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HighlightsDrainage water recycling captures and stores agricultural drainage water for reuse as supplemental irrigation.Drainage water recycling can both increase crop production and benefit downstream water quality.Depending on management, drainage water recycling can also provide other complementary benefits.Research needs to advance drainage water recycling are presented and discussed. Keywords: Drainage water quality, Drainage water reuse, Subsurface drainage, Supplemental irrigation, Agricultural resiliency.

While all sectors of the economy can be impacted by climate variability and change, the agricultural sector is arguably the most tightly coupled to climate where changes in precipitation and temperature directly control plant growth and yield, as well as livestock production. This paper analyzes the direct and cascading effects of temperature, precipitation, and carbon dioxide (CO2) on agronomic and horticultural crops, and livestock production in Indiana through 2100. Due to increased frequency of drought and heat stress, models predict that the yield of contemporary corn and soybean varieties will decline by 8–21% relative to yield potential, without considering CO2 enhancement, which may offset soybean losses. These losses could be partially compensated by adaptation measures such as changes in cropping systems, planting date, crop genetics, soil health, and providing additional water through supplemental irrigation or drainage management. Changes in winter conditions will pose a threat to some perennial crops, including tree and fruit crops, while shifts in the USDA Hardiness Zone will expand the area suitable for some fruits. Heat stress poses a major challenge to livestock production, with decreased feed intake expected with temperatures exceeding 29 °C over 100 days per year by the end of the century. Overall, continued production of commodity crops, horticultural crops, and livestock in Indiana is expected to continue with adaptations in management practice, cultivar or species composition, or crop rotation.

HighlightsA modeling framework for drainage water recycling (DWR) was developed to estimate irrigation and water quality benefits.Global sensitivity analysis was used to identify most and least influential input parameters affecting model outputs.Parameters controlling total available water had the most influence on applied irrigation and captured tile drain flow.The modeling framework and sensitivity results were used to develop an open-source, online tool for evaluating DWR.Abstract. The U.S. Midwest is experiencing growth in both irrigation and subsurface (tile) drainage. Capturing, storing, and reusing tile drain water, a practice called drainage water recycling (DWR), represents a strategy for supporting supplemental irrigation while also reducing nutrient loads in tile-drained landscapes. This article describes the development and testing of an open-source online tool, Evaluating Drainage Water Recycling Decisions (EDWRD), which integrates soil and reservoir water balances for a tile-drained field and estimates potential benefits of DWR systems across multiple reservoir sizes. Irrigation benefits are quantified by applied irrigation and its relation to the irrigation demand, while water quality benefits are quantified by the amount and percentage of tile drain flow captured by the reservoir. Global sensitivity analysis identified input parameters affecting total available water as the most influential factors in estimating outputs. Initial and mid-season crop coefficients, irrigation management, and reservoir seepage rates were also influential. Curve number, fraction of wetted surface during irrigation, crop coefficients for the end of crop growth and frozen soil conditions, and the non-growing season residue amount were identified as low-sensitivity parameters. Results from the sensitivity analysis were used to prioritize and simplify user interaction with the tool. EDWRD represents the first open-source tool capable of evaluating DWR systems and can be used by multiple user groups to estimate the potential irrigation and water quality benefits of this innovative practice. Keywords: Drainage water recycling, Dual crop coefficient, Open-source model, Sensitivity analysis, Subsurface drainage, Supplemental irrigation.

HighlightsA fuzzy rating system was created based on published criteria for subirrigation suitability.Maps showing potential suitability for subirrigation were created for the U.S. Midwest.78,500 km2 across the U.S. Midwest is potentially suitability for subirrigation.Maps identify potential subirrigation locations pending onsite assessment.Abstract. Subirrigation through subsurface tile drains has potential to increase crop yields and improve water quality in tile-drained landscapes, but it has not been widely implemented. Identifying locations with high potential suitability for subirrigation may help the planning and implementation of this practice. In this study, we developed a fuzzy rating system for subirrigation suitability using the Gridded Soil Survey Geographic Database (gSSURGO). Maps of the fuzzy rating system identified locations of high potential suitability for subirrigation and highlighted physiographic regions highly conducive to the practice. We identified 78,500 km2, about 9%, of agricultural land in the Midwest with high potential suitability for subirrigation where onsite investigation may be targeted. The largest areas of high potential suitability were found in Minnesota, Illinois, and Indiana. Results from the fuzzy rating analysis are provided to the public through three channels: a downloadable data repository, map service, and web map tool. Ultimately, this study can facilitate the adoption of subirrigation by highlighting areas where subirrigation may potentially be a viable practice. Keywords: Controlled drainage, Fuzzy rating, Geographic information system (GIS), Gridded Soil Survey Geographic Database (gSSURGO), Midwestern U.S., Subirrigation.

In this study, methods were developed to create and evaluate the performance of the Soil and Water Assessment Tool (SWAT) in southern Peru where commonly used input data sources were not av...

Studies assessing the impact of subsurface drains on hydrology and nutrient yield in a changing climate are limited, specifically for Western Lake Erie Basin. This study aimed to evaluate the impact of changing climate on hydro-climatology and nutrient loadings in agricultural subsurface-drained areas on a watershed in northeastern Indiana. The study was conducted using a hydrologic model - the Soil and Water Assessment Tool (SWAT) - under two different greenhouse gas emission scenarios (RCP 4.5 and RCP 8.5). Based on analysis, annual subsurface drain flow totals could increase by 70% with respect to the baseline by the end of the 21st century. Surface runoff could increase by 10 to 140% and changes are expected to be greater under RCP 8.5. Soluble phosphorus yield over the basin in a year via subsurface drains could decrease by 30 to 60% under either emission scenarios. Annual total soluble phosphorus yield (soluble phosphorus loading to stream) from subsurface drains and surface runoff could vary from 0.041 to 0.058 kg/ha under RCP 4.5 and 0.035 to 0.064 kg/ha under RCP 8.5 by the end of the 21st century while the values from the baseline model were 0.051 kg/ha. This was attributable to the fact that future climate could have a greater increase in surface runoff than subsurface drain flow based on analysis of the different climate scenarios. Outputs from individual climate model data rather than ensembles provided a band of influence of watershed responses, while outputs from different timelines provided details for evaluating management practice suitability with respect to anticipated differences in climate. Results provide valuable information for stakeholders and policy makers for planning management practices to protect water quality.

