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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.

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.

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.

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.

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.

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.

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.

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%.

The purpose of this study was to determine the utility of on-farm precipitation measurement for nitrogen management decisions on an Indiana farm. Site-specific farming has led some producers to measure on-farm precipitation at multiple sites, but the profitability of such intense sampling for non-irrigated agriculture is not clear. The CERES-Maize model in Decision Support System for Agrotechnology Transfer (DSSAT) version 3.5 was used to simulate corn yield for a farm in east-central Indiana for 20years of weather data from three precipitation data sources—an on-farm station, the nearest non-urban National Weather Service (NWS) station, and the weighted mean of the three nearest such stations. Stochastic dominance and descriptive statistics were used to compare simulated yield and profitability for four nitrogen strategies: variable-rate versus whole-field fertilizer application and split application (starter urea-ammonium nitrate mixture at planting and sidedressed ammonia 37days later) versus sidedress application only. Off-farm data never led to a different choice of nitrogen strategy than on-farm data, but the ability to categorize a choice as risk averse or risk neutral depended on the precipitation data source used. This suggested that although on-farm precipitation measurement could be useful for risk management decisionmaking, it might not be profitable on average. The nearest NWS station would be the most profitable source of precipitation data, if it leads to the same management strategy as on-farm data.

Backpropagation neural networks with five data coding schemes were used to predict maize yield at three scales in east-central Indiana of the Midwest USA, using 1901–1996 local crop-stage weather data and yield data from farm, county, and state levels. Input data included precipitation and air temperature during maize reproductive (R) stages R1 (silking) to R5 (denting of kernels), the year, and, for some nets, the scale of yield data. The five coding schemes were maximum value, maximum and minimum value, logarithm, thermometer (powers of 10), and binary (powers of 2). Root mean squared error over a testing set was determined at farm, county, and state scales. The best version of the network was maximum and minimum value coded and gave a root mean squared error of 10·5% overall (8·6% farm, 12·5% county, 9·0% state yield). The prediction error among the five coding types ranged from 10·5 to 46·9% for the best net of each type. Neural net software usually has a default coding scheme, which is used without considering an alternative. The results of this study suggested that the data coding method had a significant effect on neural net performance, and that sensitivity testing of data representation should be performed when constructing neural nets. The study also confirmed the usefulness of neural nets for yield prediction from simple data sets.

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.

Federal conservation agencies are recognizing the need to account for the millions of dollars spent nation-wide on conservation programs focused on implementing best management practices (BMPs), some of which have been in existence for decades. A cost-benefit analysis for many of these programs is difficult due to the limited water quality and cost data available, and because attempts to quantify the water quality benefits obtained from BMP implementation is problematic. A cost-benefit analysis was performed on a large watershed management project that installed hundreds of BMPs in the mid-1970s, the Black Creek Project. Water quality improvement for sediment and total phosphorus reduction due to BMP implementation was estimated in 2000 dollars using off-site benefit estimates, fertilizer nutrient costs and water quality trading values. The benefits received from the BMPs did not outweigh the costs for implementing and maintaining the BMPs. Benefits not captured in this economic analysis include lessons learned and used outside the watershed by the conservation community, gully erosion, erosion deposited within the watershed, nitrogen reduction, wildlife habitat improvement, human and aquatic ecosystem health, aesthetics, downstream impacts, intangible impacts and the needs of future generations. This study shows that the tools needed to compute an accurate comparison of benefits and costs concerning water quality are lacking. Economic analysis of conservation planning should continue, but should not be the sole determining factor when deciding if a conservation project is worthwhile.

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...

Constructed wetlands are an effective yet costly strategy for reducing nitrate loading from agricultural subsurface drainage in the Midwestern United States. Targeting wetland placement to sites that intercept high nitrate loads and where topography permits optimal wetland sizing can maximize wetland nitrate removal efficiency while maintaining productive agriculture. The goals of this work were first to determine targeted locations for constructed wetlands to remove nitrate by applying a geospatial approach within an Indiana study region, and second to estimate the nitrate removal efficiency of these proposed wetlands. Criteria were developed from previously published wetland siting criteria associated with the Iowa CREP program and adapted to Indiana-specific conditions. Final criteria included location on cropped land and not within open waterways, size of upland contributing area, presence of tile drainage, and wetland-like topography. Within the study region, 18 locations were found to meet the targeting criteria for strategic wetland placement, requiring land conversion of 0.08% of the study region and intercepting 2.7% of flow from tile-drained lands. Estimated wetland nitrate removal efficiency was on average 37%, including land conversion of wetland and surrounding buffers, resulting in the removal of approximately 1.0% of all nitrate currently exported from tile-drained land in the study area. Wetland placement was most influenced by criteria relating to contributing area, exclusion of streams where wetlands could be potentially located, and topography. Adjusting criteria could allow for a larger set of constructed wetlands and achieve greater overall nitrate reductions at the watershed scale, but this set would likely include less efficient wetlands.