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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.

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.

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.

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 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.

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.

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.

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.

Structural best management practices (BMPs) that reduce soil erosion and nutrient losses have been recommended and installed on agricultural land for years. A structural BMP is expected to be fully functional only for a limited period after installation, after which degradation of the BMP is likely to lead to a reduction in the water quality improvement provided by the BMP. Assessing the impact of BMPs on water quality is of widespread interest, but no standard methods exist to determine the water quality impact of structural BMPs, particularly as the impact changes through time. The objective of this study was to determine the long-term (~20 year) impact of structural BMPs in two subwatersheds of Black Creek on sediment and phosphorus loads using the Soil and Water Assessment Tool (SWAT) model. The BMPs were represented by modifying SWAT parameters to reflect the impact the practice has on the processes simulated within SWAT, both when practices are fully functional and as their condition deteriorates. The current condition of the BMPs was determined using field evaluation results from a previously developed BMP condition evaluation tool. Based on simulations in the two subwatersheds, BMPs in good condition reduced the average annual sediment yield by 16% to 32% and the average annual phosphorus yield by 10% to 24%. BMPs in their current condition reduced sediment yield by only 7% to 10% and phosphorus yield by 7% to 17%.

Although the U.S. Congress established the Total Maximum Daily Load (TMDL) program in the original Clean Water Act of 1972, Section 303(d), it did not receive attention until the 1990s. Currently, two methods are available for tracking pollution in the environment and assessing the effectiveness of the TMDL process on improving the quality of impaired water bodies: field monitoring and mathematical/computer modeling. Field monitoring may be the most appropriate method, but its use is limited due to high costs and extreme spatial and temporal ecosystem variability. Mathematical models provide an alternative to field monitoring that can potentially save time, reduce cost, and minimize the need for testing management alternatives. However, the uncertainty of the model results is a major concern. Uncertainty is defined as the estimated amount by which an observed or calculated value may depart from the true value, and it has important policy, regulatory, and management implications. The source and magnitude of uncertainty and its impact on TMDL assessment has not been studied in depth. This article describes the collective experience of scientists and engineers in the assessment of uncertainty associated with TMDL models. It reviews sources of uncertainty (e.g., input variability, model algorithms, model calibration data, and scale), methods of uncertainty evaluation (e.g., first-order approximation, mean value first-order reliability method, Monte Carlo, Latin hypercube sampling with constrained Monte Carlo, and generalized likelihood uncertainty estimation), and strategies for communicating uncertainty in TMDL models to users. Four case studies are presented to highlight uncertainty quantification in TMDL models. Results indicate that uncertainty in TMDL models is a real issue and should be taken into consideration not only during the TMDL assessment phase, but also in the design of BMPs during the TMDL implementation phase. First-order error (FOE) analysis and Monte Carlo simulation (MCS) or any modified versions of these two basic methods may be used to assess uncertainty. This collective study concludes that a more scientific method to account for uncertainty would be to develop uncertainty probability distribution functions and transfer such uncertainties to TMDL load allocation through the margin of safety component, which is selected arbitrarily at the present time. It is proposed that explicit quantification of uncertainty be made an integral part of the TMDL process. This will benefit private industry, the scientific community, regulatory agencies, and action agencies involved with TMDL development and implementation.

Background Atrazine and other corn herbicides are routinely detected in drinking water. Two studies on potential association of atrazine with small-for-gestational-age (SGA) and preterm birth prevalence found inconsistent results. Moreover, these studies did not control for individual-level potential confounders. Objectives Our retrospective cohort study evaluated whether atrazine in drinking water is associated with increased prevalence of SGA and preterm birth. Methods We developed atrazine concentration time series for 19 water systems in Indiana from 1993 to 2007 and selected all births (n = 24,154) based on geocoded mother’s residences. Log-binomial models were used to estimate prevalence ratios (PRs) for SGA and preterm delivery in relation to atrazine concentrations during various periods of the pregnancy. Models controlled for maternal demographic characteristics, prenatal care and reproductive history, and behavioral risk factors (smoking, drinking, drug use). Results Atrazine in drinking water during the third trimester and the entire pregnancy was associated with a significant increase in the prevalence of SGA. Atrazine in drinking water > 0.1 μg/L during the third trimester resulted in a 17–19% increase in the prevalence of SGA compared with the control group (< 0.1 μg/L). Mean atrazine concentrations over the entire pregnancy > 0.644 μg/L were associated with higher SGA prevalence than in the control group (adjusted PR = 1.14; 95% confidence interval, 1.03–1.24). No significant association was found for preterm delivery. Conclusions We found that atrazine, and perhaps other co-occurring herbicides in drinking water, is associated with an increased prevalence of SGA, but not preterm delivery.

Environmental research in agriculture is today largely reactive, focused on problems at small scales and conducted within narrow disciplinary boundaries. This approach has worked to abate a number of environmental problems created by agriculture, but it has not provided effective solutions for many of the most recalcitrant ones. Furthermore, the approach fails to position agriculture to deliver new environmental benefits that the public and policymakers increasingly demand. A new vision is needed for environmental research in agriculture—one that is anticipatory; promotes long-term, systems-level research at multiple scales; better incorporates important interactions between the biophysical and social sciences; and provides for the proper evaluation of deployed solutions. Achieving this vision will require major changes in funding strategies, in institutional reward structures, and in policies that presently inhibit collaborations across disciplinary and institutional boundaries. It is, neverthel...