Types Of Best Management Practices Research Articles

Efficiency analysis of best management practices under climate change conditions in the So-okcheon watershed, South Korea

Best management practices (BMPs) are widely applied to address water quality degradation issues attributed to non-point source pollutants. The objective of this study was to assess the efficiency of two types of BMPs, vegetation filter strips (VFS) and wetlands, in reducing total nitrogen (TN) and total phosphorus (TP) in a watershed, and to investigate whether the efficiency of the two BMPs is maintained under future climate scenarios by employing the Soil and Water Assessment Tool (SWAT). A set of parameters was calibrated using the SWAT Calibration and Uncertainty Program (SWAT-CUP) to ensure acceptable simulation results. Three BMP scenarios were developed by applying VFS and wetlands individually and in combination. Projected climate data from 18 global circulation models under Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) were used to depict climate change conditions. VFS demonstrated 18.2% and 22.9% greater reduction efficiency for TN and TP, respectively, relative to wetlands. When the two BMPs were simultaneously applied, the reduction efficiency was even greater than that of single-BMP implementation (by 7.4% for TN and 6.8% for TP compared to VFS alone and by 25.5% for TN and 29.7% for TP compared to wetlands alone). To assess the effect of climate change, the model simulated results for the period of 2021–2,100. The differences in efficiency between the combined BMP scenario and the individual BMPs increased with greater intensity of climate change, especially in the distant future. Therefore, this study supports the effectiveness of nutrient pollution control by applying multiple BMPs rather than by applying individual BMPs. Furthermore, this research underscores the adaptability and reliability of natural-based solutions in mitigating non-point source pollution in a changing climate, which is essential for effective ecological restoration in complex urban-agricultural landscapes. The study provides valuable insights for watershed managers and policymakers seeking effective strategies to combat nutrient pollution in the face of a changing climate within the unique landscape of South Korea.

Optimizing the Implementation Plan of Watershed Best Management Practices With Time‐Varying Effectiveness Under Stepwise Investment

AbstractOptimizing the spatial configuration of diverse best management practices (BMPs) can provide valuable decision‐making support for comprehensive watershed management. Most existing methods focus on selecting BMP types and locations but neglect their implementation time or order in management scenarios, which are often investment‐restricted. This study proposes a new simulation‐optimization framework for determining the implementation plan of BMPs by using the net present value to calculate the economic costs of BMP scenarios and the time‐varying effectiveness of BMPs to evaluate the environmental effectiveness of BMP scenarios. The proposed framework was implemented based on a Spatially Explicit Integrated Modeling System and demonstrated in an agricultural watershed case study. This case study optimized the implementation time of four erosion control BMPs in a specific spatial configuration scenario under a 5‐year stepwise investment process. The proposed method could effectively provide more feasible BMP scenarios with a lower overall investment burden with only a slight loss of environmental effectiveness. Time‐varying BMP effectiveness data should be gathered and incorporated into watershed modeling and scenario optimization to better depict the environmental improvement effects of BMPs over time. The proposed framework was sufficiently flexible to be applied to other technical implementations and extensible to more actual application cases with sufficient BMP data. Overall, this study demonstrated the basic idea of extending the spatial optimization of BMPs to a spatiotemporal level by considering stepwise investment, emphasizing the value of integrating physical geographic processes and anthropogenic influences.

Stormwater Best Management Practices: Experimental Evaluation of Chemical Cocktails Mobilized by Freshwater Salinization Syndrome.

