Least-cost control of agricultural nutrient contributions to the Gulf of Mexico hypoxic zone

A nonlinear autoregressive exogenous (NARX) model to predict nitrate concentration in rivers

Forecasting nitrate concentration in rivers is essential for environmental protection and careful treatment of drinking water. This study shows that nonlinear autoregressive with exogenous inputs neural networks can provide accurate models to predict nitrate plus nitrite concentrations in waterways. The Susquehanna River and the Raccoon River, USA, were chosen as case studies. Water discharge, water temperature, dissolved oxygen, and specific conductance were considered exogenous inputs. The forecasting sensitivity to changes in the exogenous input parameters and time series length was also assessed. For Kreutz Creek at Strickler station (Pennsylvania), the prediction accuracy increased with the number of exogenous input variables, with the best performance achieved considering all the variables (R² = 0.77). The predictions were accurate also for the Raccoon River (Iowa), although only the water discharge was considered exogenous input (South Raccoon River at Redfield-R² = 0.94). Both short- and long-term predictions were satisfactory.

Impact of Agricultural Non-Point Source Pollution on River Water Quality: Evidence From China

Identifying the effect of agricultural non-point source pollutants on water quality is very important for water pollution management. This study used NH3N as an indicator to empirically study the influence of fertilizer application on river water quality based on panel data of 46 prefecture-level cities and 18 state-controlled water quality monitoring points through which the main streams of Yangtze River and Yellow River flow from 2004 to 2019. It is found that: (1) An increase in agricultural fertilizer application amount will exacerbate water pollution, and the worsening water quality in the upper watershed and the influence of precipitation will lead to transboundary water pollution in the lower watershed. (2) The amount of fertilizer application and fertilizer application intensity had a threshold effect on river water quality pollution. When the former exceeded the threshold value of 11.496 tons, and the latter exceeded the threshold value of 7.991 ton/km2, the positive effect of fertilizer application on pollutants in rivers was further enhanced. (3) The amount of fertilizer applied had a long-term effect on water quality through a lagged effect, and as the number of lags increased, the accumulative effect of the negative influence gradually rose. Based on the findings of the empirical study, it is proposed that the inter-basin and inter-regional synergy should be formed in the prevention and control of agricultural non-point source pollution, and the overall top-level design of agricultural subsidies and agricultural environmental policies in the areas along the basin should be considered.

Targeting for nonpoint source pollution reduction: A synthesis of lessons learned, remaining challenges, and emerging opportunities

The ability to identify, target, and treat critical pollution source areas on a landscape is an ongoing challenge for water quality programs that seek to address nonpoint source (NPS) pollution. In this article, we develop a conceptual framework for targeting program design, and review recent experience with the implementation of targeting programs that corresponds with a wide range of program characteristics. Through this review, we emphasize that the complex and locally dependent nature of NPS generation and transport makes it impossible to define a narrow set of rules to guide targeting programs everywhere. Instead, we evaluate key features of NPS targeting in several different contexts, highlighting lessons learned from recent experience. This synthesis of targeting program design and implementation points toward several areas of opportunity for improved NPS policy, however more research is needed to systematically document changes in behavior and pollutant loads. The lack of monitoring data at refined scales presents a major obstacle to targeting program success. This paper synthesizes new opportunities and ongoing challenges for the implementation of targeting in NPS water quality programs.

Increasing the cost-effectiveness of nutrient reduction targets using different spatial scales

In this paper, we investigate the potential gains in cost-effectiveness from changing the spatial scale at which nutrient reduction targets are set for the Baltic Sea, with particular focus on nutrient loadings from agriculture. The costs of achieving loading reductions are compared across five levels of spatial scale, namely the entire Baltic Sea; the marine basin level; the country level; the watershed level; and the grid square level. A novel highly-disaggregated model, which represents decreases in agricultural profits, changes in root zone N concentrations and transport to the Baltic Sea is used. The model includes 14 Baltic Sea marine basins, 14 countries, 117 watersheds and 19,023 10-by-10 km grid squares. The main result which emerges is that there is a large variation in the total cost of the program depending on the spatial scale of targeting: for example, for a 40% reduction in loads, the costs of a Baltic Sea-wide target is nearly three times lower than targets set at the smallest level of spatial scale (grid square). These results have important implications for both domestic and international policy design for achieving water quality improvements where non-point pollution is a key stressor of water quality.

Integrated assessment modeling reveals near-channel management as cost-effective to improve water quality in agricultural watersheds

Despite decades of policy that strives to reduce nutrient and sediment export from agricultural fields, surface water quality in intensively managed agricultural landscapes remains highly degraded. Recent analyses show that current conservation efforts are not sufficient to reverse widespread water degradation in Midwestern agricultural systems. Intensifying row crop agriculture and increasing climate pressure require a more integrated approach to water quality management that addresses diverse sources of nutrients and sediment and off-field mitigation actions. We used multiobjective optimization analysis and integrated three biophysical models to evaluate the cost-effectiveness of alternative portfolios of watershed management practices at achieving nitrate and suspended sediment reduction goals in an agricultural basin of the Upper Midwestern United States. Integrating watershed-scale models enabled the inclusion of near-channel management alongside more typical field management and thus directly the comparison of cost-effectiveness across portfolios. The optimization analysis revealed that fluvial wetlands (i.e., wide, slow-flowing, vegetated water bodies within the riverine corridor) are the single-most cost-effective management action to reduce both nitrate and sediment loads and will be essential for meeting moderate to aggressive water quality targets. Although highly cost-effective, wetland construction was costly compared to other practices, and it was not selected in portfolios at low investment levels. Wetland performance was sensitive to placement, emphasizing the importance of watershed scale planning to realize potential benefits of wetland restorations. We conclude that extensive interagency cooperation and coordination at a watershed scale is required to achieve substantial, economically viable improvements in water quality under intensive row crop agricultural production.

