Accessibility Version: Tracking the Iowa Nutrient Reduction Strategy v2
Version 2.0 | May 2023
Access the Interactive Data Dashboards
The Iowa Nutrient Reduction Strategy is a science- and technology-based approach to assess and reduce nutrients delivered to Iowa waterways and the 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. Updates for the 2021 reporting period will be made in May and June 2023.
Tracking Inputs for the Iowa Nutrient Reduction Strategy
Introduction to INRS Inputs
Tracking efforts of the 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%. 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 NRS facets may be required to support the goals set forth by the NRS. Due to data availability, this report aims to provide an overview of reported statewide funding and staff resources supporting or complementary to the NRS.
Estimates of investment encompass public and non-governmental organizations' (NGO) funding summarized through voluntarily submitted reports of WRCC and WPAC member organizations and by other partner organizations. Most public programs described in this report 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 NRS and cannot be reliably quantified through existing reporting mechanisms. The importance of these opportunities is acknowledged, but 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 a Regents institution on land management, edge-of-field practices, nutrient management research, or multi-objective research.
More information regarding projects funded at Regents Institutions through the INRC may be found at https://www.cals.iastate.edu/inrc/.
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
Priority watersheds across Iowa were identified by the Water Resources Coordinating Council in 2013 to conduct outreach and focus targeted conservation and water quality efforts. Nine priority watersheds (hydrologic unit code 8 basins) were identified to focus implementation activities as demonstration projects. Current project information for nonpoint efforts is available at Clean Water Iowa.
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 the Watershed Planning Advisory Council (WPAC). Organizations report via a common template to standardize responses to the number of full-time employees (or equivalent) by employee function. In addition, funding by program category and shared funding source are submitted. Where data was unavailable, public records were utilized for public investments for appropriations and expenditures.
Information is collated for all partners to summarize funding, staff, outreach efforts, practice implementation, and monitoring efforts, then reported efforts are distilled to minimize duplication. For example, a grant disbursed by one organization and awarded to another may be reported by both organizations, but double-reporting 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, 2021 report available here (available as an xlsx file).
INRS Funding by Partner Organizations from 2012 to 2021
A summary of investment by the four primary investment categories - public sector programs, farmer and landowner investment, non-governmental organizations (NGOs), and land rental as Conservation Reserve Program (CRP) payments - are summarized in the table below. Note that partner funds became available for reporting in the current INRS methodology in 2016 for reporting purposes. NGO investments occurred prior to this time but are not available.
Year | Public Sector Programs | Private Investment: Farmer and Landowner Investment | Non-Governmental Organizations | CRP - Rental Payments | Total |
2012 | 91,233,895 | 15,302,863 | 212,942,766 | 319,479,524 | |
2013 | 107,516,595 | 10,708,875 | 216,365,107 | 334,590,577 | |
2014 | 98,161,485 | 16,211,646 | 214,402,613 | 328,775,744 | |
2015 | 121,613,279 | 15,452,535 | 221,360,787 | 358,426,601 | |
2016 | 114,147,810 | 14,152,067 | 2,759,434 | 243,650,296 | 374,709,607 |
2017 | 136,948,822 | 26,541,673 | 3,146,103 | 318,308,819 | 484,945,417 |
2018 | 161,959,229 | 33,524,588 | 3,659,943 | 360,771,362 | 559,915,122 |
2019 | 161,622,445 | 29,220,329 | 3,279,533 | 387,472,169 | 581,594,476 |
2020 | 155,799,332 | 20,812,020 | 3,557,452 | 387,472,174 | 567,640,978 |
2021 | 195,022,109 | 38,115,992 | 3,018,330 | 382,490,928 | 618,647,359 |
Total Investment 2012-2021 | 1,344,025,001 | 220,042,588 | 19,420,795 | 2,945,237,021 | 4,528,725,405 |
Farmer and landowner investment in the table above includes cover crops, terraces, water and sediment control basins, ponds, grade stabilization structures, and sediment basins that utilized a public sector program.
State and Federal Funding in Support of INRS by Program
Programs funding is reported as state appropriations by fiscal year or federal year obligation for programs pertaining to the INRS in Appendix A (available at the end of this document) or the tracking period data summary available here (csv on an external site). FSA expenditures are reported from the CRP Enrollment and Rental Payments by State, 1986-2022, and NRCS from annual At-A-Glance reports by federal fiscal year.
Full-Time Employees (FTEs) Reported for the INRS
A summary of FTEs by category as reported by partners can be found in the table below. Changes in tracking staff were reported by several organizations since 2019 and are known to impact FTEs reported, both as the total and within 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 | 144.005 | 102.105 | 17.25 | 17.25 | 280.61 |
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 |
Changes in Funding
State conservation programs have evolved from 2012 to 2021, with funding for longstanding conservation programs independent of the INRS continuing to receive increased funding. To directly support the INRS, the Water Quality Initiative was first established in 2014. 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. Programs offered for nonpoint sources facilitate the implementation of conservation practices through financial assistance programs or for land set aside through the Conservation Reserve Program (CRP). Expenditures through CRP in Iowa have increased, driven by an average rental rate per acre increase from $132 to $230 from 2012 to 2021. Programs to implement conservation programs administered by the NRCS are funded through the Farm Bill, for which programs have evolved over the past decade, both in programs and funding for each program. Funds obligated to projects in Iowa through conventional programs have been strong. In addition, Iowa entities have 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 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 678 events reported for the 2021 reporting period that reached an estimated 38,746 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. Information on attendance by year, as the number of events and attendance, are summarized in the table following this section. Program delivery modes have evolved over the past two 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.
Changes in event mode and travel restrictions led to smaller group programs that fostered greater engagement, primarily as youth education events coordinated by the Water Rocks! program in 2021. Similarly, many conferences transitioned to virtual or hybrid formats making participation possible for a wider audience.
These events, which provide information to make informed decisions about conservation practices and educate attendees about water quality issues, were self-reported by WRCC and WPAC member 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 a discussion on water quality but was not the primary reason for the contact.
*Supplemental contacts are not included in the statewide total because water quality was not the primary reason for the contact. In addition, attendance at these programs is reported as a statewide total as the mode by which attendees engaged in a training does not facilitate county-level reporting.
Year | Community Outreach | Conference | Field Day | Supplemental | Workshop | Youth | Total | |||||||
Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | |
2016 | 9,724 | 63 | 1,757 | 10 | 9,523 | 114 | 7,473 | 272 | 6,152 | 68 | 34,629 | 527 | ||
2017 | 21,331 | 160 | 4,763 | 18 | 9,849 | 145 | 7,625 | 259 | 18,551 | 125 | 62,119 | 707 | ||
2018 | 9,323 | 158 | 3,507 | 18 | 4,861 | 138 | 6,748 | 216 | 28,710 | 195 | 53,149 | 725 | ||
2019 | 13,296 | 156 | 2,155 | 16 | 7,798 | 158 | 14,350 | 578 | 6,307 | 216 | 28,205 | 195 | 57,761 | 741 |
2020 | 7,380 | 133 | 1,383 | 16 | 6,733 | 142 | 15,285 | 1,126 | 6,674 | 218 | 27,036 | 208 | 49,206 | 717 |
2021 | 6,028 | 67 | 2,133 | 10 | 1,858 | 47 | 5,883 | 318 | 6,639 | 225 | 21,410 | 329 | 38,068 | 678 |
A summary of programs by county can be in Appendix B (available at the end of this document) or the tracking period data summary available here (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. Watersheds for each survey appear in the panel to the right.
Reports may be found in the INRS webpage supplemental documents (https://www.nutrientstrategy.iastate.edu/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' answers in the first year in 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 | 7100006 |
Boone | 7100005 | |||
Iowa | 070802 | 2015 and 2019 | Middle Cedar | 7080205 |
Upper Mississippi-Maquoketa-Plum | 070400 | 2016 and 2017 | Turkey | 7060004 |
Upper Mississippi-Skunk-Wapsipinicon | 070801 | 2019 | South Skunk | 7080105 |
Lower Skunk | 7080107 | |||
Missouri-Little Sioux | 102300 | 2015 and 2016 | Floyd | 10230002 |
Missouri-Nishnabotna | 102400 | 2018 and 2019 | West Nishnabotna | 10240002 |
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 table below by topic area from the survey and by the basin in which the farmer operates.
Watershed by which Farmers were Surveyed | Des Moines | Missouri-Little Sioux | Missouri-Nishnabotna | Upper Mississippi-Maquoketa-Plum | Upper Mississippi-Skunk-Wapsipinicon |
Self-assessment of nutrient management | |||||
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 |
Awareness, concern, and support for action | |||||
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 |
Knowledge-related barriers | |||||
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 |
Economic barriers | |||||
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 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, pInfluenceublications, 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 USDA Census of Agriculture, nearly 90% of Iowa’s total area is dedicated for agricultural purposes, with total agricultural land averaging 31.4 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 27 million acres. Acres enrolled in the United States Department of Agriculture Conservation Reserve Program, 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.
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 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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 | 12,714,499 |
Hay | 2,317,391 | 2,035,033 | 1,968,207 | 1,762,425 | 1,575,777 | 1,533,027 | 1,125,565 | 996,316 | 1,220,000 | 1,220,000 | 1,240,000 | 1,010,000 | 1,069,770 | 995,000 | 1,115,000 | 1,225,000 | 1,350,000 | ||||||||||||||||
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 | 108,301 |
Pasture | 5,764,822 | 4,256,172 | 3,639,397 | 3,144,321 | 2,478,116 | 2,360,349 | |||||||||||||||||||||||||||
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 | 10,016,584 |
Wheat | 31,863 | 98,688 | 31,047 | 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 | 17,255 |
Records from the United States Department of Agriculture (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 (NASS) 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 (FSA) crop acreage reports and reflect the annual crop acreage values provided in NASS (in lieu of combined records from archival, NASS, and FSA databases).
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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 |
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 970,000 acres of cover crops were planted in Iowa in fall the fall of 2017, and the Survey of Agricultural Retailers estimated 1.6 million acres. That survey estimated that 2.8 million acres were planted in the fall of 2021. Based on county-level data from the 2017 USDA Census of Agriculture, the eastern and southern regions of Iowa show the highest rates of cover crop use.
Of these statewide estimates, public conservation programs accounted for more than 1,000,000 acres in 2021. 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 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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
United States Department of Agriculture - Census of Agriculture | 379,614 | 973,112 | ||||||||||
Survey of Agricultural Retailers | 1,597,614 | 2,015,688 | 2,179,304 | 3,107,063 | 2,768,754 | |||||||
Portion Funded by Public Conservation Programs | 18,702 | 30,987 | 69,955 | 211,235 | 161,000 | 275,854 | 324,097 | 549,638 | 600,972 | 558,278 | 818,606 | 1,010,822 |
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 2017. County values were assigned proportionally to Iowa HUC8 watersheds based on the percentage of county land area that intersects each watershed.
The type of cover crop species planted, as reported by the INREC Ag Retailer Survey, from 2017-2021 are summarized below. The benefits of cover crop species N and P benefits vary slightly by species that reflect the benefits from winter-hardy and winter-kill cover crop species.