One of the strategies proposed for reducing nitrate losses from subsurface tile drain systems in Midwestern agricultural lands, controlled drainage, is known to reduce drain flow on an annual basis, but is not well understood for individual events. Understanding hydrologic controls that regulate outflow from free and controlled drainage systems during drainage events can offer improved insight on the overall functioning of these systems so that they can be better managed or retrofitted to increase their environmental benefits. This study used data from a monitoring site in east central Indiana to investigate the hydrology of 22 drainage events in free and controlled subsurface drainage systems. Relationships between event drainage volume, drain flow hydrograph metrics, column soil moisture, water table depth, and precipitation time series for each event were explored to determine the effect of precipitation characteristics and antecedent conditions on these metrics. Controlled drainage reduced event drainage volume and peak flows by 22% ± 12% and 29% ± 16% respectively, and increased the time to peak of drainage by 98% ± 52%. Higher total precipitation and precipitation time spread increased infiltration, while the average precipitation intensity did not correlate with drainage volumes in either system. Peak flow rate in free draining quadrants were positively affected by higher precipitation and average precipitation intensity, while in managed quadrants, the antecedent soil moisture appeared to be more influential in affecting peak flow rate than precipitation characteristics. Surface runoff potential increased with the increase in average precipitation intensity in all quadrants. Saturation excess ponding or possibly overland flow occurred in events that have a low average precipitation intensity, and a high precipitation time spread. Field observations indicate that saturation excess overland flow was more pronounced in controlled quadrants because water table levels rose higher than the water table levels of their free draining counterpart.

CLImate GENerator (CLIGEN) (v5.3), a stochastic weather generator, is widely used in conjunction with the Water Erosion Prediction Project (WEPP) model for runoff and soil loss predictions. CLIGEN generates daily estimates of weather based on long-term observed weather station data statistics. For the United States, the original CLIGEN database released with WEPP in 1995 was derived using inconsistent periods of climate records through 1992 that could lead to significant variations in runoff and soil loss predictions on spatial and temporal scales. To achieve more reliable estimates of runoff and soil loss, an updated climate database was derived from a consistent 40 years of recent climate records of 1974 to 2013 in the United States. The objectives of this study were to (1) examine the spatial patterns in trends of differences in precipitation and maximum and minimum temperatures between the two databases, and (2) evaluate the impacts on WEPP-predicted mean annual runoff and soil loss, from the original to the updated databases. For runoff and soil loss estimates, WEPP simulations were conducted under a tilled fallow condition for 1,600 CLIGEN locations in the contiguous United States for a slope profile of 22.1 m length, 9% slope gradient, and silt loam soil. Comparison of precipitation and maximum and minimum temperatures between the original and updated databases showed variations in spatial patterns both annually and seasonally. Annual precipitation and minimum temperature generally increased across most of the country while maximum temperature increased in the western half of the United States and parts of the Northeast. Seasonally, increases in precipitation are evident in the Midwest in spring, fall, and winter, the Northwest in spring, and the Southeast in fall. Maximum daily temperature has increased in the western half of United States and parts of the Northeast in the winter, fall, and spring, whereas minimum daily temperature has increased in all seasons across the United States. Changes in WEPP-simulated mean annual runoff and soil loss from the use of the original to the updated CLIGEN database showed increases in runoff and soil loss in most of the United States. However, some stations showed either increases or decreases in runoff and/or soil loss with the updated database primarily because of differences in monthly precipitation and intensity values in the two databases. Understanding the impacts of the use of the updated database on runoff and soil loss from this study will help in making informed decisions for conservation planning and management when utilizing the WEPP erosion model.

Controlled drainage (CD), sometimes called drainage water management, is a practice whereby the drainage system outflow is managed during specific periods to retain more water in the field. Although CD has been shown to reduce downstream nitrate-N (NO3--N) load, seasonal patterns have been less consistent which can potentially impact the effectiveness of conservation practices. The main objective of this study was to assess the regional and seasonal impact of conventional free drainage (FD) and CD on drainage flow and nitrate-N load. Using experimental data from ongoing and historical CD experiments across the Corn Belt and in North Carolina, we evaluated subsurface drain flow, nitrate-N load, and performance of CD systems. Across the data set and regions, there was little difference in annual flow from FD conditions. Seasonally, more northern and western sites experienced a greater percentage of the annual flow occurring in the spring. There was no nitrate-N concentration reduction with CD. Flow and nitrate-N load reductions with CD did not vary by plant hardiness zone across the region, but the season with the greatest reduction did shift from winter to spring moving north and west in the study area. Absolute flow reductions (in mm) were similar regardless of precipitation category. Consequently, the percent reduction was lower as the amount of precipitation (category) increased. Overall, this analysis found CD to be an effective practice for reducing drain flow and nitrate-N loading directly delivered by the drains to downstream water bodies across the region.

Controlled drainage (CD) is a structural conservation practice in which the drainage outlet is managed in order to reduce drain flow volume and nutrient loads to water bodies. The goal of this study was to evaluate the potential of CD to improve water quality for two different seasons and levels of outlet control, using ten years of data collected from an agricultural drained field in eastern Indiana with two sets of paired plots. The Rank Sum test was used to quantify the impact of CD on cumulative annual drain flow and nitrate-N and phosphorus loads. CD plots had a statistically significant (at 5% level) lower annual drain flow (eastern pair: 39%; western pair: 25%) and nitrate load (eastern pair: 43%; western pair: 26%) compared to free draining (FD) plots, while annual soluble reactive phosphorus (SRP) and total phosphorus (TP) loads were not significantly different. An ANCOVA model was used to evaluate the impact of CD on daily drain flow, nitrate-N, SRP and TP concentrations and loads during the two different periods of control. The average percent reduction of daily drain flow was 68% in the eastern pair and 58% in the western pair during controlled drainage at the higher outlet level (winter) and 64% and 58% at the lower outlet level (summer) in the eastern and western pairs, respectively. Nitrate load reduction was similar to drain flow reduction, while the effect of CD on SRP and TP loads was not significant except for the increase in SRP in one pair. These results from a decade-long field monitoring and two different statistical methods enhance our knowledge about water quality impacts of CD system and support this management practice as a reliable system for reducing nitrate loss through subsurface drains, mainly caused by flow reduction.