Developing improved methods for identifying the cost-efficient abatement set in coastal water quality protection

Eutrophication of coastal waters is a recognised problem in estuaries around the globe. To analyse cross-boundary water quality management, such as protection of the Baltic Sea, economic nutrient abatement models commonly operate on a large scale, grouping river systems to large catchment areas. Theoretical deliberation suggests that modelling abatement in such a way removes the opportunity of targeting measures to the most vulnerable regions within the catchment, while overestimating the capacity of abatement measures in the upstream areas. However, the implications on designing environmental policy depend on catchment characteristics and the stringency of the abatement targets. In this study a model of the catchment area is built with zones that are an increasing distance away from the coast to show what kind of bias in the optimal abatement set is caused by the assumption of spatial homogeneity. By solving the model with and without the zones for good ecological status at the South-West coast of Sweden, it is shown that while assuming homogeneity prevents from perceiving the abatement measures where they would be the most effective, it also leads to ignoring spatial limitations that are more relevant to a subset of abatement measures, such as the wetlands and buffer zones. Following from the relatively large nitrogen abatement targets, the overall effect of assuming catchment homogeneity is to underestimate the abatement costs and to overestimate the potential of wetlands to reduce nitrogen.

Normative Influences on Farmers' Intentions to Practice Conservation Without Compensation

Non-source nutrients (e.g., nitrogen, phosphorous) from agriculture have created a massive hypoxic zone in the Gulf of Mexico. This zone contains no oxygen and is devoid of life. US Department of Agriculture programs provide direct payments to farmers to encourage adoption of practices that reduce nutrient pollution. Paying farmers to change behavior, however, is expensive. Personal and social norms may serve to reduce these payment costs by motivating farmers to take action without external reward. This study explored relationships between three normative concepts (awareness of consequences (AC), ascription of responsibility (AR), subjective norms (SN)) and Illinois farmers' intention to continue participation in conservation without financial compensation. Data were obtained from a mailed questionnaire. Only farmers who were currently being paid to participate in a conservation program were included in the analysis (n = 551). Using norm activation theory and the theory of reasoned action, we hypothesized that SN would be positively related to AC, AR, and conservation intentions without compensation. We also predicted that AC would be positively related to AR, and that AC and AR would be positively related to conservation intentions. All hypotheses were supported. Both personal norms (AC, AR) and social norms (subjective norms) were related to intentions to continue conservation without pay. Behavioral interventions that activate norms may help facilitate conservation without payments. As applied in this study, activating personal and social norms may serve to reduce nutrient pollution from agriculture that is flowing into the Gulf of Mexico and resulting in the hypoxic zone.

Analysis of alternative climate datasets and evapotranspiration methods for the Upper Mississippi River Basin using SWAT within HAWQS

This study reports the application of Soil and Water Assessment Tool (SWAT) within the Hydrologic and Water Quality System (HAWQS) on-line platform, for the Upper Mississippi River Basin (UMRB). The UMRB is an important ecosystem located in the north central U.S. that is experiencing a range of ecological stresses. Specifically, testing of SWAT was performed for: (1) Hargreaves (HG) and Penman-Monteith (PM) PET methods, and (2) Livneh, National Climatic Data Center (NCDC) and Parameter-elevation Regressions on Independent Slopes Model (PRISM) climate datasets. The Livneh-PM combination resulted in the highest average annual water yield of 380.6 mm versus the lowest estimated water yield of 193.9 mm for the Livneh-HG combination, in response to 23-year uncalibrated simulations. Higher annual ET and PET values were predicted with HG method versus the PM method for all three weather datasets in response to the uncalibrated simulations, due primarily to higher HG-based estimates during the growing season. Based on these results, it was found that the HG method is the preferred PET option for the UMRB. Initial calibration of SWAT was performed using the Livneh data and HG method for three Mississippi River main stem gauge sites, which was followed by spatial validation at 10 other gauge sites located within the UMRB stream network. Overall satisfactory results were found for the calibration and validation gauge sites, with the majority of R2 values ranging between 0.61 and 0.82, Nash-Sutcliffe modeling efficiency (NSE) values ranging between 0.50 and 0.79, and Kling-Gupta efficiency (KGE) values ranging between 0.61 and 0.84. The results of an additional experimental suite of six scenarios, which represented different combinations of climate data sets and calibrated parameters, revealed that suggested statistical criteria were again satisfied by the different scenario combinations. Overall, the PRISM data exhibited the strongest reliability for the UMRB.