Year | Rye Cover Crop | Oat Cover Crop | Mix of Cover Crop Species | Other Cover Crop |
2017 | 69.4% | 9.1% | 21.5% | |
2018 | 82.8% | 9.8% | 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% |
The use of cover crop mixes were 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 United States Department of Agriculture (USDA) Census of Agriculture provides county-level cover crop acres for fall 2012 and fall 2017, allowing for aggregated statewide totals for those 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, and are summarized in the table below.
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 USDA Census of Agriculture estimated 6.9 million acres of no-till. Since 2012, no-till acres have increased to approximately 9.5 million acres, according to both the Census and the Survey of Agricultural Retailers. 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 increased to approximately 5.3 million acres annually, according to both the Census of Agriculture and the Survey of Agricultural Retailers. The use of conservation tillage is distributed across the state, with higher rates of use in the western, north-central, and northeastern regions of Iowa.
The increased use of no-till and conservation tillage in row crop operations since the 1980s is paired with a marked decrease in the use of conventional tillage. Conventional tillage was used on an estimated 12 million acres during the baseline period and has decreased to approximately 8.3 million acres in 2021.
Data Source and Practice Name | 1980-1996 Average Annual | 2006-2010 Average Annual | 2012 | 2017 | 2018 | 2019 | 2020 | 2021 |
---|---|---|---|---|---|---|---|---|
Iowa Nutrient Reduction Strategy - Derived from data from the Conservation Technology Information Center | ||||||||
No-Till | 1,968,881 | 6,154,727 | ||||||
Conservation Tillage | 5,190,170 | 6,064,720 | ||||||
Conventional Tillage | 12,042,585 | 8,288,043 | ||||||
Census of Agriculture | ||||||||
No-Till | 6,950,836 | 8,196,199 | ||||||
Conservation Tillage | 8,760,348 | 10,132,599 | ||||||
Conventional Tillage | 7,882,556 | 5,018,129 | ||||||
Survey of Agricultural Retailers | ||||||||
No-Till | 7,707,695 | 6,972,434 | 8,153,502 | 8,589,242 | 9,461,121 | |||
Conservation Tillage | 11,611,288 | 10,247,229 | 9,475,381 | 4,935,493 | 5,253,814 | |||
Conventional Tillage | 3,676,146 | 5,733,407 | 5,294,806 | 9,822,998 | 8,259,545 |
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 2017. 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 and 2017 crop years were estimated using the United States Department of Agriculture Census of Agriculture, which provides county-level data for no-till, conservation tillage, and conventional tillage.
Annual statewide acreages of tillage practices in corn and soybean fields are estimated by the Survey of Agricultural Retailers, conducted by the Iowa Nutrient Research and Education Council, for the 2017 to 2021 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 Retailer Survey 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 2017-21 period. On average, continuous corn rotations received between 200 and 202 pounds per acre during that time.
Category (Pounds Nitrogen Per Acre) | 2017 | 2018 | 2019 | 2020 | 2021 |
---|---|---|---|---|---|
Continuous Corn | |||||
<100 | 0.0% | 0.0% | 1.3% | 0.0% | 0.0% |
100-125 | 0.0% | 0.3% | 0.0% | 0.0% | 0.0% |
126-150 | 1.5% | 2.3% | 3.6% | 0.0% | 5.7% |
151-175 | 8.9% | 8.6% | 5.7% | 4.5% | 7.8% |
176-200 | 54.2% | 38.7% | 48.5% | 32.5% | 47.1% |
201-225 | 18.7% | 33.2% | 29.2% | 31.6% | 33.8% |
226-250 | 15.3% | 11.2% | 11.0% | 27.6% | 5.6% |
>250 | 1.4% | 5.6% | 0.8% | 3.8% | 0.0% |
Corn/Soybean | |||||
<100 | 0.1% | 0.2% | 0.5% | 0.1% | 0.2% |
100-125 | 1.9% | 1.5% | 0.4% | 0.8% | 2.3% |
126-150 | 22.3% | 19.0% | 10.8% | 8.6% | 20.7% |
151-175 | 36.8% | 29.2% | 32.9% | 26.8% | 32.3% |
176-200 | 31.8% | 37.1% | 39.7% | 37.7% | 33.1% |
201-225 | 5.2% | 10.1% | 11.9% | 17.2% | 9.5% |
226-250 | 0.8% | 2.8% | 3.5% | 5.5% | 1.5% |
>250 | 1.2% | 0.1% | 0.3% | 3.2% | 0.4% |
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 2021, for example, 33 percent of corn-soybean acres received 176-200 pounds of commercial nitrogen on their most recent corn year, and 32 percent received 151-175 pounds. Some fields lay at the ends of this distribution, with 21 percent of acres receiving 150 pounds of nitrogen per acre or less and 11 percent receiving 201 pounds per acre or more. There was a similar distribution for continuous corn rotations, with 47 percent of acres receiving 176-200 pounds of commercial nitrogen fertilizer.
These estimates of annual nitrogen applications from 2017-21 represent an increase in fertilizer use since the 1980-96 baseline period. While the 2017-21 estimates of commercial fertilizer rates were obtained via a different data collection process than for the baseline and benchmark time periods, there is complementary evidence from recent fertilizer sales data 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, that is the 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.
Research into nitrogen application rates lies at the forefront of the Iowa Nitrogen Initiative, a research program piloted in 2021 that utilizes soil, weather, and management systems. With the goal of developing a probability-based decision system that incorporates regional weather parameters, expanding from the crop rotation to the individual region will help address productivity, profitability, and environmental performance, the initiative will encourage fertilizer application decisions to be made based on financial and local environmental conditions. The initiative will offer a decision-making tool based on local conditions and facilitate the evaluation of needs relative to the Maximum Return to Nitrogen (MRTN).
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 14.4 million acres received phosphorus fertilizer was incorporated, injected, or knifed into the soil within 24 hours of application for the 2017 crop year and decreased to 11.8 million acres for the 2021 crop year. These estimates account mostly for commercial fertilizer. Only 16% of surveyed fields received manure, with a small portion of these acres receiving manure and commercial P each year. In addition, approximately 80% of fields receive soil test phosphorus, more than 18,000,000 acres, that guide phosphorus application.
Phosphorus Management Type | 2017 | 2018 | 2019 | 2020 | 2021 |
Commercial P Incorporated with Planter | 2,523,799 | 862,841 | 270,492 | 639,271 | 144,756 |
Commercial P Incorporated in Knifed Bands | 656,919 | 627,900 | 619,632 | 692,078 | 625,440 |
Commercial P Broadcast & Incorporated within 1 week | 10,807,030 | 16,143,905 | 15,847,446 | 9,440,934 | 9,916,964 |
Liquid P (commercial/manure) Injected | 416,049 | 865,364 | 2,048,850 | 1,825,232 | 1,155,754 |
Other P Application Type | 8,591,331 | 4,468,931 | 4,137,269 | 10,750,218 | 11,130,161 |
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 2021.
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 NRS Nonpoint Source Science Assessment, which can be accessed at nutrientstrategy.iastate.edu/documents.
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 NRS Nonpoint Source Science Assessment, which can be accessed at nutrientstrategy.iastate.edu/documents.
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 application timing also affects nitrogen loss. Shifting nitrogen application from fall to spring reduces nitrogen loads by 6% and shifting from spring pre-plant to in-season application (i.e. side-dress) reduces nitrogen loads by 4-7%. The Survey of Agricultural Retailers provides recent estimates of when nitrogen is most commonly applied. In 2021, a split application of spring and side-dress was used on 6.9 million corn acres. That year, 1.7 million corn acres received only side-dress application and 5.2 million acres received only spring pre-plant.
Fall-applied anhydrous with nitrapyrin has been shown to reduce nitrogen loads by approximately 9% when compared with applications without an inhibitor. Based on the NRS Nonpoint Source 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 NRS 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 |
---|---|---|---|---|---|
Fall anhydrous plus Nitrification Inhibitor | 3,731,524 | 2,318,399 | 2,722,201 | 3,337,435 | 4,759,935 |
Fall Anhydrous without Nitrification Inhibitor | 1,405,251 | 817,409 | 487,618 | 643,485 | 772,300 |
In-Season Only | 281,723 | 137,166 | 148,057 | 529,107 | 219,339 |
Spring Pre-Plant | 6,487,329 | 7,652,738 | 6,950,024 | 6,443,443 | 5,165,386 |
Spring Side-Dress Split, 40-60 | 1,307,086 | 2,004,263 | 2,300,009 | 1,907,536 | 1,691,866 |
Data - Nitrogen Application Timing
The data showing the timing of commercial nitrogen applications were obtained from the Iowa Nutrient Research and Education Council's 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
Bioreactors and saturated buffers are edge-of-field practices that are made by routing agricultural drainage water through a woodchip trench or vegetated buffer to remove nitrate before the water enters an adjacent stream, ditch, or tile main. At 43% and 50% reduction, respectively, these practices are highly effective at reducing annual nitrate loads to streams. The suitability of bioreactors and saturated buffers for a farm field is highly dependent upon the presence of tile drainage, topography, and soil types.
From 2011 to 2021, at least 107 bioreactors and 87 saturated buffers were installed throughout Iowa; using a conservative assumption that these practices each protect 50 acres of drained cropland, at least 9,700 acres are protected, as of the end of 2021.
Multi-purpose oxbows are similar edge-of-field practices that were added to the Iowa Nutrient Reduction Strategy in 2019. At 52% reduction, the practice is highly effective at reducing nitrate loads to streams. A naturally occurring oxbow is a floodplain wetland that forms when a stream or river cuts a straighter path through a loop of its meander or when a stream is channelized. Routing agricultural drainage water into a restored oxbow can reduce nitrate concentration in the tile flow before it moves to the adjacent stream. Multi-purpose oxbows will be reported as multi-purpose oxbow reporting becomes available.
Row Labels | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Bioreactor - Acres Treated by New Practices Annually | 150 | 150 | 50 | 200 | 250 | 250 | 400 | 850 | 400 | 1,100 | 1,550 | |
Saturated Buffer - Acres Treated by New Practices Annually | 50 | 50 | 50 | 250 | 450 | 300 | 350 | 400 | 350 | 2,100 | ||
Cumulative Acres Treated By Bioreactors and Saturated Buffers in Iowa | 50 | 200 | 350 | 450 | 700 | 1,200 | 1,900 | 2,600 | 3,800 | 4,600 | 6,050 | 9,700 |
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 and saturated buffers were summarized using state and federal conservation program data as well as practices known to be installed by IDALS 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. Due to variable data in early years of bioreactor and saturated buffer construction (e.g. 2011 to approximately 2015), an assumption of 50 acres protected by each practice was used. A Conservation Innovation Grant is currently evaluating information to better estimate acres protected.
Acres Protected by Water Quality Wetlands Installed Each Year in Iowa
Water quality wetlands that are designed for water quality improvement have an effectiveness of 52% nitrogen load reduction. In designing these types of wetlands, agricultural tile drainage is routed through the wetland for nitrate removal. Currently, water quality 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 protected pound of nitrogen making the practice very efficient. Most of Iowa’s wetlands have been constructed under the Conservation Reserve Enhancement Program (CREP), but novel wetland siting standards have been implemented over the past decade to expand wetlands from the traditional CREP break-point wetland design. Novel wetland positions on the landscape include lateral and in-stream designs, both intentionally designed to treat 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 to water quality wetland design standards, but data currently are not available to assess the full extent of this non-CREP implementation.