Subirrigation is employed to supply water to crop root zones via subsurface drainage systems, which are typically installed for the purpose of excess soil water removal. Crop yield increases due to subirrigation have been demonstrated in numerous studies, but there is limited information regarding yield under future climate conditions when growing season conditions are expected to be drier in the U.S. Corn Belt. DRAINMOD was calibrated and validated for three locations with different soil series in northwest Ohio and used to investigate maize relative yield differences between subirrigation and free subsurface drainage for historic (1984–2013) and future (2041–2070) climate conditions. For historic conditions, the mean maize relative yield increased by 27% with subirrigation on the Nappanee loam soil, but had minimal effect on the Paulding clay and Hoytville silty clay soils. Maize relative yield under free subsurface drainage is predicted to decrease in the future, causing the relative yield difference between free subsurface drainage and subirrigation practices to nearly double from 9% to 16% between the historic and future periods. Consequently, the subirrigation practice can potentially mitigate adverse future climate change impacts on maize yield in northwest Ohio.

Accurate quantification of forest aboveground biomass (AGB) is the foundation to the responses of diverse forest ecosystems to the changing climate. Lidar-based statistical models have been used to accurately estimate AGB in large spatial extents, especially in boreal and temperate softwood forest ecosystems. However, the few available models for temperate hardwood and hardwood-dominated mixed forests are low in accuracy due both to the deliquescent growth form of hardwood trees and the strong site-to-site variations in height-diameter relationship. In this study, we established multiplicative nonlinear regression models that incorporated both lidar-derived metrics and soil-based site productivity classes (high and low productivity sites) to estimate aboveground biomass in temperate hardwood forests. The final optimized model had high accuracy (R 2 = 0.81; RMSE = 45.5 Mg ha − 1 ) with reliable performance in ABG estimation by integrating relative height metrics at 75 and 70 percentiles (RH75 and RH70), canopy coverage and site productivity class. An optimized model that included an index of site productivity explained 14% more variance than the best-fit model without the term. Moreover, the relationship between AGB and lidar-based metrics was nonlinear on low productivity sites and nearly linear on high productivity sites, further indicating the importance of including direct or indirect measures of site productivity in lidar-based biomass models, particularly for those applied to temperate hardwood forests. Our new lidar-based model provides a potential framework to integrate lidar-based structural information and soil-based site productivity to improve AGB estimation in temperate hardwood forests.

Long records of continuous drain flow are important for quantifying annual and seasonal changes in the subsurface drainage flow from drained agricultural land. Missing data due to equipment malfunction and other challenges have limited conclusions that can be made about annual flow and thus nutrient loads from field studies, including assessments of the effect of controlled drainage. Water table depth data may be available during gaps in flow data, providing a basis for filling missing drain flow data; therefore, the overall goal of this study was to examine the potential to estimate drain flow using water table observations. The objectives were to evaluate how the shape of the relationship between drain flow and water table height above drain varies depending on the soil hydraulic conductivity profile, to quantify how well the Hooghoudt equation represented the water table–drain flow relationship in five years of measured data at the Davis Purdue Agricultural Center (DPAC), and to determine the impact of controlled drainage on drain flow using the filled dataset. The shape of the drain flow–water table height relationship was found to depend on the selected hydraulic conductivity profile. Estimated drain flow using the Hooghoudt equation with measured water table height for both free draining and controlled periods compared well to observed flow with Nash-Sutcliffe Efficiency values above 0.7 and 0.8 for calibration and validation periods, respectively. Using this method, together with linear regression for the remaining gaps, a long-term drain flow record for a controlled drainage experiment at the DPAC was used to evaluate the impacts of controlled drainage on drain flow. In the controlled drainage sites, annual flow was 14–49% lower than free drainage.

A two-stage ditch involves modifications of a conventional, trapezoidal drainage ditch to better replicate the features of a natural stream through the addition of adjacent floodplains or benches. Previous research in Indiana and Ohio has shown that two-stage ditches offer the potential to reduce sediment load and extend the interaction time between water, bench vegetation, and bench soil allowing larger uptake of nutrients by the vegetation and increasing the denitrification rates. A two-stage ditch was constructed that drains an area of approximately 267 ha of farmland used for corn and soybean production. Discharge, nitrate-N (NO3), total phosphorus (TP), soluble reactive phosphorus (SRP) and total suspended sediment (TSS) were monitored in the two-stage ditch and a control reach immediately upstream. The two-stage ditch was found to significantly decrease TP, SRP and TSS concentrations and loads. Although the two-stage ditch decreased NO 3 concentrations significantly, it did not have a significant impact on NO3 loads. More specifically, the two-stage ditch reduced the loads of TP by 40%, SRP by 11% and TSS by 22–40% depending on the stage of vegetation establishment on its floodplain benches, compared to an increase in load of 78%, 2% and 1%, respectively in the control reach.

Climate change projections for the Midwest U.S. indicate a future with increased growing season dryness that will adversely impact crop production sustainability. Systems that capture water for later subirrigation use have potential as a climate adaptation strategy to mitigate this increased crop water stress. Three such systems were operated in northwest Ohio from 1996 to 2008, and they exhibited substantial crop yield benefits, especially in dry growing seasons, but also to a lesser extent in near normal or wet growing seasons. The goal of this research was to estimate the increase in crop yield benefits of water capture and subirrigation systems that can be expected under projcted 2041–2070 climate conditions in northwest Ohio. Historical subirrigated field crop yield differences with fields having free drainage only, relative to growing season dryness/wetness, were used to determine future northwest Ohio subirrigated field crop yield increases, based on the modeled climate for 2041–2070. Climate records for 2041–2070 were projected using three bias corrected model combinations, CRCM+CGCM3, RCM3+GFDL, and MM5I+HadCM3. Growing season dryness/wetness was classified based on the difference between rainfall and the crop adjusted potential evapotranspiration using the 1984–2013 climate record at the three system locations. Projected 2041–2070 growing season precipitation varied substantially between the three model combinations; however, all three indicated increased growing season dryness due to rising temperature and solar radiation. The overall subirrigated field corn yield increase rose to an estimated 27.5%–30.0% in 2041–2070 from 20.5% in 1996–2008, while the subirrigated field soybean yield increase improved from 12.2% in 1996–2008 to 19.8%–21.5% for 2041–2070. Consequently, as growing season drought becomes more frequent, the crop yield benefits with water capture and subirrigation systems will improve, and these systems therefore provide a viable climate adaptation strategy for agricultural production.

Conservation practices are designed and implemented to reduce soil erosion and protect water quality, but their effectiveness has been found to vary widely. This study investigated spatial and temporal variability in sediment and nutrient loads and load reductions achieved by implementing conservation practices to understand the implications of landscape heterogeneity and seasonal land-phase hydrologic variation on the effectiveness of the practices. Field-scale effects of nine conservation practices were evaluated in an agricultural watershed in the Midwest using the SWAT model. Results show that the conservation practice effectiveness, and the variability of the practice effectiveness at different locations, vary widely. Most practices are more effective in reducing nutrients in particulate than soluble forms. Practices applied to fields with higher nutrient loads do not necessarily lead to greater load reduction, indicating that an assumption of a proportional relationship between load and expected load reduction on which common targeting strategies for conservation practice placement are based may not be valid for nutrient, in particular soluble forms. The variation of the practices by fields and seasons suggests that achievement of water quality improvement requires careful selection of conservation practices and target areas considering hydrologic variations.