Freshwater Salinization Syndrome (FSS) refers to the suite of physical, biological, and chemical impacts of salt ions on the degradation of natural, engineered, and social systems. Impacts of FSS on mobilization of chemical cocktails has been documented in streams and groundwater, but little research has focused on the effects of FSS on stormwater best management practices (BMPs) such as: constructed wetlands, bioswales, ponds, and bioretention. However emerging research suggests that stormwater BMPs may be both sources and sinks of contaminants, shifting seasonally with road salt applications. We conducted lab experiments to investigate this premise; replicate water and soil samples were collected from four distinct stormwater feature types (bioretention, bioswale, constructed wetlands and retention ponds) and were used in salt incubation experiments conducted under six different salinities with three different salts (NaCl, CaCl2, and MgCl2). Increased salt concentrations had profound effects on major and trace element mobilization, with all three salts showing significant positive relationships across nearly all elements analyzed. Across all sites, mean salt retention was 34%, 28%, and 26% for Na+, Mg2+ and Ca2+ respectively, and there were significant differences among stormwater BMPs. Salt type showed preferential mobilization of certain elements. NaCl mobilized Cu, a potent toxicant to aquatic biota, at rates over an order of magnitude greater than both CaCl2 and MgCl2. Stormwater BMP type also had a significant effect on elemental mobilization, with ponds mobilizing significantly more Mn than other sites. However, salt concentration and salt type consistently had significant effects on mean concentrations of elements mobilized across all stormwater BMPs (p<0.05), suggesting that processes such as ion exchange mobilize metals mobilize metals and salt ions regardless of BMP type. Our results suggest that decisions regarding the amounts and types of salts used as deicers can have significant effects on reducing contaminant mobilization to freshwater ecosystems.

Effects of Regional Climate and BMP Type on Stormwater Nutrient Concentrations in BMPs: A Meta-Analysis.

Nutrient treatment performance of stormwater best management practices (BMPs) is highly variable. Improved nutrient management with BMPs requires a better understanding of factors that influence stormwater BMP treatment processes. We conducted a meta-analysis of vegetated BMPs in the International Stormwater BMP Database and compared influent and effluent nitrogen and phosphorus concentrations to quantify the BMP effect on nutrient management across climates. BMP effect on nutrient concentration change was compared between vegetated BMPs in wet and dry climates. We examined paired dissolved inorganic nitrogen (DIN), total nitrogen (TN), dissolved inorganic phosphorus (DIP), total phosphorus (TP), and combinations of these analytes as dissolved inorganic ratios and N:P ratios. Meta-analysis with subgroup analysis was used to determine differences between wet and dry climates and among vegetated BMP types. We found that across both wet and dry climates, BMPs leach DIP and TP, increase the fraction of dissolved inorganic P (DIP:TP), and decrease dissolved N:P ratios. Dry-climate BMPs leach DIP and TP more consistently and at a higher magnitude than wet-climate BMPs, and bioretention leaches more DIP than grass strips and swales. These findings generally align with biogeochemical cycling, differences in influent chemistry, and BMP design types and goals.

Synergetic Integration of SWAT and Multi-Objective Optimization Algorithms for Evaluating Efficiencies of Agricultural Best Management Practices to Improve Water Quality

Nitrate is one of the most complicated forms of nitrogen found in aquatic surface systems, which results in the eutrophication of the water. During the last few decades, due to agriculture and animal husbandry activities, as well as urban development, a significant amount of pollutants have accumulated in the Jajrood river in northern Iran. In this research, we simulated nitrate load in a rural watershed to assess the outlet stream’s qualitative status and evaluate the influence of best management practices (BMPs). To accomplish this, we prepared, processed, and integrated different datasets, including land-use land-cover (LULC) maps, physiographic layers, and hydrological and agricultural datasets. In the modeling section, the Soil and Water Assessment Tool (SWAT) was used to simulate nitrate load over 28 years (1991–2019). Additionally, the multi-objective optimization algorithm (MOPSO) was implemented to reduce the intended objective functions, including the number of best management practices and the nitrate concentration considering different scenarios. The calibration of the basin’s discharge and nitrate indicated that the SWAT model performed well in simulating the catchment’s streamflow (R2 = 0.71) and nitrate (R2 = 0.69). The recommended BMPs for reducing nutrient discharge from the basin are using vegetated filter strips on river banks and fertilizer reduction in agricultural activities. According to the results from this investigation, the integrated model demonstrates a strong ability to optimally determine the type, size, and location of BMPs in the watershed as long as the reduction criteria change. In a situation of water scarcity, the studies reported here could provide useful information for policymakers and planners to define water conservation policies and strategies.

