 0.0% | 1.0% |
These annual nitrogen fertilizer rates represent statewide averages; however, nitrogen application rates to corn vary across agricultural fields and, in some cases, vary by acre within a field. The percent of total acres that received various levels of commercial nitrogen rates varies by crop rotation. In 2023, for example, 36 percent of corn-soybean acres received 176-200 pounds of commercial nitrogen on their most recent corn year, and 30 percent received 151-175 pounds. Some fields lay at the ends of this distribution, with 25 percent of acres receiving 150 pounds of nitrogen per acre or less and 9 percent receiving 201 pounds per acre or more. Commercial nitrogen application rates trended higher for continuous corn rotations, with 41 percent of acres receiving 176-200 pounds of nitrogen per acre, 33 percent receiving at least 201 pounds per acre and 26 percent receiving 175 pounds per acre or less.
These estimates of annual nitrogen applications from 2017-23 represent an increase in acres in row crop and fertilizer use per acre since the 1980-96 baseline period. While the 2017-23 estimates of commercial fertilizer rates were obtained via a different data collection process than for the baseline and benchmark time periods, complementary evidence from recent fertilizer sales data shows that commercial fertilizer application rates for corn-soybean operations have increased gradually since before 1990. Increases in Iowa’s corn acres since that time have not increased at the same rate as the increase in commercial nitrogen fertilizer sales (disproportionate ratio of fertilizer sales to corn acres in the state), supporting the finding that average commercial nitrogen application rates (in pounds per acre) have increased over time as crop production has increased.
Research into nitrogen application rates lies at the forefront of the Iowa Nitrogen Initiative, a new program started in 2022 that incorporates soil, weather, and management data through on-farm trials throughout the state to develop the probability-based decision system N-FACT. The initiative will encourage fertilizer application decisions to be made based on more site-specific conditions to give farmers, agronomists, and landowners more confidence in determining the optimum rate at which to apply nitrogen.
Phosphorus fertilizer application methods that inject or incorporate it into the soil, compared with broadcasting across the soil surface, reduce potential nutrient losses from the field. The Survey of Agricultural Retailers estimated that 14.4 million acres received phosphorus fertilizer was incorporated, injected, or knifed into the soil for the 2017 crop year, a figure which decreased to 9.6 million acres for the 2023 crop year. These estimates account mostly for commercial fertilizer. For the 2023 crop year, approximately 82% of fields (~18.6 million acres) utilized soil testing for phosphorus, which can guide fertilizer application decisions.
| Phosphorus Management Type | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 |
|---|---|---|---|---|---|---|---|
| Commercial P Incorporated with Planter | 2,523,799 | 862,841 | 270,492 | 639,271 | 144,756 | 16,781 | 361,439 |
| Commercial P Incorporated in Knifed Bands | 656,919 | 627,900 | 619,632 | 692,078 | 625,440 | 250,599 | 915,394 |
| Commercial P Broadcast & Incorporated within 1 week | 10,807,030 | 16,143,905 | 15,847,446 | 9,440,934 | 9,916,964 | 8,611,185 | 7,110,864 |
| Liquid P (commercial/manure) Injected | 416,049 | 865,364 | 2,048,850 | 1,825,232 | 1,155,754 | 1,535,858 | 1,258,882 |
| Other P Application Type | 8,591,331 | 4,468,931 | 4,137,269 | 10,750,218 | 11,130,161 | 12,167,814 | 13,008,560 |
Data Sources - Nitrogen Rates and Phosphorus Application
Commercial nitrogen application rates were obtained from the Iowa Nutrient Research and Education Council's Survey of Agricultural Retailers, which has been conducted annually since 2017. The statewide average annual rates of commercial nitrogen fertilizer application were calculated using a stratified, weighted average approach, based on each field's size and the number of observations within each major land resource area in Iowa.
The distributions of varying application rates for continuous corn and corn-soybean rotations were determined using the survey's records for agricultural fields that received only commercial nitrogen fertilizer in 2023.
The total application of commercial nitrogen fertilizer, in tons per year, was estimated from Iowa’s fertilizer sales data and the USDA Census of Agriculture, using the methods described in the Iowa Nutrient Reduction Strategy Nonpoint Source Science Assessment.
To estimate the total plant-available nitrogen from manure applied to crops since the 1980-96 baseline period, researchers evaluated livestock animal unit data, USDA Census of Agriculture data, and published studies on manure nutrient availability. The methodology is described in the Iowa Nutrient Reduction Strategy Nonpoint Source Science Assessment.
Acres of various timing methods for commercial phosphorus application were obtained from the Iowa Nutrient Research and Education Council's Survey of Agricultural Retailers, which has been conducted annually since 2017. The statewide acreages of each phosphorus application method were calculated using a stratified, weighted approach, based on each field's size and the number of observations within each major land resource area in Iowa.
Nutrient Management in Iowa - Nitrogen Application Timing
Nitrogen (N) application timing also affects nitrogen loss, as described in the Iowa Nutrient Reduction Strategy (INRS) Science Assessment of Nonpoint Source Practices (revised in 2024). The Iowa Nutrient Research and Education Council's (INREC) Survey of Agricultural Retailers tracks and provides annual estimates of when nitrogen is most commonly applied. In 2023, commercial N fertilizer was applied via spring, split, and/or in-season application on approximately 8.36 million corn acres (~65% of Iowa's 12.9 million corn acres), with fall application occurring on approximately 6.48 million corn acres (~50% of corn acres). While the amount of fall-applied anhydrous fertilizer varies from year to year, shifting all fall-applied anhydrous fertilizer to spring application has the potential to reduce nitrate-N loads. For example, the INRS Science Assessment modeled the effectiveness of changes in fertilizer timing at reducing nitrate-N loads; this assessment found that shifting benchmark period (2006-10) anhydrous application from fall to spring could have resulted in a nitrate-N load reduction of 200 tons/year.
According to the INRS Nonpoint Source Science Assessment, fall-applied anhydrous with EPA-approved nitrification inhibitors (e.g., nitrapyrin) could reduce nitrate-N concentrations in tile drainage water by an estimated 5% when compared to fall anhydrous applications without a nitrification inhibitor. Based on the Science Assessment, researchers estimated that during the 2006-10 benchmark period, fall anhydrous was applied annually to 5.7 million acres of corn-soybean and continuous corn acres. Of these acres, nitrification inhibitor was applied to 3.5 million acres. According to the Survey of Agricultural Retailers, farmers’ nitrification inhibitor use has increased since the benchmark period. As a comparison to the 1980-96 baseline period, researchers associated with the INRS Nonpoint Source Science Assessment suggest, based on professional knowledge, that nitrification inhibitor was used on a negligible number of acres due to the recent development of the technology.
| Timing Category | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 |
|---|---|---|---|---|---|---|---|
| Fall anhydrous plus Nitrification Inhibitor | 3,731,524 | 2,318,399 | 2,722,201 | 3,337,435 | 4,759,935 | 4,126,956 | 2,987,981 |
| Fall Anhydrous without Nitrification Inhibitor | 1,405,251 | 817,409 | 487,420 | 643,484 | 772,300 | 2,248,541 | 3,354,280 |
| In-Season Only | 281,723 | 137,166 | 148,057 | 529,107 | 219,339 | 125,332 | 318,438 |
| Spring Pre-Plant | 6,487,329 | 7,652,738 | 6,950,024 | 6,443,443 | 5,165,386 | 4,294,012 | 4,668,056 |
| Spring Side-Dress Split, 40-60 | 1,307,086 | 2,004,263 | 2,300,009 | 1,907,536 | 1,691,866 | 1,836,196 | 1,343,119 |
Data - Nitrogen Application Timing
The data showing the timing of commercial N applications were obtained from the INREC Survey of Agricultural Retailers, which has been conducted annually since 2017. The statewide proportions of the data were calculated using a stratified, weighted approach, based on each field's size and the number of observations within each major land resource area in Iowa.
Bioreactors, Saturated Buffers, and Multi-Purpose Oxbows
Denitrifying bioreactors and saturated buffers are edge-of-field practices that are constructed by routing agricultural drainage water through a woodchip trench or vegetated buffer, respectively, to remove nitrate before the water enters an adjacent stream, ditch, or tile main. These practices are highly effective at reducing annual nitrate loads to streams. Estimated reduction in flow-weighted nitrate concentration is 24% for water treated by bioreactors and 45% for water treated by saturated buffers according to the Iowa Nutrient Reduction Strategy Science Assessment of Nonpoint Source Practices. The suitability of bioreactors and saturated buffers for a farm field is highly dependent upon the presence of tile drainage, topography, and soil types.
Oxbows are old stream channels that have been cut off. They fill in with sediment over time and can be restored by excavating the soil down to the original channel level. Outletting tile to an oxbow provides both wildlife habitat and water quality benefits; this practice is known as a "multi-purpose" oxbow. With an estimated 63% reduction in flow-weighted nitrate concentration according to the Iowa Nutrient Reduction Strategy Science Assessment of Nonpoint Source Practices, multi-purpose oxbows are effective at reducing nitrate delivery to streams.
| Acres Treated | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Bioreactor - Acres Treated by New Practices Annually | 50 | 50 | 50 | 150 | 50 | 400 | 300 | 200 | 250 | 100 | 350 | 650 | 600 | 600 | 300 | 900 | 1,200 | 400 |
| Saturated Buffer - Acres Treated by New Practices Annually | 0 | 0 | 0 | 0 | 50 | 0 | 0 | 150 | 50 | 200 | 450 | 400 | 850 | 400 | 200 | 1,450 | 1,850 | 500 |
| Multi-Purpose Oxbows - Acres Treated by New Practices Annually | 0 | 0 | 0 | 0 | 0 | 0 | 150 | 0 | 0 | 0 | 0 | 50 | 100 | 100 | 0 | 0 | 100 | 0 |
| Cumulative Acres Treated By Bioreactors, Saturated Buffers, and Multi-Purpose Oxbows in Iowa | 50 | 50 | 50 | 150 | 100 | 400 | 450 | 350 | 300 | 300 | 800 | 1,100 | 1,550 | 1,100 | 500 | 2,350 | 3,150 | 900 |
A summary of edge-of-field practice distribution in Iowa by HUC8 watershed is summarized in Appendix C.
Data Sources - Bioreactors, Saturated Buffers, and Multi-Purpose Oxbows
Acres protected by bioreactors, saturated buffers, and multi-purpose oxbows were summarized using state and federal conservation program data as well as practices known to be installed by conservation staff, which provide detailed, spatial records of publicly funded practices. All state programs recorded by the Iowa Department of Agriculture and Land Stewardship were included in this analysis of cost-share practices, as well as practices under the federal Environmental Quality Incentive Program and Conservation Stewardship Program. Practices installed without financial assistance were primarily designed by Iowa State University. All of these practices have undergone design standard revisions over the past decade, and it is currently estimated that 50 acres are protected by each practice.
Water Quality Wetlands
Wetlands that are designed for water quality improvement (water quality wetlands) are estimated to reduce flow-weighted nitrate concentration by 30%, according to the Iowa Nutrient Reduction Strategy Nonpoint Source Science Assessment. In designing these types of wetlands, agricultural drainage is routed through the wetland for nitrate removal. Currently, water quality (WQ) wetlands require higher financial investment and development time than many other best management practices but have a lifespan of multiple decades or more, and have a lower cost per pound of nitrogen removed. Most of Iowa’s WQ wetlands, to date, have been constructed under the Conservation Reserve Enhancement Program (CREP), but novel wetland siting standards have been implemented over the past decade to expand WQ wetlands from the traditional CREP breakpoint wetland design. Novel wetland positions on the landscape include full and fractional flow designs, both intentionally designed to protect agricultural drainage water similar to the classic breakpoint design used for CREP-designed wetlands. Programs and individuals other than the Iowa Department of Agriculture and Land Stewardship and Farm Service Agency have installed wetlands in Iowa that are similarly sited and constructed similar to WQ wetland design guidelines, but data currently are not available to assess the full extent of this non-CREP implementation.
Currently, Iowa has at least 135 WQ wetlands, which have all been constructed since the 1980-96 baseline period of the Iowa Nutrient Reduction Strategy. These wetlands have a cumulative drainage area of nearly 150,000 acres. Iowa experienced its highest rate of installations in 2020, with 14 new wetlands treating nearly 18,800 acres. Program implementation continues, with wetland design types developed in recent years expanding landscape positions on which WQ wetlands can be sited. WQ wetlands that were constructed from 2011-2023 (i.e., since the 2006-10 benchmark period of the Iowa Nutrient Reduction Strategy) protect more than 91,000 acres of agricultural land.
| Acres Treated Annually | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| New Acres Treated Annually | 2,488 | 2,949 | 3,485 | 14,271 | 7,985 | 6,954 | 12,370 | 8,074 | 6,965 | 13,519 | 9,384 | 4,294 | 3,270 | 4,603 | 7,817 | 5,597 | 1,831 | 18,771 | 8,955 | 5,133 | 1,082 |
| Cumulative Acres Treated | 2,488 | 5,437 | 8,922 | 23,193 | 31,178 | 38,131 | 50,502 | 58,576 | 65,540 | 79,059 | 88,443 | 92,737 | 96,007 | 100,610 | 108,427 | 114,024 | 115,855 | 134,626 | 143,581 | 148,714 | 149,796 |
A summary of water quality wetland distribution in Iowa by HUC8 watershed is summarized in Appendix C.
Data Sources - Water Quality Wetlands in Iowa
Acres protected by WQ wetlands were estimated using data from the Iowa Department of Agriculture and Land Stewardship. A majority of these wetlands were installed under the Conservation Reserve Enhancement Program, but some were funded through other programs and partnerships.
Structural Erosion Control Practices
The Iowa Nutrient Reduction Strategy Nonpoint Source Science Assessment identified a set of structural practices that capture sediment or reduce erosion within or at the edge of an agricultural field, leading to a reduction in soil-bound phosphorus loss. These practices include terraces, water and sediment control basins (WASCOBs), farm ponds, and grade stabilization structures. The Science Assessment estimates the effectiveness of these practices at reducing phosphorus loads to range from 77% to 85%.
Currently, it is assumed a significant portion of erosion control practices are constructed through the financial assistance of state and federal government cost-share programs and this report presents data from those sources. An estimated 280,000 acres are protected by terraces, WASCOBs, ponds, and grade stabilization structures that have been installed under cost-share programs since 2011.
An additional source of information on structural erosion control practices is the Iowa BMP Mapping Project, an ongoing effort that will estimate the extent of all erosion control installations, not just those funded by state or federal cost-share programs. Practices visible in aerial imagery and high-resolution topography data (statewide LiDAR data) during several time periods have been reviewed and practices have been mapped to track best management practice adoption over time. The project’s data collection is complete for three time periods: the 1980s, 2007-10, and 2016-17. Practices depicted by the Iowa BMP Mapping Project include both practices implemented with and without cost-share assistance; however, INRS reporting efforts only include practices that receive state or federal cost-share as self-funded practices are not reported annually.
| Acres Treated | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Terraces and Water & Sediment Control Basins - Acres Treated by New Practices Annually | 22,715 | 18,961 | 17,230 | 26,965 | 24,311 | 22,990 | 17,043 | 15,742 | 19,742 | 21,002 | 11,545 | 10,011 | 7,861 |
| Grade Stabilization and Ponds - Acres Treated by New Practices Annually | 2,100 | 1,696 | 2,252 | 1,279 | 1,458 | 8,347 | 1,423 | 1,370 | 1,350 | 7,106 | 4,387 | 7,210 | 4,059 |
| Total Acres Treated by Terraces, Water & Sediment Control Basins, Grade Stabilization, and Ponds | 24,815 | 20,657 | 19,482 | 28,244 | 25,769 | 31,337 | 18,466 | 17,112 | 21,092 | 28,108 | 15,931 | 17,221 | 11,919 |
| Cumulative Acres Treated by Terraces, Water & Sediment Control Basins, Grade Stabilization, and Ponds | 24,815 | 45,473 | 66,130 | 86,787 | 107,444 | 128,101 | 148,759 | 169,416 | 190,073 | 210,730 | 231,387 | 252,045 | 272,702 |
A summary of structural erosion practice distribution in Iowa by HUC8 watershed is summarized in Appendix C.
Data Sources - Structural Erosion Control Practices in Iowa
Structural erosion control practices were summarized using state and federal conservation program data, which provide detailed, spatial records of publicly funded acres. This report accounts for practices installed between 2011 and 2023. All state programs recorded by the Iowa Department of Agriculture and Land Stewardship were included in this analysis of cost-share practices and practices under the federal Environmental Quality Incentive Program and Conservation Stewardship Program. Structural erosion control practices reported include terraces, sediment basins, grade stabilization structures, ponds, and water and sediment control basins (NRCS practice codes 600, 350, 410, 378, and 638). The database for state programs provides an estimate of the acres protected by each erosion control practice. For terraces, water and sediment control basins, and grade stabilization structures, and within each HUC8 watershed, the state database’s mean acres protected per foot installed was applied to federally-funded cost-share practices to obtain an estimate of total acres protected. For ponds, there were no federal practices to extrapolate, so only state data were used.
Tracking Point Source Nutrient Reduction Effort - Wastewater Treatment and Industrial Facilities
Understanding Point Source Efforts Associated with the Iowa Nutrient Reduction Strategy
The Iowa Nutrient Reduction Strategy identifies 160 industrial (54 permits) and municipal wastewater treatment point source facilities (106 permits) that are required to evaluate the amounts of nutrients in their discharges in order to meet the goals of the strategy. Upon receiving a National Pollutant Discharge Elimination System (NPDES) permit under the Strategy, each facility works to develop a feasibility study, which outlines the resources required to achieve nutrient reduction goals. The permits also incorporate requirements for measuring nutrient concentrations in influent and effluent to determine current nutrient removals and provide an empirical basis for feasibility studies.
As of Fall 2023, municipal (October 2) and industrial (November 11) permits that have been amended with construction schedules to meet INRS goals are summarized in the table below.
| Activity for Permits | Municipal Facilities | Industrial Facilities |
|---|---|---|
| Count of Facilities | 49 | 16 |
| Earliest Completion Date | August 1, 2018 | January 1, 2018 |
| Latest Completion Date | July 1, 2028 | May 1, 2028 |
| Average Length of Construction Schedule | 4.4 Years | 3.4 Years |
Point source facilities listed in the strategy are required to monitor raw waste and final effluent for total nitrogen (TN) and total phosphorus (TP). However, some industries (e.g., power plants) that do not have a treatment plant are required to monitor only the final effluent as water is only to cool equipment. This extensive monitoring effort has generated one of the country’s most complete sets of point source nutrient data, and the extent of this data collection will continue to increase as the remaining permits are issued. This data has enabled the facilities and the Iowa Department of Natural Resources to determine current TN and TP loads associated with these point sources, even before additional nutrient reduction technologies are installed.
A facility uses the data collected during the two-year period after permit issuance to evaluate the feasibility and reasonableness of reducing the amounts of nutrients discharged into surface water. The Iowa Nutrient Reduction Strategy establishes a target of reducing TN and TP from point sources by 66% and 75%, respectively. A facility’s feasibility study must include an evaluation of operational changes that could be implemented to reduce the amounts of TN and TP discharged. If the implementation of operational changes alone cannot achieve the targets, the facility must evaluate new or additional treatment technologies that could achieve reductions in the nutrient amounts discharged. At the end of 2023, 152 feasibility studies had been submitted.
| Year | Permits Issued with Feasibility Studies Submitted | Permits Issued, Awaiting Feasibility Studies | Permits Remaining to be Issued |
|---|---|---|---|
| 2015 | 20 | 66 | 63 |
| 2016 | 51 | 54 | 46 |
| 2017 | 82 | 43 | 29 |
| 2018 | 95 | 37 | 20 |
| 2019 | 113 | 31 | 14 |
| 2020 | 127 | 24 | 7 |
| 2021 | 142 | 12 | 4 |
| 2022 | 148 | 5 | 5 |
| 2023 | 152 | 3 | 4 |
For INRS priority watersheds, two major POTWs are in the process of revising their NPDES permits. Note that changes in the number of facilities by year reflect changes in facility flow resulting in the change of the POTW classification, demonstrating that a source is not a nutrient source (e.g., industrial cooling purposes), or the combination of facilities (e.g., industrial waste treated by a municipal plant).
As these feasibility studies are reviewed and approved by the Iowa Department of Natural Resources, the schedules these contain for installing nutrient reduction technologies or optimizing existing treatment are added to the facilities’ NPDES permits by amendment. Once the construction or optimization outlined by the schedules is complete and treatment processes are optimized, facilities will submit twelve months of effluent TN and TP sampling results. Effluent limits based on those sampling results will then be added to facilities’ permits and become enforceable.
Point source facility permits with Nitrogen and/or Phosphorus limits as of the end of 2023 are summarized in the table below.
| Year | INRS Permits with Nitrogen and Phosphorus Limits | INRS Permits with Nitrogen Limits Only | INRS Permits with Phosphorus Limits Only |
|---|---|---|---|
| 2018 | 49 | 47 | 8 |
| 2019 | 61 | 58 | 12 |
| 2020 | 69 | 65 | 14 |
| 2021 | 75 | 71 | 16 |
| 2022 | 81 | 77 | 23 |
| 2023 | 85 | 83 | 27 |
Of the permitted point source facilities, the number achieving INRS N and P load reduction goals since 2013 are summarized in the table below.
| Year | Nitrogen - Facilities Meeting Percent Reduction Targets | Phosphorus - Facilities Meeting Percent Reduction Targets |
|---|---|---|
| 2013 | 9 | 2 |
| 2014 | 9 | 2 |
| 2015 | 14 | 6 |
| 2016 | 19 | 9 |
| 2017 | 24 | 11 |
| 2018 | 29 | 13 |
| 2019 | 32 | 18 |
| 2020 | 42 | 21 |
| 2021 | 47 | 23 |
| 2022 | 58 | 27 |
| 2023 | 54 | 30 |
Reported N and P loads for major public and industrial facilities since the INRS was adopted in 2013 are summarized in the table below. The point source N and P load goals are 7,556 and 1,303 tons, respectively.
| Year | Nitrogen Load (tons) | Phosphorus Load (tons) |
|---|---|---|
| 2013 | 14,054 | 2,623 |
| 2018 | 15,212 | 3,234 |
| 2019 | 15,076 | 3,267 |
| 2020 | 13,449 | 2,706 |
| 2021 | 14,007 | 2,931 |
| 2022 | 13,395 | 2,794 |
| 2023 | 13,427 | 2,665 |
Water
An Overview of the Water Measurement Indicator
The INRS Logic Model and reporting on efforts via the dashboards enable the documenting of key metrics that inform feedback to identify and focus inputs, activities, and outputs to advance the goals of the INRS. Reporting water quality changes includes monitored nutrient loads from rivers and modeled changes in nonpoint source nutrient export (point source tracking reported in the Land dashboard) based on agricultural management and BMPs adopted or installed.
This dashboard summarizes each tracked component of the Water indicator:
- Annual N and P export from the state of Iowa based on measured loads from rivers
- Modeled impacts of INRS-related BMP adoption and construction, agronomic practices, and land use on water quality
Monitoring results demonstrate that water quality varies from year to year as a result of the interactions between and influences of weather, land management practices, conservation practice adoption, and point source nutrient loading.
The scales, spatially and temporally, at which it is anticipated that water quality benefits may be detectable from monitoring data are reviewed in the next tab. A 2020 nitrogen-focused report prepared for the Iowa DNR, How Long Will it Take to Measure an Improvement in Iowa's Water Quality?, explored this topic in greater detail.