Controlled drainage is a best management practice that decreases nitrate loads from subsurface drainage, but questions remain about optimal operation strategies. One unanswered question is whether the outlet should be lowered prior to or directly after a rainfall event to reduce the amount of time that the water table is at a level that would be detrimental to either trafficability or crop yield. The objective of this study was to determine how much controlled drainage lengthens the time needed for the water table to fall after a rainfall event, to inform possible improvement in the management of controlled drainage systems. This objective was addressed using water table recession rates from two pairs of controlled and free-draining fields located at the Davis Purdue Agricultural Center in Indiana over a period of nine years (2006-2014). At each pair, comparison of mean recession rates from the two fields indicated that controlled drainage reduced recession rate. The significance of the relationship between paired observations and the effect of controlled drainage was determined by a paired watershed approach using analysis of variance (ANOVA) and covariance (ANCOVA). Raising the outlet of the subsurface drainage system decreased the mean rate of water table recession by 29% to 62%, increasing the time needed for the water table level to fall from the surface to 30 and 60 cm depths by approximately 12 to 26 h and 24 to 53 h, respectively. Based on these results, it can be concluded that lowering the outlet before storm events would reduce the amount of time that the water table is at a detrimental level for either crop growth or trafficability. However, the trade-off between costs and benefits of active management depends on the sensitivity of the crop and probability of a severe storm. Keywords: Drainage water management, Managed drainage, Paired watershed approach, Tile drainage, Water table drawdown.

Viable large-scale crop production in the United States requires artificial drainage in humid and poorly drained agricultural regions. Excess water removal is generally achieved by installing tile drains that export water to open ditches that eventually flow into streams. Drainage water management (DWM) is a conservation practice that allows farmers to artificially raise the outlet elevation of a field’s drain tile and can reduce nutrient loss during wet periods by storing more water in the field. We intended to assess the effectiveness of DWM to reduce drainage discharge and nutrient loads and additionally identify predictor variables that influence DWM effectiveness. We compared managed (i.e., DWM) and free draining records using paired t-tests, and identified factors associated with DWM effectiveness using a multiple linear regression approach. T-test results indicated that DWM was highly effective in reducing drainage water discharge and nutrient losses via drain tiles as tile discharge volumes were reduced on average 46%, while tile nitrate loads were reduced by 48%. In addition, total phosphorus and dissolved reactive phosphorus loads were reduced by 55% and 57%, respectively. Based on regression results, we found that several aspects of farm and tile drain management were associated with DWM effectiveness, while site specific landscape characteristics were less likely to predict effectiveness. While DWM is effective as a conservation practice to reduce discharges of water and nutrients from drain tiles, we also identified several knowledge gaps. Future research should investigate effects of DWM on water and nutrients lost in other pathways such as surface runoff, preferential flow, groundwater recharge and biological uptake, and also focus more attention on phosphorus as there is a paucity of research on this topic.

The objective of this study was to evaluate effects of conservation practices actually implemented in reducing sediment and nutrient loads at field and watershed scales. To contribute to the USDA Agency Priority Goal for Water Pilot Projects, we obtained information on conservation practices implemented in the St. Joseph River watershed. Considering expected water quality impacts and simulation ability of the Soil and Water Assessment Tool (SWAT) model, 5,583 of them were selected and incorporated into modeling at a hydrologic response unit (HRU) level by adjusting associated parameters. A calibrated SWAT model was used to estimate load reduction effectiveness of the selected practices. Model results indicated that many of the practices reduced pollutant loads between 10% and 50% at the field scale, with high variability among the practices. Most conservation practices reduced less than 1% of the loads when calculated for the entire watershed, but the load reduction was still large and thus their cumulative long-term effects were expected to be significant. Conservation crop rotation and no-till, which were the most widely applied conservation practices in the study watershed, provided the greatest sediment load reduction, while conservation crop rotation and cover crop reduced the greatest amount of nutrients. Conservation crop rotation, cover crop, no-till, and mulch-till sometimes increased loads of soluble nutrients, resulting in the overall decrease in their effectiveness. Comparison of the spatial distributions of the selected conservation practices and simulated pollutant loads showed existing conservation practices were not targeted for areas producing relatively greater loads. The findings of this study demonstrated different effectiveness of conservation practices at the different spatial scales, suggesting application area, field-scale effectiveness, and placement of the practices are equally critical in achieving watershed-scale water quality improvement.

Surface runoff is often poorly quantified in hydrologic studies of subsurface drained fields, as it is a relatively minor component of the water balance and difficult to measure in large fields. However, conservation practices that seek to mitigate pollutant transport through subsurface drainage may increase surface runoff, and therefore it needs to be better understood. The goal of this study was to determine the frequency and extent of occurrence of surface ponding and runoff, and to understand their generation processes in a seasonally frozen, subsurface drained agricultural field in eastern Indiana. Three different methods were used. Surface ponding was monitored with a time-lapse camera at the edge of the field for three years. A water table threshold for surface ponding was determined using photo evidence of ponding together with water table depth measurements and used to estimate ponding. The DRAINMOD hydrologic model was calibrated and validated by comparing model predictions of subsurface drainage and water table depth with 10 years of field observations and used to predict surface ponding and runoff. The simulation results indicated that surface runoff represented 1–10% of annual precipitation, while subsurface drainage represented between 26 and 45%. On average, 45% of simulated ponding occurred during the cold season (December-March) indicating the importance of soil freezing and snow accumulation. However, during parts of the cold season, DRAINMOD simulations of snow accumulation and melt were poor, resulting in drain flow under-prediction and runoff over-prediction during these periods. Water table depth measurements above the defined threshold provided a simple alternate for prediction of saturation excess ponding events in the absence of direct measurements. Results from both simulations and observations indicated that all of the ponding events in this location were generated by saturation excess rather than infiltration excess processes.

A survey of the literature and in particular an examination of the terminology use in a previous special collection of modeling calibration and validation articles were conducted to arrive at a list of consistent terminology recommended for writing about hydrologic and water quality model calibration and validation. The terminology list includes rudimentary terms necessary for proper understanding of modeling literature for the novice modeler. This article also provides discussions regarding confusing or conflicting terminology found in the literature, alternative terms to those recommended herein, and alternative definitions for those terms that may be used by some authors.