Optimization of best management practices to control runoff water quality in an urban watershed using a novel framework of embedding- response surface model

Best Management Practices (BMPs) are measures implemented to reduce urban runoff volume and pollution load. Determination of a cost-effective selection of BMP combinations is a challenge. In this study, an optimization model was developed to determine the optimal number, location, and type of BMPs with minimum cost and pollution load in the Majidieh catchment in Tehran, Iran. A novel framework was proposed combining the embedding technique with Response Surface Method (RSM) called “Em-RSM” in the form of a simulation–optimization (S/O) model. First, the storm water management model)SWMM(as the simulation model was linearized, and the linear programming results were used as the initial population of the genetic algorithm (GA). Then, the linearized model along with the SWMM model were alternatively used as the fitness function in the GA evolution process to increase the model run speed and results' accuracy. The results showed that the permeable pavement and infiltration trench were more effective than other BMPs because of the physical and local characteristics of the study area. It was demonstrated that the proposed model makes a considerable reduction in the model run time with acceptable accuracy in obtaining the compromise solution of the Pareto front. The proposed framework proved its effectiveness in the solution of GA-based S/O problems. It can also be applied in other case studies or optimization problems by replacing and simplifying the behavior of the simulation model in the optimization procedure.

The Presence of Denitrifiers In Bacterial Communities of Urban Stormwater Best Management Practices (BMPs)

Stormwater best management practices (BMPs) are engineered structures that attempt to mitigate the impacts of stormwater, which can include nitrogen inputs from the surrounding drainage area. The goal of this study was to assess bacterial community composition in different types of stormwater BMP soils to establish whether a particular BMP type harbors more denitrification potential. Soil sampling took place over the summer of 2015 following precipitation events. Soils were sampled from four bioretention facilities, four dry ponds, four surface sand filters, and one dry swale. 16S rRNA gene analysis of extracted DNA and RNA amplicons indicated high bacterial diversity in the soils of all BMP types sampled. An abundance of denitrifiers was also indicated in the extracted DNA using presence/absence of nirS, nirK, and nosZ denitrification genes. BMP soil bacterial communities were impacted by the surrounding soil physiochemistry. Based on the identification of a metabolically-active community of denitrifiers, this study has indicated that denitrification could potentially occur under appropriate conditions in all types of BMP sampled, including surface sand filters that are often viewed as providing low potential for denitrification. The carbon content of incoming stormwater could be providing bacterial communities with denitrification conditions. The findings of this study are especially relevant for land managers in watersheds with legacy nitrogen from former agricultural land use.

A Site-Scale Tool for Performance-Based Design of Stormwater Best Management Practices

The objective of this research is to develop a module for the design of best management practices based on percent pollutant removal. The module is a part of the site-scale integrated decision support tool (i-DSTss) that was developed for stormwater management. The current i-DSTss tool allows for the design of best management practices based on flow reduction. The new water quality module extends the capability of the i-DSTss tool by adding new procedures for the design of best management practices based on treatment performance. The water quality module can be used to assess the treatment of colloid/total suspended solid and dissolved pollutants. We classify best management practices into storage-based (e.g., pond) and infiltration-based (e.g., bioretention and permeable pavement) practices for design purposes. Several of the more complex stormwater tools require expertise to build and operate. The i-DSTss and its component modules including the newly added water quality module are built on an accessible platform (Microsoft Excel VBA) and can be operated with a minimum skillset. Predictions from the water quality module were compared with observed data, and the goodness-of-fit was evaluated. For percent total suspended solid removal, both R2 and Nash–Sutcliffe efficiency values were greater than 0.7 and 0.6 for infiltration-based and storage-based best management practices, respectively, demonstrating a good fit for both types of best management practices. For percent total phosphorous and Escherichia. coli removal, R2 and Nash–Sutcliffe efficiency values demonstrated an acceptable fit. To enhance usability of the tool by a broad range of users, the tool is designed to be flexible allowing user interaction through a graphical user interface.