Addressing the spatial disconnect between national-scale total maximum daily loads and localized land management decisions

Regulatory watershed mitigation programs typically emphasize widespread adoption of best management practices (BMPs) to meet total maximum daily load (TMDL) goals. To comply with the Chesapeake Bay TMDL, jurisdictions must develop watershed implementation plans (WIPs) to determine the number and type of BMPs to implement. However, the spatial resolution of the bay-level model used to determine these load reduction goals is so coarse that the regulatory plan cannot consider heterogeneity in local conditions, which affects BMP effectiveness. Using the Topo-SWAT modification of the Soil and Water Assessment Tool (SWAT), we simulated two BMP adoption scenarios in the Spring Creek watershed in central Pennsylvania to determine if leveraging fine-scale spatial heterogeneity to place BMPs could achieve the same (or better) nutrient and sediment reduction at a lower cost than the state-level WIP BMP adoption recommendations. Topo-SWAT was initialized with detailed land use and management practice information, systematically calibrated, and validated against 12 yr of observed data. After determining individual BMP cost effectiveness, results were ranked to design a cost-effective BMP adoption scenario that achieved equal or greater load reduction as the WIP scenario for 74% of the cost using eight management-based BMPs: no-till, manure injection, cover cropping, riparian buffers, land retirement, manure application timing, wetland restoration, and nitrogen management (15% less N input). Because watersheds of this size typically represent the smallest modeling unit in the Chesapeake Bay Model, results demonstrate the potential to use watershed models with finer inference scales to improve recommendations for BMP implementation under the Chesapeake Bay TMDL.

Statistical Analysis of Nutrient Loads from the Mississippi-Atchafalaya River Basin (MARB) to the Gulf of Mexico

This study investigated the annual and seasonal variations in nutrient loads (NO2− + NO3− and orthophosphate) delivered to the Gulf of Mexico from the Mississippi-Atchafalaya River Basin (MARB) and examined the water quality variations. The results indicate that (1) annually, the mean NO2− + NO3− and orthophosphate loads showed a steady increase during 1996–1999, a persistent level during 2000–2007, and a moderate increase during 2008–2016; (2) seasonally, NO2− + NO3− and orthophosphate in MARB in spring and summer were higher than those in autumn and winter. Analysis of variance (ANOVA) identified highly significant differences among seasonal loads; and (3) the median value of NO2− + NO3− in normal weather conditions were higher than that during and right after the hurricanes, while the median value of orthophosphate loads in normal weather conditions was higher than that during the hurricanes, but higher than that right after hurricanes. The two-sample t-test indicates a significant difference (p < 0.046) in orthophosphate loads before and after Hurricane Katrina. Moreover, it is found that there is a significant (p < 0.01) increase in nutrient loads during normal weather conditions. The results indicate that hurricane seasons can significantly influence the nutrient loads from the MARB to the Gulf of Mexico.

Biogeochemistry of dissolved inorganic nutrients in an oligotrophic coastal mariculture region of the northern Shandong Peninsula, north Yellow Sea

Fourteen field cruises were carried out in a mariculture region of the northern Shandong Peninsula, North Yellow Sea, China from 2016 to 2017 for a better understanding of the biogeochemical behaviors, sources and export of dissolved inorganic nutrients. The spatial variations of nutrients were not obvious due to the influence of complex hydrological and biochemical conditions. Potential nutritional level was characterized in oligotrophy, and trophic status was rated at medium level. A preliminary estimation of nutrient budgets demonstrated that the dissolved inorganic nitrogen (DIN) load was mainly from atmospheric deposition and scallop excretion, accounting for 56.9% and 35.6% of its total influx. Scallop excretion and sediment release were the major source of phosphate (DIP), contributing to 25.2% and 44.3%, while dissolved silicon (DSi) was mainly from sediment release, accounting for 94.2%. In addition, about 136.7 × 10³, 7.3 × 10³ and 485.5 × 10³ mol km^-2 yr^-1 of DIN, DIP and DSi could be converted into other forms, e.g. organic and particulate matter and gas species.

Including aesthetic and recreational values in cost-effectiveness analyses of land use change based nitrogen abatement measures in Denmark

In recent years there has been an increased focus on including aspects such as greenhouse gas emissions and biodiversity in cost-effectiveness analyses of nitrogen (N) abatement measures. Side-effects such as aesthetic and recreational benefits generated by the land use changes implied by some N abatement measures, such as afforestation and constructed wetlands, are included in ecosystem service approaches, but seldom explicitly in cost-effectiveness analyses. While several studies have estimated these values for e.g. forests and wetlands, per se, few have studied how these effects are valued by the general population when generated through the implementation of land use changes driven by measures aimed at reducing the loss of nitrogen from agriculture. The land use changes implied by the N abatement measures have different characteristics to that of the evaluations of forests for recreation or larger wetlands created or maintained for biodiversity, mainly because the area affected varies considerably in size and shape. In this paper, we estimate the welfare economic impacts of some of the potential side-effects, such as recreational and aesthetic effects, of three N abatement measures related to agricultural land use change: afforestation, constructed wetlands or energy crops. We incorporate the value of these side-effects in a standard cost-effectiveness analysis and discuss the policy implications. This allows us to evaluate to what extent the inclusion of these side-effects change the ranking of the measures and the cost levels used. We thereby provide a more holistic approach to the cost-effectiveness analysis of land use change based N abatement measures, and discuss the challenges relating to the spatial aspects that arise when accounting for the value of the analyzed side-effects. The analysis shows that public access to the area largely determine whether the selected measures are perceived as positive or negative. The impact of the analyzed side-effects on the cost-effectiveness analysis critically depends on the size of the affected population, as the value of the side-effects are measured per household.