Management of water resources at a watershed scale often occurs at the local level and relies on the effectiveness of local staff and leaders. Four land-grant universities in Indiana, Michigan, Minnesota and Ohio are delivering training programs that build the capacity of local water resource professionals. Based on experience from these programs, a survey on watershed management core competencies, and two surveys of information and training needs for watershed groups, we examined what core proficiencies are needed by watershed group leaders, how existing programs have approached professional training, and effective methods for delivering the training. Results indicated that successful watershed leaders said they must have skills in leadership, communication, collaboration, technology, policy, and planning along with a solid understanding of natural science disciplines. More importantly, they must be able to integrate these skills to solve problems. The mode of delivery (distance or in-person) depended on the audience and training goals, emphasized networking opportunities with the instructor and other participants, and encouraged participants to apply lessons to their own situations. Features of a successful training program that effectively build watershed leadership capacity are provided.

Collecting and analyzing water quality samples is costly and typically requires significant effort compared to streamflow data, thus water quality data are typically collected at a low frequency. Regression models, identifying a relationship between streamflow and water quality data, are often used to estimate pollutant loads. A web-based tool using LOAD ESTimator (LOADEST) as a core engine with four modules was developed to provide user-friendly interfaces and input data collection via web access. The first module requests and receives streamflow and water quality data from the U.S. Geological Survey. The second module retrieves watershed area for computation of pollutant loads per unit area. The third module examines potential error of input datasets for LOADEST runs, and the last module computes estimated and allowable annual average pollutant loads and provides tabular and graphical LOADEST outputs. The web-based tool was applied to two watersheds in this study, one agriculturally-dominated and one urban-dominated. It was found that annual sediment load at the urban-dominant watershed exceeded the target load; therefore, the web-based tool identified correctly the watershed requiring best management practices to reduce pollutant loads.

Targeting of agricultural conservation practices to the most effective locations in a watershed can promote wise use of conservation funds to protect surface waters from agricultural nonpoint source pollution. A spatial optimization procedure using the Soil and Water Assessment Tool was used to target six widely used conservation practices, namely no-tillage, cereal rye cover crops (CC), filter strips (FS), grassed waterways (GW), created wetlands, and restored prairie habitats, in two west-central Indiana watersheds. These watersheds were small, fairly flat, extensively agricultural, and heavily subsurface tile-drained. The targeting approach was also used to evaluate the model's representation of conservation practices in cost and water quality improvement, defined as export of total nitrogen, total phosphorus, and sediment from cropped fields. FS, GW, and habitats were the most effective at improving water quality, while CC and wetlands made the greatest water quality improvement in lands with multiple existing conservation practices. Spatial optimization resulted in similar cost-environmental benefit tradeoff curves for each watershed, with the greatest possible water quality improvement being a reduction in total pollutant loads by approximately 60%, with nitrogen reduced by 20-30%, phosphorus by 70%, and sediment by 80-90%.

Targeting of agricultural conservation practices to cost-effective locations has long been of interest to watershed managers, yet its implementation cannot succeed without meaningful engagement of agricultural producers who are decision makers on the lands they farm. In this study, we engaged 14 west-central Indiana producers and landowners in an adaptive targeting experiment. Interviews carried out prior to targeting provided rich spatial information on existing conservation practices as well as producers' preferences for future conservation projects. We targeted six of the most accepted conservation practices using the Soil and Water Assessment Tool and spatial optimization using a genetic algorithm approach. Fairly optimal conservation scenarios were possible with even the most limiting constraints of farmer-accepted practices. We presented in follow-up interviews a total of 176 conservation practice recommendations on 103 farm fields to 10 farmers whose lands were targeted for conservation. Primary findings indicated producers were interested in the project, were open to hearing recommendations about their lands, and expressed a high likelihood of adopting 35% of targeted recommendations. Farmers generally viewed the interview process and presentation of results quite favorably, and the interviews were found to build trust and make the targeting process more acceptable to them.

The Soil and Water Assessment Tool (SWAT) uses hydrologic response units (HRUs) as the basic unit of all model calculations. ArcSWAT, the ArcGIS interface for SWAT, allows users to specify thresholds of land cover, soil, and slope in defining HRUs to improve the computational efficiency of simulations while keeping key landscape features of a watershed in the hydrologic modeling. However, this study found that applying commonly used thresholds in defining HRUs may lead to considerable loss of information about the watershed landscape, emphasizing larger soil types on smaller land covers once the land covers meet a threshold for land cover, and potentially changing average slopes. These changes often have a minor effect on water yield and streamflow simulations by SWAT but a larger effect on sediment and nutrient load simulations, which are more sensitive to slope and soil type and are more influential on outputs at the subwatershed than at the watershed outlet. Study results can help modelers improve their understanding of the HRU strategy for simplifying watershed representation while maintaining major landscape features and make decisions in the HRU delineation process to minimize the chance of biased simulations.

The fate of ecosystem services (ESS) in the United States depends on the actions of private landowners and operators (‘farmers’). This work uses a mixed qualitative and quantitative method to understand farmer knowledge of ESS and willingness to manage lands from an ESS perspective. Fourteen interviews were conducted to analyze farmer understanding of ESS within the context of conservation management. Two hundred surveys of Indiana farmers and 33 surveys of Indiana US Department of Agriculture Natural Resource Conservation Service conservationists (‘conservationists’) were analyzed in order to assess ESS knowledge derived from varied land types. Though most farmers and conservationists were unfamiliar with ESS, both groups consistently recognized environmental benefits from land types and conservation practices. They were also able to identify trade-offs in ESS when managing lands for maximum food production. Farmers and conservationists differed in their views of the beneficiaries and stewards of ESS, wh...