Currently, Iowa has 119 water quality 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 139,000 acres. Iowa experienced its highest rate of installations in 2021, with 24 new wetlands capturing nearly 26,500 acres. Program implementation continues, with wetland design types developed in recent years expanding the position on the landscape where nutrient removal wetlands can be sited. Water quality wetlands constructed since 2011 (i.e. since the 2006-10 benchmark period of the Iowa Nutrient Reduction Strategy) protect more than 88,000 acres of agricultural land.
2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
New Acres Treated Annually | 2,488 | 2,189 | 634 | 10,941 | 14,800 | 5,962 | 13,414 | 8,074 | 6,965 | 13,519 | 6,334 | 4,940 | 0 | 10,448 | 4,596 | 1,945 | 683 | 4,829 | 26,481 |
Cumulative Acres Treated | 2,488 | 4,677 | 5,311 | 16,252 | 31,052 | 37,014 | 50,428 | 58,502 | 65,467 | 78,986 | 85,320 | 90,260 | 90,260 | 100,708 | 105,304 | 107,249 | 107,932 | 112,761 | 139,242 |
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 water quality 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.
Cumulative Acres Protected by Structural Erosion Control Practices Installed in Iowa Since 2011
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 that reduce soil-bound phosphorus loss. These practices include terraces, water and sediment control basins (WASCOBs), farm ponds, and grade stabilization structures; their effectiveness at reducing phosphorus loads 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 290,000 acres are protected by terraces, WASCOBs, ponds, and grade stabilization that have been installed under government cost-share programs since 2011. Owing to the topography and soils of the southern and northeastern regions of Iowa, erosion control practices are concentrated primarily in those geographic areas.
The Iowa BMP Mapping Project is an ongoing effort that will estimate the extent of all erosion control installations—not just those funded by state or federal cost-share programs. The project’s data collection is complete for three time periods: the 1980s, 2007-10, and 2016-17. Efforts to utilize this invaluable data source include both the acres protected by practices, within each watershed and statewide, as well as the nutrient reduction benefits of practices. These active areas of research will be summarized as data becomes available.
2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | |
---|---|---|---|---|---|---|---|---|---|---|---|
Terraces and Water & Sediment Control Basins - Acres Treated by New Practices Annually | 30,277 | 8,789 | 21,917 | 27,947 | 26,008 | 24,132 | 18,558 | 17,017 | 21,312 | 23,150 | 12,040 |
Grade Stabilization and Ponds - Acres Treated by New Practices Annually | 9,043 | 4,671 | 5,049 | 6,470 | 3,993 | 6,878 | 4,262 | 2,315 | 3,792 | 6,278 | 5,711 |
Cumulative Acres Treated by Terraces, Water & Sediment Control Basins, Grade Stabilization, and Ponds | 39,320 | 52,780 | 79,746 | 114,163 | 144,163 | 175,174 | 197,994 | 216,189 | 242,430 | 271,858 | 289,609 |
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 cover crop acres. This report accounts for practices installed between 2011 and 2021. 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. Structural erosion control practices reported include terraces, water and sediment control 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 the federal 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.
Structural best management practice adoption prior to the INRS annual report tracking, which began in 2011, was summarized by the Iowa BMP Mapping Project. Practices visible in aerial imagery and high-resolution topography data (statewide LiDAR data) were reviewed and practices mapped. This integrates practices constructed over several decades to track best management practice adoption. Practices depicted by the Iowa BMP Mapping Project include both practices implemented with and without cost-share assistance; note that INRS reporting efforts only include practices that receive state or federal cost-share as self-funded practices are not reported annually the evaluation of all practice benefits will be explored in the future.
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 161 industrial (54 permits) and municipal wastewater treatment point source facilities (107 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 January 1, 2022, municipal and industrial 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 | 47 | 14 |
Earliest Completion Date | August 1, 2018 | January 1, 2018 |
Latest Completion Date | October 1, 2027 | December 1, 2025 |
Average Length of Construction Schedule | 4.3 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 2021, 154 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 |
For INRS priority watersheds, three 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 2021 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 | Total permits with nutrient monitoring |
2018 | 49 | 47 | 8 | 388 |
2019 | 61 | 58 | 12 | 394 |
2020 | 69 | 65 | 14 | 401 |
2021 | 75 | 71 | 16 | 400 |
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 |
Reported N and P loads since the INRS was adopted in 2013 for major public and industrial facilities are summarized in the table below. The points 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 |
Water
An Overview of the Water Measurement Indicator
Monitored water quality reflects the dynamic interaction of current and historical land management practices, structural conservation practice adoption, and point source loading with the weather. 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 modeled changes in nonpoint source nutrient export (point source tracking reported in the Land dashboard) based on agricultural management and BMPs adopted or installed and monitored nutrient loads from rivers.
This dashboard summarizes each tracked component of the Water indicator:
- Modeled impacts of BMP adoption and construction, agronomic practices, and land use for which INRS progress is evaluated; and
- Statewide, annual N and P export from Iowa based on measured loads from rivers.
The scales, spatially and temporally, at which water quality benefits might be anticipated to be detectable from monitoring data are reviewed in the next tab. This topic was explored for nitrogen loads for Iowa in a 2020 report titled How Long Will it Take to Measure an Improvement in Iowa's Water Quality? prepared for the Iowa DNR.
Changes from 1980-1996, the "baseline," to the initial INRS assessment from 2006-2010, the "benchmark," are summarized in the table below for nonpoint (NPS) and point (PS) loads. A summary of the nonpoint and point source changes between the two periods can be found here. 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 |
PS | 13,170 | 14,054 | 6.7% Increase | Flow increase | |
Total | 292,022 | 307,449 | 5.3% Increase | ||
Phosphorus | NPS | 21,436 | 16,800 | 21.6% Decrease | Reduced tillage and soil test P |
PS | 2,386 | 2,623 | 9.9% Increase | Flow increase | |
Total | 23,822 | 19,423 | 18.5% Decrease |
*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
The scale at which changes in N and P loads can be measured is a continued area of focus for the INRS. With a goal of 45% N and P load reduction, the spatial and temporal scales within a watershed at which management and conservation practices – representing the land use, wastewater management improvements, and agronomic and conservation practice adoption – are reflected in nutrient loads. Ongoing research continues to examine the watershed and temporal scale at which load reductions can be quantified. Assessing the nutrient load over time is challenging due to “legacy nutrients” that vary in movement through soil and shallow groundwater before reaching streams and rivers. Measuring nutrient load changes at the landscape scale is equally challenging as flow, the amount of runoff that leaves fields, is the strongest predictor of nutrient loss and varies annually. Currently understood scales for 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
Tracking water quality for the NRS for statewide reporting in 2021 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). The USGS monitors a large number of sites for flow, providing a long-term historical record, that allows for nutrient loads to be estimated since 2000 at least based on monitoring efforts by state agencies. The Ambient Water Quality Monitoring Network was comprised of 62 monitoring sites to measure N and P in 2021. Of these 62 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
- USGS resources: See the USGS National Water Dashboard for nationwide gages,
- DNR resources: DNR’s Water Monitoring summary (see Ambient Stream Monitoring program), and
- IIHR resources: IIHR’s Iowa Water Quality Information System for 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 smaller rivers, streams, and lakes as well as research programs conducted by Regents Institutions, Iowa Soybean Association, and the Agriculture’s Clean Water Alliance. Efforts include the general monitoring of surface waters, small watersheds to monitor the impact of a BMP at the field or small catchment scale, or tile monitoring. 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. The siting of these monitoring sites is able to cover the majority of the surface area of the 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 rivers and contributing area, the upstream area draining to the monitoring point, are summarized by watershed size at the HUC-12 watershed scale in Appendix D. Note that only monitoring sites reported by INRS reporting partners are summarized.
Iowa Precipitation Summary
The INRS reports on nutrient loading and water yields at the state scale. However, the amount of water each region receives drives the amount of flow, varying regionally and temporally each year. In 2021, the average precipitation for Iowa was 31.06 inches, 4.45 inches greater than the long-term average. But, the 2021 average was within the average precipitation range for the INRS (29-36.5 inches). The water yield during the INRS baseline was approximately one-third of precipitation, comparable to 2021.
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 at the Iowa Agriculture and Land Stewardship.
The 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 |
Flow (in/yr) | 4.21 | 10.17 | 4.75 | 5.03 | 8.77 | 6.22 | 5.6 | 14.35 | 18.38 | 12.71 | 20.8 | 11.09 | 3.51 | 10.25 | 10.87 | 12.95 | 15.76 | 10.45 | 17.84 | 18.73 | 10 | 5.45 |
Five-Year Average Flow (in/yr) | 6.59 | 6.99 | 6.07 | 7.99 | 10.66 | 11.45 | 14.37 | 15.47 | 13.3 | 11.67 | 11.3 | 9.73 | 10.67 | 12.06 | 13.57 | 15.15 | 14.56 | 12.5 |
Measured Changes in N Export Based on River Monitoring
The nitrogen load from Iowa for 2021 was the second lowest observed during the period for which statewide data is available (2000). Similarly, the flow-weighted nitrate load (FWNL) was also low and recorded as the lowest since 2000. The FWNL characterizes changes in nitrate losses normalized to flow. Periods of low statewide flow correspond with low statewide N load as nitrogen is not lost through runoff from fields. Precipitation is the strongest predictor of N loads, precipitation in the current year and previous year, and can compound N losses following periods of prolonged low flow. Cyclical responses in statewide N load are anticipated and will reflect agronomic practices and BMPs adopted regarding N management.
2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | |
Annual Nitrate-N Load | 101,297 | 300,428 | 115,070 | 144,048 | 264,356 | 186,995 | 174,989 | 450,132 | 434,611 | 281,028 | 455,312 | 297,245 | 66,188 | 342,921 | 267,052 | 417,793 | 531,776 | 318,111 | 426,416 | 396,289 | 241,254 | 81,619 |
5-year Moving Average Nitrate-N Load | 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 | 382,769 | 292,738 | ||||
Annual Nitrate-N Flow-Weighted Load | 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 |
5-year Moving Average Nitrate-N Flow-Weighted Load | 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 |
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.
Water Quality - Nitrogen Monitoring
Quantifying 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 nutrient 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 loads - nutrient loads as concentration, the amount of a nutrient lost per unit time as a load, or normalize nutrient loss to the amount of flow within the river.
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 is not only simple, but 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 with flow from rivers monitored by the USGS (see more about gaging locations in the previous panel). The amount of flow at each monitoring site is normalized each year. Flow is measured as the average depth of water that runs off the watershed and is calculated by deducting from precipitation that falls in the watershed from soil saturation and temperature. Statewide flow is then based on the weighted average flow of each watershed as a proportion of the area of the watershed.
Measured Changes in P Export Based on River Monitoring
Phosphorus loads are strongly correlated with the amount of flow, with large flood events regularly accounting for more than half of an annual load. With lower flow in 2020 and 2021, the P load and flow-weighted P load (FWPL) have been lower than the period for which P load data is available. Similar to N, the annual P load is “noisy” and a 5-year moving average is used to assess patterns over time. Since 2010, the 5-year moving average P load has been greater than the INRS load goal for P, driven by years of average or above-average flow.
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 trend in the 5-year moving average FWPL is observed.