Embedding co-production and addressing uncertainty in watershed modeling decision-support tools: successes and challenges

Decision-support tools (DSTs) are often produced from collaborations between technical experts and stakeholders to address environmental problems and inform decision making. Studies in the past two decades have provided key insights on the use of DSTs and the importance of bidirectional information flows among technical experts and stakeholders - a process that is variously referred to as co-production, participatory modeling, structured decision making, or simply stakeholder participation. Many of these studies have elicited foundational insights for the broad field of water resources management; however, questions remain on approaches for balancing co-production with uncertainty specifically for watershed modeling decision support tools. In this paper, we outline a simple conceptual model that focuses on the DST development process. Then, using watershed modeling case studies found in the literature, we discuss successful outcomes and challenges associated with embedding various forms of co-production into each stage of the conceptual model. We also emphasize the "3 Cs" (i.e., characterization, calculation, communication) of uncertainty and provide evidence-based suggestions for their incorporation in the watershed modeling DST development process. We conclude by presenting a list of best practices derived from current literature for achieving effective and robust watershed modeling decision-support tools.

Dynamic adjustment in agricultural practices to economic incentives aiming to decrease fertilizer application

Input- and output-based economic policies designed to reduce water pollution from fertilizer runoff by adjusting management practices are theoretically justified and well-understood. Yet, in practice, adjustment in fertilizer application or land allocation may be sluggish. We provide practical guidance for policymakers regarding the relative magnitude and speed of adjustment of input- and output-based policies. Through a dynamic dual model of corn production that takes fertilizer as one of several production inputs, we measure the short- and long-term effects of policies that affect the relative prices of inputs and outputs through the short- and long-term price elasticities of fertilizer application, and also the total time required for different policies to affect fertilizer application through the adjustment rates of capital and land. These estimates allow us to compare input- and output-based policies based on their relative cost-effectiveness. Using data from Indiana and Illinois, we find that input-based policies are more cost-effective than their output-based counterparts in achieving a target reduction in fertilizer application. We show that input- and output-based policies yield adjustment in fertilizer application at the same speed, and that most of the adjustment takes place in the short-term.

Catchment legacies and time lags: a parsimonious watershed model to predict the effects of legacy storage on nitrogen export

Nutrient legacies in anthropogenic landscapes, accumulated over decades of fertilizer application, lead to time lags between implementation of conservation measures and improvements in water quality. Quantification of such time lags has remained difficult, however, due to an incomplete understanding of controls on nutrient depletion trajectories after changes in land-use or management practices. In this study, we have developed a parsimonious watershed model for quantifying catchment-scale time lags based on both soil nutrient accumulations (biogeochemical legacy) and groundwater travel time distributions (hydrologic legacy). The model accurately predicted the time lags observed in an Iowa watershed that had undergone a 41% conversion of area from row crop to native prairie. We explored the time scales of change for stream nutrient concentrations as a function of both natural and anthropogenic controls, from topography to spatial patterns of land-use change. Our results demonstrate that the existence of biogeochemical nutrient legacies increases time lags beyond those due to hydrologic legacy alone. In addition, we show that the maximum concentration reduction benefits vary according to the spatial pattern of intervention, with preferential conversion of land parcels having the shortest catchment-scale travel times providing proportionally greater concentration reductions as well as faster response times. In contrast, a random pattern of conversion results in a 1:1 relationship between percent land conversion and percent concentration reduction, irrespective of denitrification rates within the landscape. Our modeling framework allows for the quantification of tradeoffs between costs associated with implementation of conservation measures and the time needed to see the desired concentration reductions, making it of great value to decision makers regarding optimal implementation of watershed conservation measures.

Agricultural conservation planning framework: 1. Developing multipractice watershed planning scenarios and assessing nutrient reduction potential