The important questions about agriculture, climate, and sustainability have become increasingly complex and require a coordinated, multifaceted approach for developing new knowledge and understanding. A multistate, transdisciplinary project was begun in 2011 to study the potential for both mitigation and adaptation of corn-based cropping systems to climate variations. The team is measuring the baseline as well as change of the system's carbon (C), nitrogen (N), and water footprints, crop productivity, and pest pressure in response to existing and novel production practices. Nine states and 11 institutions are participating in the project, necessitating a well thought out approach to coordinating field data collection pro- cedures at 35 research sites. In addition, the collected data must be brought together in a way that can be stored and used by persons not originally involved in the data collection, necessi- tating robust procedures for linking metadata with the data and clearly delineated rules for use and publication of data from the overall project. In order to improve the ability to compare data across sites and begin to make inferences about soil and cropping system responses to cli- mate across the region, detailed research protocols were developed to standardize the types of measurements taken and the specific details such as depth, time, method, numbers of samples, and minimum data set required from each site. This process required significant time, debate, and commitment of all the investigators involved with field data collection and was also informed by the data needed to run the simulation models and life cycle analyses. Although individual research teams are collecting additional measurements beyond those stated in the standardized protocols, the written protocols are used by the team for the base measurements to be compared across the region. A centralized database was constructed to meet the needs of current researchers on this project as well as for future use for data synthesis and modeling for agricultural, ecosystem, and climate sciences.

Summary Estimation of annual nutrient loads is critical for many applications in water quality management; however, measurement errors and infrequent monitoring could raise considerable uncertainty in the load estimations. The objectives of this study were to quantify the overall uncertainty in annual nitrate-N load estimates. Nitrate was selected as the study object because of the high loads common in Midwestern streams, and its important influence on hypoxia in the Gulf of Mexico. A standard error propagation method was used to quantify the uncertainty from both measurement and load calculation processes to evaluate the accumulative effect. The measurement uncertainty was assessed based on standard information; the load calculation uncertainty was evaluated through numerical simulation. The study found that uncertainty in annual nitrate-N load estimates for a 30-day sampling frequency, expressed as coefficient of variation (CV), was 14–34%. This included measurement (flow and concentration) uncertainty of 12% and load calculation uncertainty of 7–32%. These results can be used to evaluate different uncertainty sources, estimate uncertainty for similar watersheds, and design sampling programs balancing cost and accuracy.

Watershed managers have largely embraced targeting of agricultural conservation as a way to manage strategically non-point source pollution from agricultural lands. However, while targeting of particular watersheds is not uncommon, targeting farms and fields within a specific watershed has lagged. In this work, we employed a qualitative approach, using farmer interviews in west-central Indiana to better understand their views on targeting. Interviews focused on adoption of conservation practices on farmers' lands and identified their views on targeting, disproportionality, and monetary incentives. Results show consistent support for the targeting approach, despite dramatic differences in farmers' views of land stewardship, in their views about disproportionality of water quality impacts, and in their trust in conservation programming. While the theoretical concept of targeting was palatable to all participants, many raised concerns about its practical implementation, pointing to the need for flexibility when applying targeting solutions and revealing misgivings about the government agencies that perform targeting.

Subsurface tile-drained agricultural fields are known to be important contributors to nitrate in surface water in the Midwest, but the effect of these fields on nitrate at the watershed scale is difficult to quantify. Data for 25 watersheds monitored by the Indiana Department of Environmental Management and located near a U.S. Geological Survey stream gage were used to investigate the relationship between flow-weighted mean concentration (FWMC) of nitrate-N and the subsurface tile-drained area (DA) of the watershed. The tile DA was estimated from soil drainage class, land use, and slope. Nitrate loads from point sources were estimated based on reported flows of major permitted facilities with mean nitrate-N concentrations from published sources. Linear regression models exhibited a statistically significant relationship between annual/monthly nonpoint source (NPS) nitrate-N and DA percentage. The annual model explained 71% of the variation in FWMC of nitrate-N. The annual and monthly models were tested in 10 additional watersheds, most with absolute errors within 1 mg/l in the predicted FWMC. These models can be used to estimate NPS nitrate for unmonitored watersheds in similar areas, especially for drained agricultural areas where model performance was strongest, and to predict the nitrate reduction when various tile drainage management techniques are employed.

Drainage water recycling, the practice of capturing and storing water drained from fields and using the stored water to irrigate crops when there is a soil water deficit, has been proposed to increase the resiliency of drained agriculture, but the potential benefits have not been quantified. This study determined irrigation and nutrient reduction benefits of drainage water recycling for various reservoir sizes at two tile-drained sites in the U.S. Midwest with differing climates and soils. Field and reservoir water budgets were developed using ten years of measured tile drain flow and weather data. The calculated volume of drain flow that could be captured by the reservoir was combined with measured nitrate-nitrogen and soluble reactive phosphorus concentrations to determine nutrient load reductions. At the Indiana site, a reservoir size representing 6% of the field area (3.05 m depth) would provide water storage for meeting irrigation requirements in all ten years. This reservoir would capture 37% of annual tile drain flow on average, resulting in average annual load reductions of 11 kg ha−1 yr−1 (37%) for nitrate-N and 0.05 kg ha−1 yr−1 (39%) for soluble reactive phosphorus. At the Iowa site, a reservoir size of 8% was necessary to meet the irrigation requirements, which were zero in most years but were higher than at the Indiana site for the three years in which irrigation was needed. This larger reservoir would capture 23% of annual tile drain flow on average, with average annual load reductions of 9 kg ha−1 yr−1 (24%) for nitrate-nitrogen and 0.02 kg ha−1 yr−1 (21%) for soluble reactive phosphorus. Quantifying nutrient load reductions and irrigation potential at these two sites showed that drainage water recycling is a promising practice for the tile-drained landscape of the U.S. Midwest, providing a strategy to manage water-related risks while also contributing to water quality goals.

There is an increasing need to document the impacts of conservation-related best management practices (BMPs) on water quality within a watershed. However, this impact analysis depends upon accurate geospatial locations of existing practices, which are difficult to obtain. This study demonstrates and evaluates three different methods for obtaining geospatial information for BMPs. This study was focused on the Eagle Creek Watershed, a mixed use watershed in central Indiana. We obtained geospatial information for BMPs through government records, producer interviews, and remote-sensing aerial photo interpretation. Aerial photos were also used to validate the government records and producer interviews. This study shows the variation in results obtained from the three sources of information as well as the benefits and drawbacks of each method. Using only one method for obtaining BMP information can be incomplete, and this study demonstrates how multiple methods can be used for the most accurate picture.

Drained lands, which include some of the most productive lands in the world, can experience both water excess and water deficit within a year. Storing drained water within the landscape could increase the sustainability of water for agriculture, particularly as intense rainfall and prolonged summer drought continue to increase under future climate change. A team of researchers and extension specialists from nine states are currently working towards a vision of transforming the process of designing and implementing agricultural drainage to include storage through the use of controlled drainage, saturated buffers, and drainage water recycling (i.e. capture, storage, and reuse). Field research data from experimental drainage sites from across the U.S. Corn Belt have been brought together in a database to support synthesis and modeling to determine economic and environmental impacts of drainage water storage. Results from this effort will extend the strategies and tools to agricultural producers, the drainage industry, watershed managers, agencies, and policy makers, and educate the next generation of engineers and scientists to design drainage systems that include water storage in the landscape.