Changes from 1980-1996, the "baseline period", to the initial INRS assessment from 2006-2010, the "benchmark period", are summarized in the table below for nonpoint (NPS) and point (PS) loads. Nonpoint and point source changes between the two periods are also summarized in a short publication. Practice effects on nutrient loads are compared to the baseline period.
| Nutrient | Source | Baseline Load (tons) | Benchmark Load (tons) | Change from Baseline to Benchmark | Major Cause of Change |
|---|---|---|---|---|---|
| Nitrogen | NPS | 278,852* | 293,395 | 5.2% Increase | Land use change |
| Nitrogen | PS | 13,170 | 14,054 | 6.7% Increase | Flow increase |
| Nitrogen | Total | 292,022 | 307,449 | 5.3% Increase | N/A |
| Phosphorus | NPS | 21,436 | 16,800 | 21.6% Decrease | Reduced tillage and soil test P |
| Phosphorus | PS | 2,386 | 2,623 | 9.9% Increase | Flow increase |
| Phosphorus | Total | 23,822 | 19,423 | 18.5% Decrease | N/A |
*The methods used to derive the total nitrogen estimate of 292,022 tons indirectly reflected the point source contributions.
Measuring N and P Load at Scale and Time
Measuring changes in nutrient loads is challenging, as flow, the amount of runoff that leaves fields, is the strongest predictor of nutrient loss and varies annually. Detecting change at any scale over time is further complicated by the presence of "legacy nutrients" which have accumulated in soil and groundwater over time and are slowly lost to waterways, contributing to persistent water quality impairment even in areas with improved management practices. Understanding water quality improvement over time is important to evaluating progress towards INRS goals, and it is important to note that longer-term trends are better at illustrating progress than values associated with individual years.
Ongoing research continues to examine the spatial and temporal scales at which N and P load reductions can be quantified. The scales at which changes in water quality are likely detectable are summarized in the table below.
| Landscape Scale | Progress Measurable (years) | Description of Scale |
|---|---|---|
| Edge of a Farm Field | 0-10 | Loss can occur through tile flow, soil loss, and runoff |
| Farm Fields in a Sub-Catchment | 0-10 | Crop rotations, buffer use, and erosion control vary by watershed |
| Small Watershed (HUC12) | 10+ | HUC12s average 22,500 acres, or about 16 per county |
| Large Watershed (HUC8) | 10-20 | HUC8s average 961 acres, or cover the area of about 2.5 counties |
| State of Iowa within the Mississippi River Basin | 20+ | Iowa covers 4.5% of the Mississippi River Basin by area |
Water Quality Monitoring Infrastructure in Iowa
Statewide Monitoring
Water quality monitoring for statewide reporting in 2023 was conducted by the United States Geological Survey (USGS), the Iowa Department of Natural Resources (DNR), the Iowa Institute of Hydraulic Research (IIHR), and the Iowa Geological Survey (IGS). For years, the USGS has monitored a large number of sites, providing a long-term historical flow record. This allows for estimation of nutrient loads for prior years based on monitoring efforts by state agencies.
The Ambient Water Quality Monitoring Network was comprised of 59 monitoring sites to measure N and P in 2023. Of these 59 sites, statewide loads were estimated from monitoring sites near the boundaries of Iowa at 18 and 16 sites for N and P, respectively. Nutrient loads reported are the total for each river at the monitoring site, including loads that originated from outside of Iowa. These sites utilize DNR monthly sampling data, and USGS sensor data or IIHR-operated probes that offer “real-time” data as available, for each monitoring site to estimate load based on USGS flow data for each site.
More information about USGS, DNR, or IIHR-administered monitoring sites can be found on the following websites:
- USGS resources: See the USGS National Water Dashboard for nationwide gages
- DNR resources: DNR’s Water Monitoring summary (see Ambient Monitoring Programs)
- IIHR resources: IIHR’s Iowa Water Quality Information System provides real-time data
Note that real-time data from sensors is made publicly available upon collection, but records may not be certified until several months after data collection by the agency operating the gage or sensor.
Local Monitoring
Local monitoring efforts have been implemented by INRS reporting partners to monitor baseline conditions or to measure the effect of implementing a BMP(s). These efforts include DNR programs (other than the Ambient Stream Network) that monitor smaller rivers, streams, and lakes, and research programs conducted by Regents institutions, Iowa Soybean Association, and Agriculture’s Clean Water Alliance. The scope of monitoring includes general monitoring of surface waters, small watersheds (to assess the impact of a BMP at the field or small catchment scale), or tile drain outlet monitoring. Monitoring locations submitted by reporting partners are summarized at the HUC-12 watershed scale on the map in the adjacent tab.
Monitoring efforts submitted by reporting partners are summarized at the HUC-12 watershed scale in Appendix D.
Surface Water Monitoring Sites in Iowa
Statewide N and P loads are measured at monitoring sites on major rivers (18 N sites and 16 P sites) near the boundary of Iowa before flowing into the Mississippi or Missouri Rivers. These monitoring sites are able to cover the majority of the surface area of the state of Iowa. In addition, areas of river basins originating in Minnesota are included in the Iowa statewide load as loads are reported at the basin outlet.
The major rivers and contributing areas (upstream areas draining to each monitoring point), as well as monitoring efforts by organizations submitting monitoring efforts to INRS tracking, are summarized by HUC-12 watershed size in Appendix D.
Iowa Precipitation Summary (2023)
The INRS reports on nutrient loading and water yields at the state scale. However, the amount of water each region receives, which varies regionally and temporally each year, drives the amount of flow. In 2023, the average precipitation for Iowa was 26.82 inches, 8.73 inches less than the long-term average. The water yield during the INRS baseline period was approximately one-third of precipitation, while in 2023, the water yield was about 16% of precipitation.
More information about Iowa's climate - monthly or annual climate summaries, maps, current conditions, and drought reports - can be found on the Iowa Climate Bureau's webpage on the Iowa Department of Agriculture and Land Stewardship website.
Iowa Precipitation Summary (2024)
The INRS reports on nutrient loading and water yields at the state scale. However, the amount of water each region receives, which varies regionally and temporally each year, drives the amount of flow. In 2024, the 29th wettest year on record for Iowa, the state's average precipitation was 36.95 inches, which is 1.4 inches greater than the long-term average precipitation depth. The water yield during the INRS baseline period was approximately one-third of precipitation, while in 2024, the water yield was about one-fourth of precipitation.
More information about Iowa's climate - monthly or annual climate summaries, maps, current conditions, and drought reports - can be found on the Iowa Climate Bureau's webpage on the Iowa Department of Agriculture and Land Stewardship website.
Water Yield for Iowa
The net amount of water generated on the basis of stream flow versus precipitation regressions for watersheds across Iowa. Flow is summarized below and used to assess nutrient load relative to flow in subsequent sections.
| Year | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Flow (in/yr) | 4.22 | 10.17 | 4.75 | 5.03 | 8.78 | 6.23 | 5.6 | 14.35 | 18.38 | 12.72 | 20.8 | 11.1 | 3.51 | 10.25 | 10.87 | 12.96 | 15.76 | 10.46 | 17.85 | 18.74 | 10.01 | 5.46 | 5.48 | 4.3 | 8.99 |
| Five-Year Average Flow (in/yr) | N/A | N/A | N/A | N/A | 6.59 | 6.99 | 6.08 | 8.0 | 10.67 | 11.46 | 14.37 | 15.47 | 13.3 | 11.68 | 11.31 | 9.74 | 10.67 | 12.06 | 13.58 | 15.15 | 14.56 | 12.5 | 11.51 | 8.8 | 6.85 |
Measured Changes in N Export Based on River Monitoring (2023)
The nitrate-N load from Iowa for 2023 was about four times lower than the 24-year average load, while the 2023 flow-weighted nitrate-N load (FWNL) was about 60% of the 24-year average load.
The statewide water yield in 2023 was less than half of the average water yield for the 2000-2023 period. Periods of low statewide flow tend to correspond to low statewide N loads, as less N is lost through runoff or drainage from fields. However, N losses per water yield (FWNL) during wet periods following a drought year are typically larger as increased flow leads to leaching of unutilized nutrients from soils.
Measured Changes in N Export Based on River Monitoring (2024)
The nitrate-N load from Iowa for 2024 was about 1.2 times greater than the 25-year average load, while the 2024 flow-weighted nitrate-N load (FWNL) was the greatest recorded since 2000 (approximately 135% of the 25-year average load).
The statewide water yield in 2024 was about 1.25 inches less than the average water yield for the 2000-2024 period. While years with lower flows (drier years) often see low statewide N loads, N losses per water yield (FWNL) in a year following a drought year (e.g., 2024) are typically larger, as unutilized nutrients that have been able to accumulate in soils are "flushed out" with increased flow.
| Year | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Annual Nitrate-N Load (ton/yr) | 101,298 | 300,428 | 115,070 | 144,049 | 264,357 | 186,995 | 174,990 | 450,132 | 434,611 | 281,029 | 455,312 | 297,246 | 66,189 | 342,921 | 267,053 | 417,793 | 531,776 | 318,111 | 426,416 | 396,289 | 241,254 | 81,619 | 141,383 | 66,080 | 320,001 |
| 5-year Moving Average Nitrate-N Load (ton/yr) | N/A | N/A | N/A | N/A | 185,040 | 202,180 | 177,092 | 244,105 | 302,217 | 305,551 | 359,215 | 383,666 | 306,877 | 288,539 | 285,744 | 278,240 | 325,146 | 375,531 | 392,230 | 418,077 | 382,770 | 292,738 | 257,392 | 185,325 | 170,068 |
| Annual Nitrate-N Flow-Weighted Load (ton/in/yr) | 24,023 | 29,539 | 24,206 | 28,631 | 30,113 | 30,034 | 31,248 | 31,358 | 23,642 | 22,101 | 21,889 | 26,782 | 18,852 | 33,449 | 24,565 | 32,239 | 33,741 | 30,416 | 23,895 | 21,152 | 24,102 | 14,959 | 25,784 | 15,352 | 35,584 |
| 5-year Moving Average Nitrate-N Flow-Weighted Load (ton/in/yr) | N/A | N/A | N/A | N/A | 27,302 | 28,505 | 28,846 | 30,277 | 29,279 | 27,677 | 26,048 | 25,154 | 22,653 | 24,615 | 25,107 | 27,177 | 28,569 | 30,882 | 28,971 | 28,289 | 26,661 | 22,905 | 21,978 | 20,270 | 23,156 |
Annual data is driven primarily by flow within each monitoring year. Applying a five-year moving average assists in characterizing statewide loads and variability anticipated with changes in inter-annual precipitation. These trends are cyclical and are observed in the nearly twenty years of available data. Statewide N loads reflect agronomic practices and adoption of N management BMPs in addition to hydrologic trends.
Water Quality - Nitrogen Monitoring
Nutrient loading from Iowa is reported as the monitored load in rivers (modeled for each river based on collected monitoring data) and modeled impact of land use practices on nutrient load. Information on how nonpoint and point source loads were determined for the INRS baseline can be found in the reports titled:
- Assessment of the Estimated Non-Point Source Nitrogen and Phosphorus Loading from Agricultural Sources from Iowa During the 1980-96 Hypoxia Task Force Baseline Period; and
- Nitrogen and Phosphorus Load Estimates from Iowa Point Sources During the 1980-96 Hypoxia Task Force Baseline Period
These resources established the baseline from which the nutrient load reduction goals for nonpoint and point sources are established. Both N and P loads during the baseline and benchmark periods (INRS Science Assessment period of 2006-2010) are summarized in the reports above.
State agencies, universities, and the United States Geological Survey have expanded river monitoring over the past decades to improve understanding of flow and monitor nutrients. Monitoring infrastructure was not available to measure N loads during the INRS baseline period of 1980-1996, so nonpoint and point source loads were interpolated from wastewater and population data, land use, agronomic management, practice adoption, and precipitation during the time period. The infrastructure that has been available since at least 2000 now provides a means to quantify statewide nutrient losses. Nitrogen losses can be represented as concentrations, annual loads, and flow-normalized loads.
In 2017, the INRS science team evaluated and recommended the Linear Interpolation method be used to model N load for river monitoring data (see Schilling et al. 2017 and the NRS 2017 Supplemental report titled “Assessment of the Estimated Non-Point Source Nitrogen and Phosphorus Loading from Agricultural Sources from Iowa During the 1980-96 Hypoxia Task Force Baseline Period"). This method fills in data gaps between sampling events for each monitoring site by drawing a straight line and provides a robust measure of N load. Frequent sampling provides the highest quality data with a longer time between sampling periods increasing the potential uncertainty in the modeled load.
Precipitation is the primary driver of stream flow in Iowa's rivers, and flow from rivers is monitored by the USGS (see more about gaging locations in the previous panel). Annual average flow depths by watershed are calculated using streamflow and watershed area. Statewide flow is then calculated as an area-weighted average of the flow calculated for each watershed.
Measured Changes in P Export Based on River Monitoring
Total phosphorus (P) loads are strongly correlated with the amount of flow, and P losses associated with just a few large storm events can comprise the majority of a year's P load.
Corresponding to lower flows over many of the past several years, annual P loads and flow-weighted P loads (FWPL) have generally been lower than the target loads set by the INRS (i.e., 45% reduction in total P loads from those of the 1980-1996 baseline period).
However, a 5-year moving average is a better metric of patterns over time as it reduces the influence of year-to-year streamflow variation on P loads. For nearly every year since 2002 (the period where calculations begin), the 5-year moving average P load has been greater than the INRS P load goal, driven by P losses during years of average or above-average flow despite the lower losses from occasional periods of drought.
The FWPL is largely below the INRS baseline for the available historical record annually, and the 5-year moving average FWPL is continuously below the baseline period. This demonstrates the impact of high flow years compared to the 5-year moving average. However, no consistent trend in the annual or 5-year moving average FWPL is observed.
Annual P loads are calculated using the WRTDS-K model. Streamflow, season, measured P, and turbidity data from monitoring stations are used to calibrate the model. Values are updated each year as inclusion of additional data results in improved P load predictions. Annual flow-weighted P loads are calculated by dividing annual P loads (tons) by the amount of streamflow occurring that year (inches of flow/year). This reduces the influence of annual streamflow variation on nutrient loads when looking at trends over time.
| Year | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Annual Phosphorus Load (ton/yr) | 6,248 | 26,341 | 8,148 | 7,913 | 18,391 | 9,833 | 6,973 | 29,422 | 38,776 | 21,787 | 38,890 | 17,169 | 5,994 | 20,849 | 28,121 | 24,635 | 24,181 | 16,226 | 34,830 | 48,178 | 12,715 | 7,974 | 6,833 | 6,018 | 17,189 |
| 5-year Moving Average Phosphorus Load (ton/yr) | N/A | N/A | N/A | N/A | 13,408 | 14,125 | 10,252 | 14,506 | 20,679 | 21,358 | 27,170 | 29,209 | 24,523 | 20,938 | 22,204 | 19,353 | 20,756 | 22,802 | 25,599 | 29,610 | 27,226 | 23,985 | 22,106 | 16,344 | 10,146 |
| Annual Phosphorus Flow-Weighted Load (ton/in/yr) | 1,482 | 2,590 | 1,714 | 1,573 | 2,095 | 1,579 | 1,245 | 2,050 | 2,109 | 1,713 | 1,870 | 1,547 | 1,707 | 2,034 | 2,587 | 1,901 | 1,534 | 1,551 | 1,952 | 2,572 | 1,270 | 1,461 | 1,246 | 1,398 | 1,911 |
| 5-year Moving Average Phosphorus Flow-Weighted Load (ton/in/yr) | N/A | N/A | N/A | N/A | 1,891 | 1,910 | 1,641 | 1,708 | 1,816 | 1,739 | 1,797 | 1,858 | 1,789 | 1,774 | 1,949 | 1,955 | 1,953 | 1,921 | 1,905 | 1,902 | 1,776 | 1,761 | 1,700 | 1,590 | 1,457 |
Between the baseline period and the historical record for which statewide P loads have become available, there were significant changes in farm operations. Farm tillage practices rapidly transitioned in the 1980s to comply with soil conservation provisions established in the 1985 Farm Bill, the development of farm implement tools to manage higher residue systems, P application management in conjunction with soil testing, and crop protection practices. These phases of soil erosion conservation and P application management had significant impacts on statewide P losses during the INRS baseline period and before the release of the INRS in 2013.
Water Quality - P Monitoring
The river monitoring network for P is comparable to N, and infrastructure was described previously in the N section.
Iowa’s annual P loads are modeled as two distinct chemical forms, orthophosphate (OP) and particulate phosphorus (Part P). Part P is the P bound to particulate matter, such as sediment, while OP represents the dissolved form of P. Summing these two P sources, OP and Part P, produce Iowa’s overall P load.
While they are used for estimating N loads, linear interpolation methods are not appropriate for estimating P. P loads in rivers are strongly influenced by storms, and high flow events, although infrequent, can strongly impact the P load; hence, other estimation methods are needed.
Using data from monitoring stations, P loads are estimated for each of 16 rivers near the border of Iowa using a combination of two modeling techniques: 1) the Weighted Regression on Time, Discharge and Season-Kalman Filter (WRTDS-K; Hirsch et al., 2010; Zhang & Hirsch, 2019) framework developed by the United States Geological Survey and 2) turbidity-based surrogacy models. A unique relationship between streamflow, measured P, and turbidity is used for each monitoring station to estimate P loads for that river. Data are made available for the state of Iowa. Additional research is ongoing to improve estimates of P loads during high-flow events in several watersheds in the western half of the state.
The WRTDS-K models used for measuring P use streamflow, time of year, water quality trends, and observed P data to fill gaps between measured P concentrations. The surrogacy models use power regression to establish a relationship between turbidity, a measure of the water’s cloudiness, and Part P. These surrogacy models are more accurate than their WRTDS-K counterparts in estimating Part P and are used whenever on-site turbidity data are available.
More information about the WRTDS-K methodology may be found in the following references:
Hirsch, R. M., Moyer, D. L., & Archfield, S. A. (2010). Weighted regressions on time, discharge, and season (WRTDS), with an application to Chesapeake Bay river inputs. Journal of the American Water Resources Association, 46(5), 857-880. doi:10.1111/j.1752-1688.2010.00482.x
Zhang, Q., & Hirsch, R. M. (2019). River Water-Quality Concentration and Flux Estimation Can be Improved by Accounting for Serial Correlation Through an Autoregressive Model. Water Resources Research, 55(11), 9705-9723. doi:10.1029/2019WR025338
Changes in N from Nonpoint Sources
Modeled N load impacts of INRS practices for which reported practice adoption data is currently available compared to the baseline period. Negative values indicate a modeled N load reduction – practices are advancing statewide INRS N goals - and positive values indicate a modeled increase in N load for management or practice compared with the 1980-1996 INRS baseline period (292,022 tons N). The percent change for each practice is calculated independently of other practices and represents the benefits of the stand-alone practice without interaction with any other practice or management effect (values aren’t additive). The potential interaction of practices remains an active area to be assessed and will be integrated into reporting as methods become available.
| INRS Practice | Impact on N Load 2022 (tons) | Per. N Load Impact in 2022 (%) |
|---|---|---|
| Cover Crop | -15,355.90 | -5.3 |
| N Rate Continuous Corn | -1,430.40 | -0.5 |
| Water Quality Wetlands | -863.3 | -0.3 |
| Bioreactor, Saturated Buffer, or Multi-Purpose Oxbow | -46.9 | 0 |
| N Timing: Changes to Spring Pre-Plant, Sidedress, or In-Season | -4,256 | -1.5 |
| N Timing: Nitrification Inhibitor | -7,375.90 | -2.5 |
| N Rate Corn-Soybean | 38,930.20 | 13.3 |
Adoption of BMPs that can be broadly adopted across Iowa increased in number, and the acreage benefitted from these practices. Cover crop adoption increased to an estimated 3.7 million acres in 2022 (INREC Ag Retailer Survey) – up from 2.8 million acres in 2021 – and is estimated to reduce N losses from the baseline period by 5.3%, or more than 15,356 tons. A rye cover crop reduces N load by an estimated 28% per the INRS (majority of cover crops planted are cereal rye or include it in the mix), with cereal rye accounting for more than 85% of cover crops planted in each of the past five years per the INREC Survey.
Similarly, practices that can be implemented at the edge-of-field (bioreactors, saturated buffers, and multi-purpose oxbows) and water quality wetlands, have seen an increase in practice adoption in recent years. These practices benefitted at least 12,600 and 147,000 for EOF practices and wetlands, respectively. These practices reduced N loads by 46.8 and 863 tons for EOF practices and nitrate removal wetlands in 2022. The adoption of these practices has increased primarily due to more recent developments of these practices and increasing prioritization in the state to scale up installations.
The effect of in-field management and land use on modeled N load indicated an increase in statewide N load with changes in agronomic practices and land use. Agronomic management and land uses are cyclical and reflect market conditions and field access. The N application rate to corn in a corn-soybean rotation had the greatest estimated increase in statewide N load, with an increase of approximately 13.3% (38,900 tons) when compared to the estimated rate during the baseline period. These rates are stand-alone and compare rates from 2022 to the 1980-1996 baseline period. The adoption of other agronomic practices or BMPs (application timing, method, inhibitor use, etc.) that have been adopted at the same time N rates have increased are also depicted in the estimated N load.
For some nutrient reduction practices, insufficient data are available to complete a statewide assessment. The evaluation of other data sources for tracking these practices over time is ongoing.
Data Analysis - N Modelling of Nonpoint Sources
Consistent with modeling approaches as in the original INRS Science Assessment, load reduction estimates were calculated for a selection of INRS practices for which practice adoption data is available. The acreages and extent of these practices were determined using various data sources, including public conservation program databases, the Cropland Data Layer, the USDA Census of Agriculture, and the Iowa Nutrient Research Education Council Agricultural Retailer Survey. For more information on the approximation of BMP use in Iowa, refer to the "Tracking Nonpoint Source Nutrient Reduction Practices - Agricultural Conservation Practices" section (farther above). These assessments are on a per-practice basis and don’t factor in the additive or in-series effects of multiple or layered practices. Modeled load changes for the INRS are based on changes by Major Land Resource Area aggregated to the state level for individual practices.
Changes in P from Nonpoint Sources
Modeled P load impacts of INRS practices for which reported practice adoption data is currently available compared to the baseline period, except for terraces and basins that are compared to changes since 2010 (contingent on records availability). Negative values indicate a modeled P load reduction – practices are advancing statewide INRS P goals - and positive values indicate a modeled increase in P load for management or practice compared with the 1980-1996 INRS baseline period (23,822 tons P). The percent change for each practice is calculated independently of other practices and represents the benefits of the stand-alone practice without interaction with any other practice or management effect (values aren’t additive). The potential interaction of practices remains an active area to be assessed and will be integrated into reporting as methods become available.
| INRS Practice | Impact on P Load 2021 (tons) | Per. P Load Impact in 2021 (%) |
|---|---|---|
| No-Till | -4,230.70 | -17.8 |
| Cover Crop | -2,801.60 | -11.8 |
| Terrace | -113.6 | -0.5 |
| WASCOB, Grade Stabilization Structure, Pond | -78.1 | -0.3 |
| Conservation Tillage | -31.6 | -0.1 |
In contrast to N, nonpoint P losses in Iowa from fields are dominated by erosion of sediment and phosphorus bound to it. Adopting tillage practices that decrease soil disturbance or leave residue to protect soil is critical to reducing P loads. Tillage practices such as no-till and conservation tillage (leaving at least 30% residue) are estimated to reduce P loads by 90% and 33%, respectively, per the INRS. The adoption of these practices has grown to an estimated 8,467,057 and 6,550,844 acres, reflecting a reduction of 17.8% (4,230 tons) and 0.1% (31.6 tons) in statewide P load as of 2022, respectively.
Structural BMPs such as terraces and basins that can reduce or trap sediment offer similar benefits by preventing soil and, thereby, the attached phosphorus from leaving a field. Since 2010, practices that protect approximately 310,000 acres have been built using public financial assistance programs and are estimated to reduce P loads by 191 tons, or 0.8% of the baseline P load. The modeled benefits of practices are independent of other practices and the interaction of adopted BMPs, agronomic practices, and land use continue to be explored.