2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | |
Annual Phosphorus Load | 6,786 | 26,499 | 8,319 | 8,102 | 18,103 | 9,874 | 6,918 | 29,142 | 38,647 | 21,669 | 38,835 | 17,144 | 6,068 | 20,754 | 28,192 | 24,554 | 24,361 | 16,572 | 32,052 | 47,551 | 13,643 | 8,173 |
5-year Moving Average Phosphorus Load | 13,562 | 14,179 | 10,263 | 14,428 | 20,537 | 21,250 | 27,042 | 29,087 | 24,472 | 20,894 | 22,199 | 19,342 | 20,786 | 22,887 | 25,146 | 29,018 | 26,836 | 23,598 | ||||
Annual Phosphorus Flow-Weighted Load | 1,612 | 2,606 | 1,751 | 1,611 | 2,064 | 1,588 | 1,235 | 2,031 | 2,103 | 1,705 | 1,867 | 1,546 | 1,729 | 2,025 | 2,594 | 1,896 | 1,546 | 1,586 | 1,797 | 2,539 | 1,364 | 1,500 |
5-year Moving Average Phosphorus Flow-Weighted Load | 1,929 | 1,924 | 1,650 | 1,706 | 1,804 | 1,732 | 1,788 | 1,850 | 1,790 | 1,774 | 1,952 | 1,958 | 1,958 | 1,929 | 1,884 | 1,873 | 1,766 | 1,757 |
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 meet soil conservation compliance established in the 1986 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 is described in that section as well as the Water Monitoring Infrastructure tab (bottom-left panel ). The mode by which the P load is calculated differs. In contrast with N, linear interpolation methods are not appropriate for estimating phosphorus (P). Phosphorus concentrations are dynamic and positively skewed, with some measurements far greater than the median concentration observed in a river under baseflow conditions. This means that phosphorus loads in rivers are strongly influenced by storms and high flow events, although infrequent, can strongly impact the P load. Linear interpolation as is used for N results in significant errors when modeling P, so more sophisticated modeling techniques are needed to quantify it.
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. 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 but 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
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, INREC Survey, and the USDA Census of Agriculture. For more information on the approximation of BMP use in Iowa see the Land indicator dashboards or the Data tab below.
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 2021 (tons) | Per. N Load Impact in 2021 (%) |
Cover Crop | -12,015.7 | -4.1 |
N Timing: Nitrification Inhibitor | -7,872.0 | -2.7 |
N Timing: Changes to Spring Pre-Plant, Sidedress, or In-Season | -2,274.0 | -0.8 |
Water Quality Wetlands | -947.3 | -0.3 |
Bioreactor or Saturated Buffer | -56.0 | 0 |
N Rate Continuous Corn | 174.9 | 0.1 |
Extended to Continuous Corn | 1,432.3 | 0.5 |
Pasture, Grass, Hay or CRP to Continuous Corn | 1,782.8 | 0.6 |
Extended to Corn-Soybean | 2,239.2 | 0.8 |
Pasture, Grass, Hay or CRP to Corn/Soybean | 7,711.4 | 2.6 |
N Rate Corn-Soybean | 32,229.4 | 11 |
Adoption of BMPs that can be broadly adopted across Iowa increased in number, and the acreage benefitted from these practices since the 2019 INRS report. Cover crop adoption increased to an estimated 2.77 million acres in 2021 (INREC Ag Retailer Survey) – up from the 0.97 million acres reported in the last INRS report – and are estimated to reduce N losses from the baseline period by 4.1%, or more than 12,000 tons. A rye cover crop reduces N load by an estimated 31% per the INRS, 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, such as bioreactors, saturated buffers, and water quality wetlands, have seen an increase in practice adoption in recent years. These practices benefitted at least 9,700 acres and 139,000 for bioreactors/saturated buffers and wetlands, respectively. These practices reduced N loads by 56 and 947 tons for bioreactors/saturated buffers and wetlands in 2021. The adoption of these practices has increased primarily due to more recent development 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 11% (32,200 tons) when compared to the estimated rate during the baseline period. These rates are stand-alone and compare rates from 2021 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 conservation practice use in Iowa see the Land indicator dashboards. 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
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, INREC Survey, and the USDA Census of Agriculture. For more information on the approximation of BMP use in Iowa, see the Land indicator sections.
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 | -3919.5 | -16.5 |
Cover Crop | -2072.8 | -8.7 |
Terrace | -79.4 | -0.3 |
WASCOB, Grade Stabilization Structure, Pond | -77.5 | -0.3 |
Conservation Tillage | -19.3 | -0.1 |
Pasture, Grass, and Hay | 826.2 | 3.5 |
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 9,461,121 and 5,253,814 acres, reflecting a reduction of 16.4% (3,920 tons) and 0.2% (19.3 tons) in statewide P load as of 2021, 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 250,000 acres have been built using public financial assistance programs and are estimated to reduce P loads by 156 tons, or 0.7% 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.
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. (2023, August 6). Tracking the Iowa Nutrient Reduction Strategy. Version 2.0. https://nrstracking.cals.iastate.edu/tracking-iowa-nutrient-reduction-s…
Appendix A
Program | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | Program Total |
Ag Drainage Well Closure (ADW) - IDALS | $3,170,000 | $1,920,000 | $1,920,000 | $1,875,000 | $1,875,000 | $1,875,000 | $1,875,000 | $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 | $145,314,000 |
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 | $10,000,000 |
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 | $2,945,237,021 |
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 | $9,600,000 |
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 | $120,500,000 |
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 | $106,292,908 |
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 | $36,334,118 |
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 | $24,722,799 |
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 | $10,414,258 |
CWSRF - Sponsored Projects - DNR | $3,736,000 | $5,748,000 | $5,424,823 | $2,618,283 | $1,627,000 | $8,109,000 | $7,438,958 | $34,702,064 | |||
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 | $29,550,000 |
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 | $273,100,000 |
Farm Management Demonstration Program - IDALS | $625,000 | $625,000 | $625,000 | $625,000 | $625,000 | $625,000 | $375,000 | $287,500 | $100,000 | $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 | $7,128,832 |
In-Field Agricultural Practices Pilot Project - ISU | $1,230,000 | $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 | $3,559,500 |
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 | $67,630,500 |
Iowa Geological Survey - Water Resource Management - IGS | $495,000 | $495,000 | $495,000 | $1,485,000 | |||||||
Iowa Nutrient Research Center - ISU | $1,500,000 | $1,325,000 | $1,625,000 | $1,400,000 | $2,269,811 | $1,976,653 | $2,015,121 | $2,135,195 | $14,246,780 | ||
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 | $85,909,000 |
Leopold Center - ISU | $1,643,615 | $1,838,630 | $1,791,916 | $1,876,738 | $1,918,525 | $2,032,465 | $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 | $1,019,375 |
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 | $4,478,125 |
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 | $29,582,075 |
Regional Conservation Partnership Program (RCPP) - NRCS | $406,785 | $1,597,000 | $4,340,000 | $5,021,100 | $4,552,300 | $2,829,981 | $18,747,166 | ||||
Regional Conservation Partnership Program (RCPP-EQIP) - NRCS | $261,000 | $2,212,878 | $2,473,878 | ||||||||
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 | $26,800,000 |
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 | $35,968,300 |
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 | $30,350,000 |
Wastewater and Drinking Water Treatment Financial Assistance Program - IFA | $782,000 | $1,600,000 | $4,928,000 | $7,310,000 | |||||||
Water Quality Agriculture Infrastructure Program - IDALS | $1,955,000 | $4,000,000 | $15,000,000 | $20,955,000 | |||||||
Water Quality Financing Program - IFA | $879,750 | $1,800,000 | $6,750,000 | $9,429,750 | |||||||
Water Quality Initiative Fund - IDALS | $12,400,000 | $4,400,000 | $9,150,000 | $9,375,000 | $10,575,000 | $10,575,000 | $12,175,000 | $12,175,000 | $80,825,000 | ||
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 | $1,993,000 |
Water Quality Urban Infrastructure Program - IDALS | $293,250 | $600,000 | $1,848,000 | $2,741,250 | |||||||
Watershed Improvement Fund - IDALS | $2,000,000 | $4,000,000 | $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 | $9,000,000 |
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 | $4,244,754,088 |
Appendix B
County | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Community Outreach | Conference | Field Day | Workshop | Youth and School Visits | Total | Community Outreach | Conference | Field Day | Workshop | Youth and School Visits | Total | Community Outreach | Conference | Field Day | Workshop | Youth and School Visits | Total | Community Outreach | Conference | Field Day | Workshop | Youth and School Visits | Total | Community Outreach | Conference | Field Day | Workshop | Youth and School Visits | Total | Community Outreach | Conference | Field Day | Workshop | Youth and School Visits | Total | |||||||||||||||||||||||||||||||||||||
Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | No. Events | Attendance | 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 | 0 | 0 | 0 | 0 | 105 | 2 | 105 | 2 |