Spatial data on soils, land use, and topography, combined with knowledge of conservation effectiveness, can be used to identify alternatives to reduce nutrient discharge from small (hydrologic unit code [HUC]12) watersheds. Databases comprising soil attributes, agricultural land use, and light detection and ranging-derived elevation models were developed for two glaciated midwestern HUC12 watersheds: Iowa's Beaver Creek watershed has an older dissected landscape, and Lime Creek in Illinois is young and less dissected. Subsurface drainage is common in both watersheds. We identified locations for conservation practices, including in-field practices (grassed waterways), edge-of-field practices (nutrient-removal wetlands, saturated buffers), and drainage-water management, by applying terrain analyses, geographic criteria, and cross-classifications to field- and watershed-scale geographic data. Cover crops were randomly distributed to fields without geographic prioritization. A set of alternative planning scenarios was developed to represent a variety of extents of implementation among these practices. The scenarios were assessed for nutrient reduction potential using a spreadsheet approach to calculate the average nutrient-removal efficiency required among the practices included in each scenario to achieve a 40% NO-N reduction. Results were evaluated in the context of the Iowa Nutrient Reduction Strategy, which reviewed nutrient-removal efficiencies of practices and established the 40% NO-N reduction as Iowa's target for Gulf of Mexico hypoxia mitigation by agriculture. In both test watersheds, planning scenarios that could potentially achieve the targeted NO-N reduction but remove <5% of cropland from production were identified. Cover crops and nutrient removal wetlands were common to these scenarios. This approach provides an interim technology to assist local watershed planning and could provide planning scenarios to evaluate using watershed simulation models. A set of ArcGIS tools is being released to enable transfer of this mapping technology.

Cost of areal reduction of gulf hypoxia through agricultural practice

A major share of the area of hypoxic growth in the Northern Gulf of Mexico has been attributed to nutrient run-off from agricultural fields, but no estimate is available for the cost of reducing Gulf hypoxic area using agricultural conservation practices. We apply the Soil and Water Assessment Tool using observed daily weather to simulate the reduction in nitrogen loading in the Upper Mississippi River Basin (UMRB) that would result from enrolling all row crop acreage in the Conservation Reserve Program (CRP). Nitrogen loadings at the outlet of the UMRB are used to predict Gulf hypoxic area, and net cash farm rent is used as the price for participation in the CRP. Over the course of the 42 year simulation, direct CRP costs total more than $388 billion, and the Inter-Governmental Task Force goal of hypoxic area less than 5000 square kilometers is met in only two years.

Cost-effective targeting of conservation investments to reduce the northern Gulf of Mexico hypoxic zone

A seasonally occurring summer hypoxic (low oxygen) zone in the northern Gulf of Mexico is the second largest in the world. Reductions in nutrients from agricultural cropland in its watershed are needed to reduce the hypoxic zone size to the national policy goal of 5,000 km(2) (as a 5-y running average) set by the national Gulf of Mexico Task Force's Action Plan. We develop an integrated assessment model linking the water quality effects of cropland conservation investment decisions on the more than 550 agricultural subwatersheds that deliver nutrients into the Gulf with a hypoxic zone model. We use this integrated assessment model to identify the most cost-effective subwatersheds to target for cropland conservation investments. We consider targeting of the location (which subwatersheds to treat) and the extent of conservation investment to undertake (how much cropland within a subwatershed to treat). We use process models to simulate the dynamics of the effects of cropland conservation investments on nutrient delivery to the Gulf and use an evolutionary algorithm to solve the optimization problem. Model results suggest that by targeting cropland conservation investments to the most cost-effective location and extent of coverage, the Action Plan goal of 5,000 km(2) can be achieved at a cost of $2.7 billion annually. A large set of cost-hypoxia tradeoffs is developed, ranging from the baseline to the nontargeted adoption of the most aggressive cropland conservation investments in all subwatersheds (estimated to reduce the hypoxic zone to less than 3,000 km(2) at a cost of $5.6 billion annually).

Effects of agricultural conservation practices on N loads in the Mississippi-atchafalaya river basin

A modeling framework consisting of a farm-scale model, Agricultural Policy Environmental Extender (APEX); a watershed-scale model, Soil and Water Assessment Tool (SWAT); and databases was used in the Conservation Effects Assessment Project to quantify the environmental benefits of conservation practices on cropland. APEX is used to simulate conservation practices on cultivated cropland and Conservation Reserve Program land to assess the edge-of-field water-quality benefits. Flow and pollutant loadings from APEX are input to SWAT. SWAT simulates the remaining noncultivated land and routes flow and loads generated from noncultivated land, point sources, and cropland to the basin outlet. SWAT is used for assessing the effects of practices on local and in-stream water-quality benefits. Each river basin is calibrated and validated for streamflow and loads at multiple gauging stations. The objectives of the current study are to estimate the effects of currently existing and additional conservation practices on total N (TN) loads in the Mississippi-Atchafalaya River Basin (MARB) and draw insights on TN load reductions necessary for reducing the hypoxic zone in the Gulf of Mexico. The effects of conservation practice scenarios on local and in-stream (riverine) water quality are evaluated. Model results indicate that conservation practices currently on cropland have reduced the TN losses to local waters between 20 and 59% in the six river basins within MARB and the TN load discharged to the Gulf by 17%. Further water-quality improvement can be obtained in the MARB with additional conservation treatment.