An analysis by Geosyntec consultants, Quantification of Phosphorus Loss due to Structural Agricultural BMP Implementation – Final Report, supported by the Iowa Nutrient Research Education Council, leveraged the Iowa BMP Mapping project to assess the benefits of practice adoption from the 1980s (the leading period of the INRS baseline) to 2016-2018 (the last data collection period of the BMP mapping project). This project assessed practice adoption in approximately 20% of HUC-12 watersheds across Iowa that were determined to be statistically representative of the Iowa Major Land Resource Areas for which nutrient losses were determined for the INRS. Using INRS practice efficiencies, these practices were estimated to reduce phosphorus losses from fields by 5.2% in the 1980s and increase to 9.5% by 2016-2018. Researchers continue to develop models to assess the benefits of structural BMPs at the state level and build upon this first effort to assess structural BMPs that provide year-over-year benefits in reducing phosphorus runoff from fields.
For some nutrient reduction practices, insufficient data are available to complete a statewide assessment. The evaluation of other data sources for tracking these practices over time is ongoing.
Data Analysis - P Modelling of Nonpoint Sources
The same sources for P modeling were used as N (see Data Analysis - N Modelling of Nonpoint Sources above).
Recommended citation: Iowa Department of Agriculture and Land Stewardship, Iowa Department of Natural Resources, and Iowa State University. (October 2025). Tracking the Iowa Nutrient Reduction Strategy. Version 4.0.
Appendix A
| Program | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | Program Total |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Ag Drainage Well Closure (ADW) - IDALS | N/A | $3,170,000 | N/A | N/A | $1,920,000 | $1,920,000 | $1,875,000 | $1,875,000 | $1,875,000 | $1,875,000 | N/A | N/A | $14,510,000 |
| Agricultural Conservation Easement Program (ACEP) - NRCS | $21,100,000 | $13,900,000 | $11,000,000 | $10,714,000 | $12,500,000 | $14,500,000 | $10,500,000 | $9,400,000 | $12,300,000 | $29,400,000 | $12,162,300 | $14,043,000 | $171,519,300 |
| Conservation Reserve Enhancement Program (CREP) - IDALS | $1,000,000 | $1,000,000 | $1,000,000 | $1,000,000 | $1,000,000 | $1,000,000 | $1,000,000 | $1,000,000 | $1,000,000 | $1,000,000 | $1,000,000 | $1,000,000 | $12,000,000 |
| Conservation Reserve Program (CRP) - FSA | $212,942,766 | $216,365,107 | $214,402,613 | $221,360,787 | $243,650,296 | $318,308,819 | $360,771,362 | $387,472,169 | $387,472,174 | $382,490,928 | $396,275,000 | $403,663,000 | $3,745,175,021 |
| Conservation Reserve Program (District Buffer Initiative) - IDALS | $1,000,000 | $1,000,000 | $1,000,000 | $1,000,000 | $1,000,000 | $1,000,000 | $900,000 | $900,000 | $900,000 | $900,000 | $900,000 | $900,000 | $11,400,000 |
| Conservation Stewardship Program (CSP) - NRCS | $6,800,000 | $3,800,000 | $4,500,000 | $11,600,000 | $6,300,000 | $5,500,000 | $28,600,000 | $16,300,000 | $17,400,000 | $19,700,000 | $16,500,000 | $22,200,000 | $159,200,000 |
| CWSRF - General Nonpoint Source Program (GNS) - DNR | $1,448,374 | $19,097,952 | $5,855,169 | $33,087,739 | $9,031,750 | $7,317,468 | $6,066,869 | $15,818,908 | $5,658,638 | $2,910,041 | $2,009,390 | $3,196,208 | $111,498,506 |
| CWSRF - Livestock Water Quality Facilities Program (LWQ) - DNR | $7,920,004 | $5,354,917 | $5,426,596 | $3,047,121 | $3,340,508 | $1,805,882 | $2,517,174 | $5,331,462 | $990,299 | $600,155 | $271,765 | $3,405,938 | $40,011,821 |
| CWSRF - Local Water Protection Program (LWPP) - DNR | $5,841,175 | $3,462,811 | $2,903,378 | $2,419,318 | $1,824,691 | $1,739,977 | $2,023,572 | $1,708,438 | $1,583,310 | $1,216,129 | $1,074,712 | $1,959,214 | $27,756,725 |
| CWSRF - Onsite Wastewater Assistance Program (OSWAP) - DNR | $1,697,550 | $839,618 | $1,034,395 | $898,030 | $935,237 | $868,812 | $1,212,829 | $915,480 | $1,089,180 | $923,127 | $727,270 | $1,130,132 | $12,271,660 |
| CWSRF - Sponsored Projects - DNR | N/A | N/A | N/A | $3,736,000 | $5,748,000 | $5,424,823 | $2,618,283 | $1,627,000 | $8,109,000 | $7,438,958 | $8,543,803 | $5,466,704 | $48,712,571 |
| DNR - Water Quality Monitoring - DNR | $2,955,000 | $2,955,000 | $2,955,000 | $2,955,000 | $2,955,000 | $2,955,000 | $2,955,000 | $2,955,000 | $2,955,000 | $2,955,000 | $2,955,000 | $2,955,000 | $35,460,000 |
| Environmental Quality Incentives Program (EQIP) - NRCS | $25,900,000 | $27,300,000 | $23,800,000 | $16,400,000 | $17,700,000 | $26,800,000 | $34,600,000 | $36,600,000 | $30,100,000 | $33,900,000 | $31,900,000 | $31,900,000 | $344,100,000 |
| Farm Management Demonstration Program - IDALS | $625,000 | $625,000 | $625,000 | $625,000 | $625,000 | $625,000 | $375,000 | $287,500 | $100,000 | N/A | N/A | N/A | $4,512,500 |
| GWP - IDALS Ag Drainage Well & Sinkhole - IDALS | $611,656 | $684,090 | $666,739 | $698,244 | $713,765 | $756,085 | $732,645 | $729,870 | $741,396 | $794,343 | $786,964 | $839,424 | $8,755,220 |
| In-Field Agricultural Practices Pilot Project - ISU | N/A | N/A | N/A | N/A | $1,230,000 | N/A | N/A | N/A | N/A | N/A | N/A | N/A | $1,230,000 |
| Iowa Financial Incentives Program - Publicly Owned Lakes (IFIP-POL) - IDALS | $315,000 | $332,500 | $332,500 | $337,500 | $337,500 | $337,500 | $391,750 | $391,750 | $391,750 | $391,750 | $409,250 | $365,550 | $4,334,300 |
| Iowa Financial Incentives Program (IFIP) - IDALS | $5,985,000 | $6,317,500 | $6,317,500 | $6,412,500 | $6,412,500 | $6,412,500 | $7,443,250 | $7,443,250 | $7,443,250 | $7,443,250 | $7,775,750 | $7,819,450 | $83,225,700 |
| Iowa Geological Survey - Water Resource Management - IGS | N/A | N/A | N/A | N/A | N/A | N/A | N/A | $495,000 | $495,000 | $495,000 | $495,000 | $495,000 | $2,475,000 |
| Iowa Nitrogen Initiative - IDALS | N/A | N/A | N/A | N/A | N/A | N/A | N/A | N/A | N/A | N/A | N/A | $1,000,000 | $1,000,000 |
| Iowa Nutrient Research Center - ISU | N/A | N/A | $1,500,000 | $1,325,000 | $1,625,000 | $1,400,000 | $2,269,811 | $1,976,653 | $2,015,121 | $2,135,195 | $2,076,691 | $2,245,638 | $18,569,109 |
| Lake Restoration - DNR | $5,109,000 | $6,000,000 | $8,600,000 | $9,600,000 | $9,600,000 | $9,600,000 | $9,600,000 | $9,600,000 | $9,600,000 | $8,600,000 | $9,600,000 | $9,600,000 | $105,109,000 |
| Leopold Center - ISU | $1,643,615 | $1,838,630 | $1,791,916 | $1,876,738 | $1,918,525 | $2,032,465 | N/A | N/A | N/A | N/A | N/A | N/A | $11,101,889 |
| Loess Hills Development and Conservation Fund - Alliance Account - IDALS | $118,750 | $131,250 | $150,000 | $159,375 | $150,000 | $150,000 | $40,000 | $40,000 | $40,000 | $40,000 | $40,000 | $40,000 | $1,099,375 |
| Loess Hills Development and Conservation Fund - Hungry Canyons Account - IDALS | $356,250 | $393,750 | $450,000 | $478,125 | $450,000 | $450,000 | $450,000 | $450,000 | $500,000 | $500,000 | $500,000 | $500,000 | $5,478,125 |
| NPDES - 106 Grant - Wastewater Program Management - DNR | $3,090,700 | $2,930,000 | $2,993,000 | $2,973,375 | $2,966,000 | $2,941,000 | $2,925,000 | $2,896,000 | $2,887,000 | $2,980,000 | $2,983,692 | $2,993,000 | $35,558,767 |
| Regional Conservation Partnership Program (RCPP) - NRCS | N/A | $406,785 | N/A | N/A | $1,597,000 | $4,340,000 | $5,021,100 | $4,552,300 | $2,829,981 | $2,212,878 | N/A | $10,520,287 | $29,267,753 |
| Regional Conservation Partnership Program (RCPP-EQIP) - NRCS | N/A | N/A | N/A | $261,000 | N/A | N/A | N/A | N/A | N/A | $2,212,878 | $1,367,900 | N/A | $3,841,778 |
| Resource Enhancement and Protection Program (REAP) - Soil and Water Enhancement Account - IDALS | $2,400,000 | $2,400,000 | $3,200,000 | $3,200,000 | $3,200,000 | $3,200,000 | $2,400,000 | $2,000,000 | $2,400,000 | $2,400,000 | $2,400,000 | $2,400,000 | $31,600,000 |
| Section 319 - Nonpoint Source Activities - DNR | $3,585,000 | $3,398,000 | $3,476,000 | $3,440,300 | $3,556,000 | $3,679,000 | $3,634,000 | $3,598,000 | $3,750,000 | $3,852,000 | $3,852,000 | $3,852,000 | $43,672,300 |
| Soil and Water Conservation Administration - IDALS | $2,000,000 | $2,550,000 | $2,550,000 | $2,550,000 | $2,700,000 | $2,800,000 | $3,800,000 | $3,800,000 | $3,800,000 | $3,800,000 | $3,800,000 | $3,800,000 | $37,950,000 |
| Wastewater and Drinking Water Treatment Financial Assistance Program - IFA | N/A | N/A | N/A | N/A | N/A | N/A | N/A | $782,000 | $1,600,000 | $4,928,000 | $5,052,000 | $5,200,000 | $17,562,000 |
| Water Quality Agriculture Infrastructure Program - IDALS | N/A | N/A | N/A | N/A | N/A | N/A | N/A | $1,955,000 | $4,000,000 | $15,000,000 | $15,000,000 | $15,000,000 | $50,955,000 |
| Water Quality Financing Program - IFA | N/A | N/A | N/A | N/A | N/A | N/A | N/A | $879,750 | $1,800,000 | $6,750,000 | $6,750,000 | $6,750,000 | $22,929,750 |
| Water Quality Initiative Fund - IDALS | N/A | N/A | $12,400,000 | $4,400,000 | $9,150,000 | $9,375,000 | $10,575,000 | $10,575,000 | $12,175,000 | $12,175,000 | $10,575,000 | $10,575,000 | $101,975,000 |
| Water Quality Planning - 604b - DNR | $193,000 | $183,000 | $192,000 | $191,000 | $183,000 | $181,000 | $219,000 | $217,000 | $217,000 | $217,000 | $217,000 | $414,000 | $2,624,000 |
| Water Quality Urban Infrastructure Program - IDALS | N/A | N/A | N/A | N/A | N/A | N/A | N/A | $293,250 | $600,000 | $1,848,000 | $1,894,500 | $1,950,000 | $6,585,750 |
| Watershed Improvement Fund - IDALS | $2,000,000 | $4,000,000 | N/A | N/A | N/A | N/A | N/A | N/A | N/A | N/A | N/A | N/A | $6,000,000 |
| Watershed Protection - IDALS | $900,000 | $900,000 | $900,000 | $900,000 | $900,000 | $900,000 | $900,000 | $900,000 | $900,000 | $900,000 | $900,000 | $900,000 | $10,800,000 |
| Total by Year | $317,537,840 | $331,335,910 | $320,021,805 | $347,646,152 | $355,219,772 | $438,320,331 | $506,416,645 | $535,765,780 | $529,718,098 | $562,771,754 | $550,794,987 | $586,278,845 | $5,381,827,920 |
Appendix B
| County | 2016 Community Outreach - Attendance | 2016 Community Outreach - No. Events | 2016 Conference - Attendance | 2016 Conference - No. Events | 2016 Field Day - Attendance | 2016 Field Day - No. Events | 2016 Workshop - Attendance | 2016 Workshop - No. Events | 2016 Youth and School Visits - Attendance | 2016 Youth and School Visits - No. Events | 2016 Total - Attendance | 2016 Total - No. Events | 2017 Community Outreach - Attendance | 2017 Community Outreach - No. Events | 2017 Conference - Attendance | 2017 Conference - No. Events | 2017 Field Day - Attendance | 2017 Field Day - No. Events | 2017 Workshop - Attendance | 2017 Workshop - No. Events | 2017 Youth and School Visits - Attendance | 2017 Youth and School Visits - No. Events | 2017 Total - Attendance | 2017 Total - No. Events | 2018 Community Outreach - Attendance | 2018 Community Outreach - No. Events | 2018 Conference - Attendance | 2018 Conference - No. Events | 2018 Field Day - Attendance | 2018 Field Day - No. Events | 2018 Workshop - Attendance | 2018 Workshop - No. Events | 2018 Youth and School Visits - Attendance | 2018 Youth and School Visits - No. Events | 2018 Total - Attendance | 2018 Total - No. Events | 2019 Community Outreach - Attendance | 2019 Community Outreach - No. Events | 2019 Conference - Attendance | 2019 Conference - No. Events | 2019 Field Day - Attendance | 2019 Field Day - No. Events | 2019 Workshop - Attendance | 2019 Workshop - No. Events | 2019 Youth and School Visits - Attendance | 2019 Youth and School Visits - No. Events | 2019 Total - Attendance | 2019 Total - No. Events | 2020 Community Outreach - Attendance | 2020 Community Outreach - No. Events | 2020 Conference - Attendance | 2020 Conference - No. Events | 2020 Field Day - Attendance | 2020 Field Day - No. Events | 2020 Workshop - Attendance | 2020 Workshop - No. Events | 2020 Youth and School Visits - Attendance | 2020 Youth and School Visits - No. Events | 2020 Total - Attendance | 2020 Total - No. Events | 2021 Community Outreach - Attendance | 2021 Community Outreach - No. Events | 2021 Conference - Attendance | 2021 Conference - No. Events | 2021 Field Day - Attendance | 2021 Field Day - No. Events | 2021 Workshop - Attendance | 2021 Workshop - No. Events | 2021 Youth and School Visits - Attendance | 2021 Youth and School Visits - No. Events | 2021 Total - Attendance | 2021 Total - No. Events | 2022 Community Outreach - Attendance | 2022 Community Outreach - No. Events | 2022 Conference - Attendance | 2022 Conference - No. Events | 2022 Field Day - Attendance | 2022 Field Day - No. Events | 2022 Workshop - Attendance | 2022 Workshop - No. Events | 2022 Youth and School Visits - Attendance | 2022 Youth and School Visits - No. Events | 2022 Total - Attendance | 2022 Total - No. Events | 2023 Community Outreach - Attendance | 2023 Community Outreach - No. Events | 2023 Conference - Attendance | 2023 Conference - No. Events | 2023 Field Day - Attendance | 2023 Field Day - No. Events | 2023 Workshop - Attendance | 2023 Workshop - No. Events | 2023 Youth and School Visits - Attendance | 2023 Youth and School Visits - No. Events | 2023 Total - Attendance | 2023 Total - No. Events |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Adair | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 70 | 1 | 70 | 1 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 1 | 41 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 41 | 1 | 101 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 101 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 20 | 1 | 144 | 2 | 164 | 3 | 0 | 0 | 0 | 0 | 13 | 1 | 0 | 0 | 105 | 2 | 118 | 3 | 32 | 2 | 0 | 0 | 26 | 1 | 0 | 0 | 0 | 0 | 58 | 3 | 50 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 50 | 0 |
| Adams | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 80 | 1 | 80 | 1 | 0 | 0 | 0 | 0 | 30 | 1 | 0 | 0 | 0 | 0 | 30 | 1 | 33 | 1 | 0 | 0 | 80 | 2 | 0 | 0 | 0 | 0 | 113 | 3 | 0 | 0 | 0 | 0 | 30 | 1 | 0 | 0 | 0 | 0 | 30 | 1 | 106 | 1 | 0 | 0 | 75 | 1 | 0 | 0 | 0 | 0 | 181 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 55 | 2 | 0 | 0 | 0 | 0 | 55 | 2 |
| Allamakee | 0 | 0 | 0 | 0 | 88 | 3 | 0 | 0 | 0 | 0 | 88 | 3 | 0 | 0 | 0 | 0 | 50 | 1 | 0 | 1 | 74 | 1 | 124 | 3 | 0 | 0 | 0 | 0 | 30 | 1 | 0 | 0 | 0 | 0 | 30 | 1 | 30 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 198 | 2 | 228 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 233 | 1 | 233 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 56 | 1 | 56 | 1 | 0 | 0 | 0 | 0 | 20 | 1 | 0 | 0 | 67 | 1 | 87 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 61 | 1 | 61 | 1 |
| Appanoose | 0 | 0 | 0 | 0 | 0 | 0 | 18 | 1 | 0 | 0 | 18 | 1 | 0 | 0 | 0 | 0 | 91 | 1 | 0 | 0 | 82 | 1 | 173 | 2 | 71 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 65 | 1 | 136 | 3 | 0 | 0 | 0 | 0 | 71 | 1 | 20 | 1 | 126 | 2 | 217 | 4 | 96 | 1 | 0 | 0 | 112 | 1 | 0 | 0 | 0 | 0 | 208 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 88 | 1 | 88 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 15 | 1 | 15 | 1 |
| Audubon | 150 | 1 | 0 | 0 | 55 | 2 | 37 | 3 | 52 | 1 | 294 | 7 | 0 | 0 | 0 | 0 | 45 | 1 | 0 | 0 | 0 | 0 | 45 | 1 | 0 | 0 | 0 | 0 | 30 | 1 | 0 | 0 | 150 | 2 | 180 | 3 | 15 | 1 | 0 | 0 | 20 | 1 | 0 | 0 | 173 | 1 | 208 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 1 | 12 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 123 | 1 | 123 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Benton | 92 | 4 | 0 | 0 | 68 | 2 | 119 | 4 | 73 | 1 | 352 | 11 | 50 | 1 | 0 | 0 | 90 | 2 | 50 | 1 | 213 | 3 | 403 | 7 | 490 | 6 | 0 | 0 | 0 | 0 | 20 | 1 | 457 | 2 | 967 | 9 | 71 | 4 | 0 | 0 | 15 | 1 | 72 | 2 | 467 | 4 | 625 | 11 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 127 | 1 | 127 | 1 | 201 | 4 | 0 | 0 | 0 | 1 | 0 | 0 | 231 | 4 | 432 | 9 | 203 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 36 | 2 | 239 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 101 | 1 | 101 | 1 |
| Black Hawk | 54 | 4 | 0 | 0 | 257 | 5 | 117 | 2 | 208 | 1 | 636 | 12 | 274 | 3 | 200 | 1 | 362 | 6 | 140 | 6 | 542 | 5 | 1,518 | 21 | 402 | 4 | 0 | 0 | 170 | 8 | 126 | 7 | 414 | 5 | 1,112 | 24 | 75 | 10 | 0 | 0 | 634 | 6 | 136 | 2 | 776 | 5 | 1,621 | 23 | 200 | 2 | 0 | 0 | 32 | 1 | 0 | 0 | 403 | 7 | 635 | 10 | 121 | 5 | 0 | 0 | 41 | 4 | 0 | 0 | 461 | 7 | 623 | 16 | 30 | 1 | 0 | 0 | 145 | 2 | 343 | 3 | 164 | 3 | 682 | 9 | 200 | 1 | 60 | 1 | 0 | 0 | 146 | 2 | 283 | 4 | 689 | 8 |