Subirrigation has been proposed as a water table management practice to maintain appropriate soil water content during periods of high crop water demand on subsurface drained croplands in the Corn Belt. Subirrigation takes advantage of the subsurface drainage systems already installed on drained agricultural lands to remove excess soil water after precipitation events. However, limited information regarding corn yield under subirrigation is available to promote its implementation at a large scale. In addition, its performance within the backdrop of climate change has not been explored in the context of the Corn Belt. DRAINMOD was calibrated and validated for a location with Nappanee loam soil in the Maumee River Basin in Northwest Ohio. The model was then used to investigate relative corn yield differences between subirrigation and free subsurface drainage for historical (1984-2013) and projected future (2041-2070) climate conditions. For historical conditions, the mean relative corn yield increased by 26.5% under subirrigation. Under free subsurface drainage, corn relative yields were lower for future climate conditions than for historical climate conditions. For the projected future climate conditions, overall relative corn yields under subirrigation increased by 36.5% compared to relative yields under free subsurface drainage. Subirrigation contributed in sustaining relative corn yields under future climate conditions.

The increasing number of citizen science projects around the world brings the need to evaluate the effectiveness of these projects and to show the applicability of the data they collect. This research describes the Wabash River Sampling Blitz, a volunteer water-quality monitoring program in Central Indiana developed by the Wabash River Enhancement Corporation (WREC). Results indicate that field test strips for nitrate+nitrite-N read by volunteers generally agree with lab-determined values. Orthophosphate results are less transferable owing to low observed concentrations, although the field test strip values from unfiltered samples consistently over-predicted the lab values. Hierarchical cluster analysis (HCA) applied to volunteer-collected data groups sampling sites into meaningful management clusters that can help to identify water-quality priorities across the watershed as a proof of concept for watershed managers. Results of the HCA provide an opportunity for WREC to target future programs, education, and activities by analyzing the data collected by citizen scientists. Overall this study demonstrates how citizen science water quality data can be validated and applied in subsequent watershed management strategies.

Drainage water management is a conservation practice that has the potential to reduce drainage outflow and nitrate (NO3) loss from agricultural fields while maintaining or improving crop yields. The goal of this study was to quantify the impact of drainage water management on drain flow, NO3 concentration, and NO3 load from subsurface drainage on two farms in Indiana. Paired field studies were conducted following the paired watershed statistical approach modified to accommodate autocorrelation. Annual NO3 load reductions ranged from 15% to 31%, with an overall reduction of 18% to 23% over the 2-year period, resulting from reductions in both flow and NO3 concentration. Although the study revealed weaknesses in using the paired statistical approach for a dynamic practice like drainage water management, the results of this study support the use of drainage water management as a conservation practice and provide information for decision-makers about the level of benefits that can be anticipated.

Drainage water management, also known as controlled drainage, is the practice of using a water table control structure at the end of the subsurface drain pipe to reduce subsurface drainage, and thereby nitrate losses. Methods to quantify the potential effects of drainage water management for entire watersheds are needed to evaluate the impacts of large-scale adoption. A distributed modeling approach was developed to apply the field-scale DRAINMOD model at the watershed scale, and used to assess the impact of drainage water management on nitrate load from an intensively subsurface drained agricultural watershed in west central Indiana. The watershed was divided into 6460 grid cells for which drain spacing, soil parent material, and cropping pattern were estimated, resulting in 600 unique field conditions. The annual edge-of-field nitrate load from each grid cell was estimated as the product of DRAINMOD-predicted drain flow and the average annual nitrate concentration in drain flow, estimated from observations from related drainage sites in northern Indiana. Predicted monthly streamflow was in good agreement with the observed streamflow (Nash–Sutcliffe efficiency of 0.87 and 0.84 during the calibration and validation periods, respectively) and the predicted drain flow matched well with the measured drain flow (77.1 cm vs. 77.8 cm and 121.3 cm vs. 128.4 cm). Drainage water management decreased the average annual (1985–2009) predicted drain flow from 11.0 to 5.9 cm, and the total nitrate load through subsurface drainage from 236 to 126 ton (both about 47% reduction). The percent reduction in nitrate load varied between 40% and 53% for all combinations of drain spacing, soil parent material and cropping patterns, with drain spacing and soil parent material having a greater effect than cropping pattern. The methodology developed in this study showed potential for predicting the watershed-scale effects of subsurface drainage and drainage water management in drained agricultural watersheds.

The effects of climate variability, drain spacing, and growing season operational strategy on annual drain flow and crop yield were studied for a hypothetical drainage water management (DWM) system at Purdue University9s Water Quality Field Station using the DRAINMOD model. Drainage water management showed potential for reducing annual average (1915–2006) drain flow from all drain spacings (10–35 m) regardless of the growing season operational strategy, with reductions varying between 52 and 55% for the drain spacings considered. Approximately 81 to 99% of the annual drain flow reduction occurred during the non-growing season, depending on the operational strategy. Fixed DWM operational strategies led to an increase in mean predicted yield for narrower spacings compared with conventional drainage systems. Maximum yield was achieved with no control for drain spacings wider than 20 m in 50% of the years. Overall, the height of control had more influence on relative yield than the date of initiation of control. The greatest positive impacts of DWM on relative yield (1.2%) occurred in cool, dry years, while the greatest average negative impacts (−0.2%) occurred in cool, wet years. On average, with the best-case operation selected for annual weather conditions, DWM increased relative yield by approximately 0.8, 0.4, and 0.2% for the 10-, 20-, and 30-m drain spacing, respectively. Accumulated growing degree days and antecedent precipitation index show promise for identifying appropriate operational strategies for DWM.