Seasonal patterns of nitrogen and phosphorus limitation in four German lakes and the predictability of limitation status from ambient nutrient concentrations

To identify the seasonal pattern of nitrogen (N) and phosphorus (P) limitation of phytoplankton in four different lakes, biweekly experiments were conducted from the end of March to September 2011. Lake water samples were enriched with N, P or both nutrients and incubated under two different light intensities. Chlorophyll a fluorescence (Chla) was measured and a model selection procedure was used to assign bioassay outcomes to different limitation categories. N and P were both limiting at some point. For the shallow lakes there was a trend from P limitation in spring to N or light limitation later in the year, while the deep lake remained predominantly P limited. To determine the ability of in-lake N:P ratios to predict the relative strength of N vs. P limitation, three separate regression models were fit with the log-transformed ratio of Chla of the P and N treatments (Response ratio = RR) as the response variable and those of ambient total phosphorus:total nitrogen (TN:TP), dissolved inorganic nitrogen:soluble reactive phosphorus (DIN:SRP), TN:SRP and DIN:TP mass ratios as predictors. All four N:P ratios had significant positive relationships with RR, such that high N:P ratios were associated with P limitation and low N:P ratios with N limitation. The TN:TP and DIN:TP ratios performed better than the DIN:SRP and TN:SRP in terms of misclassification rate and the DIN:TP ratio had the highest R₂ value. Nitrogen limitation was predictable, frequent and persistent, suggesting that nitrogen reduction could play a role in water quality management. However, there is still uncertainty about the efficacy of N restriction to control populations of N₂ fixing cyanobacteria.

Modelling the cost-effectiveness of mitigation methods for multiple pollutants at farm scale

Reductions in agricultural pollution are essential for meeting nationally and internationally agreed policy targets for losses to both air and water. Numerous studies quantify the impact of relevant mitigation methods by field experimentation or computer modelling. The majority of these studies have addressed individual methods and frequently also individual pollutants. This paper presents a conceptual model for the synthesis of the evidence base to calculate the impact of multiple methods addressing multiple pollutants in order to identify least cost solutions for multiple policy objectives. The model is implemented as a farm scale decision support tool that quantifies baseline pollutant losses for identifiable sources, areas and pathways and incorporates a genetic algorithm based multi-objective procedure for determining optimal suites of mitigation methods. The tool is generic as baseline losses can be replaced with measured data and the default library of mitigation methods can be edited and expanded. The tool is demonstrated through application to two contrasting farm systems, using survey data on agricultural practices typical of England and Wales. These examples show how the tool could be used to help target the adoption of mitigation options for the control of diffuse pollution from agriculture. The feedback from workshops where Farmscoper was demonstrated is included to highlight the potential role of Farmscoper as part of the farm advisory process.

Environmental and economic trade-offs in a watershed when using corn stover for bioenergy

There is an abundant supply of corn stover in the United States that remains after grain is harvested which could be used to produce cellulosic biofuels mandated by the current Renewable Fuel Standard (RFS). This research integrates the Soil Water Assessment Tool (SWAT) watershed model and the DayCent biogeochemical model to investigate water quality and soil greenhouse gas flux that results when corn stover is collected at two different rates from corn-soybean and continuous corn crop rotations with and without tillage. Multiobjective watershed-scale optimizations are performed for individual pollutant-cost minimization criteria based on the economic cost of each cropping practice and (individually) the effect on nitrate, total phosphorus, sediment, or global warming potential. We compare these results with a purely economic optimization that maximizes stover production at the lowest cost without taking environmental impacts into account. We illustrate trade-offs between cost and different environmental performance criteria, assuming that nutrients contained in any stover collected must be replaced. The key finding is that stover collection using the practices modeled results in increased contributions to atmospheric greenhouse gases while reducing nitrate and total phosphorus loading to the watershed relative to the status quo without stover collection. Stover collection increases sediment loading to waterways relative to when no stover is removed for each crop rotation-tillage practice combination considered; no-till in combination with stover collection reduced sediment loading below baseline conditions without stover collection. Our results suggest that additional information is needed about (i) the level of nutrient replacement required to maintain grain yields and (ii) cost-effective management practices capable of reducing soil erosion when crop residues are removed in order to avoid contributions to climate change and water quality impairments as a result of using corn stover to satisfy the RFS.

A topography analysis incorporated optimization method for the selection and placement of best management practices

Best Management Practices (BMPs) are one of the most effective methods to control nonpoint source (NPS) pollution at a watershed scale. In this paper, the use of a topography analysis incorporated optimization method (TAIOM) was proposed, which integrates topography analysis with cost-effective optimization. The surface status, slope and the type of land use were evaluated as inputs for the optimization engine. A genetic algorithm program was coded to obtain the final optimization. The TAIOM was validated in conjunction with the Soil and Water Assessment Tool (SWAT) in the Yulin watershed in Southwestern China. The results showed that the TAIOM was more cost-effective than traditional optimization methods. The distribution of selected BMPs throughout landscapes comprising relatively flat plains and gentle slopes, suggests the need for a more operationally effective scheme, such as the TAIOM, to determine the practicability of BMPs before widespread adoption. The TAIOM developed in this study can easily be extended to other watersheds to help decision makers control NPS pollution.