| Boone | 1,000 | 1 | 0 | 0 | 40 | 1 | 0 | 5 | 147 | 2 | 1187 | 9 | 170 | 1 | 0 | 0 | 80 | 2 | 29 | 1 | 64 | 2 | 343 | 6 | 100 | 1 | 0 | 0 | 87 | 3 | 40 | 1 | 681 | 5 | 908 | 10 | 4,319 | 5 | 0 | 0 | 376 | 7 | 108 | 3 | 152 | 3 | 4,955 | 18 | 146 | 3 | 0 | 0 | 65 | 1 | 59 | 2 | 271 | 5 | 541 | 11 | 40 | 1 | 0 | 0 | 30 | 1 | 0 | 0 | 101 | 3 | 171 | 5 | 85 | 2 | 0 | 0 | 0 | 0 | 48 | 1 | 275 | 2 | 408 | 5 | 0 | 0 | 0 | 0 | 88 | 1 | 39 | 2 | 42 | 1 | 169 | 4 |
| Bremer | 0 | 0 | 0 | 0 | 145 | 3 | 0 | 0 | 47 | 1 | 192 | 4 | 28 | 1 | 0 | 0 | 20 | 1 | 0 | 0 | 254 | 3 | 302 | 5 | 39 | 3 | 0 | 0 | 175 | 1 | 0 | 0 | 228 | 3 | 442 | 7 | 18 | 1 | 0 | 0 | 45 | 2 | 6 | 1 | 0 | 0 | 69 | 4 | 177 | 2 | 0 | 0 | 55 | 1 | 18 | 2 | 549 | 5 | 799 | 10 | 16 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 57 | 2 | 73 | 3 | 45 | 1 | 0 | 0 | 90 | 2 | 0 | 0 | 208 | 3 | 343 | 6 | 12 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 16 | 1 | 28 | 2 |
| Buchanan | 50 | 3 | 0 | 0 | 42 | 1 | 0 | 0 | 0 | 0 | 92 | 4 | 86 | 3 | 0 | 0 | 19 | 1 | 0 | 0 | 0 | 0 | 105 | 4 | 44 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 644 | 1 | 688 | 5 | 327 | 2 | 0 | 0 | 12 | 1 | 0 | 0 | 132 | 1 | 471 | 4 | 54 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 181 | 3 | 235 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 295 | 4 | 295 | 4 | 69 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 148 | 2 | 217 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 101 | 1 | 101 | 1 |
| Buena Vista | 74 | 2 | 0 | 0 | 110 | 2 | 180 | 5 | 58 | 1 | 422 | 10 | 139 | 2 | 0 | 0 | 198 | 4 | 70 | 2 | 0 | 0 | 407 | 8 | 0 | 0 | 0 | 0 | 45 | 2 | 15 | 1 | 0 | 0 | 60 | 3 | 20 | 1 | 0 | 0 | 106 | 2 | 30 | 3 | 173 | 1 | 329 | 7 | 0 | 1 | 0 | 0 | 196 | 3 | 0 | 0 | 184 | 1 | 380 | 5 | 41 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 108 | 1 | 149 | 2 | 73 | 2 | 0 | 0 | 121 | 3 | 76 | 5 | 285 | 3 | 555 | 13 | 1 | 1 | 0 | 0 | 0 | 0 | 95 | 2 | 323 | 3 | 419 | 6 |
| Butler | 0 | 0 | 0 | 0 | 30 | 1 | 0 | 0 | 0 | 0 | 30 | 1 | 117 | 1 | 0 | 0 | 40 | 1 | 13 | 1 | 201 | 2 | 371 | 5 | 0 | 0 | 0 | 0 | 59 | 2 | 0 | 0 | 120 | 2 | 179 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 186 | 1 | 186 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 65 | 1 | 65 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 16 | 1 | 16 | 1 | 67 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 18 | 1 | 85 | 2 | 0 | 0 | 0 | 0 | 31 | 1 | 0 | 0 | 123 | 2 | 154 | 3 |
| Calhoun | 0 | 0 | 0 | 0 | 0 | 0 | 30 | 1 | 140 | 1 | 170 | 2 | 71 | 1 | 0 | 0 | 39 | 1 | 0 | 0 | 26 | 1 | 136 | 3 | 0 | 0 | 0 | 0 | 35 | 1 | 0 | 0 | 26 | 1 | 61 | 2 | 81 | 1 | 0 | 0 | 85 | 2 | 15 | 2 | 0 | 0 | 181 | 5 | 46 | 2 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 47 | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 113 | 2 | 114 | 2 | 1 | 0 | 0 | 0 | 52 | 2 | 21 | 4 | 125 | 3 | 199 | 9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Carroll | 0 | 0 | 0 | 0 | 234 | 5 | 53 | 5 | 0 | 0 | 287 | 10 | 90 | 3 | 25 | 1 | 145 | 4 | 75 | 1 | 150 | 1 | 485 | 10 | 68 | 3 | 0 | 0 | 220 | 5 | 30 | 1 | 140 | 2 | 458 | 11 | 72 | 1 | 0 | 0 | 55 | 2 | 45 | 3 | 83 | 2 | 255 | 8 | 51 | 1 | 0 | 0 | 0 | 0 | 28 | 2 | 85 | 1 | 164 | 4 | 1 | 0 | 0 | 0 | 0 | 0 | 4 | 1 | 170 | 2 | 175 | 3 | 153 | 2 | 0 | 0 | 0 | 0 | 2 | 1 | 302 | 3 | 457 | 6 | 0 | 0 | 0 | 0 | 37 | 2 | 30 | 2 | 311 | 3 | 378 | 7 |
| Cass | 100 | 0 | 0 | 0 | 88 | 2 | 25 | 1 | 0 | 0 | 213 | 3 | 0 | 0 | 0 | 0 | 85 | 1 | 0 | 0 | 0 | 0 | 85 | 1 | 0 | 0 | 0 | 0 | 25 | 1 | 0 | 0 | 85 | 2 | 110 | 3 | 85 | 2 | 0 | 0 | 140 | 2 | 50 | 2 | 51 | 1 | 326 | 7 | 0 | 0 | 0 | 0 | 113 | 1 | 8 | 1 | 107 | 1 | 228 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 104 | 2 | 104 | 2 | 130 | 1 | 100 | 1 | 137 | 3 | 0 | 0 | 206 | 2 | 573 | 7 | 0 | 0 | 0 | 0 | 0 | 0 | 70 | 2 | 0 | 0 | 70 | 2 |
| Cedar | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 142 | 2 | 142 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 72 | 1 | 72 | 1 | 50 | 2 | 0 | 0 | 0 | 0 | 30 | 1 | 140 | 2 | 220 | 5 | 162 | 4 | 42 | 1 | 0 | 0 | 0 | 0 | 87 | 1 | 291 | 6 | 125 | 1 | 0 | 0 | 158 | 3 | 0 | 0 | 0 | 0 | 283 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 115 | 1 | 0 | 0 | 30 | 1 | 0 | 0 | 260 | 6 | 405 | 8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 90 | 2 | 90 | 2 |
| Cerro Gordo | 0 | 0 | 0 | 0 | 92 | 2 | 0 | 0 | 58 | 1 | 150 | 3 | 0 | 0 | 0 | 0 | 99 | 1 | 0 | 0 | 101 | 1 | 200 | 2 | 143 | 1 | 0 | 0 | 0 | 2 | 30 | 1 | 345 | 2 | 518 | 6 | 0 | 0 | 0 | 0 | 167 | 2 | 0 | 0 | 1,288 | 5 | 1,455 | 7 | 168 | 1 | 0 | 0 | 90 | 1 | 0 | 0 | 0 | 0 | 258 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 641 | 6 | 641 | 6 | 267 | 2 | 0 | 0 | 29 | 3 | 0 | 0 | 164 | 3 | 460 | 8 | 0 | 0 | 40 | 1 | 0 | 0 | 187 | 2 | 247 | 4 | 474 | 7 |
| Cherokee | 0 | 0 | 0 | 0 | 0 | 0 | 37 | 1 | 0 | 0 | 37 | 1 | 0 | 0 | 0 | 0 | 39 | 1 | 0 | 0 | 0 | 0 | 39 | 1 | 27 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 159 | 2 | 186 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 139 | 2 | 139 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 205 | 3 | 205 | 3 | 1 | 1 | 0 | 0 | 32 | 1 | 12 | 1 | 0 | 0 | 45 | 3 | 35 | 2 | 0 | 0 | 0 | 0 | 30 | 1 | 171 | 4 | 236 | 7 |
| Chickasaw | 0 | 0 | 0 | 0 | 145 | 2 | 0 | 0 | 141 | 1 | 286 | 3 | 0 | 0 | 0 | 0 | 129 | 3 | 60 | 1 | 0 | 0 | 189 | 4 | 0 | 0 | 0 | 0 | 122 | 2 | 109 | 4 | 0 | 0 | 231 | 6 | 0 | 0 | 0 | 0 | 83 | 2 | 88 | 2 | 183 | 3 | 354 | 7 | 23 | 1 | 0 | 0 | 83 | 3 | 0 | 0 | 78 | 1 | 184 | 5 | 0 | 0 | 0 | 0 | 80 | 2 | 0 | 0 | 205 | 4 | 285 | 6 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 130 | 3 | 130 | 3 |
| Clarke | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 45 | 1 | 45 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 30 | 1 | 372 | 1 | 402 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 45 | 1 | 45 | 1 | 92 | 1 | 0 | 0 | 40 | 1 | 0 | 0 | 0 | 0 | 132 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 46 | 3 | 46 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 106 | 2 | 106 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Clay | 60 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 60 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 65 | 1 | 65 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 755 | 2 | 755 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 200 | 1 | 75 | 1 | 275 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 1 | 0 | 0 | 8 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 41 | 1 | 41 | 1 | 0 | 0 | 0 | 0 | 40 | 1 | 11 | 1 | 0 | 0 | 51 | 2 |
| Clayton | 100 | 1 | 0 | 0 | 45 | 2 | 20 | 2 | 0 | 0 | 165 | 5 | 149 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 149 | 3 | 60 | 2 | 0 | 0 | 150 | 3 | 0 | 0 | 0 | 0 | 210 | 5 | 90 | 2 | 0 | 0 | 37 | 1 | 47 | 2 | 210 | 3 | 384 | 8 | 0 | 0 | 0 | 0 | 0 | 0 | 39 | 1 | 0 | 0 | 39 | 1 | 8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 82 | 3 | 90 | 3 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 49 | 1 | 49 | 1 |
| Clinton | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 55 | 1 | 0 | 0 | 30 | 1 | 0 | 0 | 0 | 0 | 85 | 2 | 100 | 1 | 0 | 0 | 0 | 0 | 30 | 1 | 53 | 1 | 183 | 3 | 0 | 0 | 0 | 0 | 25 | 1 | 0 | 0 | 33 | 1 | 58 | 2 | 42 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 90 | 2 | 132 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 20 | 1 | 0 | 0 | 20 | 1 | 0 | 0 | 0 | 0 | 44 | 1 | 0 | 0 | 382 | 4 | 426 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 170 | 2 | 170 | 2 |
| Crawford | 0 | 0 | 0 | 0 | 20 | 1 | 0 | 0 | 155 | 1 | 175 | 2 | 0 | 0 | 0 | 0 | 139 | 2 | 0 | 0 | 72 | 2 | 211 | 4 | 24 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 130 | 2 | 154 | 3 | 63 | 1 | 0 | 0 | 98 | 2 | 0 | 0 | 203 | 2 | 364 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,705 | 7 | 1,705 | 7 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 222 | 3 | 222 | 3 | 1 | 0 | 0 | 0 | 58 | 1 | 11 | 1 | 122 | 2 | 192 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 63 | 1 | 72 | 2 | 135 | 3 |
| Dallas | 0 | 1 | 0 | 0 | 100 | 3 | 37 | 1 | 103 | 1 | 240 | 6 | 100 | 1 | 0 | 0 | 40 | 1 | 15 | 2 | 51 | 1 | 206 | 5 | 52 | 3 | 0 | 0 | 45 | 2 | 25 | 1 | 772 | 3 | 894 | 9 | 0 | 0 | 0 | 0 | 33 | 2 | 35 | 2 | 479 | 3 | 547 | 7 | 531 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 218 | 3 | 749 | 5 | 60 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 629 | 12 | 689 | 14 | 208 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 117 | 2 | 325 | 4 | 43 | 2 | 0 | 0 | 0 | 0 | 102 | 2 | 576 | 6 | 721 | 10 |
| Davis | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 34 | 1 | 0 | 0 | 34 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 916 | 1 | 916 | 1 | 36 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 36 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 88 | 1 | 88 | 1 | 1 | 1 | 0 | 0 | 36 | 5 | 0 | 0 | 0 | 0 | 37 | 6 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Decatur | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 49 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 150 | 1 | 199 | 2 | 61 | 1 | 0 | 0 | 66 | 2 | 0 | 0 | 0 | 0 | 127 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 146 | 2 | 146 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 94 | 2 | 94 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 16 | 1 | 16 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 1 | 133 | 3 | 137 | 4 |
| Delaware | 0 | 0 | 0 | 0 | 0 | 0 | 112 | 5 | 130 | 1 | 242 | 6 | 0 | 0 | 0 | 0 | 0 | 0 | 10 | 1 | 0 | 0 | 10 | 1 | 187 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 187 | 1 | 95 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 58 | 1 | 153 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 162 | 2 | 162 | 2 | 0 | 0 | 0 | 0 | 27 | 2 | 0 | 0 | 245 | 3 | 272 | 5 | 0 | 0 | 0 | 0 | 30 | 1 | 0 | 0 | 65 | 1 | 95 | 2 | 46 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 71 | 1 | 117 | 3 |
| Des Moines | 0 | 0 | 0 | 0 | 75 | 1 | 20 | 1 | 99 | 2 | 194 | 4 | 150 | 1 | 0 | 0 | 86 | 2 | 0 | 0 | 259 | 2 | 495 | 5 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 469 | 2 | 469 | 5 | 66 | 1 | 0 | 0 | 121 | 6 | 0 | 0 | 38 | 1 | 225 | 8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 113 | 2 | 113 | 3 | 0 | 0 | 0 | 0 | 121 | 1 | 5 | 1 | 503 | 4 | 629 | 6 | 0 | 0 | 0 | 0 | 0 | 0 | 152 | 1 | 0 | 0 | 152 | 1 |
| Dickinson | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 367 | 2 | 0 | 0 | 309 | 3 | 0 | 0 | 310 | 3 | 986 | 8 | 300 | 1 | 40 | 1 | 121 | 4 | 0 | 0 | 128 | 1 | 589 | 7 | 153 | 1 | 0 | 0 | 223 | 3 | 0 | 0 | 225 | 3 | 601 | 7 | 0 | 0 | 0 | 0 | 102 | 1 | 0 | 0 | 262 | 2 | 364 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 195 | 3 | 195 | 3 | 33 | 2 | 0 | 0 | 80 | 1 | 0 | 0 | 0 | 0 | 113 | 3 | 37 | 1 | 0 | 0 | 0 | 0 | 99 | 1 | 39 | 2 | 175 | 4 |
| Dubuque | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 128 | 1 | 128 | 1 | 102 | 1 | 350 | 2 | 30 | 1 | 0 | 0 | 264 | 3 | 746 | 7 | 75 | 1 | 0 | 0 | 0 | 0 | 25 | 1 | 143 | 2 | 243 | 4 | 189 | 1 | 155 | 1 | 90 | 3 | 0 | 0 | 231 | 3 | 665 | 8 | 0 | 0 | 0 | 0 | 147 | 2 | 0 | 0 | 269 | 3 | 416 | 5 | 0 | 0 | 0 | 0 | 91 | 2 | 0 | 0 | 1,430 | 12 | 1,521 | 14 | 12 | 1 | 600 | 2 | 65 | 2 | 1,065 | 4 | 2,724 | 6 | 4,466 | 15 | 100 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2,637 | 3 | 2,737 | 4 |
| Emmet | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 107 | 1 | 107 | 1 | 45 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 31 | 2 | 76 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 84 | 1 | 84 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 71 | 1 | 71 | 1 | 8 | 1 | 0 | 0 | 0 | 0 | 22 | 1 | 0 | 0 | 30 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 86 | 1 | 86 | 1 |
| Fayette | 0 | 0 | 0 | 0 | 61 | 2 | 0 | 0 | 337 | 4 | 398 | 6 | 0 | 0 | 0 | 0 | 50 | 1 | 44 | 2 | 330 | 2 | 424 | 5 | 0 | 0 | 0 | 0 | 250 | 2 | 0 | 0 | 1,072 | 3 | 1,322 | 5 | 209 | 2 | 50 | 1 | 0 | 0 | 0 | 0 | 371 | 2 | 630 | 5 | 0 | 0 | 0 | 0 | 60 | 1 | 0 | 0 | 400 | 1 | 460 | 2 | 10 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 244 | 6 | 254 | 7 | 74 | 1 | 0 | 0 | 60 | 1 | 0 | 0 | 229 | 3 | 363 | 5 | 0 | 0 | 0 | 0 | 97 | 2 | 0 | 0 | 0 | 0 | 97 | 2 |
| Floyd | 307 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 307 | 2 | 141 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 478 | 2 | 619 | 3 | 75 | 4 | 0 | 0 | 73 | 2 | 0 | 0 | 0 | 0 | 148 | 6 | 0 | 0 | 0 | 0 | 23 | 1 | 0 | 0 | 94 | 1 | 117 | 2 | 0 | 0 | 0 | 0 | 24 | 1 | 40 | 0 | 56 | 1 | 120 | 2 | 2 | 0 | 0 | 0 | 30 | 1 | 30 | 1 | 222 | 3 | 284 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 40 | 1 | 483 | 6 | 523 | 7 | 24 | 1 | 0 | 0 | 75 | 1 | 0 | 0 | 165 | 2 | 264 | 4 |
| Franklin | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 386 | 2 | 386 | 2 | 58 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 48 | 1 | 106 | 2 | 16 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 218 | 1 | 234 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 93 | 2 | 93 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 47 | 1 | 47 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Fremont | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 20 | 1 | 0 | 0 | 55 | 1 | 0 | 0 | 0 | 0 | 75 | 2 | 74 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 74 | 1 | 24 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 24 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 87 | 1 | 88 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 129 | 2 | 129 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Greene | 0 | 0 | 0 | 0 | 90 | 3 | 0 | 0 | 0 | 0 | 90 | 3 | 32 | 1 | 0 | 0 | 110 | 1 | 34 | 1 | 55 | 1 | 231 | 4 | 0 | 0 | 0 | 0 | 30 | 1 | 0 | 0 | 0 | 0 | 30 | 1 | 51 | 2 | 0 | 0 | 125 | 1 | 31 | 1 | 0 | 0 | 207 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 133 | 2 | 133 | 2 | 17 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 92 | 1 | 109 | 3 | 124 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 92 | 1 | 216 | 3 | 26 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 26 | 1 |
| Grundy | 0 | 0 | 0 | 0 | 0 | 0 | 135 | 1 | 0 | 0 | 135 | 1 | 262 | 3 | 0 | 0 | 73 | 3 | 0 | 0 | 180 | 2 | 515 | 8 | 128 | 4 | 0 | 0 | 42 | 1 | 0 | 0 | 895 | 3 | 1,065 | 8 | 180 | 6 | 0 | 0 | 61 | 2 | 0 | 0 | 150 | 2 | 391 | 10 | 0 | 0 | 0 | 0 | 2 | 1 | 120 | 2 | 332 | 2 | 454 | 5 | 10 | 1 | 0 | 0 | 0 | 0 | 27 | 1 | 104 | 2 | 141 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 40 | 2 | 188 | 1 | 229 | 4 |
| Guthrie | 0 | 0 | 0 | 0 | 55 | 1 | 0 | 0 | 0 | 0 | 55 | 1 | 0 | 0 | 0 | 0 | 35 | 1 | 0 | 0 | 54 | 1 | 89 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 10 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 183 | 2 | 193 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 80 | 1 | 80 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 102 | 4 | 103 | 4 | 0 | 0 | 0 | 0 | 22 | 1 | 50 | 1 | 0 | 0 | 72 | 2 |
| Hamilton | 0 | 0 | 0 | 0 | 14 | 2 | 12 | 2 | 18 | 1 | 44 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 91 | 2 | 91 | 2 | 2 | 0 | 0 | 0 | 71 | 2 | 0 | 0 | 196 | 1 | 269 | 3 | 285 | 1 | 0 | 0 | 60 | 1 | 42 | 1 | 122 | 2 | 509 | 5 | 41 | 1 | 0 | 0 | 0 | 0 | 37 | 1 | 22 | 1 | 100 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 100 | 1 | 113 | 2 | 213 | 3 | 0 | 0 | 0 | 0 | 82 | 1 | 4 | 1 | 115 | 3 | 201 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 50 | 1 | 71 | 1 | 121 | 2 |
| Hancock | 0 | 0 | 0 | 0 | 60 | 1 | 0 | 0 | 0 | 0 | 60 | 1 | 153 | 2 | 0 | 0 | 50 | 1 | 0 | 0 | 83 | 1 | 286 | 4 | 49 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 302 | 2 | 351 | 4 | 270 | 2 | 0 | 0 | 133 | 2 | 0 | 0 | 0 | 0 | 403 | 4 | 1 | 0 | 0 | 0 | 90 | 1 | 0 | 0 | 0 | 0 | 91 | 1 | 1 | 0 | 0 | 0 | 22 | 1 | 0 | 0 | 163 | 2 | 186 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 110 | 1 | 0 | 0 | 0 | 0 | 110 | 1 |
| Hardin | 0 | 0 | 0 | 0 | 45 | 1 | 0 | 0 | 0 | 0 | 45 | 1 | 185 | 10 | 0 | 0 | 270 | 3 | 35 | 1 | 135 | 2 | 625 | 16 | 32 | 2 | 0 | 0 | 303 | 4 | 35 | 2 | 59 | 2 | 429 | 10 | 97 | 2 | 0 | 0 | 318 | 3 | 81 | 2 | 0 | 0 | 496 | 7 | 91 | 10 | 0 | 0 | 335 | 6 | 14 | 1 | 512 | 2 | 952 | 19 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 314 | 2 | 314 | 3 | 61 | 1 | 0 | 0 | 74 | 1 | 9 | 1 | 23 | 2 | 167 | 5 | 102 | 3 | 0 | 0 | 18 | 1 | 0 | 0 | 0 | 0 | 120 | 4 |
| Harrison | 0 | 0 | 0 | 0 | 40 | 2 | 0 | 0 | 0 | 0 | 40 | 2 | 0 | 0 | 0 | 0 | 75 | 1 | 0 | 0 | 125 | 2 | 200 | 3 | 0 | 0 | 0 | 0 | 30 | 1 | 0 | 0 | 266 | 1 | 296 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 61 | 1 | 61 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 50 | 1 | 50 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 98 | 3 | 98 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 1 | 209 | 4 | 221 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 92 | 4 | 92 | 4 |