The hypothetical effects of drainage water management operational strategy on hydrology and crop yield at the Purdue University Water Quality Field Station (WQFS) were simulated using DRAINMOD, a field-scale hydrologic model. The WQFS has forty-eight cropping system treatment plots with 10 m drain spacing. Drain flow observations from a subset of the treatment plots with continuous corn (Zea mays L.) were used to calibrate the model, which was then used to develop an operational strategy for drainage water management. The chosen dates of raising and lowering the outlet during the crop period were 10 and 85 days after planting, respectively, with a control height of 50 cm above the drain (40 cm from the surface). The potential effects of this operational strategy on hydrology and corn yield were simulated over a period of 15 years from 1991 to 2005. On average, the predicted annual drain flows were reduced by 60% (statistically significant at 95% level). This is the most significant benefit of drainage water management since it may reduce the nitrate load to the receiving streams. About 68% of the reduced drain flow contributed to an increase in seepage. Drainage water management increased the average surface runoff by about 85% and slightly decreased the relative yield of corn crop by 0.5% (both are not statistically significant at 95% level). On average, the relative yield due to wet stress (RYw) decreased by 1.3% while relative yield due to dry stress (RYd) increased by 1%. Overall, the relative crop yield increased in 5 years (within a range of 0.8�6.9%), decreased in 8 years (within a range of 0.2�5.5%), and was not affected in the remaining 2 years. With simulated drainage water management, the water table rose above the conventional drainage level during both the winter and the crop periods in all years (except 2002 crop season). The annual maximum winter period rise ranged between 47 cm (1995) and 87 cm (1992), and the annual maximum crop period rise ranged between no effect (2002) and 47 cm (1993).

Results of modelling studies for the evaluation of water quality impacts of agricultural conservation practices depend heavily on the numerical procedure used to represent the practices. Herein, a method for the representation of several agricultural conservation practices with the Soil and Water Assessment Tool (SWAT) is developed and evaluated. The representation procedure entails identifying hydrologic and water quality processes that are affected by practice implementation, selecting SWAT parameters that represent the affected processes, performing a sensitivity analysis to ascertain the sensitivity of model outputs to selected parameters, adjusting the selected parameters based on the function of conservation practices, and verifying the reasonableness of the SWAT results. This representation procedure is demonstrated for a case study of a small agricultural watershed in Indiana in the Midwestern USA. The methods developed in the present work can be applied with other watershed models that employ similar underlying equations to represent hydrologic and water quality processes.

Phosphorus (P) loss from agricultural fields and watersheds has been an important water quality issue for decades because of the critical role P plays in eutrophication. Historically, most research has focused on P losses by surface runoff and erosion because subsurface P losses were often deemed to be negligible. Perceptions of subsurface P transport, however, have evolved, and considerable work has been conducted to better understand the magnitude and importance of subsurface P transport and to identify practices and treatments that decrease subsurface P loads to surface waters. The objectives of this paper were (i) to critically review research on P transport in subsurface drainage, (ii) to determine factors that control P losses, and (iii) to identify gaps in the current scientific understanding of the role of subsurface drainage in P transport. Factors that affect subsurface P transport are discussed within the framework of intensively drained agricultural settings. These factors include soil characteristics (e.g., preferential flow, P sorption capacity, and redox conditions), drainage design (e.g., tile spacing, tile depth, and the installation of surface inlets), prevailing conditions and management (e.g., soil-test P levels, tillage, cropping system, and the source, rate, placement, and timing of P application), and hydrologic and climatic variables (e.g., baseflow, event flow, and seasonal differences). Structural, treatment, and management approaches to mitigate subsurface P transport-such as practices that disconnect flow pathways between surface soils and tile drains, drainage water management, in-stream or end-of-tile treatments, and ditch design and management-are also discussed. The review concludes by identifying gaps in the current understanding of P transport in subsurface drains and suggesting areas where future research is needed.

Agriculture in the Great Lakes region has benefited from precipitation patterns that are fairly regular throughout the year. The beneficial climate, coupled with soils that generally have high water holding abilities, has allowed agriculture in the region to become highly productive and a substantial contributor to the region’s economy. However, predicted shifts in temperature and precipitation patterns towards warmer and wetter winter and spring months, a greater frequency of intense storms throughout the year, and more severe and longer droughts in the summer suggest the potential for decreased crop yields in the future unless ways are found to provide additional water to crops during growing season drought, while also being able to quickly remove excess soil water when conditions are wet.

Good modelling practice requires the incorporation of uncertainty analysis into hydrologic/water quality models. The generalized likelihood uncertainty estimation procedure was used to evaluate the uncertainty in DRAINMOD predictions of daily, monthly, and yearly subsurface drain flow. A variance-based sensitivity analysis technique, the extended Fourier amplitude sensitivity test, was used to identify the main sources of prediction uncertainty. The analysis was conducted for the experimental drainage field at the Southeast Purdue Agricultural Center in Indiana. Six years of data were used and the uncertainties in eight model parameters were considered to analyse how uncertainties in input parameters propagate to model outputs. The width of 90% confidence interval bands of drain flow ranged from 0 to 0·6 cm day−1 for daily predictions, from 0 to 3·1 cm month−1 for the monthly predictions, and from 7·6 to 12·4 cm year−1 for yearly predictions. Annual drain flow predicted by DRAINMOD fell well within the 90% confidence bounds. Model results were most sensitive to the vertical saturated hydraulic conductivity of the restrictive layer and the lateral hydraulic conductivity of the deepest soil layer, followed by the lateral hydraulic conductivity of the top soil layer and surface micro-storage. Parameter interactions also contributed to the prediction uncertainty. Copyright © 2006 John Wiley & Sons, Ltd.

DRAINMOD was run for 15 years to predict and compare drain flow for three drain spacings and crop yield for four drain spacings at the Southeastern Purdue Agricultural Center (SEPAC). Data from two continuous years of daily drain flow from one spacing were used to calibrate the eight most uncertain parameters using a multi-objective calibration function and an automatic calibration method. The model was tested using the remaining field data for the 5, 10, and 20 m drain spacings for drain flow and the additional 40 m spacing for yield predictions. Nash–Sutcliffe efficiency (EF) for daily drain flow simulations for the calibration years and drain spacing ranged from 0.62 to 0.79. The daily EF for model testing ranged from −0.66 to 0.81, with the average deviations of 0.01 to 0.07 cm/day and standard errors of 0.03–0.17 cm/day. On a monthly basis, 91% of plot years had EF values over 0.5 and 76% over 0.6 for years with on-site rainfall data. The total yearly drain flow was predicted within ±25% in 71% of plot years, and within ±50% in 93% of plot years with on-site rainfall data. Statistical tests of daily drain flow EF values for three spacings and percent errors of crop relative yield for four spacings indicated that the reliability of the model is not significantly different among different spacings, supporting the use of DRAINMOD to study the efficiencies of different drain spacings and to guide the drain spacing design for specific soils. In general, the model correctly predicted the pattern of yearly relative yield change. The relative corn ( Zea mays L.) and soybean ( Glycine max L.) yields were well predicted on average, with percent errors ranging from 1.3 to 9.7% for corn and from −3.3 to 10.3% for soybean.