Spatial multiobjective optimization of agricultural conservation practices using a SWAT model and an evolutionary algorithm

Finding the cost-efficient (i.e., lowest-cost) ways of targeting conservation practice investments for the achievement of specific water quality goals across the landscape is of primary importance in watershed management. Traditional economics methods of finding the lowest-cost solution in the watershed context (e.g.,(5,12,20)) assume that off-site impacts can be accurately described as a proportion of on-site pollution generated. Such approaches are unlikely to be representative of the actual pollution process in a watershed, where the impacts of polluting sources are often determined by complex biophysical processes. The use of modern physically-based, spatially distributed hydrologic simulation models allows for a greater degree of realism in terms of process representation but requires a development of a simulation-optimization framework where the model becomes an integral part of optimization. Evolutionary algorithms appear to be a particularly useful optimization tool, able to deal with the combinatorial nature of a watershed simulation-optimization problem and allowing the use of the full water quality model. Evolutionary algorithms treat a particular spatial allocation of conservation practices in a watershed as a candidate solution and utilize sets (populations) of candidate solutions iteratively applying stochastic operators of selection, recombination, and mutation to find improvements with respect to the optimization objectives. The optimization objectives in this case are to minimize nonpoint-source pollution in the watershed, simultaneously minimizing the cost of conservation practices. A recent and expanding set of research is attempting to use similar methods and integrates water quality models with broadly defined evolutionary optimization methods(3,4,9,10,13-15,17-19,22,23,25). In this application, we demonstrate a program which follows Rabotyagov et al.'s approach and integrates a modern and commonly used SWAT water quality model(7) with a multiobjective evolutionary algorithm SPEA2(26), and user-specified set of conservation practices and their costs to search for the complete tradeoff frontiers between costs of conservation practices and user-specified water quality objectives. The frontiers quantify the tradeoffs faced by the watershed managers by presenting the full range of costs associated with various water quality improvement goals. The program allows for a selection of watershed configurations achieving specified water quality improvement goals and a production of maps of optimized placement of conservation practices.

Assessing regional hydrology and water quality implications of large-scale biofuel feedstock production in the Upper Mississippi River Basin

A recent U.S. Department of Energy study estimated that more than one billion tons of biofuel feedstock could be produced by 2030 in the United States from increased corn yield, and changes in agricultural and forest residue management and land uses. To understand the implications of such increased production on water resources and stream quality at regional and local scales, we have applied a watershed model for the Upper Mississippi River Basin, where most of the current and future crop/residue-based biofuel production is expected. The model simulates changes in water quality (soil erosion, nitrogen and phosphorus loadings in streams) and resources (soil-water content, evapotranspiration, and runoff) under projected biofuel production versus the 2006 baseline year and a business-as-usual scenario. The basin average results suggest that the projected feedstock production could change the rate of evapotranspiration in the UMRB by approximately +2%, soil-water content by about -2%, and discharge to streams by -5% from the baseline scenario. However, unlike the impacts on regional water availability, the projected feedstock production has a mixed effect on water quality, resulting in 12% and 45% increases in annual suspended sediment and total phosphorus loadings, respectively, but a 3% decrease in total nitrogen loading. These differences in water quantity and quality are statistically significant (p < 0.05). The basin responses are further analyzed at monthly time steps and finer spatial scales to evaluate underlying physical processes, which would be essential for future optimization of environmentally sustainable biofuel productions.

Reforming agricultural nonpoint pollution policy in an increasingly budget-constrained environment

Agricultural nonpoint source water pollution has long been recognized as an important contributor to U.S. water quality problems and the subject of an array of local, state, and federal initiatives to reduce the problem. A "pay-the-polluter" approach to getting farmers to adopt best management practices has not succeeded in improving water quality in many impaired watersheds. With the prospects of reduced funding for the types of financial and technical assistance programs that have been the mainstay of agricultural water quality policy, alternative approaches need to be considered. Some changes to the way current conservation programs are implemented could increase their efficiency, but there are limits to how effective a purely voluntary approach can be. An alternative paradigm is the "polluter pays" approach, which has been successfully employed to reduce point source pollution. A wholesale implementation of the polluter-pays approach to agriculture is likely infeasible, but elements of the polluter-pays approach could be incorporated into agricultural water quality policy.

Development of environmental thresholds for streams in agricultural watersheds

Global increases in consumption of chemical nutrients, application of pesticides, and water withdrawal to enhance agricultural yield have resulted in degraded water quality and reduced water availability. Efforts to safeguard or improve environmental conditions of agroecosystems have usually focused on managing on-farm activities to reduce materials loss and conserve habitat. Another management measure for improving environmental quality is adoption of environmental performance standards (also called outcome-based standards). This special collection of six papers presents the results of four years of research to devise scientifically credible approaches for setting environmental performance standards to protect water quantity and quality in Canadian agriculturally dominated watersheds. The research, conducted as part of Canada's National Agri-Environmental Standards Initiative, aimed to identify Ideal Performance Standards (the desired environmental state needed to maintain ecosystem health) and Achievable Performance Standards (the environmental conditions achievable using currently available and recommended best available processes and technologies). Overviews of the papers, gaps in knowledge, and future research directions are presented. As humans, livestock, and wildlife (both terrestrial and aquatic) experience greater pressures to share the same limited water resources, innovative research is needed that incorporates a landscape perspective, economics, farm practices, and ecology to advance the development and application of tools for protecting water resources in agricultural watersheds.