| Henry | 0 | 0 | 0 | 0 | 100 | 2 | 0 | 0 | 0 | 0 | 100 | 2 | 153 | 2 | 0 | 0 | 362 | 3 | 0 | 0 | 171 | 1 | 686 | 6 | 26 | 1 | 0 | 0 | 0 | 0 | 2 | 1 | 233 | 3 | 261 | 5 | 442 | 5 | 0 | 0 | 104 | 2 | 0 | 0 | 91 | 2 | 637 | 9 | 181 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 49 | 1 | 230 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 522 | 5 | 522 | 5 | 5 | 0 | 0 | 0 | 0 | 0 | 14 | 1 | 170 | 2 | 189 | 3 | 0 | 0 | 0 | 0 | 20 | 2 | 0 | 0 | 0 | 0 | 20 | 2 |
| Howard | 20 | 1 | 0 | 0 | 2 | 1 | 0 | 0 | 362 | 2 | 384 | 4 | 0 | 0 | 0 | 0 | 12 | 1 | 0 | 0 | 0 | 0 | 12 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 305 | 2 | 305 | 5 | 0 | 0 | 0 | 0 | 30 | 1 | 15 | 1 | 50 | 1 | 95 | 3 | 145 | 2 | 0 | 0 | 2 | 1 | 15 | 3 | 15 | 1 | 177 | 7 | 6 | 1 | 0 | 0 | 25 | 1 | 305 | 3 | 436 | 7 | 772 | 12 | 229 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 60 | 2 | 289 | 4 | 300 | 1 | 0 | 0 | 0 | 0 | 30 | 2 | 0 | 0 | 330 | 3 |
| Humboldt | 0 | 0 | 0 | 0 | 106 | 2 | 37 | 1 | 0 | 0 | 143 | 3 | 13 | 1 | 0 | 0 | 93 | 2 | 0 | 0 | 0 | 0 | 106 | 3 | 53 | 3 | 0 | 0 | 40 | 1 | 0 | 0 | 580 | 1 | 673 | 5 | 1 | 0 | 0 | 0 | 40 | 1 | 22 | 3 | 229 | 2 | 292 | 6 | 0 | 0 | 0 | 0 | 35 | 1 | 5 | 1 | 151 | 3 | 191 | 5 | 0 | 0 | 0 | 0 | 26 | 2 | 0 | 0 | 15 | 1 | 41 | 3 | 51 | 1 | 60 | 1 | 0 | 0 | 0 | 0 | 299 | 3 | 410 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Ida | 0 | 0 | 0 | 0 | 34 | 1 | 0 | 0 | 42 | 1 | 76 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 70 | 1 | 70 | 1 | 60 | 1 | 0 | 0 | 0 | 0 | 57 | 5 | 71 | 1 | 188 | 7 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 85 | 1 | 0 | 0 | 82 | 1 | 0 | 0 | 251 | 3 | 418 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 | 1 | 25 | 1 | 32 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 81 | 2 | 81 | 2 |
| Iowa | 50 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 50 | 1 | 289 | 3 | 0 | 0 | 12 | 1 | 34 | 1 | 311 | 3 | 646 | 8 | 369 | 2 | 0 | 0 | 40 | 8 | 0 | 0 | 43 | 1 | 452 | 11 | 67 | 1 | 0 | 0 | 0 | 4 | 0 | 0 | 0 | 0 | 67 | 5 | 318 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 159 | 2 | 477 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 124 | 2 | 124 | 2 | 2 | 2 | 0 | 0 | 110 | 1 | 0 | 0 | 0 | 0 | 112 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Jackson | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 42 | 1 | 42 | 1 | 0 | 0 | 0 | 0 | 165 | 2 | 30 | 1 | 182 | 1 | 377 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 593 | 2 | 593 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 10 | 1 | 47 | 1 | 57 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 149 | 4 | 149 | 4 | 0 | 0 | 0 | 0 | 20 | 1 | 0 | 0 | 283 | 4 | 303 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 242 | 3 | 242 | 3 |
| Jasper | 0 | 0 | 0 | 0 | 134 | 4 | 125 | 3 | 116 | 1 | 375 | 8 | 0 | 0 | 0 | 0 | 90 | 2 | 0 | 0 | 191 | 2 | 281 | 4 | 116 | 1 | 0 | 0 | 101 | 2 | 0 | 0 | 154 | 2 | 371 | 5 | 194 | 2 | 0 | 0 | 45 | 2 | 0 | 0 | 550 | 2 | 789 | 6 | 126 | 2 | 0 | 0 | 60 | 1 | 38 | 1 | 991 | 6 | 1,215 | 10 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 120 | 2 | 120 | 2 | 21 | 1 | 75 | 1 | 13 | 1 | 40 | 1 | 0 | 0 | 149 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 60 | 1 | 0 | 0 | 60 | 1 |
| Jefferson | 0 | 0 | 250 | 1 | 0 | 0 | 50 | 2 | 0 | 0 | 300 | 3 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 26 | 2 | 200 | 1 | 54 | 1 | 1 | 1 | 0 | 0 | 281 | 5 | 90 | 2 | 0 | 0 | 50 | 1 | 45 | 2 | 57 | 1 | 242 | 6 | 27 | 1 | 0 | 0 | 0 | 0 | 21 | 1 | 62 | 2 | 110 | 4 | 5 | 1 | 0 | 0 | 0 | 0 | 20 | 1 | 0 | 0 | 25 | 2 | 74 | 2 | 0 | 0 | 38 | 1 | 61 | 2 | 200 | 1 | 373 | 6 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Johnson | 0 | 0 | 0 | 0 | 120 | 2 | 41 | 1 | 471 | 2 | 632 | 5 | 739 | 5 | 40 | 1 | 210 | 3 | 220 | 2 | 0 | 0 | 1,209 | 11 | 50 | 1 | 30 | 1 | 140 | 2 | 90 | 2 | 129 | 2 | 439 | 8 | 25 | 1 | 0 | 0 | 130 | 1 | 0 | 0 | 75 | 1 | 230 | 3 | 146 | 2 | 0 | 0 | 143 | 1 | 0 | 0 | 195 | 3 | 484 | 6 | 135 | 2 | 50 | 1 | 0 | 0 | 0 | 0 | 173 | 8 | 358 | 11 | 94 | 7 | 0 | 0 | 99 | 1 | 30 | 1 | 574 | 10 | 797 | 19 | 1,050 | 20 | 0 | 0 | 0 | 0 | 98 | 2 | 1,101 | 9 | 2,249 | 31 |
| Jones | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 100 | 1 | 0 | 0 | 100 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 30 | 1 | 88 | 1 | 118 | 2 | 118 | 1 | 0 | 0 | 0 | 0 | 30 | 1 | 150 | 2 | 298 | 4 | 97 | 1 | 0 | 0 | 66 | 1 | 0 | 0 | 15 | 1 | 178 | 3 | 0 | 0 | 0 | 0 | 30 | 1 | 0 | 0 | 137 | 2 | 167 | 3 | 64 | 1 | 0 | 0 | 49 | 3 | 0 | 0 | 143 | 8 | 256 | 12 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Keokuk | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 65 | 1 | 0 | 0 | 0 | 0 | 65 | 1 | 124 | 2 | 0 | 0 | 50 | 1 | 30 | 1 | 0 | 0 | 204 | 4 | 113 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 113 | 1 | 0 | 0 | 0 | 0 | 40 | 1 | 0 | 0 | 0 | 0 | 40 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 51 | 1 | 0 | 0 | 102 | 3 | 0 | 0 | 58 | 1 | 211 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 1 | 12 | 1 |
| Kossuth | 0 | 0 | 0 | 0 | 146 | 6 | 0 | 1 | 239 | 2 | 385 | 9 | 189 | 2 | 0 | 0 | 78 | 2 | 0 | 0 | 0 | 0 | 267 | 4 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 65 | 1 | 67 | 1 | 1 | 0 | 0 | 0 | 160 | 3 | 0 | 0 | 299 | 2 | 460 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 7 | 1 | 192 | 2 | 199 | 3 | 2 | 0 | 0 | 0 | 65 | 2 | 42 | 1 | 166 | 2 | 275 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 1 | 0 | 0 | 5 | 1 | 0 | 0 | 0 | 0 | 73 | 1 | 0 | 0 | 120 | 2 | 193 | 3 |
| Lee | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 56 | 1 | 10 | 1 | 577 | 4 | 643 | 6 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 1 | 90 | 1 | 93 | 2 | 158 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 261 | 2 | 419 | 4 | 323 | 1 | 0 | 0 | 28 | 1 | 6 | 1 | 221 | 2 | 578 | 5 | 15 | 1 | 0 | 0 | 0 | 0 | 11 | 1 | 144 | 2 | 170 | 4 | 16 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 77 | 1 | 93 | 2 | 0 | 0 | 0 | 0 | 60 | 1 | 0 | 0 | 154 | 2 | 214 | 3 |
| Linn | 0 | 0 | 0 | 0 | 0 | 0 | 37 | 1 | 446 | 2 | 483 | 3 | 26 | 1 | 200 | 1 | 100 | 2 | 83 | 3 | 958 | 4 | 1,367 | 11 | 140 | 4 | 100 | 1 | 26 | 2 | 50 | 2 | 877 | 7 | 1,193 | 16 | 268 | 5 | 0 | 0 | 25 | 1 | 130 | 3 | 1,114 | 6 | 1,537 | 15 | 446 | 4 | 0 | 0 | 214 | 4 | 0 | 0 | 1,370 | 9 | 2,030 | 17 | 71 | 4 | 0 | 0 | 0 | 0 | 7 | 2 | 1,262 | 18 | 1,340 | 24 | 296 | 4 | 0 | 0 | 60 | 6 | 0 | 0 | 627 | 10 | 983 | 20 | 830 | 4 | 300 | 1 | 40 | 1 | 10 | 3 | 818 | 7 | 1,998 | 16 |
| Louisa | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 20 | 1 | 0 | 0 | 0 | 0 | 20 | 1 | 52 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 145 | 1 | 197 | 2 | 34 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 64 | 1 | 98 | 2 | 66 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 226 | 3 | 292 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 46 | 2 | 46 | 2 | 94 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 588 | 7 | 682 | 8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 180 | 1 | 180 | 1 |
| Lucas | 0 | 0 | 0 | 0 | 30 | 1 | 0 | 0 | 191 | 2 | 221 | 3 | 36 | 1 | 0 | 0 | 50 | 1 | 0 | 0 | 0 | 0 | 86 | 2 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 677 | 3 | 677 | 6 | 0 | 0 | 0 | 0 | 0 | 3 | 49 | 1 | 247 | 2 | 296 | 6 | 0 | 0 | 0 | 0 | 20 | 1 | 0 | 0 | 92 | 1 | 112 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 85 | 1 | 85 | 1 | 0 | 0 | 0 | 0 | 30 | 1 | 0 | 0 | 72 | 1 | 102 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Lyon | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 110 | 1 | 0 | 0 | 100 | 1 | 34 | 1 | 0 | 0 | 244 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 10 | 1 | 0 | 0 | 10 | 1 | 20 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 339 | 2 | 359 | 3 | 0 | 0 | 0 | 0 | 70 | 1 | 0 | 0 | 131 | 2 | 201 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 145 | 3 | 145 | 3 | 255 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 28 | 1 | 283 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 75 | 3 | 75 | 3 |
| Madison | 0 | 0 | 0 | 0 | 0 | 0 | 20 | 1 | 0 | 0 | 20 | 1 | 97 | 1 | 0 | 0 | 0 | 0 | 38 | 1 | 58 | 1 | 193 | 3 | 100 | 2 | 0 | 0 | 0 | 1 | 0 | 0 | 85 | 2 | 185 | 5 | 0 | 0 | 0 | 0 | 35 | 2 | 0 | 0 | 36 | 1 | 71 | 3 | 178 | 2 | 0 | 0 | 208 | 1 | 18 | 1 | 0 | 0 | 404 | 4 | 0 | 0 | 0 | 0 | 25 | 1 | 0 | 0 | 214 | 1 | 239 | 2 | 29 | 1 | 0 | 0 | 0 | 0 | 25 | 1 | 208 | 2 | 262 | 4 | 17 | 1 | 0 | 0 | 38 | 1 | 0 | 0 | 108 | 1 | 163 | 3 |
| Mahaska | 0 | 0 | 0 | 0 | 43 | 1 | 37 | 1 | 0 | 0 | 80 | 2 | 65 | 1 | 0 | 0 | 158 | 3 | 7 | 1 | 173 | 1 | 403 | 6 | 77 | 1 | 0 | 0 | 40 | 1 | 0 | 0 | 164 | 2 | 281 | 4 | 44 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 44 | 2 | 48 | 1 | 0 | 0 | 43 | 3 | 30 | 1 | 347 | 4 | 468 | 9 | 5 | 0 | 0 | 0 | 42 | 1 | 0 | 0 | 50 | 1 | 97 | 2 | 150 | 2 | 0 | 0 | 27 | 1 | 250 | 1 | 201 | 4 | 628 | 8 | 0 | 0 | 0 | 0 | 67 | 1 | 0 | 0 | 44 | 1 | 111 | 2 |
| Marion | 20 | 1 | 0 | 0 | 6 | 1 | 14 | 1 | 0 | 0 | 40 | 3 | 0 | 0 | 0 | 0 | 50 | 1 | 50 | 1 | 0 | 0 | 100 | 2 | 48 | 1 | 0 | 0 | 0 | 0 | 60 | 2 | 78 | 2 | 186 | 5 | 33 | 2 | 0 | 0 | 20 | 1 | 0 | 0 | 223 | 1 | 276 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 7 | 1 | 316 | 3 | 323 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 121 | 2 | 121 | 2 | 378 | 2 | 0 | 0 | 0 | 0 | 25 | 1 | 472 | 7 | 875 | 10 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 96 | 1 | 97 | 1 |
| Marshall | 0 | 0 | 0 | 0 | 35 | 1 | 0 | 0 | 0 | 0 | 35 | 1 | 0 | 0 | 0 | 0 | 149 | 4 | 0 | 0 | 0 | 0 | 149 | 4 | 147 | 1 | 85 | 1 | 0 | 0 | 0 | 0 | 107 | 2 | 339 | 4 | 163 | 3 | 0 | 0 | 209 | 2 | 25 | 1 | 0 | 0 | 397 | 6 | 9 | 1 | 0 | 0 | 25 | 1 | 24 | 1 | 384 | 2 | 442 | 5 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 486 | 6 | 486 | 7 | 1 | 0 | 0 | 0 | 72 | 2 | 0 | 0 | 530 | 5 | 603 | 7 | 0 | 0 | 0 | 0 | 50 | 1 | 0 | 0 | 378 | 3 | 428 | 4 |
| Mills | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 80 | 1 | 80 | 1 | 20 | 1 | 0 | 0 | 82 | 2 | 0 | 0 | 0 | 0 | 102 | 3 | 0 | 0 | 0 | 0 | 40 | 1 | 0 | 0 | 0 | 0 | 40 | 1 | 0 | 0 | 0 | 0 | 30 | 1 | 0 | 0 | 45 | 1 | 75 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 116 | 2 | 116 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 189 | 3 | 189 | 3 | 73 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 403 | 3 | 476 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Mitchell | 0 | 0 | 0 | 0 | 0 | 0 | 25 | 2 | 195 | 1 | 220 | 3 | 313 | 5 | 0 | 0 | 250 | 1 | 0 | 0 | 79 | 1 | 642 | 7 | 146 | 2 | 0 | 0 | 50 | 2 | 17 | 1 | 0 | 0 | 213 | 5 | 84 | 1 | 0 | 0 | 111 | 2 | 0 | 0 | 0 | 0 | 195 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 1 | 0 | 0 | 4 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 10 | 1 | 11 | 1 | 16 | 1 | 0 | 0 | 20 | 1 | 0 | 0 | 219 | 3 | 255 | 5 | 0 | 0 | 0 | 0 | 40 | 1 | 14 | 1 | 120 | 1 | 174 | 3 |
| Monona | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 59 | 1 | 59 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 55 | 1 | 55 | 1 | 0 | 0 | 0 | 0 | 20 | 1 | 0 | 0 | 267 | 1 | 287 | 2 | 94 | 2 | 0 | 0 | 17 | 1 | 0 | 0 | 14 | 1 | 125 | 4 | 49 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 136 | 2 | 185 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 183 | 1 | 183 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 7 | 2 | 0 | 0 | 7 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Monroe | 0 | 0 | 0 | 0 | 57 | 1 | 15 | 1 | 0 | 0 | 72 | 2 | 0 | 0 | 0 | 0 | 29 | 1 | 0 | 0 | 89 | 1 | 118 | 2 | 75 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 75 | 1 | 65 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 65 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 176 | 1 | 176 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 161 | 2 | 161 | 2 | 20 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 20 | 1 |
| Montgomery | 0 | 0 | 0 | 0 | 110 | 2 | 20 | 2 | 0 | 0 | 130 | 4 | 265 | 2 | 0 | 0 | 0 | 1 | 42 | 3 | 0 | 0 | 307 | 6 | 0 | 0 | 0 | 0 | 78 | 3 | 0 | 0 | 0 | 0 | 78 | 3 | 250 | 1 | 0 | 0 | 157 | 3 | 0 | 0 | 32 | 1 | 439 | 5 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 163 | 2 | 163 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 179 | 3 | 179 | 3 | 70 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 70 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 124 | 1 | 124 | 1 |
| Muscatine | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 36 | 1 | 36 | 1 | 131 | 2 | 0 | 0 | 25 | 1 | 0 | 0 | 0 | 0 | 156 | 3 | 0 | 0 | 70 | 1 | 0 | 0 | 0 | 0 | 318 | 2 | 388 | 3 | 38 | 1 | 0 | 0 | 50 | 1 | 0 | 0 | 154 | 3 | 242 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 78 | 2 | 78 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 106 | 3 | 39 | 1 | 145 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 180 | 3 | 180 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 20 | 1 | 53 | 1 | 73 | 2 |
| O'Brien | 0 | 0 | 0 | 0 | 97 | 2 | 10 | 1 | 136 | 1 | 243 | 4 | 0 | 0 | 0 | 0 | 251 | 3 | 0 | 0 | 269 | 1 | 520 | 4 | 0 | 0 | 0 | 0 | 52 | 1 | 25 | 2 | 164 | 2 | 241 | 5 | 20 | 1 | 0 | 0 | 389 | 5 | 0 | 0 | 186 | 2 | 595 | 8 | 0 | 0 | 0 | 0 | 445 | 5 | 19 | 1 | 93 | 1 | 557 | 7 | 0 | 0 | 0 | 0 | 0 | 0 | 10 | 1 | 392 | 2 | 402 | 3 | 1 | 0 | 0 | 0 | 107 | 1 | 7 | 1 | 170 | 1 | 285 | 3 | 56 | 3 | 0 | 0 | 80 | 1 | 30 | 1 | 243 | 4 | 409 | 9 |
| Osceola | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 100 | 1 | 0 | 0 | 54 | 1 | 154 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 40 | 1 | 0 | 0 | 0 | 0 | 40 | 1 | 154 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 154 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 14 | 1 | 14 | 1 |
| Page | 35 | 1 | 0 | 0 | 25 | 1 | 0 | 0 | 0 | 0 | 60 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 100 | 1 | 0 | 0 | 554 | 2 | 654 | 3 | 50 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 618 | 3 | 668 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 203 | 2 | 203 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 198 | 4 | 198 | 4 | 725 | 25 | 0 | 0 | 50 | 1 | 0 | 0 | 0 | 0 | 775 | 26 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Palo Alto | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 34 | 1 | 465 | 2 | 499 | 3 | 0 | 0 | 0 | 0 | 75 | 1 | 15 | 1 | 98 | 1 | 188 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 643 | 2 | 648 | 3 | 320 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 320 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 36 | 1 | 0 | 0 | 0 | 0 | 36 | 1 |
| Plymouth | 0 | 0 | 0 | 0 | 50 | 1 | 0 | 1 | 75 | 1 | 125 | 3 | 7 | 1 | 0 | 0 | 147 | 1 | 15 | 1 | 406 | 2 | 575 | 5 | 0 | 0 | 0 | 0 | 62 | 2 | 10 | 1 | 0 | 0 | 72 | 3 | 802 | 5 | 0 | 0 | 292 | 4 | 0 | 0 | 128 | 3 | 1,222 | 12 | 0 | 0 | 0 | 0 | 220 | 3 | 0 | 0 | 246 | 3 | 466 | 6 | 2,018 | 8 | 0 | 0 | 0 | 0 | 1 | 1 | 158 | 5 | 2,177 | 14 | 2 | 0 | 0 | 0 | 144 | 2 | 59 | 3 | 227 | 3 | 432 | 8 | 1 | 1 | 0 | 0 | 0 | 0 | 105 | 1 | 0 | 1 | 106 | 3 |
| Pocahontas | 6 | 1 | 0 | 0 | 0 | 0 | 25 | 1 | 0 | 0 | 31 | 2 | 166 | 5 | 0 | 0 | 40 | 1 | 35 | 2 | 136 | 2 | 377 | 10 | 0 | 0 | 0 | 0 | 20 | 1 | 35 | 1 | 84 | 1 | 139 | 3 | 0 | 0 | 0 | 0 | 53 | 2 | 0 | 0 | 0 | 0 | 53 | 2 | 42 | 1 | 0 | 0 | 0 | 0 | 15 | 1 | 47 | 1 | 104 | 3 | 1 | 0 | 0 | 0 | 32 | 1 | 35 | 1 | 38 | 1 | 106 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 1 | 182 | 3 | 187 | 4 | 7 | 1 | 0 | 0 | 0 | 0 | 9 | 1 | 127 | 1 | 143 | 3 |
| Polk | 7,485 | 13 | 1,105 | 7 | 209 | 3 | 1,021 | 41 | 458 | 9 | 10,278 | 73 | 11,051 | 21 | 1,912 | 10 | 180 | 4 | 967 | 48 | 7,240 | 19 | 21,350 | 102 | 285 | 5 | 1,443 | 9 | 166 | 4 | 489 | 8 | 5,095 | 25 | 7,478 | 51 | 824 | 14 | 771 | 6 | 275 | 3 | 228 | 8 | 7,149 | 31 | 9,247 | 62 | 824 | 10 | 45 | 2 | 9 | 2 | 125 | 7 | 5,664 | 23 | 6,667 | 44 | 247 | 15 | 561 | 3 | 1 | 0 | 753 | 15 | 2,773 | 56 | 4,335 | 89 | 1,378 | 23 | 570 | 3 | 180 | 5 | 711 | 25 | 4,502 | 22 | 7,341 | 78 | 2,481 | 11 | 1,998 | 8 | 133 | 4 | 716 | 29 | 2,143 | 15 | 7,471 | 67 |
| Pottawattamie | 0 | 0 | 0 | 0 | 35 | 1 | 0 | 0 | 0 | 0 | 35 | 1 | 101 | 1 | 0 | 0 | 30 | 1 | 0 | 0 | 290 | 2 | 421 | 4 | 0 | 0 | 0 | 0 | 50 | 1 | 70 | 2 | 2,445 | 14 | 2,565 | 17 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 303 | 5 | 303 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 20 | 1 | 150 | 3 | 170 | 4 | 50 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 305 | 1 | 355 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 106 | 2 | 106 | 2 | 0 | 0 | 0 | 0 | 34 | 1 | 25 | 1 | 413 | 5 | 472 | 7 |