Regionalization of Default Parameters for Urban Stormwater Quality Models

AbstractAccurate parameterization of water quality routines within stormwater models can improve simulation, prediction of system behavior, and lead to more informed decision making. This work recognizes that factors controlling runoff concentrations and treatment in stormwater best management practices (BMPs) vary with region, assumes region is a proxy for these factors, and seeks to improve tool parameterization by (1) identifying a regionalization scheme that best explains variability in national datasets of runoff water quality and BMP performance, (2) generating region‐specific model parameter values, and (3) demonstrating how model output varies when using national vs. regional parameters. Of the four regionalization schemes tested, the National Climatic Data Center’s Regions best explained variance in pollutant runoff concentrations from the National Stormwater Quality Database, accounting for more data variability (1.1%) than the watershed’s land use (0.4%). For BMP performance extracted from the International Stormwater BMP Database, the United States (U.S.) Environmental Protection Agency’s Rain Zones explained the most variance (1.1%), which is one‐fifth of the variance explained by BMP type (5.0%). These results were used to generate regional parameter lookup tables for stormwater quality modeling. Test cases from the 100 most populous cites in the U.S. showed national parameters predicted BMP effluent concentrations that were 15% lower than the regional parameters for five pollutants.

Sediment dynamics and implications for management: State of the science from long‐term research in the Chesapeake Bay watershed, USA

AbstractThis review aims to synthesize the current knowledge of sediment dynamics using insights from long‐term research conducted in the watershed draining to the Chesapeake Bay, the largest estuary in the U.S., to inform management actions to restore the estuary and its watershed. The sediment dynamics of the Chesapeake are typical of many impaired watersheds and estuaries around the world, and this synthesis is intended to be relevant and transferable to other sediment‐impaired systems. The watershed's sediment sources, transport, delivery, and impacts are discussed with implications for effectively implementing best management practices (BMPs) to mitigate sediment issues. This synthesis revealed three key issues to consider when planning actions to reduce sediment loading: Scale, time, and land use. Geology and historical land use generated a template that current land use and climate, in addition to management, are acting upon to control sediment delivery. Important sediment sources in the Chesapeake include the Piedmont physiographic region, urban, and agricultural land use, and streambank erosion of headwater streams, whereas floodplain trapping is important along larger streams and rivers. Implementation of BMPs is widespread and is predicted to lead to decreased sediment loading; however, reworking of legacy sediment stored in stream valleys, with potentially long residence times in storage, can delay and complicate detection of the effects of BMPs on sediment loads. In conclusion, the improved understanding of sediment sources, storage areas, and transport lag times reviewed here can help target choices of BMP types and locations to better manage sediment problems—for both local streams and receiving waters.This article is categorized under: Science of Water &gt; Water Quality Water and Life &gt; Stresses and Pressures on Ecosystems Water and Life &gt; Conservation, Management, and Awareness

Stormwater Management: A Keystone for Sustainable Development

Sustainable development is a major goal of the 21st century, and there are many ways to ensure that one generation’s lifestyle and consumption habits do not comprise those of a future generation. It can be overwhelming to look at the many ways sustainable development can be achieved. In this paper, I focus on sustainable stormwater management practices, called Best Management Practices (BMPs). There are many different types of BMPs, and in this paper, I look at explore several popular options. I also look through several policies that impact sustainable water management and look to possible policy solutions for the future.

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.