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 |
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 |
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 |
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 |
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 | 70 | 4 | 0 | 0 | 15 | 1 | 72 | 2 | 467 | 4 | 624 | 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 |
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 | 70 | 5 | 0 | 0 | 41 | 4 | 0 | 0 | 461 | 7 | 572 | 16 |
Boone | 1,000 | 1 | 0 | 0 | 40 | 1 | 0 | 5 | 147 | 2 | 1,187 | 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 | 4,318 | 4 | 0 | 0 | 376 | 7 | 108 | 3 | 152 | 3 | 4,954 | 17 | 146 | 3 | 0 | 0 | 65 | 1 | 59 | 2 | 271 | 5 | 541 | 11 | 40 | 1 | 0 | 0 | 30 | 1 | 0 | 0 | 101 | 3 | 171 | 5 |
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 |
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 |
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 | 40 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 108 | 1 | 148 | 2 |
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 |
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 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 113 | 2 | 113 | 2 |
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 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 1 | 170 | 2 | 174 | 3 |
Cass | 0 | 0 | 0 | 0 | 88 | 2 | 25 | 1 | 0 | 0 | 113 | 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 |
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 |
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 |
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 |
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 | 5 | 0 | 0 | 78 | 1 | 184 | 7 | 0 | 0 | 0 | 0 | 80 | 2 | 0 | 0 | 205 | 4 | 285 | 6 |
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 |
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 |
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 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 82 | 3 | 82 | 5 |
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 |
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 |
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 | 120 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 629 | 12 | 749 | 16 |
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 |
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 |
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 | 0 | 1 | 0 | 0 | 245 | 3 | 245 | 4 |
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 |
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 |
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 | 0 | 0 | 0 | 0 | 1,430 | 12 | 1,430 | 12 |
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 |
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 |
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 | 0 | 0 | 0 | 0 | 0 | 1 | 30 | 1 | 222 | 3 | 252 | 5 |
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 |
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 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 87 | 1 | 87 | 1 | 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 |
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 | 2 | 104 | 2 | 141 | 5 |
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 |
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 | 0 | 0 | 0 | 0 | 71 | 2 | 0 | 0 | 196 | 1 | 267 | 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 |
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 | 45 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 302 | 2 | 347 | 4 | 270 | 2 | 0 | 0 | 133 | 2 | 0 | 0 | 0 | 0 | 403 | 4 | 0 | 0 | 0 | 0 | 90 | 1 | 0 | 1 | 0 | 0 | 90 | 2 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 163 | 2 | 163 | 3 |
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 |
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 |
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 |
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 | 122 | 3 | 0 | 0 | 2 | 1 | 15 | 3 | 15 | 1 | 154 | 8 | 6 | 1 | 0 | 0 | 25 | 1 | 305 | 3 | 436 | 7 | 772 | 12 |
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 | 51 | 3 | 0 | 0 | 40 | 1 | 0 | 0 | 580 | 1 | 671 | 5 | 0 | 0 | 0 | 0 | 40 | 1 | 22 | 3 | 229 | 2 | 291 | 6 | 0 | 0 | 0 | 0 | 35 | 1 | 5 | 1 | 151 | 3 | 191 | 5 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 15 | 1 | 15 | 2 |
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 |
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 |
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 |
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 |
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 |
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 |
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 |
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 |
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 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 65 | 1 | 65 | 1 | 0 | 0 | 0 | 0 | 160 | 3 | 0 | 0 | 299 | 2 | 459 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 7 | 1 | 192 | 2 | 199 | 3 | 0 | 0 | 0 | 0 | 65 | 2 | 42 | 1 | 166 | 2 | 273 | 5 |
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 |
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 | 4 | 0 | 0 | 25 | 1 | 130 | 3 | 1,114 | 6 | 1,537 | 14 | 446 | 4 | 0 | 0 | 214 | 4 | 0 | 0 | 1,370 | 9 | 2,030 | 17 | 70 | 4 | 0 | 0 | 0 | 0 | 7 | 2 | 1,262 | 18 | 1,339 | 24 |
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 |
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 |
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 |
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 | 0 | 0 | 0 | 0 | 214 | 1 | 214 | 1 |
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 | 200 | 2 | 0 | 0 | 42 | 1 | 0 | 0 | 50 | 1 | 292 | 4 |
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 |
Marshall | 0 | 1 | 0 | 0 | 35 | 1 | 0 | 0 | 0 | 0 | 35 | 2 | 0 | 0 | 0 | 0 | 149 | 4 | 0 | 0 | 0 | 0 | 149 | 4 | 147 | 1 | 0 | 0 | 0 | 0 | 85 | 1 | 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 |
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 |
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 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 10 | 1 | 10 | 1 |
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 |
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 |
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 |
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 | 48 | 2 | 0 | 0 | 50 | 1 | 0 | 0 | 154 | 3 | 252 | 6 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 78 | 2 | 78 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 106 | 3 | 39 | 1 | 145 | 4 |
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 |
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 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
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 |
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 |
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 | 800 | 5 | 0 | 0 | 292 | 4 | 0 | 0 | 128 | 3 | 1,220 | 12 | 0 | 0 | 0 | 0 | 220 | 3 | 0 | 0 | 246 | 3 | 466 | 6 | 2,010 | 8 | 0 | 0 | 0 | 0 | 1 | 1 | 166 | 6 | 2,177 | 15 |
Pocahontas | 27 | 2 | 0 | 0 | 0 | 0 | 25 | 1 | 0 | 0 | 52 | 3 | 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 | 0 | 0 | 0 | 0 | 0 | 0 | 35 | 1 | 38 | 1 | 73 | 2 |
Polk | 7,485 | 13 | 1,105 | 7 | 209 | 3 | 1,021 | 41 | 458 | 9 | 10,278 | 73 | 11,049 | 20 | 1,912 | 10 | 180 | 4 | 967 | 48 | 7,240 | 19 | 21,348 | 101 | 285 | 4 | 1,331 | 8 | 166 | 4 | 601 | 9 | 5,095 | 25 | 7,478 | 50 | 823 | 13 | 771 | 6 | 275 | 3 | 228 | 8 | 7,149 | 31 | 9,246 | 61 | 877 | 10 | 45 | 2 | 9 | 2 | 125 | 7 | 5,664 | 23 | 6,720 | 44 | 50 | 2 | 561 | 2 | 0 | 0 | 813 | 27 | 2,790 | 57 | 4,214 | 88 |
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 |
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 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 398 | 2 | 398 | 3 |
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 |
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 |
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 | 0 | 0 | 0 | 0 | 177 | 4 | 177 | 4 |
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 |
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 | 87 | 2 | 0 | 0 | 346 | 3 | 0 | 0 | 530 | 3 | 963 | 8 | 50 | 1 | 0 | 0 | 25 | 1 | 185 | 3 | 24 | 1 | 284 | 6 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 562 | 4 | 564 | 6 |
Story | 0 | 0 | 402 | 2 | 54 | 2 | 77 | 4 | 153 | 5 | 686 | 13 | 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 | 385 | 10 | 1,137 | 7 | 587 | 12 | 53 | 2 | 1,818 | 12 | 3,980 | 43 | 206 | 3 | 1,298 | 3 | 246 | 6 | 220 | 5 | 2,085 | 10 | 4,055 | 27 | 44 | 7 | 578 | 3 | 579 | 12 | 321 | 17 | 659 | 16 | 2,181 | 55 |
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 | 0 | 0 | 13 | 1 | 103 | 2 | 236 | 4 |
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 | 230 | 1 | 0 | 0 | 14 | 2 | 21 | 2 | 71 | 1 | 336 | 6 | 0 | 0 | 0 | 0 | 50 | 1 | 0 | 0 | 78 | 1 | 128 | 2 | 250 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 282 | 2 | 532 | 4 |
Union | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 72 | 1 | 72 | 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 |
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 | 362 | 4 | 362 | 4 |
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 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 358 | 6 | 358 | 6 |
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 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 54 | 1 | 54 | 1 |
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 | 281 | 4 | 326 | 7 |