| Poweshiek | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 90 | 3 | 0 | 0 | 0 | 0 | 90 | 3 | 0 | 0 | 0 | 0 | 29 | 1 | 0 | 0 | 448 | 2 | 477 | 3 | 94 | 2 | 0 | 0 | 127 | 3 | 0 | 0 | 288 | 2 | 509 | 7 | 0 | 0 | 0 | 0 | 35 | 1 | 25 | 1 | 0 | 0 | 60 | 2 | 1 | 0 | 0 | 0 | 53 | 2 | 0 | 0 | 398 | 2 | 452 | 4 | 0 | 0 | 0 | 0 | 65 | 1 | 0 | 0 | 105 | 1 | 170 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Ringgold | 0 | 0 | 0 | 0 | 35 | 1 | 0 | 0 | 0 | 0 | 35 | 1 | 41 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 112 | 1 | 153 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 15 | 1 | 371 | 1 | 386 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 44 | 1 | 44 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 17 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 17 | 1 |
| Sac | 5 | 1 | 0 | 0 | 0 | 0 | 3 | 1 | 41 | 1 | 49 | 3 | 40 | 1 | 0 | 0 | 86 | 3 | 25 | 1 | 224 | 3 | 375 | 8 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 119 | 2 | 119 | 3 | 20 | 1 | 0 | 0 | 61 | 2 | 25 | 2 | 52 | 1 | 158 | 6 | 0 | 0 | 0 | 0 | 0 | 0 | 46 | 3 | 34 | 1 | 80 | 4 | 600 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 355 | 2 | 955 | 3 | 901 | 2 | 0 | 0 | 0 | 0 | 10 | 1 | 28 | 1 | 939 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Scott | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 382 | 2 | 382 | 2 | 0 | 0 | 0 | 0 | 268 | 4 | 0 | 0 | 89 | 2 | 357 | 6 | 124 | 1 | 0 | 0 | 68 | 2 | 0 | 0 | 818 | 8 | 1,010 | 11 | 0 | 0 | 0 | 0 | 213 | 2 | 0 | 0 | 407 | 3 | 620 | 5 | 63 | 2 | 0 | 0 | 181 | 2 | 0 | 0 | 1,256 | 5 | 1,500 | 9 | 0 | 0 | 0 | 0 | 42 | 1 | 0 | 0 | 177 | 4 | 219 | 5 | 31 | 2 | 180 | 1 | 121 | 1 | 139 | 3 | 211 | 6 | 682 | 13 | 47 | 1 | 35 | 1 | 0 | 0 | 143 | 1 | 106 | 2 | 331 | 5 |
| Shelby | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 34 | 1 | 0 | 0 | 34 | 1 | 0 | 0 | 0 | 0 | 80 | 1 | 15 | 1 | 156 | 1 | 251 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 115 | 1 | 115 | 1 | 112 | 1 | 0 | 0 | 150 | 2 | 0 | 0 | 238 | 2 | 500 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 82 | 1 | 82 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 1 | 0 | 0 | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Sioux | 0 | 0 | 0 | 0 | 300 | 3 | 0 | 0 | 89 | 1 | 389 | 4 | 0 | 0 | 0 | 0 | 1,845 | 3 | 39 | 1 | 96 | 1 | 1,980 | 5 | 60 | 1 | 0 | 0 | 133 | 3 | 113 | 4 | 753 | 4 | 1,059 | 12 | 88 | 2 | 0 | 0 | 346 | 3 | 0 | 0 | 530 | 3 | 964 | 8 | 50 | 1 | 0 | 0 | 25 | 1 | 185 | 3 | 24 | 1 | 284 | 6 | 7 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 562 | 4 | 570 | 6 | 7 | 0 | 0 | 0 | 165 | 1 | 0 | 0 | 123 | 2 | 295 | 3 | 0 | 0 | 0 | 0 | 81 | 3 | 3 | 1 | 164 | 4 | 248 | 8 |
| Story | 0 | 0 | 402 | 3 | 54 | 2 | 77 | 4 | 153 | 5 | 686 | 14 | 496 | 5 | 2,036 | 2 | 333 | 6 | 200 | 12 | 452 | 5 | 3,517 | 30 | 563 | 10 | 1,736 | 5 | 425 | 10 | 154 | 7 | 1,072 | 13 | 3,950 | 45 | 387 | 10 | 1,137 | 7 | 587 | 12 | 53 | 2 | 1,818 | 12 | 3,982 | 43 | 207 | 3 | 1,298 | 4 | 246 | 6 | 220 | 5 | 2,085 | 10 | 4,056 | 28 | 564 | 16 | 728 | 4 | 65 | 3 | 321 | 17 | 659 | 16 | 2,337 | 56 | 662 | 51 | 814 | 3 | 176 | 4 | 336 | 35 | 656 | 7 | 2,644 | 100 | 343 | 38 | 114 | 2 | 228 | 5 | 151 | 21 | 408 | 7 | 1,244 | 73 |
| Tama | 0 | 0 | 0 | 0 | 220 | 3 | 0 | 0 | 16 | 1 | 236 | 4 | 77 | 2 | 0 | 0 | 261 | 2 | 25 | 1 | 0 | 0 | 363 | 5 | 40 | 1 | 0 | 0 | 49 | 3 | 25 | 1 | 36 | 1 | 150 | 6 | 375 | 4 | 0 | 0 | 73 | 3 | 225 | 3 | 83 | 2 | 756 | 12 | 0 | 0 | 0 | 0 | 90 | 1 | 0 | 0 | 42 | 1 | 132 | 2 | 120 | 1 | 0 | 0 | 42 | 1 | 13 | 1 | 103 | 2 | 278 | 5 | 56 | 1 | 0 | 0 | 136 | 3 | 0 | 0 | 500 | 2 | 692 | 6 | 0 | 0 | 0 | 0 | 23 | 1 | 0 | 0 | 74 | 1 | 97 | 2 |
| Taylor | 0 | 0 | 0 | 0 | 45 | 1 | 37 | 1 | 0 | 0 | 82 | 2 | 20 | 6 | 0 | 0 | 61 | 2 | 47 | 3 | 0 | 0 | 128 | 11 | 30 | 3 | 0 | 0 | 135 | 3 | 15 | 3 | 121 | 1 | 301 | 10 | 238 | 4 | 0 | 0 | 14 | 2 | 21 | 2 | 71 | 1 | 344 | 9 | 0 | 0 | 0 | 0 | 50 | 1 | 0 | 0 | 78 | 1 | 128 | 2 | 258 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 282 | 2 | 540 | 4 | 723 | 4 | 0 | 0 | 53 | 2 | 30 | 2 | 98 | 2 | 904 | 10 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Union | 100 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 72 | 1 | 172 | 1 | 75 | 1 | 0 | 0 | 29 | 1 | 0 | 0 | 0 | 0 | 104 | 2 | 20 | 1 | 0 | 0 | 40 | 1 | 8 | 1 | 0 | 0 | 68 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 43 | 1 | 43 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 29 | 1 | 29 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 146 | 1 | 146 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Van Buren | 0 | 0 | 0 | 0 | 129 | 2 | 0 | 2 | 0 | 0 | 129 | 4 | 174 | 2 | 0 | 0 | 103 | 1 | 0 | 0 | 0 | 0 | 277 | 3 | 91 | 2 | 0 | 0 | 0 | 0 | 1 | 1 | 193 | 1 | 285 | 4 | 98 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 120 | 2 | 218 | 3 | 86 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 178 | 1 | 264 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 248 | 3 | 248 | 3 | 48 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 234 | 3 | 282 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Wapello | 0 | 0 | 0 | 0 | 127 | 4 | 0 | 0 | 0 | 0 | 127 | 4 | 0 | 0 | 0 | 0 | 25 | 1 | 64 | 2 | 138 | 3 | 227 | 6 | 20 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 83 | 1 | 103 | 2 | 0 | 0 | 0 | 0 | 110 | 3 | 7 | 1 | 1,292 | 3 | 1,409 | 7 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 488 | 3 | 488 | 3 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 316 | 5 | 319 | 5 | 10 | 0 | 0 | 0 | 0 | 0 | 14 | 1 | 1,099 | 3 | 1,123 | 4 | 0 | 0 | 0 | 0 | 30 | 1 | 0 | 0 | 162 | 2 | 192 | 3 |
| Warren | 50 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 50 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 41 | 1 | 74 | 1 | 115 | 2 | 61 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 85 | 1 | 146 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 752 | 2 | 752 | 2 | 53 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 58 | 1 | 111 | 2 | 29 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 54 | 1 | 83 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 23 | 1 | 23 | 1 | 0 | 0 | 0 | 0 | 65 | 1 | 0 | 0 | 262 | 3 | 327 | 4 |
| Washington | 0 | 0 | 0 | 0 | 130 | 2 | 20 | 1 | 100 | 1 | 250 | 4 | 149 | 3 | 0 | 0 | 137 | 4 | 91 | 3 | 264 | 2 | 641 | 12 | 129 | 4 | 0 | 0 | 74 | 2 | 48 | 1 | 385 | 6 | 636 | 13 | 60 | 2 | 0 | 0 | 203 | 4 | 37 | 3 | 233 | 4 | 533 | 13 | 110 | 2 | 0 | 0 | 236 | 5 | 8 | 1 | 362 | 3 | 716 | 11 | 0 | 0 | 0 | 0 | 45 | 2 | 0 | 1 | 233 | 3 | 278 | 6 | 179 | 103 | 0 | 0 | 24 | 1 | 14 | 1 | 8 | 1 | 225 | 106 | 1 | 1 | 0 | 0 | 84 | 2 | 0 | 0 | 190 | 3 | 275 | 6 |
| Wayne | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 124 | 1 | 124 | 1 | 44 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 37 | 1 | 81 | 2 | 73 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 53 | 1 | 126 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 48 | 1 | 48 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Webster | 0 | 0 | 0 | 0 | 86 | 1 | 0 | 0 | 44 | 1 | 130 | 2 | 30 | 1 | 0 | 0 | 194 | 3 | 25 | 1 | 63 | 2 | 312 | 7 | 340 | 3 | 0 | 0 | 0 | 0 | 21 | 1 | 122 | 1 | 483 | 5 | 147 | 2 | 0 | 0 | 206 | 4 | 39 | 3 | 378 | 3 | 770 | 12 | 0 | 0 | 0 | 0 | 90 | 1 | 20 | 1 | 53 | 1 | 163 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 260 | 3 | 260 | 3 | 200 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 123 | 2 | 323 | 4 | 1 | 0 | 0 | 0 | 22 | 1 | 35 | 1 | 158 | 2 | 216 | 4 |
| Winnebago | 0 | 0 | 0 | 0 | 0 | 0 | 47 | 2 | 0 | 0 | 47 | 2 | 0 | 0 | 0 | 0 | 25 | 1 | 0 | 0 | 124 | 1 | 149 | 2 | 0 | 0 | 0 | 0 | 30 | 1 | 0 | 0 | 0 | 0 | 30 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 99 | 2 | 99 | 2 | 62 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 702 | 3 | 764 | 4 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 67 | 1 | 69 | 1 | 50 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 71 | 1 | 121 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 97 | 2 | 97 | 2 |
| Winneshiek | 0 | 0 | 0 | 0 | 40 | 1 | 0 | 0 | 118 | 2 | 158 | 3 | 338 | 3 | 0 | 0 | 0 | 0 | 20 | 1 | 361 | 2 | 719 | 6 | 0 | 0 | 0 | 0 | 57 | 2 | 0 | 0 | 692 | 3 | 749 | 5 | 0 | 0 | 0 | 0 | 40 | 1 | 125 | 1 | 387 | 3 | 552 | 5 | 0 | 0 | 0 | 0 | 110 | 1 | 175 | 1 | 617 | 5 | 902 | 7 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 347 | 4 | 349 | 6 | 91 | 1 | 0 | 0 | 15 | 1 | 138 | 4 | 120 | 2 | 364 | 8 | 70 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 70 | 2 |
| Woodbury | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 188 | 1 | 0 | 0 | 187 | 2 | 0 | 0 | 96 | 1 | 471 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 805 | 2 | 805 | 2 | 20 | 1 | 0 | 0 | 45 | 1 | 0 | 0 | 66 | 2 | 131 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 539 | 3 | 539 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 75 | 1 | 9 | 1 | 84 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 475 | 4 | 475 | 4 | 0 | 0 | 0 | 0 | 28 | 1 | 3 | 1 | 35 | 1 | 66 | 3 |
| Worth | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 34 | 1 | 0 | 0 | 34 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 80 | 2 | 80 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 105 | 1 | 105 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Wright | 5 | 1 | 0 | 0 | 159 | 6 | 0 | 1 | 0 | 0 | 164 | 8 | 27 | 3 | 0 | 0 | 70 | 3 | 8 | 1 | 0 | 0 | 105 | 7 | 85 | 4 | 0 | 0 | 145 | 5 | 30 | 1 | 105 | 2 | 365 | 12 | 0 | 0 | 0 | 0 | 57 | 2 | 14 | 1 | 148 | 2 | 219 | 5 | 26 | 1 | 0 | 0 | 0 | 0 | 16 | 1 | 30 | 1 | 72 | 3 | 9 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 318 | 5 | 327 | 6 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 19 | 1 | 19 | 1 | 0 | 0 | 0 | 0 | 9 | 1 | 0 | 0 | 46 | 1 | 55 | 2 |
Appendix C
| HUC-8 Name | HUC-8 ID | No-Till (Acres) | Conservation Tillage (Acres) | Cover Crops (Acres) | Bioreactors and Saturated Buffers (Number) | Water Quality Wetlands (Number) | Structural Erosion Control Practices (Acres) |
|---|---|---|---|---|---|---|---|
| Blue Earth | 07020009 | 9,800 | 94,100 | 5,000 | 0 | 0 | 4 |
| Root | 07040008 | 600 | 700 | 200 | 0 | 0 | 0 |
| Coon-Yellow | 07060001 | 60,000 | 43,300 | 13,800 | 0 | 0 | 6,100 |
| Upper Iowa | 07060002 | 93,200 | 121,600 | 27,000 | 0 | 2 | 2,600 |
| Grant-Little Maquoketa | 07060003 | 43,400 | 44,900 | 16,200 | 0 | 0 | 980 |
| Turkey | 07060004 | 220,500 | 303,600 | 63,300 | 1 | 1 | 3,400 |
| Apple-Plum | 07060005 | 54,600 | 46,900 | 11,500 | 0 | 0 | 130 |
| Maquoketa | 07060006 | 226,600 | 332,600 | 52,900 | 3 | 1 | 3,700 |
| Copperas-Duck | 07080101 | 79,000 | 68,100 | 13,100 | 2 | 0 | 90 |
| Upper Wapsipinicon | 07080102 | 172,300 | 374,100 | 45,400 | 4 | 0 | 1,100 |
| Lower Wapsipinicon | 07080103 | 172,200 | 182,400 | 25,800 | 2 | 0 | 170 |
| Flint-Henderson | 07080104 | 46,900 | 83,800 | 9,000 | 1 | 0 | 3,300 |
| South Skunk | 07080105 | 250,200 | 364,300 | 46,400 | 26 | 13 | 3,500 |
| North Skunk | 07080106 | 188,400 | 123,900 | 28,600 | 2 | 2 | 3,800 |
| Skunk | 07080107 | 197,600 | 259,500 | 52,800 | 5 | 1 | 25,000 |
| Upper Cedar | 07080201 | 80,600 | 210,000 | 33,700 | 11 | 12 | 710 |
| Shell Rock | 07080202 | 66,900 | 180,400 | 23,900 | 0 | 6 | 150 |
| Winnebago | 07080203 | 23,500 | 138,700 | 9,000 | 0 | 6 | 0 |
| West Fork Cedar | 07080204 | 76,000 | 225,600 | 17,300 | 0 | 2 | 100 |
| Middle Cedar | 07080205 | 380,400 | 561,800 | 99,400 | 28 | 16 | 2,200 |
| Lower Cedar | 07080206 | 198,300 | 219,700 | 40,800 | 11 | 0 | 2,800 |
| Upper Iowa | 07080207 | 110,100 | 375,500 | 21,400 | 3 | 7 | 340 |
| Middle Iowa | 07080208 | 347,600 | 265,400 | 55,000 | 4 | 0 | 1,800 |
| Lower Iowa | 07080209 | 301,300 | 233,700 | 68,600 | 0 | 0 | 13,500 |
| Upper Des Moines | 07100002 | 32,900 | 257,300 | 12,000 | 1 | 10 | 140 |
| East Fork Des Moines | 07100003 | 32,500 | 287,700 | 14,300 | 0 | 5 | 40 |
| Middle Des Moines | 07100004 | 89,600 | 366,200 | 25,600 | 15 | 11 | 640 |
| Boone | 07100005 | 29,700 | 231,000 | 10,200 | 24 | 4 | 60 |
| North Raccoon | 07100006 | 236,100 | 502,100 | 49,000 | 32 | 20 | 1,500 |
| South Raccoon | 07100007 | 221,500 | 148,700 | 21,200 | 3 | 6 | 3,100 |
| Lake Red Rock | 07100008 | 358,500 | 225,900 | 34,000 | 78 | 2 | 12,500 |
| Lower Des Moines | 07100009 | 169,200 | 208,100 | 36,900 | 2 | 0 | 17,700 |
| Bear-Wyaconda | 07110001 | 18,500 | 24,800 | 5,400 | 0 | 0 | 7,800 |
| North Fabius | 07110002 | 5,900 | 7,500 | 1,800 | 0 | 0 | 1,100 |
| Lower Big Sioux | 10170203 | 104,300 | 144,200 | 16,900 | 0 | 0 | 5,200 |
| Rock | 10170204 | 91,000 | 166,400 | 18,200 | 2 | 1 | 3,000 |
| Blackbird-Soldier | 10230001 | 187,900 | 104,500 | 12,500 | 0 | 0 | 2,000 |
| Floyd | 10230002 | 154,600 | 208,200 | 22,500 | 6 | 0 | 7,700 |
| Little Sioux | 10230003 | 291,600 | 459,600 | 26,500 | 2 | 6 | 3,100 |
| Monona-Harrison Ditch | 10230004 | 218,300 | 146,500 | 15,000 | 0 | 0 | 2,000 |
| Maple | 10230005 | 128,800 | 131,600 | 9,100 | 0 | 0 | 2,100 |
| Big Papillion-Mosquito | 10230006 | 204,900 | 49,700 | 10,400 | 0 | 0 | 4,100 |
| Boyer | 10230007 | 330,400 | 155,400 | 20,300 | 2 | 1 | 8,600 |
| Keg-Weeping Water | 10240001 | 134,100 | 34,200 | 9,200 | 0 | 0 | 2,800 |
| West Nishnabotna | 10240002 | 584,900 | 144,200 | 34,900 | 4 | 0 | 14,500 |
| East Nishnabotna | 10240003 | 388,100 | 86,100 | 25,200 | 0 | 0 | 12,800 |
| Nishnabotna | 10240004 | 24,500 | 12,900 | 1,300 | 0 | 0 | 350 |
| Tarkio-Wolf | 10240005 | 101,200 | 28,300 | 6,500 | 0 | 0 | 8,600 |
| West Nodaway | 10240009 | 240,100 | 59,000 | 15,100 | 0 | 0 | 9,700 |
| Nodaway | 10240010 | 112,200 | 36,300 | 7,100 | 0 | 0 | 7,300 |
| Platte | 10240012 | 84,300 | 25,200 | 3,700 | 0 | 0 | 4,100 |
| One Hundred and Two | 10240013 | 97,200 | 28,600 | 4,100 | 0 | 0 | 3,900 |
| Upper Grand | 10280101 | 88,200 | 21,500 | 3,300 | 0 | 0 | 6,100 |
| Thompson | 10280102 | 158,100 | 58,100 | 15,000 | 0 | 0 | 13,300 |
| Lower Grand | 10280103 | 23,100 | 12,300 | 2,400 | 0 | 0 | 970 |
| Upper Chariton | 10280201 | 107,100 | 59,300 | 12,200 | 0 | 0 | 21,900 |
Note that in the table above, HUC8-level tillage and cover crop acreages are derived from USDA Census of Agriculture data (collected every five years) and reflect values for acres planted in the fall of 2022.
Appendix D
| HUC-12 Name | HUC-12 ID | Large Watershed | Medium Watershed | Small Catchment or Field-Scale | Small Watershed | Very Small Watershed | Tile |
|---|---|---|---|---|---|---|---|
| 101702040702 | 101702040702 | 0 | 0 | 0 | 1 | 0 | 0 |
| Aldrich Creek-Maple River | 102300050304 | 0 | 0 | 0 | 1 | 0 | 0 |
| Allen Creek-Des Moines River | 071000040702 | 1 | 0 | 0 | 0 | 0 | 0 |
| Allison Creek-Maquoketa River | 070600060210 | 0 | 1 | 0 | 0 | 0 | 0 |
| Alloway Creek-North Skunk River | 070801060103 | 0 | 0 | 0 | 1 | 0 | 0 |
| Ash Creek-Rock River | 101702040306 | 0 | 0 | 0 | 1 | 0 | 0 |
| Bacon Creek-Missouri River | 102300010305 | 0 | 0 | 0 | 2 | 0 | 0 |
| Badger Creek | 071000040403 | 0 | 0 | 0 | 1 | 0 | 0 |
| Badger Creek | 071000080402 | 0 | 0 | 0 | 1 | 0 | 0 |
| Ballinger Creek-South Skunk River | 070801051202 | 0 | 0 | 0 | 0 | 2 | 0 |
| Bays Branch | 071000070602 | 0 | 0 | 0 | 0 | 0 | 1 |
| Bear Creek | 070802051204 | 0 | 0 | 0 | 1 | 0 | 0 |
| Bear Creek | 071000070901 | 0 | 0 | 0 | 1 | 0 | 0 |
| Bear Creek | 071000040705 | 0 | 0 | 0 | 0 | 0 | 1 |
| Bear Creek | 102300031208 | 0 | 0 | 0 | 0 | 0 | 1 |
| Bear Creek School-Bear Creek | 071000090706 | 0 | 0 | 0 | 1 | 0 | 0 |
| Bear Creek-Cedar River | 070802051004 | 0 | 0 | 1 | 1 | 0 | 0 |
| Beaver Branch-Beaver Creek | 071000040906 | 0 | 0 | 0 | 1 | 0 | 0 |
| Beaver Creek | 071000040911 | 0 | 3 | 0 | 0 | 0 | 0 |
| Beaver Creek | 071000020803 | 0 | 0 | 1 | 0 | 0 | 2 |
| Beaver Creek | 070802070502 | 0 | 0 | 0 | 1 | 0 | 0 |
| Beaver Creek | 070802020702 | 0 | 0 | 0 | 0 | 0 | 3 |
| Bennett Creek-Iowa River | 070802080407 | 1 | 0 | 0 | 0 | 0 | 0 |
| Big Bear Creek | 070802080806 | 0 | 1 | 1 | 0 | 0 | 1 |
| Big Creek | 071000040803 | 0 | 0 | 0 | 1 | 0 | 0 |
| Big Hollow-Flint Creek | 070801041203 | 0 | 0 | 0 | 1 | 0 | 0 |
| Big Marsh State Wildlife Area-West Fork Cedar River | 070802040605 | 0 | 0 | 1 | 0 | 0 | 0 |
| Birch Creek-Sugar Creek | 071000091102 | 0 | 0 | 1 | 0 | 0 | 1 |
| Bitter Creek-Little Sioux River | 102300031411 | 1 | 0 | 0 | 0 | 0 | 0 |
| Black Cat Creek | 071000030504 | 0 | 0 | 0 | 1 | 0 | 0 |
| Black Hawk Park-Cedar River | 070802050703 | 1 | 0 | 0 | 1 | 0 | 0 |
| Blood Run | 101702031702 | 0 | 0 | 0 | 1 | 0 | 0 |