Application of a multi-objective optimization method to provide least cost alternatives for NPS pollution control

Nonpoint source (NPS) pollutants such as phosphorus, nitrogen, sediment, and pesticides are the foremost sources of water contamination in many of the water bodies in the Midwestern agricultural watersheds. This problem is expected to increase in the future with the increasing demand to provide corn as grain or stover for biofuel production. Best management practices (BMPs) have been proven to effectively reduce the NPS pollutant loads from agricultural areas. However, in a watershed with multiple farms and multiple BMPs feasible for implementation, it becomes a daunting task to choose a right combination of BMPs that provide maximum pollution reduction for least implementation costs. Multi-objective algorithms capable of searching from a large number of solutions are required to meet the given watershed management objectives. Genetic algorithms have been the most popular optimization algorithms for the BMP selection and placement. However, previous BMP optimization models did not study pesticide which is very commonly used in corn areas. Also, with corn stover being projected as a viable alternative for biofuel production there might be unintended consequences of the reduced residue in the corn fields on water quality. Therefore, there is a need to study the impact of different levels of residue management in combination with other BMPs at a watershed scale. In this research the following BMPs were selected for placement in the watershed: (a) residue management, (b) filter strips, (c) parallel terraces, (d) contour farming, and (e) tillage. We present a novel method of combing different NPS pollutants into a single objective function, which, along with the net costs, were used as the two objective functions during optimization. In this study we used BMP tool, a database that contains the pollution reduction and cost information of different BMPs under consideration which provides pollutant loads during optimization. The BMP optimization was performed using a NSGA-II based search method. The model was tested for the selection and placement of BMPs in Wildcat Creek Watershed, a corn dominated watershed located in northcentral Indiana, to reduce nitrogen, phosphorus, sediment, and pesticide losses from the watershed. The Pareto optimal fronts (plotted as spider plots) generated between the optimized objective functions can be used to make management decisions to achieve desired water quality goals with minimum BMP implementation and maintenance cost for the watershed. Also these solutions were geographically mapped to show the locations where various BMPs should be implemented. The solutions with larger pollution reduction consisted of buffer filter strips that lead to larger pollution reduction with greater costs compared to other alternatives.

Potential water quality changes due to corn expansion in the Upper Mississippi River Basin

While biofuels may yield renewable fuel benefits, there could be downsides in terms of water quality and other environmental stressors, particularly if corn is relied upon exclusively as the feedstock. The consequences of increased corn production will depend importantly on where (and how) the additional corn is grown, which, in turn, depends on the characteristics of land and its associated profitability. Previous work has relied on rules of thumb for allocating land to increased acreage based on historical land use or other heuristics. Here, we advance our understanding of these phenomena by describing a modeling system that links an economics-driven land use model with a watershed-based water quality model for the Upper Mississippi River Basin (UMRB). This modeling system is used to assess the water quality changes due to increased corn acreage, which is associated with higher relative corn prices. We focus on six scenarios based on six realistic pairs of corn and soybean prices which correspond to a scale of decreasing soybean to corn price ratio. These price-driven land use changes provide estimates of the water quality effects that current biofuel policies may have in the UMRB. Our analysis can help evaluate the costs and environmental consequences associated with implementation strategies for the biofuel mandates of the new energy bill. The amounts of total N and P delivered to the outlet of the UMRB (located at Grafton, Illinois, USA) rise as corn production becomes more intensive in the region. Our results indicate that a 14.4% in corn acreage in the watershed due to corn intensification in the most economically profitable locations would result in a 5.4% increase in total nitrogen loads and in a 4.1% increase in total phosphorus loads at Grafton. Our most aggressive scenario, driven by high but not out of reach crop prices, results in about a 57% increase in corn acreage with a corresponding 18.5% increase in N and 12% increase in P. These are somewhat conservative increases in nutrients, compared to those of previous studies, likely due to our focus on cultivated cropland which is already heavily fertilized.

The limitations of environmental management systems in Australian agriculture

The efficacy of government-supported programs to encourage improved management of land and water systems associated with agricultural land in Australia has been mixed. The broad approach of Australian governments is reviewed briefly. Evidence is presented from case assessments of a program to promote adoption of environmental management systems (EMSs) to improve environmental outcomes from agricultural practices. EMSs are systems implemented to manage the environmental impacts and ameliorate environmental risk associated with business activity. Data are presented on reported EMS activity and experience of four selected groups of farmers in Victoria, south-eastern Australia, representing broad-acre cropping, beef and dairy farming. The pro-environmental behaviours of farmers were mediated through voluntary adoption of government and industry sponsored EMSs, often with financial incentives and other support. Findings from the study were that adoption of EMS practices with sufficient public benefits is unlikely to occur at sufficient scale for significant environmental impact. Farmers more readily adopted practices which were financially beneficial than those which had a positive environmental impact. Although the focus on voluntary market-based instrument (MBI) type programs is popular in western countries, enforcing regulation is an important, but usually politically unpopular, component of land use policy. The comparative advantage of EMSs differed for the industries studied, but overall there were insufficient market drivers for widespread EMS adoption in Australia. Environmental outcomes could be more effectively achieved by directly funding land management practices which have highest public net benefits. Having a clear and unambiguous management objective for a particular land management policy is more likely to achieve outcomes than having multiple objectives as occurs in a number of international programs currently.