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 |
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 | 338 | 3 | 0 | 0 | 0 | 0 | 21 | 1 | 122 | 1 | 481 | 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 |
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 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 67 | 1 | 67 | 1 |
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 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 347 | 4 | 347 | 6 |
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 |
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 |
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 | 79 | 4 | 0 | 0 | 145 | 5 | 30 | 1 | 105 | 2 | 359 | 12 | 0 | 0 | 0 | 0 | 57 | 2 | 14 | 1 | 148 | 2 | 219 | 5 | 25 | 1 | 0 | 0 | 0 | 0 | 16 | 1 | 30 | 1 | 71 | 3 | 9 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 318 | 5 | 327 | 6 |
Appendix C
HUC-8 Name | HUC-8 ID | No-Till | Conservation Tillage | Cover Crops | Bioreactors and Saturated Buffers | Water Quality Wetlands | Structural Erosion Control Practices |
Blue Earth | 07020009 | 6,719 | 102,708 | 2,715 | |||
Root | 07040008 | 411 | 1,030 | 111 | |||
Coon-Yellow | 07060001 | 47,075 | 55,951 | 10,870 | 1 | 4,090 | |
Upper Iowa | 07060002 | 70,778 | 161,999 | 18,552 | 2,280 | ||
Grant-Little Maquoketa | 07060003 | 44,173 | 42,944 | 8,870 | 990 | ||
Turkey | 07060004 | 192,011 | 329,965 | 42,264 | 3 | 3,420 | |
Apple-Plum | 07060005 | 61,720 | 49,398 | 7,778 | 830 | ||
Maquoketa | 07060006 | 246,312 | 353,476 | 35,484 | 3,300 | ||
Copperas-Duck | 07080101 | 82,062 | 80,030 | 9,072 | 2 | 380 | |
Upper Wapsipinicon | 07080102 | 170,808 | 384,714 | 30,948 | 1 | 820 | |
Lower Wapsipinicon | 07080103 | 181,792 | 191,354 | 16,415 | 1 | 110 | |
Flint-Henderson | 07080104 | 53,992 | 92,578 | 7,823 | 1 | 2,850 | |
South Skunk | 07080105 | 226,689 | 364,029 | 36,299 | 14 | 10 | 3,050 |
North Skunk | 07080106 | 182,323 | 129,007 | 23,346 | 1 | 3,920 | |
Skunk | 07080107 | 233,979 | 237,207 | 51,343 | 3 | 1 | 19,400 |
Upper Cedar | 07080201 | 91,279 | 244,565 | 21,601 | 12 | 12 | 650 |
Shell Rock | 07080202 | 84,267 | 203,821 | 14,017 | 1 | 5 | 140 |
Winnebago | 07080203 | 28,497 | 164,539 | 2,782 | 6 | ||
West Fork Cedar | 07080204 | 83,196 | 238,889 | 12,398 | 2 | 100 | |
Middle Cedar | 07080205 | 360,231 | 614,596 | 70,753 | 16 | 12 | 1,660 |
Lower Cedar | 07080206 | 189,038 | 197,038 | 29,405 | 6 | 1,500 | |
Upper Iowa | 07080207 | 109,450 | 384,931 | 17,484 | 2 | 8 | 220 |
Middle Iowa | 07080208 | 333,300 | 315,470 | 43,908 | 5 | 1,640 | |
Lower Iowa | 07080209 | 325,454 | 242,069 | 63,892 | 12,400 | ||
Upper Des Moines | 07100002 | 25,656 | 277,137 | 9,728 | 2 | 9 | 80 |
East Fork Des Moines | 07100003 | 23,679 | 319,790 | 10,785 | 5 | 40 | |
Middle Des Moines | 07100004 | 81,852 | 414,651 | 20,207 | 11 | 10 | 650 |
Boone | 07100005 | 29,854 | 243,484 | 7,666 | 7 | 4 | 40 |
North Raccoon | 07100006 | 174,148 | 657,213 | 38,322 | 39 | 18 | 1,520 |
South Raccoon | 07100007 | 207,047 | 194,404 | 18,537 | 6 | 2,550 | |
Lake Red Rock | 07100008 | 347,683 | 183,636 | 27,477 | 55 | 2 | 12,000 |
Lower Des Moines | 07100009 | 182,326 | 204,658 | 26,574 | 1 | 15,100 | |
Bear-Wyaconda | 07110001 | 17,116 | 25,770 | 4,669 | 6,990 | ||
North Fabius | 07110002 | 5,458 | 7,792 | 1,862 | 1,050 | ||
Lower Big Sioux | 10170203 | 85,460 | 155,683 | 12,429 | 4,930 | ||
Rock | 10170204 | 79,416 | 201,718 | 17,285 | 3,100 | ||
Blackbird-Soldier | 10230001 | 182,919 | 104,363 | 8,477 | 1,860 | ||
Floyd | 10230002 | 112,483 | 195,630 | 14,321 | 6 | 6,910 | |
Little Sioux | 10230003 | 240,052 | 482,125 | 22,382 | 1 | 5 | 3,150 |
Monona-Harrison Ditch | 10230004 | 203,594 | 146,996 | 10,201 | 2,180 | ||
Maple | 10230005 | 130,569 | 157,863 | 7,633 | 2,070 | ||
Big Papillion-Mosquito | 10230006 | 199,047 | 57,809 | 7,385 | 3,940 | ||
Boyer | 10230007 | 308,661 | 198,083 | 18,103 | 1 | 6,610 | |
Keg-Weeping Water | 10240001 | 131,122 | 37,131 | 6,117 | 2,610 | ||
West Nishnabotna | 10240002 | 581,332 | 155,488 | 25,675 | 2 | 13,000 | |
East Nishnabotna | 10240003 | 392,854 | 85,635 | 21,158 | 11,400 | ||
Nishnabotna | 10240004 | 24,473 | 10,032 | 1,544 | 420 | ||
Tarkio-Wolf | 10240005 | 111,089 | 31,736 | 6,331 | 6,690 | ||
West Nodaway | 10240009 | 237,052 | 54,552 | 11,800 | 8,190 | ||
Nodaway | 10240010 | 116,974 | 30,496 | 7,154 | 5,920 | ||
Platte | 10240012 | 82,767 | 21,469 | 3,546 | 3,440 | ||
One Hundred and Two | 10240013 | 94,354 | 21,397 | 4,485 | 3,130 | ||
Upper Grand | 10280101 | 77,563 | 17,909 | 2,640 | 4,920 | ||
Thompson | 10280102 | 151,860 | 54,020 | 10,764 | 12,900 | ||
Lower Grand | 10280103 | 17,028 | 10,212 | 722 | 870 | ||
Upper Chariton | 10280201 | 82,064 | 47,092 | 5,364 | 18,700 |
Appendix D
HUC-12 Name | HUC-12 ID | Large Watershed | Medium Watershed | Small Catchment or Field-Scale | Very Small Watershed | Small Watershed | Tile |
Drainage Ditch No 21 | 070200090401 | 1 | |||||
Iowa Lake | 070200090601 | 1 | |||||
Village Creek | 070600010602 | 1 | |||||
Clear Creek-Mississippi River | 070600010702 | 1 | |||||
Wexford Creek | 070600010706 | 1 | |||||
Lower Yellow River | 070600010906 | 3 | |||||
Bloody Run | 070600011002 | 1 | 3 | ||||
City of Prairie du Chien-Mississippi River | 070600011003 | 1 | |||||
Town of Granger-Upper Iowa River | 070600020107 | 1 | |||||
Daisy Valley-Upper Iowa River | 070600020203 | 1 | |||||
Martha Creek-Upper Iowa River | 070600020206 | 1 | |||||
Canoe Creek | 070600020302 | 1 | |||||
City of Decorah-Upper Iowa River | 070600020404 | 1 | |||||
Waterloo Creek | 070600020502 | 2 | |||||
Paint Creek-Upper Iowa River | 070600020602 | 3 | |||||
French Creek | 070600020604 | 3 | |||||
Clear Creek-Upper Iowa River | 070600020605 | 1 | |||||
Middle Fork Little Maquoketa River | 070600030601 | 1 | |||||
Lower Little Maquoketa River | 070600030604 | 1 | |||||
Sny Magill Creek | 070600030701 | 1 | |||||
Lock and Dam No 10-Mississippi River | 070600030704 | 1 | |||||
Spring Creek-Crane Creek | 070600040102 | 1 | |||||
Bohemian Creek | 070600040304 | 1 | |||||
Burr Oak Creek-Turkey River | 070600040308 | 1 | |||||
Brockamp Creek-Turkey River | 070600040309 | 1 | |||||
Coulee Creek-Volga River | 070600040504 | 1 | |||||
Mink Creek | 070600040602 | 1 | |||||
Nagle Creek-Volga River | 070600040604 | 1 | |||||
Honey Creek-Volga River | 070600040606 | 1 | |||||
Doe Creek-Volga River | 070600040608 | 1 | |||||
Village of Eldorado-Turkey River | 070600040703 | 1 | |||||
Bell Creek-Turkey River | 070600040707 | 1 | |||||
French Hollow-Turkey River | 070600040709 | 1 | |||||
Carlan Creek-Turkey River | 070600040902 | 4 | |||||
Catfish Creek | 070600050102 | 1 | 1 | ||||
Allison Creek-Maquoketa River | 070600060210 | 1 | 1 | ||||
Rat Run-Bear Creek | 070600060303 | 1 | |||||
Mineral Creek | 070600060409 | 2 | |||||
Johns Creek | 070600060502 | 1 | |||||
Buck Creek-North Fork Maquoketa River | 070600060803 | 2 | |||||
Cedar Creek-North Fork Maquoketa River | 070600060804 | 1 | |||||
Pumpkin Creek-Maquoketa River | 070600061001 | 1 | |||||
Hainer Creek-Maquoketa River | 070600061005 | 2 | |||||
Maquoketa River | 070600061007 | 1 | |||||
Cattail Slough-Mississippi River | 070801010204 | 5 | |||||
Upper Duck Creek | 070801010301 | 1 | |||||
Lower Duck Creek | 070801010302 | 1 | |||||
Crow Creek | 070801010405 | 1 | |||||
Kickapoo Slu-Mississippi River | 070801010601 | 1 | 1 | ||||
Watsons Creek-Wapsipinicon River | 070801020202 | 1 | |||||
Middle Crane Creek | 070801020402 | 4 | |||||
Village of Oran-Little Wapsipinicon River | 070801020503 | 1 | |||||
Etter Creek-Wapsipinicon River | 070801020601 | 1 | |||||
Otterville Bridge State Access-Wapsipinicon River | 070801020801 | 1 | |||||
Malone Creek-Wapsipinicon River | 070801020803 | 1 | |||||
Silver Creek-Buffalo Creek | 070801020904 | 1 | |||||
Helmer Creek-Buffalo Creek | 070801020906 | 1 | |||||
Heatons Creek-Wapsipinicon River | 070801021002 | 1 | |||||
Dutch Creek-Wapsipinicon River | 070801030201 | 1 | |||||
Hickory Creek | 070801030301 | 5 | |||||
Walnut Creek | 070801030408 | 1 | |||||
Brophy Creek | 070801030502 | 1 | |||||
Negro Creek-Silver Creek | 070801030601 | 1 | |||||
Silver Creek | 070801030602 | 1 | |||||
Barber Creek-Wapsipinicon River | 070801030603 | 1 | 1 | ||||
McDonald Creek-Wapsipinicon River | 070801030605 | 2 | 1 | ||||
Lost Creek | 070801030606 | 2 | 1 | ||||
Big Hollow-Flint Creek | 070801041203 | 1 | |||||
West Branch Sugar Creek | 070801041601 | 1 | 1 | ||||
Picayune Creek-Sugar Creek | 070801041602 | 1 | 2 | ||||
Pitman Creek-Sugar Creek | 070801041604 | 1 | 2 | ||||
Drainage Ditch 71 | 070801050102 | 1 | |||||
Lundys Creek-Squaw Creek | 070801050306 | 1 | |||||
Worrell Creek-Squaw Creek | 070801050307 | 2 | |||||
Miller Creek-South Skunk River | 070801050402 | 1 | |||||
Bear Creek | 070801050403 | 1 | 1 | ||||
Keigley Branch | 070801050405 | 1 | |||||
City of Ames-South Skunk River | 070801050406 | 1 | 1 | ||||
Mud Creek-Clear Creek | 070801050702 | 1 | |||||
Peoria Cemetery-Indian Creek | 070801050803 | 1 | |||||
Byers Branch-Indian Creek | 070801050804 | 1 | |||||
Turkey Creek-Indian Creek | 070801050805 | 1 | |||||
Walnut Creek | 070801050901 | 1 | 1 | ||||
Drainage Ditch 13-South Skunk River | 070801050903 | 2 | |||||
Sugar Creek-South Skunk River | 070801050908 | 1 | |||||
Elk Creek | 070801051002 | 15 | |||||
Carson Creek-South Skunk River | 070801051104 | 1 | |||||
Van Zante Creek-South Skunk River | 070801051106 | 1 | 4 | ||||
Buckley Creek | 070801051201 | 1 | 1 | ||||
Ballinger Creek-South Skunk River | 070801051202 | 2 | |||||
Spring Creek-South Skunk River | 070801051203 | 2 | 1 | 3 | 1 | ||