| Bloody Run | 070600011002 | 0 | 0 | 0 | 2 | 1 | 0 |
| Bloody Run-Cedar River | 070802011005 | 2 | 0 | 0 | 0 | 0 | 5 |
| Blue Creek | 070802051502 | 0 | 1 | 0 | 0 | 0 | 0 |
| Bluegrass Creek | 102400030203 | 0 | 0 | 0 | 1 | 0 | 0 |
| Bluff Creek | 071000040703 | 0 | 0 | 0 | 2 | 0 | 0 |
| Bluff Creek | 071000090503 | 0 | 0 | 0 | 1 | 0 | 0 |
| Brandywine Creek | 070801070902 | 0 | 1 | 0 | 1 | 1 | 0 |
| Brewers Creek | 071000050702 | 0 | 0 | 0 | 1 | 1 | 0 |
| Bridge Creek | 070801060602 | 0 | 0 | 0 | 1 | 0 | 0 |
| Britton Branch-Little River | 102801020701 | 0 | 0 | 0 | 1 | 0 | 0 |
| Brockamp Creek-Turkey River | 070600040309 | 0 | 0 | 0 | 1 | 0 | 0 |
| Brown Creek-Des Moines River | 071000090704 | 1 | 0 | 0 | 0 | 0 | 0 |
| Brush Creek | 070802080202 | 0 | 0 | 0 | 1 | 0 | 0 |
| Brush Creek-Big Creek | 070801070904 | 0 | 0 | 0 | 2 | 0 | 0 |
| Brushy Creek | 071000040504 | 0 | 0 | 0 | 1 | 0 | 0 |
| Buck Creek | 070801020504 | 0 | 0 | 0 | 1 | 0 | 0 |
| Buck Creek | 071000050502 | 0 | 0 | 0 | 1 | 0 | 0 |
| Buck Creek-North Fork Maquoketa River | 070600060803 | 0 | 1 | 0 | 0 | 0 | 0 |
| Buck Run | 071000060309 | 0 | 0 | 1 | 0 | 0 | 2 |
| Buckley Creek | 070801051201 | 0 | 1 | 0 | 0 | 1 | 0 |
| Buffalo Creek | 070802040301 | 0 | 0 | 0 | 0 | 0 | 1 |
| Buffalo Creek-Maple River | 102300050207 | 0 | 0 | 0 | 1 | 0 | 0 |
| Burr Oak Creek | 101702040801 | 0 | 0 | 0 | 1 | 0 | 0 |
| Burr Oak Creek-Little Sioux River | 102300031301 | 0 | 0 | 0 | 1 | 0 | 0 |
| Burr Oak Creek-Turkey River | 070600040308 | 0 | 1 | 0 | 0 | 0 | 0 |
| Bush Branch | 071000080606 | 0 | 0 | 0 | 0 | 1 | 0 |
| Buss Creek-Boyer River | 102300070306 | 0 | 0 | 0 | 1 | 0 | 0 |
| Buttrick Creek | 071000061204 | 0 | 0 | 0 | 1 | 0 | 0 |
| Byers Branch-Indian Creek | 070801050804 | 0 | 1 | 0 | 0 | 0 | 0 |
| Camp Creek | 071000060505 | 0 | 1 | 0 | 0 | 0 | 0 |
| Camp Creek-West Nishnabotna River | 102400020805 | 2 | 0 | 0 | 0 | 0 | 0 |
| Carlan Creek-Turkey River | 070600040902 | 3 | 0 | 0 | 0 | 0 | 0 |
| Catfish Creek | 070600050102 | 0 | 0 | 0 | 1 | 0 | 0 |
| Cattail Slough-Mississippi River | 070801010204 | 3 | 0 | 0 | 0 | 0 | 0 |
| Cedar Bend County Park-Cedar River | 070802011204 | 1 | 0 | 0 | 0 | 0 | 0 |
| Cedar Creek | 070801070710 | 0 | 2 | 0 | 2 | 0 | 0 |
| Cedar Creek | 071000060904 | 0 | 1 | 0 | 0 | 0 | 0 |
| Cedar Creek | 071000090310 | 0 | 2 | 0 | 0 | 0 | 0 |
| Cedar Creek | 070801071004 | 0 | 0 | 0 | 1 | 0 | 0 |
| Cedar Creek-North Fork Maquoketa River | 070600060804 | 0 | 1 | 0 | 0 | 0 | 0 |
| Cheslea Creek-Willow Creek | 070802030203 | 0 | 0 | 0 | 1 | 0 | 0 |
| City of Ames-South Skunk River | 070801050406 | 0 | 1 | 0 | 0 | 0 | 0 |
| City of Bouton-Beaver Creek | 071000040909 | 0 | 0 | 0 | 0 | 0 | 7 |
| City of Carroll-Middle Raccoon River | 071000070203 | 0 | 0 | 0 | 1 | 1 | 0 |
| City of Decorah-Upper Iowa River | 070600020404 | 0 | 1 | 0 | 0 | 0 | 0 |
| City of Emmetsburg-Des Moines River | 071000020404 | 1 | 0 | 0 | 0 | 0 | 0 |
| City of Guthrie Center-South Raccon River | 071000070404 | 0 | 1 | 0 | 0 | 0 | 0 |
| City of Mason City-Winnebago River | 070802030306 | 0 | 1 | 0 | 0 | 0 | 0 |
| City of Panora-Middle Raccoon River | 071000070603 | 0 | 2 | 0 | 0 | 0 | 0 |
| City of Prairie du Chien-Mississippi River | 070600011003 | 1 | 0 | 0 | 0 | 1 | 0 |
| City of Spencer-Little Sioux River | 102300030804 | 0 | 0 | 1 | 0 | 0 | 0 |
| Clear Creek | 070802030201 | 0 | 0 | 0 | 1 | 0 | 0 |
| Coal Creek-South Raccoon River | 071000070902 | 0 | 3 | 0 | 0 | 0 | 0 |
| Coon Creek | 070802050805 | 0 | 0 | 0 | 1 | 0 | 0 |
| Coon Creek-Iowa River | 070802080904 | 0 | 0 | 0 | 1 | 0 | 0 |
| Cooper Creek | 102802010403 | 0 | 0 | 0 | 1 | 0 | 0 |
| Coppers Creek-Des Moines River | 071000091206 | 4 | 0 | 0 | 1 | 0 | 0 |
| Cottonwood Drain | 070801041101 | 0 | 0 | 0 | 0 | 1 | 0 |
| County Ditch No 55 | 070802020106 | 0 | 0 | 0 | 1 | 0 | 0 |
| Crane Creek-Cedar River | 070802060806 | 3 | 0 | 0 | 0 | 0 | 0 |
| Crooked Creek | 071000040605 | 0 | 0 | 0 | 0 | 0 | 1 |
| Crow Creek | 070801010405 | 0 | 0 | 0 | 1 | 0 | 0 |
| Davis Creek | 070802090801 | 0 | 0 | 0 | 0 | 0 | 2 |
| Davisons Creek-Iowa River | 070802080405 | 0 | 1 | 0 | 0 | 0 | 0 |
| Deep River | 070802090403 | 0 | 0 | 0 | 1 | 0 | 0 |
| Deer Creek | 070802010403 | 0 | 0 | 0 | 1 | 0 | 0 |
| Devils Run | 070802090405 | 0 | 0 | 0 | 1 | 0 | 0 |
| Devils Run-Wolf Creek | 070802050808 | 0 | 0 | 0 | 1 | 0 | 0 |
| Dickerson Branch-Thompson River | 102801020601 | 0 | 2 | 0 | 1 | 0 | 0 |
| Ditch No 25-Iowa River | 070802091102 | 1 | 0 | 0 | 0 | 0 | 0 |
| Ditch Number 60 | 102300030703 | 0 | 0 | 0 | 1 | 0 | 0 |
| Doe Creek-Volga River | 070600040608 | 0 | 1 | 0 | 0 | 0 | 0 |
| Drainage Ditch 101-North Raccoon River | 071000060308 | 0 | 1 | 0 | 0 | 0 | 4 |
| Drainage Ditch 116-Prairie Creek | 071000050103 | 0 | 0 | 0 | 1 | 0 | 0 |
| Drainage Ditch 117 | 071000050101 | 0 | 0 | 0 | 1 | 0 | 0 |
| Drainage Ditch 13-Lake Creek | 071000060603 | 0 | 0 | 0 | 1 | 0 | 0 |
| Drainage Ditch 13-South Skunk River | 070801050903 | 0 | 2 | 0 | 0 | 0 | 0 |
| Drainage Ditch 148-Beaver Creek | 070802050203 | 0 | 0 | 0 | 0 | 1 | 0 |
| Drainage Ditch 171-North Raccoon River | 071000061405 | 2 | 0 | 0 | 0 | 0 | 0 |
| Drainage Ditch 19-Little Sioux River | 102300030305 | 0 | 1 | 1 | 0 | 0 | 0 |
| Drainage Ditch 1-Boone River | 071000050205 | 0 | 1 | 0 | 0 | 0 | 0 |
| Drainage Ditch 206 | 071000050703 | 0 | 0 | 0 | 2 | 0 | 1 |
| Drainage Ditch 20-Cedar Creek | 071000060208 | 0 | 1 | 0 | 0 | 0 | 0 |
| Drainage Ditch 25-North Raccoon River | 071000060802 | 0 | 0 | 1 | 0 | 0 | 1 |
| Drainage Ditch 3 | 070802011002 | 0 | 0 | 0 | 1 | 2 | 0 |
| Drainage Ditch 3 | 071000050603 | 0 | 0 | 0 | 1 | 0 | 1 |
| Drainage Ditch 32-Boone River | 071000050704 | 0 | 2 | 0 | 0 | 0 | 0 |
| Drainage Ditch 35-Des Moines River | 071000020903 | 2 | 0 | 1 | 0 | 0 | 1 |
| Drainage Ditch 44-Boone River | 071000050204 | 0 | 0 | 0 | 2 | 0 | 0 |
| Drainage Ditch 46-Boone River | 071000050605 | 0 | 1 | 0 | 0 | 0 | 0 |
| Drainage Ditch 4-Boone River | 071000050604 | 0 | 2 | 0 | 0 | 0 | 0 |
| Drainage Ditch 51-East Fork Des Moines River | 071000030802 | 0 | 1 | 0 | 0 | 0 | 0 |
| Drainage Ditch 62-Silver Creek | 071000020301 | 0 | 0 | 0 | 1 | 0 | 0 |
| Drainage Ditch 68-Boone River | 071000050606 | 0 | 1 | 0 | 0 | 0 | 0 |
| Drainage Ditch 71 | 070801050102 | 0 | 0 | 0 | 1 | 0 | 0 |
| Drainage Ditch 73-North Raccoon River | 071000060801 | 0 | 3 | 0 | 0 | 0 | 0 |
| Drainage Ditch 74-Cedar Creek | 071000060204 | 0 | 1 | 0 | 0 | 0 | 0 |
| Drainage Ditch 80 | 071000020501 | 0 | 0 | 0 | 1 | 0 | 0 |
| Drainage Ditch 9 | 071000050602 | 0 | 0 | 0 | 1 | 0 | 0 |
| Drainage Ditch 94-East Fork Des Moines River | 071000030806 | 0 | 1 | 0 | 0 | 0 | 0 |
| Drainage Ditch No 1 | 070802070102 | 0 | 0 | 0 | 1 | 0 | 0 |
| Drainage Ditch No 21 | 070200090401 | 0 | 0 | 0 | 0 | 0 | 1 |
| Drainage Ditch No 9-East Branch Iowa River | 070802070204 | 0 | 0 | 1 | 0 | 0 | 4 |
| Dry Branch-Iowa River | 070802080403 | 1 | 0 | 0 | 0 | 0 | 0 |
| Dry Creek | 070802051505 | 0 | 0 | 0 | 1 | 0 | 0 |
| Dry Run | 070802050701 | 0 | 0 | 0 | 2 | 0 | 0 |
| Dry Run | 102300030504 | 0 | 0 | 0 | 0 | 1 | 0 |
| Dry Run Creek | 101702040803 | 0 | 0 | 0 | 1 | 0 | 0 |
| Dudgeon Lake State Wildlife Management Area-Cedar River | 070802051105 | 1 | 0 | 0 | 1 | 0 | 1 |
| Dunns Creek-West Nodaway River | 102400090603 | 0 | 0 | 0 | 1 | 0 | 0 |
| Dutch Creek-Wapsipinicon River | 070801030201 | 1 | 0 | 0 | 0 | 0 | 0 |
| Eagle Creek | 071000050403 | 0 | 1 | 0 | 0 | 0 | 0 |
| East Branch Blue Creek | 070802051501 | 0 | 1 | 0 | 0 | 0 | 0 |
| East Branch Boone River | 071000050203 | 0 | 0 | 0 | 1 | 0 | 2 |
| East Branch Iowa River | 070802070205 | 0 | 0 | 0 | 1 | 0 | 0 |
| East Branch Panther Creek | 071000070802 | 0 | 0 | 0 | 0 | 0 | 1 |
| East Branch Salt Creek | 070802080505 | 0 | 0 | 0 | 0 | 0 | 1 |
| East Buttrick Creek | 071000061102 | 0 | 0 | 0 | 1 | 0 | 0 |
| East Cedar Creek | 071000060903 | 0 | 0 | 0 | 0 | 0 | 11 |
| East Fork Des Moines River | 071000030903 | 1 | 0 | 0 | 0 | 0 | 0 |
| East Indian Creek | 070801050604 | 0 | 0 | 0 | 1 | 0 | 0 |
| East Nodaway River | 102400100110 | 0 | 2 | 0 | 0 | 0 | 0 |
| East Okoboji Lake | 102300030203 | 0 | 0 | 0 | 3 | 0 | 0 |
| East Otter Creek-Otter Creek | 070802051302 | 0 | 0 | 0 | 0 | 1 | 0 |
| Elk Creek | 102300031101 | 0 | 0 | 1 | 0 | 0 | 0 |
| Elk Creek | 102801020402 | 0 | 0 | 0 | 1 | 0 | 0 |
| Elk Run | 070802050901 | 0 | 1 | 0 | 0 | 0 | 0 |
| Elk Run-North Raccoon River | 071000060804 | 0 | 1 | 4 | 2 | 2 | 9 |
| Elliott Creek | 102300040401 | 0 | 0 | 0 | 1 | 0 | 0 |
| Elm Lake State Game Management Area-Iowa River | 070802070302 | 0 | 1 | 0 | 0 | 0 | 1 |
| Emery Creek | 101702040605 | 0 | 0 | 0 | 1 | 0 | 0 |
| English Creek | 071000090102 | 0 | 0 | 0 | 1 | 0 | 0 |
| English River | 070802090606 | 0 | 1 | 0 | 0 | 1 | 0 |
| Etter Creek-Wapsipinicon River | 070801020601 | 0 | 1 | 0 | 0 | 0 | 0 |
| Fannys Branch-North Raccoon River | 071000061501 | 0 | 0 | 0 | 0 | 0 | 2 |
| Felters Branch-Middle River | 071000080701 | 0 | 2 | 0 | 0 | 0 | 0 |
| Floyd River | 102300020504 | 0 | 3 | 0 | 0 | 0 | 0 |
| Fourmile Creek | 070802050804 | 0 | 0 | 0 | 1 | 0 | 0 |
| Fourmile Creek | 102801020207 | 0 | 0 | 0 | 1 | 0 | 0 |
| Fourmile Creek-East Nishnabotna River | 102400030706 | 1 | 0 | 0 | 1 | 0 | 0 |
| French Hollow-Turkey River | 070600040709 | 0 | 1 | 0 | 1 | 1 | 0 |
| Frog Creek-North Raccoon River | 071000061503 | 1 | 0 | 0 | 0 | 0 | 1 |
| Frog Hollow | 070600040505 | 0 | 0 | 0 | 1 | 0 | 0 |
| German Creek | 070801060603 | 0 | 0 | 0 | 1 | 0 | 0 |
| Gizzard Creek | 070802011004 | 0 | 0 | 0 | 0 | 1 | 0 |
| Gran Creek-Beaver Creek | 070802050204 | 0 | 0 | 0 | 1 | 0 | 0 |
| Greenbrier Creek | 071000061302 | 0 | 0 | 1 | 1 | 0 | 1 |
| Gypsum Creek-Des Moines River | 071000040604 | 1 | 0 | 0 | 0 | 0 | 0 |
| Hainer Creek-Maquoketa River | 070600061005 | 2 | 0 | 0 | 0 | 0 | 0 |
| Halfway Creek | 102300050202 | 0 | 0 | 0 | 0 | 1 | 0 |
| Hammers Creek-Beaver Creek | 070802050304 | 0 | 2 | 0 | 1 | 0 | 0 |
| Hardin Creek | 071000061005 | 0 | 1 | 1 | 0 | 0 | 2 |
| Harris Grove Creek-Boyer River | 102300070604 | 0 | 2 | 0 | 0 | 0 | 0 |
| Hawleyville Cemetary-East Nodaway River | 102400100109 | 0 | 0 | 0 | 0 | 0 | 1 |
| Headwaters Beaver Creek | 070802050201 | 1 | 0 | 0 | 0 | 0 | 0 |
| Headwaters Beaver Creek | 070802030107 | 0 | 0 | 0 | 1 | 0 | 0 |
| Headwaters Beaver Creek | 071000040905 | 0 | 0 | 0 | 0 | 0 | 1 |
| Headwaters Big Creek | 070801070901 | 0 | 0 | 0 | 1 | 0 | 0 |
| Headwaters Black Hawk Creek | 070802050502 | 0 | 0 | 0 | 0 | 1 | 0 |
| Headwaters Boone River | 071000050201 | 0 | 0 | 0 | 0 | 0 | 1 |
| Headwaters Cedar Creek | 070801070601 | 0 | 1 | 0 | 1 | 0 | 1 |
| Headwaters Cedar Creek | 071000060202 | 0 | 0 | 4 | 0 | 0 | 5 |
| Headwaters Deep Creek | 070600060901 | 0 | 0 | 0 | 0 | 1 | 0 |
| Headwaters Deer Creek | 070802080301 | 0 | 0 | 0 | 1 | 0 | 0 |
| Headwaters Eagle Creek | 071000050402 | 0 | 0 | 0 | 1 | 0 | 0 |
| Headwaters East Branch Iowa River | 070802070203 | 0 | 0 | 0 | 0 | 1 | 0 |
| Headwaters East Nishnabotna River | 102400030201 | 0 | 0 | 0 | 0 | 0 | 3 |
| Headwaters East Nodaway River | 102400100102 | 0 | 0 | 0 | 1 | 0 | 0 |
| Headwaters English Creek | 071000090101 | 0 | 0 | 0 | 1 | 0 | 0 |
| Headwaters Flood Creek | 070802020501 | 0 | 0 | 0 | 1 | 0 | 0 |
| Headwaters Hardin Creek | 071000061001 | 0 | 0 | 0 | 1 | 0 | 0 |
| Headwaters Honey Creek | 070802070701 | 0 | 0 | 0 | 0 | 1 | 0 |
| Headwaters Jack Creek | 071000020202 | 0 | 0 | 0 | 1 | 0 | 0 |
| Headwaters Middle Creek | 070801060301 | 0 | 0 | 0 | 1 | 0 | 0 |
| Headwaters Middle Fork One Hundred and Two River | 102400130103 | 0 | 0 | 0 | 0 | 0 | 2 |
| Headwaters Miller Creek | 070802050904 | 0 | 1 | 0 | 0 | 1 | 0 |
| Headwaters North English River | 070802090401 | 0 | 0 | 0 | 1 | 0 | 0 |
| Headwaters North Fork Black Hawk Creek | 070802050402 | 0 | 0 | 0 | 1 | 0 | 0 |
| Headwaters North Raccoon River | 071000060301 | 0 | 0 | 1 | 0 | 0 | 1 |
| Headwaters Otter Creek | 071000050302 | 0 | 0 | 0 | 1 | 0 | 1 |
| Headwaters Prairie Creek | 071000050102 | 0 | 0 | 0 | 1 | 0 | 0 |
| Headwaters South Beaver Creek | 070802050102 | 0 | 0 | 0 | 0 | 1 | 0 |
| Headwaters South Fork Iowa River | 070802070601 | 0 | 0 | 0 | 0 | 1 | 0 |
| Headwaters Tarkio River | 102400050602 | 0 | 0 | 0 | 0 | 3 | 0 |
| Headwaters Tipton Creek | 070802070401 | 0 | 0 | 0 | 0 | 0 | 2 |
| Headwaters Twelvemile Creek | 102801020101 | 0 | 0 | 0 | 1 | 0 | 0 |
| Headwaters West Branch Iowa River | 070802070101 | 0 | 0 | 0 | 1 | 0 | 0 |
| Headwaters West Branch One Hundred Two River | 102400130202 | 0 | 0 | 0 | 0 | 0 | 1 |
| Headwaters West Buttrick Creek | 071000061202 | 0 | 0 | 0 | 0 | 0 | 2 |
| Headwaters West Fork One Hundred Two River | 102400130204 | 0 | 0 | 0 | 0 | 0 | 1 |
| Headwaters West Nodaway River | 102400090401 | 0 | 0 | 0 | 1 | 0 | 0 |
| Headwaters White Breast Creek | 071000081302 | 0 | 0 | 0 | 1 | 0 | 0 |
| Headwaters White Fox Creek | 071000050501 | 0 | 0 | 0 | 2 | 1 | 0 |
| Heisler Creek-Maple River | 102300050308 | 0 | 2 | 0 | 0 | 0 | 0 |
| Henry Creek-Little Sioux River | 102300031109 | 0 | 0 | 0 | 0 | 1 | 0 |
| Hickory Creek | 070801030301 | 0 | 0 | 1 | 0 | 0 | 2 |
| Hickory Creek-Chariton River | 102802010405 | 0 | 1 | 0 | 0 | 0 | 0 |
| Hickory Creek-North Raccoon River | 071000061505 | 1 | 0 | 0 | 0 | 0 | 0 |
| Hinkle Creek | 070802051102 | 0 | 0 | 0 | 1 | 0 | 0 |
| Holland Creek | 070802050501 | 0 | 0 | 0 | 0 | 1 | 0 |
| Honey Creek | 070801070304 | 0 | 0 | 0 | 1 | 0 | 0 |
| Honey Creek-Des Moines River | 071000040706 | 0 | 0 | 0 | 0 | 1 | 0 |
| Honey Creek-Volga River | 070600040606 | 0 | 1 | 0 | 0 | 0 | 0 |
| Indian Creek | 070802050903 | 0 | 1 | 0 | 0 | 0 | 0 |
| Indian Creek | 071000020902 | 0 | 0 | 1 | 0 | 0 | 3 |
| Indian Creek | 070802060103 | 0 | 0 | 0 | 1 | 0 | 0 |
| Indian Creek-North Raccoon River | 071000060403 | 0 | 0 | 0 | 1 | 0 | 0 |
| Iowa Lake | 070200090601 | 0 | 0 | 0 | 1 | 0 | 0 |
| Jefferies Creek-Thompson River | 102801020603 | 0 | 0 | 0 | 1 | 0 | 0 |
| Jefferson Cemetary-Middle River | 071000080605 | 0 | 0 | 1 | 0 | 0 | 0 |
| Jim Creek-West Nishnabotna River | 102400020501 | 0 | 1 | 0 | 0 | 0 | 0 |
| Johnson Creek | 070802050301 | 0 | 0 | 0 | 1 | 0 | 0 |
| Johnson Creek-Mill Creek | 102300031205 | 0 | 0 | 0 | 1 | 0 | 0 |
| Johnson Creek-Raccoon River | 071000061702 | 2 | 0 | 0 | 0 | 0 | 0 |
| Joint Drainage Ditch 3-Boone River | 071000050601 | 0 | 1 | 0 | 0 | 0 | 0 |
| Jordan Creek-Raccoon River | 071000061703 | 3 | 0 | 0 | 2 | 0 | 0 |
| Kanaranzi Creek | 101702040205 | 0 | 0 | 0 | 1 | 0 | 0 |
| Keg Creek Ditch | 102400010105 | 0 | 0 | 0 | 0 | 1 | 0 |
| Keigley Branch | 070801050405 | 0 | 0 | 0 | 1 | 0 | 0 |
| Kemp Creek | 102400100106 | 0 | 0 | 0 | 1 | 0 | 0 |
| Kettle Creek-Des Moines River | 071000090709 | 2 | 0 | 0 | 1 | 0 | 0 |
| Kickapoo Slu-Mississippi River | 070801010601 | 0 | 0 | 0 | 1 | 0 | 0 |
| Kirk Branch-White Breast Creek | 071000081403 | 0 | 2 | 0 | 0 | 0 | 0 |
| Klondike Creek | 101702031901 | 0 | 0 | 0 | 2 | 0 | 0 |
| Lake Creek | 071000060605 | 0 | 1 | 0 | 0 | 0 | 0 |
| Lake MacBride-Mill Creek | 070802081008 | 0 | 0 | 0 | 1 | 1 | 0 |
| Lake Manawa-Missouri River | 102300060602 | 0 | 0 | 0 | 1 | 0 | 0 |
| Lake Panorama-Middle Raccoon River | 071000070601 | 0 | 2 | 0 | 1 | 0 | 1 |
| Lake Quinnebaugh-Missouri River | 102300010407 | 0 | 0 | 0 | 1 | 0 | 0 |
| Lake Rathbun-Chariton River | 102802010209 | 0 | 0 | 0 | 1 | 0 | 0 |
| Lateral 2 | 071000060304 | 0 | 0 | 2 | 1 | 0 | 10 |
| Lateral 3-North Raccoon River | 071000060306 | 0 | 1 | 0 | 0 | 0 | 0 |
| Lateral 6-North Raccoon River | 071000060303 | 0 | 0 | 1 | 0 | 0 | 1 |
| Lime Creek | 070802051003 | 0 | 0 | 0 | 0 | 1 | 0 |
| Little Bear Creek | 070802051203 | 0 | 0 | 0 | 1 | 0 | 0 |
| Little Beaver Creek-Beaver Creek | 071000040908 | 0 | 0 | 0 | 0 | 0 | 2 |
| Little Cedar Creek | 071000060103 | 0 | 0 | 1 | 1 | 0 | 1 |
| Little Cedar Creek | 070801070707 | 0 | 0 | 0 | 1 | 0 | 0 |
| Little Cedar River | 070802010903 | 0 | 1 | 0 | 0 | 0 | 0 |
| Little Eagle Creek | 071000050401 | 0 | 0 | 0 | 1 | 0 | 0 |
| Little Floyd River | 102300020302 | 0 | 0 | 0 | 0 | 2 | 0 |
| Little Sioux River | 102300031510 | 3 | 1 | 0 | 0 | 0 | 0 |
| Little White Breast Creek | 071000081305 | 0 | 0 | 0 | 1 | 1 | 0 |
| Little Wolf Creek | 070802050802 | 0 | 1 | 0 | 0 | 0 | 0 |
| Long Branch-South Raccoon River | 071000070704 | 0 | 1 | 0 | 0 | 0 | 0 |
| Lost Branch-Chariton River | 102802010207 | 0 | 1 | 0 | 0 | 0 | 0 |