Evaluating the performance of conservation practices under climate change scenarios in the Miyun Reservoir Watershed, China

Climate change is one of the major challenges in watershed management systems. Rising air temperatures, increasing precipitation in winter, and decreasing precipitation in summer as well as increases in extreme weather events have increased flooding and droughts and further affected water quality in the Miyun Reservoir Watershed (MRW). This study used the Soil and Water Assessment Tool (SWAT) model with five downscaled general circulation models (GCMs) to quantify the impact of climate change on hydrology, soil erosion, nutrient cycling, and the performance of Best Management Practices (BMPs) at watershed scale, driven by RCPs 2.6, 4.5, and 8.5. Compared with the baseline scenario, the results indicated that climate variability, especially precipitation and temperature, had great effects on surface runoff, sediment yields, and nutrient losses and further significantly affected BMP efficiency, although the magnitudes of change differed among the RCPs. Monthly sediment and nutrient loads increased substantially in all climate change scenarios, especially in flood season, due to the increase in precipitation intensity. Although BMPs were identified to be not appreciably effective in controlling water balance, they were effective in reducing sediment and nutrient losses. Based on this case, a simulation-optimization framework was applied to develop future watershed management strategies with BMP configurations because of their climate adaptation benefits, water improvement targets, and economical cost. The results indicated that the discrepancy among different climate scenarios was reflected by the number and types of BMPs and their spatial distributions, especially structural BMPs. This study suggests that the increasing frequency of rainfall events may decrease the efficiency of BMPs in the MRW, and watershed management should be adjusted according to changing climate in the future.

Site-Scale Integrated Decision Support Tool (i-DSTss) for Stormwater Management

A site-scale integrated decision support tool (i-DSTss) is developed for selection and sizing of stormwater Best Management Practices (BMPs). The tool has several component modules—hydrology, BMP selection, BMP sizing, and life-cycle cost analysis (LCCA)—integrated into a single platform. The hydrology module predicts runoff from small catchment on event and continuous basis using the Green-Ampt and Curve Number methods. The module predicted runoff from a small residential area and a parking lot with R2 value of 0.77 and 0.74, respectively. The BMP selection module recommends a BMP type appropriate for a site based on economic, technical, social and environmental criteria using a multi-criteria optimization approach. The BMP sizing module includes sizing options for green roofs, infiltration-based BMPs, and storage-based BMPs. A mass balance approach is implemented for all types of BMPs. The tool predicted outflow rates from a permeable pavement with R2 value of 0.89. A cost module is included where capital, operation and maintenance, and rehabilitation costs are estimated based on BMP size obtained from the sizing module. The i-DSTss is built on an accessible platform (Microsoft Excel VBA) and can be operated with a basic skillset. The i-DSTss is intended for designers, regulators, and municipalities for quick analysis of scenarios involving interaction among several factors.

Capture of stormwater runoff and pollutants by three types of urban best management practices

Land cover changes associated with urbanization produce hydrological alterations, which often diminish infiltration, leading to increased runoff volumes, peak flows, and greater need for pollution control. A number of urban “green infrastructure” best management practices (BMPs) have been designed to capture and contain stormwater runoff near the source. Although implementation of such practices has slowly increased, lack of evidence about their effectiveness in reducing the quantity and improving the quality of stormwater runoff may still limit the degree to which they are implemented. The objectives of this study were to assess performance of three types of urban stormwater BMPs by measuring their soil characteristics, infiltration rates, runoff reduction, and water quality parameters compared to adjacent contributing areas. Three types of practices—bioretention cells, native landscaping (reconstructed prairie areas), and three-zone vegetated riparian buffers located in Ames and Ankeny, Iowa—were assessed by conducting infiltration tests and collecting soil and water samples. For the biocells in particular, practice surface areas were smaller in relation to their contributing areas than is recommended in current design criteria. On average, the bioretention cells and the buffers9 wooded zones had significantly lower soil bulk densities, higher infiltration rates, and smaller runoff volumes than those of contributing areas. Time-to-runoff was particularly high for bioretention cells. Infiltration characteristics of the native landscapes (reconstructed prairie) and buffer prairie zones we studied were not significantly different from those of the contributing areas. Total extractable hydrocarbon concentrations were elevated in the bioretention cells, while metals such as chromium (Cr) had greater concentrations in the contributing areas. Based on these findings, we recommend careful attention to sizing, particularly for biocells, and suggest routine incorporation of soil amendments (such as compost) to improve the performance of reconstructed prairie areas. Our findings also suggest that more widespread implementation of these source-control measures in retrofit of existing developments and/or in the design of newly urbanizing areas will be effective for reducing stormwater runoff volumes and improving water quality.