Snyder Creek-South Skunk River | 070801051204 | 1 | 2 | 2 | 1 | ||
Matrix Branch-South Skunk River | 070801051206 | 2 | |||||
South Skunk River | 070801051208 | 2 | 2 | ||||
Snipe Creek | 070801060101 | 2 | |||||
Alloway Creek-North Skunk River | 070801060103 | 1 | |||||
Rock Creek-North Skunk River | 070801060104 | 1 | |||||
Burr Oak Creek-North Skunk River | 070801060105 | 2 | |||||
Sugar Creek | 070801060203 | 1 | |||||
Headwaters Middle Creek | 070801060301 | 1 | |||||
Moon Creek | 070801060402 | 1 | |||||
Pleasant Creek-North Skunk River | 070801060404 | 2 | |||||
Village of Delta-North Skunk River | 070801060601 | 1 | |||||
German Creek | 070801060603 | 1 | |||||
North Skunk River | 070801060604 | 1 | |||||
Upper West Fork Crooked Creek | 070801070101 | 1 | 1 | 1 | |||
Middle West Fork Crooked Creek | 070801070102 | 4 | 2 | 8 | |||
Lower West Fork Crooked Creek | 070801070103 | 1 | |||||
Honey Creek | 070801070304 | 1 | |||||
Coon Creek | 070801070501 | 1 | |||||
Competine Creek | 070801070502 | 3 | |||||
Headwaters Cedar Creek | 070801070601 | 1 | 1 | ||||
Spring Creek-Cedar Creek | 070801070602 | 1 | 2 | ||||
Buckeye Creek | 070801070603 | 1 | 1 | 4 | |||
Wolf Creek-Cedar Creek | 070801070604 | 3 | 1 | ||||
Church Creek-Cedar Creek | 070801070702 | 2 | |||||
Little Cedar Creek | 070801070707 | 1 | 1 | ||||
Summer Creek-Cedar Creek | 070801070708 | 2 | |||||
Wolf Creek | 070801070709 | 1 | 1 | ||||
Cedar Creek | 070801070710 | 4 | |||||
Shawnee Creek-Skunk Rvier | 070801070802 | 1 | |||||
Headwaters Big Creek | 070801070901 | 1 | |||||
Brandywine Creek | 070801070902 | 3 | |||||
North Branch Big Creek-Big Creek | 070801070903 | 2 | 2 | ||||
Brush Creek-Big Creek | 070801070904 | 1 | 2 | ||||
Lynn Creek-Big Creek | 070801070905 | 1 | 1 | 2 | |||
Fish Creek | 070801071001 | 1 | |||||
Prairie Creek-Skunk River | 070801071002 | 2 | |||||
Cedar Creek | 070801071004 | 1 | |||||
Skunk River | 070801071006 | 3 | 1 | ||||
Deer Creek | 070802010403 | 2 | |||||
Spring Creek | 070802010602 | 2 | |||||
Rock Creek | 070802010604 | 1 | 1 | 1 | |||
Beaver Creek | 070802010901 | 2 | 1 | 1 | |||
Colwell County Park-Little Cedar River | 070802010902 | 1 | 1 | ||||
Little Cedar River | 070802010903 | 1 | |||||
Skunk Creek-Cedar River | 070802011001 | 3 | |||||
Drainage Ditch 3 | 070802011002 | 1 | |||||
Stewart Creek-Cedar River | 070802011003 | 2 | 3 | ||||
Bloody Run-Cedar River | 070802011005 | 2 | 4 | ||||
Cedar Bend County Park-Cedar River | 070802011204 | 1 | |||||
Village of Janesville-Cedar River | 070802011205 | 3 | |||||
County Ditch No 55 | 070802020106 | 1 | |||||
Headwaters Flood Creek | 070802020501 | 1 | |||||
Peters Creek-Flood Creek | 070802020503 | 1 | |||||
Heery Woods State Park-Shell Rock River | 070802020704 | 1 | |||||
Shell Rock River | 070802020705 | 3 | 1 | ||||
Headwaters Beaver Creek | 070802030107 | 1 | |||||
Clear Creek | 070802030201 | 2 | |||||
Cheslea Creek-Willow Creek | 070802030203 | 3 | |||||
Willow Creek | 070802030302 | 1 | |||||
Spring Creek | 070802030304 | 1 | |||||
City of Mason City-Winnebago River | 070802030306 | 1 | |||||
Mason Creek-Winnebago River | 070802030401 | 1 | |||||
Bailey Creek | 070802040102 | 1 | |||||
Buffalo Creek | 070802040301 | 1 | |||||
Spring Creek | 070802040303 | 1 | |||||
Big Marsh State Wildlife Area-West Fork Cedar River | 070802040605 | 1 | |||||
West Fork Cedar River | 070802040607 | 2 | |||||
Middle Fork South Beaver Creek | 070802050101 | 1 | |||||
Headwaters South Beaver Creek | 070802050102 | 1 | |||||
South Beaver Creek | 070802050103 | 1 | |||||
Headwaters Beaver Creek | 070802050201 | 1 | |||||
North Beaver Creek | 070802050202 | 1 | |||||
Drainage Ditch 148-Beaver Creek | 070802050203 | 1 | |||||
Gran Creek-Beaver Creek | 070802050204 | 1 | |||||
Johnson Creek | 070802050301 | 1 | |||||
Phelps Creek-Beaver Creek | 070802050302 | 1 | |||||
Max Creek-Beaver Creek | 070802050303 | 1 | |||||
Hammers Creek-Beaver Creek | 070802050304 | 3 | |||||
South Fork Black Hawk Creek | 070802050401 | 1 | |||||
Headwaters North Fork Black Hawk Creek | 070802050402 | 1 | |||||
North Fork Black Hawk Creek | 070802050403 | 1 | |||||
Holland Creek | 070802050501 | 1 | 1 | ||||
Headwaters Black Hawk Creek | 070802050502 | 1 | |||||
Mosquito Creek | 070802050503 | 1 | |||||
Minnehaha Creek-Black Hawk Creek | 070802050504 | 1 | |||||
Village of Reinbeck-Black Hawk Creek | 070802050505 | 2 | 1 | 3 | |||
Wilson Creek-Black Hawk Creek | 070802050601 | 1 | 1 | 2 | |||
Prescotts Creek-Black Hawk Creek | 070802050602 | 2 | 1 | ||||
Dry Run | 070802050701 | 4 | |||||
Waterloo Municipal Airport Waterloo Muncipal Airport Airport. | 070802050702 | 2 | |||||
Black Hawk Park-Cedar River | 070802050703 | 1 | 1 | ||||
Little Wolf Creek | 070802050802 | 1 | |||||
Village of Conrad-Wolf Creek | 070802050803 | 2 | |||||
Fourmile Creek | 070802050804 | 1 | |||||
Coon Creek | 070802050805 | 1 | |||||
Rock Creek | 070802050806 | 1 | 2 | ||||
Twelvemile Creek | 070802050807 | 1 | |||||
Devils Run-Wolf Creek | 070802050808 | 1 | |||||
Wolf Creek | 070802050809 | 8 | 1 | 2 | 1 | ||
Elk Run | 070802050901 | 1 | |||||
Poyner Creek | 070802050902 | 1 | |||||
Indian Creek | 070802050903 | 1 | |||||
Headwaters Miller Creek | 070802050904 | 4 | 3 | 1 | 3 | ||
Miller Creek | 070802050905 | 1 | 3 | 3 | 7 | ||
Sink Creek-Cedar River | 070802050906 | 1 | 2 | ||||
Rock Creek-Cedar River | 070802051001 | 3 | 2 | ||||
Spring Creek | 070802051002 | 1 | |||||
Lime Creek | 070802051003 | 3 | |||||
Bear Creek-Cedar River | 070802051004 | 2 | |||||
McFarlane State Park-Cedar River | 070802051005 | 5 | |||||
Pratt Creek | 070802051101 | 1 | 3 | ||||
Hinkle Creek | 070802051102 | 3 | |||||
Prairie Creek-Cedar River | 070802051103 | 1 | |||||
Mud Creek | 070802051104 | 2 | 3 | ||||
Dudgeon Lake State Wildlife Management Area-Cedar River | 070802051105 | 1 | 1 | 1 | |||
Opossum Creek | 070802051201 | 2 | |||||
Wildcat Creek | 070802051202 | 1 | 2 | ||||
Little Bear Creek | 070802051203 | 1 | |||||
Bear Creek | 070802051204 | 2 | |||||
West Otter Creek | 070802051301 | 2 | |||||
East Otter Creek-Otter Creek | 070802051302 | 1 | |||||
Village of Van Horne-Prairie Creek | 070802051402 | 1 | |||||
Mud Creek-Prairie Creek | 070802051403 | 1 | |||||
Weasel Creek-Prairie Creek | 070802051404 | 2 | |||||
Prairie Creek | 070802051405 | 1 | |||||
East Branch Blue Creek | 070802051501 | 1 | |||||
Blue Creek | 070802051502 | 1 | |||||
Nelson Creek-Cedar River | 070802051504 | 1 | |||||
Dry Creek | 070802051505 | 1 | |||||
Morgan Creek | 070802051506 | 2 | 3 | ||||
Silver Creek-Cedar River | 070802051507 | 8 | 1 | ||||
Indian Creek | 070802060103 | 1 | |||||
Pleasant Run-Cedar River | 070802060401 | 1 | 1 | ||||
Mill Creek-Cedar River | 070802060405 | 1 | |||||
Community of Buchanan-Cedar River | 070802060407 | 1 | |||||
West Branch Wapsinonoc Creek | 070802060702 | 6 | |||||
Crane Creek-Cedar River | 070802060806 | 4 | |||||
Headwaters West Branch Iowa River | 070802070101 | 1 | |||||
Drainage Ditch No 1 | 070802070102 | 1 | |||||
Eagle Lake State Game Management Area-West Branch Iowa River | 070802070103 | 1 | |||||
West Branch Iowa River | 070802070104 | 1 | 1 | 1 | |||
Drainage Ditch No 9-East Branch Iowa River | 070802070204 | 1 | 4 | ||||
East Branch Iowa River | 070802070205 | 2 | |||||
Elm Lake State Game Management Area-Iowa River | 070802070302 | 1 | 1 | ||||
Headwaters Tipton Creek | 070802070401 | 2 | |||||
Tipton Creek | 070802070402 | 1 | |||||
Beaver Creek | 070802070502 | 1 | |||||
Headwaters South Fork Iowa River | 070802070601 | 1 | |||||
Middle South Fork Iowa River | 070802070603 | 3 | |||||
Lower South Fork Iowa River | 070802070604 | 1 | 3 | 1 | |||
Pine Creek-Iowa River | 070802070902 | 2 | 2 | ||||
Brush Creek | 070802080202 | 1 | |||||
Timber Creek | 070802080206 | 1 | |||||
Headwaters Deer Creek | 070802080301 | 1 | |||||
Dry Branch-Iowa River | 070802080403 | 1 | |||||
Davisons Creek-Iowa River | 070802080405 | 1 | |||||
Bennett Creek-Iowa River | 070802080407 | 1 | |||||
Stein Creek | 070802080504 | 1 | 2 | ||||
East Branch Salt Creek | 070802080505 | 1 | |||||
Salt Creek | 070802080507 | 1 | |||||
Walnut Creek | 070802080603 | 1 | |||||
Richland Creek | 070802080701 | 1 | |||||
Otter Creek | 070802080702 | 1 | |||||
Big Bear Creek | 070802080806 | 1 | |||||
Village of Belle Plaine-Iowa River | 070802080903 | 1 | |||||
Coon Creek-Iowa River | 070802080904 | 1 | |||||
Price Creek | 070802081002 | 1 | |||||
Mill Race-Iowa River | 070802081003 | 1 | |||||
Lake MacBride-Mill Creek | 070802081008 | 1 | |||||
Upper Clear Creek | 070802090101 | 1 | |||||
Middle Clear Creek | 070802090102 | 3 | |||||
Lower Clear Creek | 070802090103 | 1 | 2 | ||||
Old Womans Creek-Old Mans Creek | 070802090207 | 3 | 1 | ||||
Deep River | 070802090403 | 1 | |||||
Devils Run | 070802090405 | 1 | |||||
Outlet North English River | 070802090408 | 1 | |||||
Ramsey Creek-English River | 070802090605 | 2 | |||||
English River | 070802090606 | 1 | |||||
Rapid Creek | 070802090701 | 2 | 1 | ||||
Ralston Creek-Iowa River | 070802090703 | 3 | 1 | 2 | |||
Davis Creek | 070802090801 | 3 | |||||
Short Creek | 070802090805 | 3 | |||||
Prairie Creek-Iowa River | 070802090806 | 2 | |||||
North Fork Long Creek | 070802090901 | 1 | 1 | ||||
South Fork Long Creek | 070802090902 | 3 | |||||
Johnny Creek-Long Creek | 070802090905 | 1 | |||||
Long Creek | 070802090906 | 1 | 1 | ||||
Ditch No 25-Iowa River | 070802091102 | 1 | |||||
Otter Creek-Iowa River | 070802091104 | 8 | 1 | ||||
School Creek-Des Moines River | 071000020106 | 1 | |||||
Headwaters Jack Creek | 071000020202 | 3 | |||||