| Lost Creek | 070801030606 | 0 | 0 | 0 | 1 | 0 | 0 |
| Lost Island Outlet | 102300030704 | 0 | 0 | 0 | 1 | 0 | 0 |
| Lower Brushy Creek | 071000070303 | 0 | 1 | 1 | 0 | 0 | 2 |
| Lower Clear Creek | 070802090103 | 0 | 0 | 0 | 2 | 0 | 0 |
| Lower Duck Creek | 070801010302 | 0 | 0 | 0 | 1 | 0 | 0 |
| Lower East Boyer River | 102300070103 | 0 | 0 | 0 | 1 | 0 | 0 |
| Lower East Fork One Hundred Two River | 102400130104 | 0 | 0 | 0 | 2 | 0 | 1 |
| Lower Fourmile Creek | 071000080103 | 0 | 0 | 0 | 1 | 0 | 0 |
| Lower Indian Creek | 102400020402 | 0 | 0 | 0 | 1 | 0 | 0 |
| Lower Little Maquoketa River | 070600030604 | 0 | 0 | 0 | 0 | 1 | 0 |
| Lower Lizard Creek | 071000040303 | 0 | 1 | 0 | 0 | 0 | 0 |
| Lower Mosquito Creek | 071000070502 | 0 | 1 | 0 | 0 | 0 | 0 |
| Lower Mud Creek | 101702040403 | 0 | 0 | 0 | 2 | 0 | 0 |
| Lower South Branch Lizard Creek | 071000040204 | 0 | 0 | 0 | 0 | 0 | 1 |
| Lower South Fork Chariton River | 102802010108 | 0 | 1 | 0 | 0 | 0 | 0 |
| Lower South Fork Iowa River | 070802070604 | 0 | 3 | 0 | 0 | 0 | 0 |
| Lower Squaw Creek | 071000080804 | 0 | 0 | 0 | 1 | 0 | 0 |
| Lower West Fork Middle Nodaway River | 102400090104 | 0 | 0 | 0 | 1 | 0 | 0 |
| Lower Willow Creek | 071000070104 | 0 | 1 | 0 | 0 | 0 | 0 |
| Lower Yellow River | 070600010906 | 0 | 3 | 0 | 0 | 0 | 0 |
| Lynn Creek-Big Creek | 070801070905 | 1 | 0 | 0 | 0 | 2 | 0 |
| Lyons Creek | 071000050701 | 0 | 0 | 0 | 1 | 0 | 0 |
| Malone Creek-Wapsipinicon River | 070801020803 | 1 | 0 | 0 | 0 | 0 | 0 |
| Marrowbone Creek-North Raccoon River | 071000060806 | 2 | 0 | 2 | 1 | 0 | 1 |
| Martha Creek-Upper Iowa River | 070600020206 | 0 | 1 | 0 | 0 | 0 | 0 |
| Martin Area County Park-Little Sioux River | 102300031302 | 1 | 0 | 0 | 0 | 0 | 0 |
| Max Creek-Beaver Creek | 070802050303 | 0 | 0 | 0 | 0 | 1 | 0 |
| McDonald Creek-Wapsipinicon River | 070801030605 | 2 | 1 | 0 | 0 | 0 | 0 |
| McFarlane State Park-Cedar River | 070802051005 | 0 | 0 | 0 | 0 | 0 | 5 |
| Mead Creek-Little Wapsipinicon River | 070801020102 | 0 | 0 | 0 | 0 | 1 | 0 |
| Middle Branch Boone River | 071000050202 | 0 | 0 | 0 | 1 | 0 | 0 |
| Middle Branch One Hundred and Two River | 102400130201 | 0 | 0 | 0 | 1 | 0 | 0 |
| Middle Brushy Creek | 071000070302 | 0 | 0 | 0 | 2 | 0 | 3 |
| Middle Clear Creek | 070802090102 | 0 | 0 | 0 | 3 | 0 | 0 |
| Middle East Branch West Nishnabotna River | 102400020104 | 0 | 0 | 0 | 1 | 1 | 0 |
| Middle East Fork One Hundred Two River | 102400130102 | 0 | 0 | 0 | 0 | 0 | 2 |
| Middle Fork Little Maquoketa River | 070600030601 | 0 | 0 | 0 | 1 | 0 | 0 |
| Middle Fork One Hundred and Two River | 102400130105 | 0 | 0 | 1 | 0 | 0 | 2 |
| Middle Fork South Beaver Creek | 070802050101 | 0 | 0 | 0 | 0 | 1 | 0 |
| Middle Fourmile Creek | 071000080102 | 0 | 0 | 0 | 1 | 0 | 0 |
| Middle Mud Creek | 101702040402 | 0 | 0 | 0 | 1 | 0 | 0 |
| Middle Soap Creek | 071000090605 | 0 | 0 | 0 | 1 | 0 | 0 |
| Middle Troublesome Creek | 102400030103 | 0 | 0 | 0 | 1 | 0 | 0 |
| Middle West Fork Crooked Creek | 070801070102 | 0 | 0 | 0 | 1 | 0 | 0 |
| Middle Willow Creek | 102300070402 | 0 | 0 | 0 | 1 | 0 | 0 |
| Milford Creek | 102300030204 | 0 | 1 | 0 | 3 | 0 | 0 |
| Mill Creek | 102300070305 | 0 | 0 | 0 | 1 | 0 | 0 |
| Mill Creek-Cedar River | 070802060405 | 1 | 0 | 0 | 0 | 0 | 0 |
| Mill Race-Iowa River | 070802081003 | 1 | 0 | 0 | 0 | 0 | 0 |
| Miller Creek | 070802050905 | 0 | 1 | 1 | 1 | 0 | 2 |
| Miller Creek-South Skunk River | 070801050402 | 0 | 0 | 0 | 1 | 0 | 0 |
| Mineral Creek | 070600060409 | 0 | 0 | 0 | 1 | 0 | 0 |
| Minnehaha Creek-Black Hawk Creek | 070802050504 | 0 | 0 | 0 | 1 | 0 | 0 |
| Monona-Harrison Ditch | 102300040503 | 0 | 1 | 0 | 0 | 0 | 0 |
| Moon Creek | 070801060402 | 0 | 0 | 0 | 1 | 0 | 0 |
| Moon Creek-Rock River | 101702040703 | 0 | 1 | 0 | 1 | 0 | 0 |
| Morgan Creek | 070802051506 | 0 | 0 | 0 | 2 | 1 | 0 |
| Mormon Branch-East Nishnabotna River | 102400030702 | 0 | 1 | 0 | 0 | 0 | 0 |
| Moser Creek-Mosquito Creek | 102300060401 | 0 | 0 | 0 | 1 | 0 | 0 |
| Mosquito Creek | 070802050503 | 0 | 0 | 0 | 1 | 0 | 0 |
| Mud Creek | 070802051104 | 0 | 1 | 0 | 2 | 3 | 0 |
| Mud Creek-Prairie Creek | 070802051403 | 0 | 0 | 0 | 0 | 1 | 0 |
| Murphy Branch-Des Moines River | 071000041001 | 0 | 0 | 0 | 0 | 0 | 3 |
| Negro Creek-Silver Creek | 070801030601 | 0 | 0 | 0 | 0 | 1 | 0 |
| Nelson Creek-Cedar River | 070802051504 | 0 | 0 | 0 | 1 | 0 | 0 |
| Neola Creek-Mosquito Creek | 102300060404 | 0 | 0 | 0 | 1 | 1 | 0 |
| Nishnabotna River | 102400040202 | 1 | 0 | 0 | 1 | 0 | 0 |
| No Business Creek-West Nodaway River | 102400090703 | 0 | 3 | 0 | 0 | 0 | 0 |
| Nodaway Lake-Middle Nodaway River | 102400090201 | 0 | 0 | 0 | 2 | 0 | 0 |
| North Beaver Creek | 070802050202 | 0 | 0 | 0 | 0 | 1 | 0 |
| North Branch Big Creek-Big Creek | 070801070903 | 0 | 2 | 0 | 1 | 1 | 0 |
| North Fork Black Hawk Creek | 070802050403 | 0 | 0 | 0 | 1 | 0 | 0 |
| North Fork Little Maquoketa River | 070600030602 | 0 | 0 | 0 | 1 | 0 | 0 |
| North Fork Long Creek | 070802090901 | 0 | 0 | 0 | 1 | 0 | 0 |
| North River | 071000080405 | 0 | 2 | 0 | 0 | 0 | 0 |
| North Skunk River | 070801060604 | 0 | 1 | 0 | 0 | 0 | 0 |
| Ocheyedan River | 102300030510 | 0 | 1 | 0 | 0 | 0 | 0 |
| Old Womans Creek-Old Mans Creek | 070802090207 | 0 | 2 | 0 | 0 | 0 | 0 |
| Opossum Creek | 070802051201 | 0 | 0 | 0 | 1 | 0 | 0 |
| Osterman Creek-Ocheyedan River | 102300030503 | 0 | 0 | 0 | 1 | 0 | 0 |
| Otter Creek | 071000050303 | 0 | 0 | 0 | 1 | 0 | 0 |
| Otter Creek | 101702040505 | 0 | 0 | 0 | 1 | 1 | 0 |
| Otter Creek-Iowa River | 070802091104 | 4 | 0 | 0 | 0 | 0 | 0 |
| Otterville Bridge State Access-Wapsipinicon River | 070801020801 | 0 | 1 | 0 | 0 | 0 | 0 |
| Our Saviors Church-Big Sioux River | 101702031903 | 0 | 1 | 0 | 0 | 0 | 0 |
| Outlet Creek | 071000060307 | 0 | 0 | 0 | 3 | 0 | 0 |
| Outlet South Raccoon River | 071000070904 | 1 | 0 | 0 | 0 | 0 | 0 |
| Paint Creek-Upper Iowa River | 070600020602 | 0 | 3 | 0 | 0 | 0 | 0 |
| Panther Creek | 071000070803 | 0 | 0 | 0 | 1 | 0 | 0 |
| Parnell Creek-Little Sioux River | 102300031506 | 1 | 0 | 0 | 0 | 0 | 0 |
| Peters Creek-Flood Creek | 070802020503 | 0 | 0 | 0 | 0 | 0 | 1 |
| Phelps Creek-Beaver Creek | 070802050302 | 0 | 0 | 0 | 0 | 1 | 0 |
| Picayune Creek-Sugar Creek | 070801041602 | 0 | 2 | 0 | 1 | 0 | 0 |
| Pickerel Run | 102300030702 | 0 | 0 | 0 | 1 | 0 | 0 |
| Pilot Creek | 071000020703 | 0 | 0 | 0 | 0 | 0 | 5 |
| Pine Creek | 070801020802 | 0 | 0 | 0 | 0 | 1 | 0 |
| Pine Creek-Iowa River | 070802070902 | 0 | 2 | 0 | 2 | 0 | 0 |
| Pitman Creek-Sugar Creek | 070801041604 | 0 | 0 | 0 | 2 | 0 | 0 |
| Pleasant Creek-North Skunk River | 070801060404 | 0 | 0 | 0 | 1 | 0 | 0 |
| Pleasant Run-Cedar River | 070802060401 | 1 | 1 | 0 | 0 | 0 | 0 |
| Poor Farm Creek | 071000060305 | 0 | 0 | 0 | 1 | 0 | 0 |
| Poyner Creek | 070802050902 | 0 | 0 | 0 | 0 | 1 | 0 |
| Prairie Creek | 071000040603 | 0 | 0 | 3 | 2 | 0 | 3 |
| Prairie Creek | 070802051405 | 0 | 0 | 0 | 1 | 0 | 0 |
| Prairie Creek | 071000060205 | 0 | 0 | 0 | 1 | 0 | 0 |
| Prairie Creek | 071000060803 | 0 | 0 | 0 | 1 | 0 | 1 |
| Prairie Creek | 102300030803 | 0 | 0 | 0 | 1 | 0 | 0 |
| Prairie Creek-Boone River | 071000050705 | 0 | 2 | 0 | 0 | 1 | 0 |
| Prairie Creek-Cedar River | 070802051103 | 0 | 1 | 0 | 0 | 0 | 0 |
| Prairie Creek-Iowa River | 070802090806 | 2 | 0 | 0 | 0 | 0 | 0 |
| Prairie Creek-Skunk River | 070801071002 | 0 | 0 | 0 | 1 | 1 | 0 |
| Pratt Creek | 070802051101 | 0 | 0 | 0 | 1 | 1 | 0 |
| Prescotts Creek-Black Hawk Creek | 070802050602 | 0 | 1 | 0 | 2 | 0 | 0 |
| Price Creek-Des Moines River | 071000090501 | 2 | 0 | 0 | 0 | 0 | 0 |
| Pumpkin Creek-Maquoketa River | 070600061001 | 0 | 1 | 0 | 0 | 0 | 0 |
| Purgatory Creek | 071000060702 | 0 | 0 | 0 | 1 | 0 | 0 |
| Rainbow Bend County Park-North Raccoon River | 071000060805 | 1 | 0 | 3 | 0 | 0 | 3 |
| Ralston Creek-Iowa River | 070802090703 | 3 | 0 | 1 | 0 | 2 | 0 |
| Ramsey Creek-English River | 070802090605 | 0 | 1 | 0 | 0 | 0 | 0 |
| Rapid Creek | 070802090701 | 0 | 0 | 0 | 1 | 0 | 0 |
| Richland Creek | 070802080701 | 0 | 0 | 0 | 1 | 0 | 0 |
| Rock Creek | 070802050806 | 0 | 1 | 0 | 0 | 0 | 0 |
| Rock Creek | 070802010604 | 0 | 0 | 0 | 0 | 0 | 2 |
| Rock Creek-Cedar River | 070802051001 | 0 | 0 | 0 | 1 | 1 | 1 |
| Rock Creek-Des Moines River | 071000041002 | 1 | 1 | 0 | 0 | 0 | 0 |
| Rock Creek-North Skunk River | 070801060104 | 0 | 0 | 0 | 1 | 0 | 0 |
| Rock River | 101702040805 | 1 | 0 | 0 | 0 | 0 | 0 |
| Rogg Creek-Rock River | 101702040804 | 2 | 0 | 0 | 0 | 0 | 0 |
| Rollins Creek-Des Moines River | 071000091209 | 0 | 0 | 0 | 1 | 0 | 0 |
| Royer Creek-Beaver Creek | 071000040910 | 0 | 1 | 0 | 0 | 0 | 0 |
| Sac City-North Raccoon River | 071000060310 | 0 | 1 | 0 | 0 | 0 | 0 |
| Salt Creek | 070802080507 | 0 | 1 | 0 | 0 | 0 | 0 |
| Sand Creek | 070600060208 | 0 | 0 | 0 | 0 | 1 | 0 |
| Saylor Creek-Des Moines River | 071000041003 | 2 | 0 | 0 | 0 | 0 | 0 |
| School Creek-Des Moines River | 071000020106 | 1 | 0 | 0 | 0 | 0 | 0 |
| Schutte Creek-Otter Creek | 101702040502 | 0 | 0 | 0 | 0 | 1 | 0 |
| Sevenmile Creek | 102801020208 | 0 | 0 | 0 | 0 | 1 | 0 |
| Shell Rock River | 070802020705 | 3 | 0 | 0 | 1 | 0 | 0 |
| Short Creek-South River | 071000081201 | 0 | 2 | 0 | 0 | 0 | 0 |
| Silver Creek-Cedar River | 070802051507 | 3 | 0 | 0 | 0 | 0 | 0 |
| Sink Creek-Cedar River | 070802050906 | 1 | 0 | 0 | 2 | 0 | 0 |
| Skillet Creek | 071000040701 | 0 | 0 | 0 | 0 | 0 | 1 |
| Skunk Creek-Cedar River | 070802011001 | 0 | 0 | 0 | 0 | 0 | 2 |
| Skunk River | 070801071006 | 3 | 0 | 0 | 0 | 0 | 0 |
| Slough Creek | 071000040907 | 0 | 1 | 0 | 0 | 0 | 2 |
| Snake Creek | 102400050604 | 0 | 0 | 0 | 0 | 1 | 0 |
| Snyder Branch-Chariton River | 102802010404 | 0 | 2 | 0 | 0 | 0 | 0 |
| Snyder Creek-South Skunk River | 070801051204 | 0 | 0 | 0 | 2 | 2 | 1 |
| Soldier Creek-Little Sioux River | 102300031107 | 1 | 0 | 0 | 0 | 0 | 0 |
| Soldier River | 102300010606 | 0 | 3 | 0 | 0 | 0 | 0 |
| South Avery Creek | 071000090705 | 0 | 0 | 0 | 1 | 0 | 0 |
| South Beaver Creek | 070802050103 | 0 | 0 | 0 | 0 | 1 | 0 |
| South Fork Black Hawk Creek | 070802050401 | 0 | 0 | 0 | 1 | 0 | 0 |
| South Squaw Creek | 071000080801 | 0 | 0 | 0 | 1 | 0 | 0 |
| South Turkey Creek | 071000080603 | 0 | 0 | 0 | 1 | 0 | 0 |
| Spanish Bridge Skunk River State Wildlife Area-Skunk River | 070801070305 | 0 | 0 | 0 | 0 | 1 | 0 |
| Spring Branch-Middle Raccoon River | 071000070204 | 0 | 0 | 0 | 1 | 0 | 0 |
| Spring Creek | 070802051002 | 0 | 0 | 1 | 1 | 0 | 0 |
| Spring Creek | 070802030304 | 0 | 0 | 0 | 1 | 0 | 0 |
| Spring Creek | 070802040303 | 0 | 0 | 0 | 1 | 0 | 0 |
| Spring Creek | 071000040203 | 0 | 0 | 0 | 0 | 0 | 3 |
| Spring Creek | 070802010602 | 0 | 0 | 0 | 0 | 2 | 0 |
| Spring Creek-East Nishnabotna River | 102400030502 | 0 | 1 | 0 | 1 | 0 | 2 |
| Spring Creek-South Skunk River | 070801051203 | 2 | 1 | 1 | 1 | 2 | 0 |
| Squaw Creek-Grand River | 102801010103 | 0 | 0 | 0 | 1 | 0 | 0 |
| Stein Creek | 070802080504 | 0 | 0 | 0 | 1 | 0 | 0 |
| Stewart Creek-Cedar River | 070802011003 | 0 | 1 | 0 | 1 | 3 | 3 |
| Sugar Creek | 070801060203 | 0 | 0 | 0 | 1 | 0 | 0 |
| Sugar Creek-South Skunk River | 070801050908 | 0 | 1 | 0 | 0 | 0 | 0 |
| Summer Creek-Cedar Creek | 070801070708 | 0 | 1 | 0 | 1 | 0 | 0 |
| Swan Lake Branch | 071000061502 | 0 | 0 | 0 | 0 | 2 | 0 |
| Threemile Creek | 102801020205 | 0 | 0 | 0 | 1 | 0 | 0 |
| Threemile Creek-Little Sioux River | 102300031503 | 0 | 0 | 0 | 1 | 0 | 0 |
| Timber Creek | 070802080206 | 0 | 1 | 0 | 0 | 0 | 0 |
| Timber Creek-Boyer River | 102300070605 | 0 | 1 | 0 | 0 | 0 | 0 |
| Tipton Creek | 070802070402 | 0 | 0 | 0 | 1 | 0 | 0 |
| Tom Creek | 101702040701 | 0 | 0 | 0 | 1 | 0 | 0 |
| Tug Fork-Big Indian Creek | 071000091001 | 0 | 0 | 0 | 1 | 0 | 0 |
| Turkey Creek-Indian Creek | 070801050805 | 0 | 1 | 0 | 0 | 0 | 0 |
| Turkey Creek-Platte River | 102400120107 | 0 | 1 | 0 | 0 | 0 | 0 |
| Twelvemile Creek | 070802050807 | 0 | 0 | 0 | 1 | 0 | 0 |
| Upper Clear Creek | 070802090101 | 0 | 0 | 0 | 0 | 1 | 0 |
| Upper Duck Creek | 070801010301 | 0 | 0 | 0 | 0 | 0 | 1 |
| Upper Little Maquoketa River | 070600030603 | 0 | 0 | 0 | 1 | 0 | 0 |
| Upper Middle Raccoon River | 071000070206 | 0 | 1 | 0 | 0 | 2 | 0 |
| Upper North Branch Lizard Creek | 071000040102 | 0 | 0 | 1 | 0 | 0 | 1 |
| Upper North English River | 070802090402 | 0 | 0 | 0 | 1 | 0 | 0 |
| Upper South Fork Chariton River | 102802010102 | 0 | 0 | 0 | 1 | 0 | 0 |
| Upper Turkey Creek | 102400030301 | 0 | 0 | 0 | 1 | 0 | 0 |
| Upper Willow Creek | 102300070401 | 0 | 0 | 0 | 1 | 0 | 0 |
| Van Zante Creek-South Skunk River | 070801051106 | 1 | 0 | 0 | 0 | 0 | 0 |
| Village Creek | 070600010602 | 0 | 0 | 0 | 1 | 0 | 0 |
| Village of Alton-Floyd River | 102300020306 | 0 | 1 | 0 | 0 | 0 | 0 |
| Village of Belle Plaine-Iowa River | 070802080903 | 1 | 0 | 0 | 0 | 0 | 0 |
| Village of Conrad-Wolf Creek | 070802050803 | 0 | 1 | 0 | 1 | 0 | 0 |
| Village of Delta-North Skunk River | 070801060601 | 0 | 1 | 0 | 0 | 0 | 0 |
| Village of Doon-Little Rock River | 101702040606 | 0 | 0 | 0 | 1 | 0 | 0 |
| Village of Eldorado-Turkey River | 070600040703 | 0 | 1 | 0 | 0 | 0 | 0 |
| Village of Farlin-Harrdin Creek | 071000061004 | 0 | 1 | 0 | 0 | 0 | 0 |
| Village of Inwood-Big Sioux River | 101702031904 | 0 | 1 | 0 | 0 | 0 | 0 |
| Village of Janesville-Cedar River | 070802011205 | 3 | 0 | 0 | 0 | 0 | 0 |
| Village of Klondike-Big Sioux River | 101702031902 | 0 | 0 | 0 | 1 | 0 | 0 |
| Village of Oran-Little Wapsipinicon River | 070801020503 | 0 | 0 | 0 | 1 | 0 | 0 |
| Village of Reinbeck-Black Hawk Creek | 070802050505 | 0 | 0 | 0 | 1 | 0 | 0 |
| Village of Soldier-Soldier River | 102300010604 | 0 | 0 | 0 | 1 | 0 | 0 |
| Village of Van Horne-Prairie Creek | 070802051402 | 1 | 0 | 0 | 0 | 3 | 0 |
| Wall Lake Inlet | 071000060401 | 0 | 0 | 0 | 2 | 1 | 0 |
| Wallingslock Creek-Des Moines River | 071000081509 | 0 | 0 | 0 | 1 | 0 | 0 |
| Walnut Creek | 070802080603 | 0 | 0 | 0 | 1 | 0 | 0 |
| Walnut Creek | 071000061602 | 0 | 0 | 0 | 1 | 0 | 0 |
| Walnut Creek | 071000081505 | 0 | 0 | 0 | 1 | 1 | 0 |
| Walnut Creek | 070801030408 | 0 | 0 | 0 | 0 | 0 | 2 |
| Walnut Creek | 070801050901 | 0 | 0 | 0 | 0 | 1 | 1 |
| Waterloo Creek | 070600020502 | 0 | 0 | 0 | 2 | 0 | 0 |
| Waterloo Municipal Airport | 070802050702 | 0 | 0 | 0 | 2 | 0 | 0 |
| Watsons Creek-Wapsipinicon River | 070801020202 | 0 | 0 | 0 | 1 | 0 | 0 |
| Weasel Creek-Prairie Creek | 070802051404 | 0 | 0 | 0 | 2 | 1 | 0 |
| West Beaver Creek | 071000040902 | 0 | 0 | 0 | 0 | 0 | 1 |
| West Branch Floyd River | 102300020408 | 0 | 1 | 0 | 0 | 0 | 0 |
| West Branch Little Sioux River | 102300030104 | 0 | 0 | 1 | 1 | 0 | 0 |
| West Branch Mill Creek-Mill Creek | 102300031201 | 0 | 0 | 0 | 0 | 0 | 1 |
| West Branch One Hundred Two River | 102400130203 | 0 | 0 | 0 | 1 | 0 | 0 |
| West Branch Perry Creek-Perry Creek | 102300010301 | 0 | 0 | 0 | 1 | 2 | 0 |
| West Branch Sugar Creek | 070801041601 | 0 | 0 | 0 | 1 | 1 | 0 |
| West Branch Wapsinonoc Creek | 070802060702 | 0 | 0 | 0 | 0 | 1 | 0 |
| West Buttrick Creek | 071000061203 | 0 | 0 | 0 | 1 | 0 | 0 |
| West Fork Cedar River | 070802040607 | 0 | 3 | 0 | 0 | 0 | 0 |
| West Fork Ditch | 102300040407 | 0 | 1 | 0 | 0 | 0 | 0 |
| West Fork One Hundred Two River | 102400130205 | 0 | 0 | 0 | 0 | 0 | 2 |
| West Okoboji Lake | 102300030202 | 0 | 0 | 0 | 2 | 0 | 0 |
| West Otter Creek | 070802051301 | 0 | 0 | 0 | 1 | 0 | 0 |
| West Otter Creek | 071000050301 | 0 | 0 | 0 | 1 | 0 | 0 |
| West Platte River-Platte River | 102400120102 | 0 | 0 | 0 | 2 | 0 | 0 |
| Whisky Creek | 102300040103 | 0 | 0 | 0 | 0 | 1 | 0 |
| White Cloud-West Nishnabotna River | 102400020801 | 0 | 1 | 0 | 0 | 0 | 0 |
| White Fox Creek | 071000050503 | 0 | 0 | 0 | 1 | 0 | 2 |
| Whitney Creek-Little Rock River | 101702040604 | 0 | 0 | 0 | 2 | 0 | 0 |
| Wildcat Creek | 070802051202 | 0 | 0 | 0 | 0 | 1 | 0 |
| Wildcat Creek-Des Moines River | 071000081507 | 1 | 0 | 0 | 0 | 0 | 0 |
| Willey Branch-Middle Raccoon River | 071000070205 | 0 | 1 | 0 | 0 | 0 | 0 |
| Willow Creek | 102300030902 | 0 | 0 | 0 | 1 | 0 | 0 |
| Willow Creek-Mill Creek | 102300031207 | 0 | 0 | 0 | 0 | 1 | 0 |
| Wilson Creek-Black Hawk Creek | 070802050601 | 0 | 1 | 0 | 0 | 0 | 0 |
| Wolf Creek | 070802050809 | 0 | 3 | 0 | 1 | 1 | 0 |
| Worrell Creek-Squaw Creek | 070801050307 | 0 | 2 | 0 | 0 | 0 | 0 |
| Yeader Creek-Des Moines River | 071000081503 | 1 | 0 | 0 | 1 | 0 | 0 |