Jack Creek | 071000020205 | 1 | |||||
Drainage Ditch 62-Silver Creek | 071000020301 | 1 | 1 | ||||
City of Emmetsburg-Des Moines River | 071000020404 | 1 | |||||
Drainage Ditch 80 | 071000020501 | 1 | |||||
Cylinder Creek | 071000020503 | 1 | |||||
Pilot Creek | 071000020703 | 1 | 1 | 5 | |||
Beaver Creek | 071000020803 | 1 | 2 | ||||
Indian Creek | 071000020902 | 1 | 3 | ||||
Drainage Ditch 35-Des Moines River | 071000020903 | 2 | 1 | 1 | |||
Ditch No 40 | 071000030106 | 1 | |||||
Okamanpeedan Lake-East Fork Des Moines River | 071000030108 | 1 | |||||
Black Cat Creek | 071000030504 | 1 | |||||
Drainage Ditch 51-East Fork Des Moines River | 071000030802 | 1 | |||||
Drainage Ditch 182 | 071000030805 | 1 | 1 | ||||
Drainage Ditch 94-East Fork Des Moines River | 071000030806 | 1 | |||||
East Fork Des Moines River | 071000030903 | 1 | |||||
Headwaters North Branch Lizard Creek | 071000040101 | 1 | |||||
Upper North Branch Lizard Creek | 071000040102 | 1 | 1 | ||||
Lower North Branch Lizard Creek | 071000040104 | 1 | 1 | ||||
Spring Creek | 071000040203 | 3 | |||||
Lower South Branch Lizard Creek | 071000040204 | 1 | |||||
Middle Lizard Creek | 071000040302 | 1 | |||||
Lower Lizard Creek | 071000040303 | 1 | 1 | ||||
Badger Creek | 071000040403 | 1 | |||||
Brushy Creek | 071000040504 | 1 | |||||
Prairie Creek | 071000040603 | 3 | 2 | 3 | |||
Gypsum Creek-Des Moines River | 071000040604 | 1 | |||||
Crooked Creek | 071000040605 | 1 | |||||
Skillet Creek | 071000040701 | 1 | |||||
Allen Creek-Des Moines River | 071000040702 | 1 | |||||
Bluff Creek | 071000040703 | 2 | |||||
Bear Creek | 071000040705 | 1 | |||||
Big Creek | 071000040803 | 1 | |||||
West Beaver Creek | 071000040902 | 2 | |||||
Beaver Branch-Beaver Creek | 071000040906 | 1 | |||||
Slough Creek | 071000040907 | 1 | 1 | 3 | |||
Little Beaver Creek-Beaver Creek | 071000040908 | 2 | |||||
City of Bouton-Beaver Creek | 071000040909 | 7 | |||||
Royer Creek-Beaver Creek | 071000040910 | 1 | |||||
Beaver Creek | 071000040911 | 4 | |||||
Murphy Branch-Des Moines River | 071000041001 | 4 | |||||
Rock Creek-Des Moines River | 071000041002 | 2 | |||||
Saylor Creek-Des Moines River | 071000041003 | 2 | |||||
Drainage Ditch 117 | 071000050101 | 1 | |||||
Headwaters Prairie Creek | 071000050102 | 1 | |||||
Drainage Ditch 116-Prairie Creek | 071000050103 | 1 | 2 | 1 | 1 | ||
Drainage Ditch 18-Prairie Creek | 071000050104 | 1 | 1 | 2 | |||
Headwaters Boone River | 071000050201 | 1 | |||||
Middle Branch Boone River | 071000050202 | 1 | |||||
East Branch Boone River | 071000050203 | 1 | 2 | ||||
Drainage Ditch 44-Boone River | 071000050204 | 1 | 1 | ||||
Drainage Ditch 1-Boone River | 071000050205 | 1 | 1 | ||||
West Otter Creek | 071000050301 | 1 | |||||
Headwaters Otter Creek | 071000050302 | 1 | 2 | ||||
Otter Creek | 071000050303 | 1 | |||||
Little Eagle Creek | 071000050401 | 1 | |||||
Headwaters Eagle Creek | 071000050402 | 1 | |||||
Eagle Creek | 071000050403 | 1 | 1 | 2 | 1 | 5 | |
Headwaters White Fox Creek | 071000050501 | 1 | 2 | ||||
Buck Creek | 071000050502 | 2 | |||||
White Fox Creek | 071000050503 | 1 | 3 | 1 | 5 | ||
Joint Drainage Ditch 3-Boone River | 071000050601 | 1 | |||||
Drainage Ditch 9 | 071000050602 | 1 | |||||
Drainage Ditch 3 | 071000050603 | 1 | |||||
Drainage Ditch 4-Boone River | 071000050604 | 3 | 2 | ||||
Drainage Ditch 46-Boone River | 071000050605 | 1 | |||||
Drainage Ditch 68-Boone River | 071000050606 | 1 | |||||
Lyons Creek | 071000050701 | 2 | |||||
Brewers Creek | 071000050702 | 1 | |||||
Drainage Ditch 206 | 071000050703 | 2 | 1 | ||||
Drainage Ditch 32-Boone River | 071000050704 | 2 | |||||
Prairie Creek-Boone River | 071000050705 | 1 | 1 | 1 | 1 | ||
Little Cedar Creek | 071000060103 | 1 | 2 | 1 | |||
Headwaters Cedar Creek | 071000060202 | 4 | 1 | 6 | |||
Drainage Ditch 74-Cedar Creek | 071000060204 | 1 | |||||
Prairie Creek | 071000060205 | 1 | |||||
Drainage Ditch 20-Cedar Creek | 071000060208 | 1 | |||||
Headwaters North Raccoon River | 071000060301 | 1 | 3 | ||||
Lateral 6-North Raccoon River | 071000060303 | 1 | 1 | ||||
Lateral 2 | 071000060304 | 2 | 1 | 10 | |||
Poor Farm Creek | 071000060305 | 1 | 2 | ||||
Lateral 3-North Raccoon River | 071000060306 | 1 | |||||
Outlet Creek | 071000060307 | 1 | 2 | ||||
Drainage Ditch 101-North Raccoon River | 071000060308 | 1 | 1 | 4 | |||
Buck Run | 071000060309 | 1 | 2 | ||||
Sac City-North Raccoon River | 071000060310 | 1 | 1 | ||||
Wall Lake Inlet | 071000060401 | 1 | 3 | ||||
Indian Creek-North Raccoon River | 071000060403 | 1 | |||||
Camp Creek | 071000060505 | 1 | |||||
Drainage Ditch 13-Lake Creek | 071000060603 | 2 | |||||
Lake Creek | 071000060605 | 1 | |||||
Purgatory Creek | 071000060702 | 1 | |||||
Drainage Ditch 73-North Raccoon River | 071000060801 | 3 | |||||
Drainage Ditch 25-North Raccoon River | 071000060802 | 1 | 1 | ||||
Prairie Creek | 071000060803 | 1 | 1 | ||||
Elk Run-North Raccoon River | 071000060804 | 3 | 3 | 2 | 9 | ||
Rainbow Bend County Park-North Raccoon River | 071000060805 | 1 | 3 | 3 | |||
Marrowbone Creek-North Raccoon River | 071000060806 | 1 | 1 | 1 | 1 | 1 | |
East Cedar Creek | 071000060903 | 11 | |||||
Cedar Creek | 071000060904 | 1 | |||||
Headwaters Hardin Creek | 071000061001 | 1 | |||||
Hardin Creek | 071000061005 | 1 | 1 | 3 | |||
East Buttrick Creek | 071000061102 | 1 | 1 | ||||
Headwaters West Buttrick Creek | 071000061202 | 2 | |||||
West Buttrick Creek | 071000061203 | 1 | |||||
Buttrick Creek | 071000061204 | 1 | 1 | ||||
Greenbrier Creek | 071000061302 | 1 | 1 | 1 | |||
Doe Brook-North Raccoon River | 071000061402 | 1 | |||||
Drainage Ditch 171-North Raccoon River | 071000061405 | 3 | |||||
Fannys Branch-North Raccoon River | 071000061501 | 2 | |||||
Swan Lake Branch | 071000061502 | 2 | |||||
Frog Creek-North Raccoon River | 071000061503 | 1 | 1 | ||||
Hickory Creek-North Raccoon River | 071000061505 | 1 | |||||
Walnut Creek | 071000061602 | 1 | |||||
Johnson Creek-Raccoon River | 071000061702 | 2 | |||||
Jordan Creek-Raccoon River | 071000061703 | 4 | 3 | ||||
Lower Willow Creek | 071000070104 | 1 | |||||
City of Carroll-Middle Raccoon River | 071000070203 | 1 | 1 | ||||
Spring Branch-Middle Raccoon River | 071000070204 | 1 | |||||
Willey Branch-Middle Raccoon River | 071000070205 | 1 | |||||
Upper Middle Raccoon River | 071000070206 | 1 | 2 | ||||
Upper Brushy Creek | 071000070301 | 1 | |||||
Middle Brushy Creek | 071000070302 | 3 | 3 | ||||
Lower Brushy Creek | 071000070303 | 1 | 1 | 2 | |||
Mason Creek | 071000070403 | 2 | |||||
City of Guthrie Center-South Raccon River | 071000070404 | 1 | |||||
Lower Mosquito Creek | 071000070502 | 1 | |||||
Lake Panorama-Middle Raccoon River | 071000070601 | 2 | 1 | 1 | |||
Bays Branch | 071000070602 | 1 | |||||
City of Panora-Middle Raccoon River | 071000070603 | 4 | |||||
Town of Monteith-South Raccoon River | 071000070702 | 1 | |||||
Deer Creek-South Raccoon River | 071000070703 | 1 | |||||
Long Branch-South Raccoon River | 071000070704 | 1 | |||||
East Branch Panther Creek | 071000070802 | 1 | |||||
Panther Creek | 071000070803 | 1 | |||||
Bear Creek | 071000070901 | 1 | |||||
Coal Creek-South Raccoon River | 071000070902 | 3 | |||||
Outlet South Raccoon River | 071000070904 | 1 | |||||
Upper Fourmile Creek | 071000080101 | 29 | 1 | 15 | |||
Middle Fourmile Creek | 071000080102 | 2 | |||||
Lower Fourmile Creek | 071000080103 | 2 | |||||
Howerdon Creek | 071000080303 | 1 | |||||
Cedar Creek | 071000080401 | 1 | |||||
Badger Creek | 071000080402 | 1 | |||||
North River | 071000080405 | 2 | 1 | ||||
South Turkey Creek | 071000080603 | 1 | |||||
Jefferson Cemetary-Middle River | 071000080605 | 1 | |||||
Felters Branch-Middle River | 071000080701 | 2 | |||||
South Squaw Creek | 071000080801 | 1 | |||||
Lower Squaw Creek | 071000080804 | 2 | |||||
Short Creek-South River | 071000081201 | 2 | |||||
Headwaters White Breast Creek | 071000081302 | 1 | |||||
Little White Breast Creek | 071000081305 | 3 | |||||
Kirk Branch-White Breast Creek | 071000081403 | 2 | |||||
Yeader Creek-Des Moines River | 071000081503 | 1 | 1 | ||||
Walnut Creek | 071000081505 | 1 | 1 | ||||
Wildcat Creek-Des Moines River | 071000081507 | 1 | |||||
Wallingslock Creek-Des Moines River | 071000081509 | 1 | |||||
Headwaters English Creek | 071000090101 | 1 | |||||
English Creek | 071000090102 | 1 | |||||
Headwaters North Cedar Creek | 071000090201 | 1 | |||||
Hickory Creek | 071000090202 | 1 | |||||
Carruthers Creek | 071000090203 | 1 | |||||
North Cedar Creek | 071000090204 | 1 | |||||
Bleubaugh Branch | 071000090302 | 3 | |||||
Inghram Branch | 071000090303 | 1 | |||||
Coal Creek-Cedar Creek | 071000090304 | 1 | |||||
Whippoorwill Creek | 071000090305 | 1 | |||||
Whites Creek | 071000090306 | 1 | |||||
Whippoorwill Branch-Cedar Creek | 071000090308 | 1 | |||||
Walnut Creek | 071000090309 | 1 | |||||
Cedar Creek | 071000090310 | 2 | 1 | ||||
Price Creek-Des Moines River | 071000090501 | 2 | |||||
Bluff Creek | 071000090503 | 1 | |||||
Middle Soap Creek | 071000090605 | 1 | |||||
Lower Soap Creek | 071000090607 | 1 | |||||
Brown Creek-Des Moines River | 071000090704 | 1 | |||||
Bear Creek School-Bear Creek | 071000090706 | 1 | |||||
Kettle Creek-Des Moines River | 071000090709 | 2 | 1 | ||||
Chippewa Creek-Des Moines River | 071000090710 | 1 | |||||
Tug Fork-Big Indian Creek | 071000091001 | 1 | |||||
Birch Creek-Sugar Creek | 071000091102 | 1 | 1 | ||||
Coppers Creek-Des Moines River | 071000091206 | 5 | 1 | ||||
Rollins Creek-Des Moines River | 071000091209 | 1 | |||||
Bitter Creek-Little Sioux River | 102000000000 | 20 | 39 | 1 | 6 | 97 | 15 |
Dickerson Branch-Thompson River | 103000000000 | 9 | 15 |