New methodology of evaluation of best management practices performances for an agricultural watershed according to the climate change scenarios: A hybrid use of deterministic and decision support models

Climate change is a primary driver that alters water pollution hotspots in watersheds, which complicates the use of Best management practices (BMPs) for diffuse pollution mitigation strategies. The objective of this study is to evaluate future changes in BMPs on total phosphorus (TP) loads to the river system, depending on climate change. Current weather data were collected from 2000 to 2010 and future weather data from 2040 to 2050 were obtained from regional climate model simulations based on Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5 scenarios. This study describes various BMP implementation plans at affordable cost that are adapted to different weather conditions, current (for 2000–2010) and future climate scenarios (for 2040–2050). The Soil and Water Assessment Tool (SWAT), i.e., one of the deterministic models for watershed management, was used to estimate total phosphorus (TP) removal efficiency of various types of BMP at two crop fields (rice paddy and soybean fields) in the Yeongsan River (YR) watershed of Korea. The Non-dominated Sorting Genetic Algorithm II (NSGA-II), i.e., one of the artificial intelligence (AI) models for decision support framework, was applied to obtain allow for trade-off analysis between two conflict objectives, the maximum TP load reduction against implementation costs. The SWAT simulation results showed that the model performance based on the Nash-Sutcliffe efficiency and percent bias was acceptable for simulating three parameters; daily flow discharge, monthly sediment loads, and TP loads in the river. As a result, monthly sediment loads and TP loads increase remarkably under all future climate change scenarios except for July, when a comparable amount of precipitation is recorded during the present and future conditions. New implementation of BMPs, therefore, will be required for future climate change scenarios to achieve 50% TP load reduction in the given watershed condition. Interestingly, parallel terraces which showed good efficiency in reducing TP loads at both fields under the current weather condition cannot be effective any more under the worst-case weather scenario in the future climate. In such a case, detention ponds can be proposed as BMP alternative to parallel terraces. Overall, this study not only demonstrates that watershed management plans using BMPs should be adjusted according to climate change scenarios, but also that the hybrid use of SWAT model and AI can help in refining existing and future BMPs at affordable cost.

Assessing the impact of the MRBI program in a data limited Arkansas watershed using the SWAT model

The USDA Natural Resources Conservation Service (NRCS) developed the Mississippi River Basin Healthy Watersheds Initiative (MRBI) program to improve the health, water quality and wildlife habitat within the Mississippi River Basin. Lake Conway Point Remove (LCPR) watershed was identified as one of the watersheds for the MRBI program implementation. The goal of this paper is to evaluate the effectiveness of the MRBI program in LCPR watershed using a computer simulation model. Seven best management practices (BMPs) (pond, wetland, pond and wetland, cover crops, vegetative filter strips, grassed waterways and forage and biomass planting) were modelled under four placement strategies: random placement in 30% of the watershed, random placement in 30% hydrologic response units (HRUs) of the high priority hydrological unit code (HUCs), placement in the top 30% of the high priority HUCs, and top 30% of the HRUs in the HUCs near the outlet of the watershed. The model was calibrated for flow for the period 1987–2006 and validated for the period 2007–2012. Sediment and nutrients were validated from 2011 to 2012. Out of the BMPs evaluated, grassed waterways proved to be the most effective BMP in reducing sediment and nutrient loads from row crop (soy beans) and pasture fields. Reductions at the watershed outlet ranged 0–1% for flow, 0.28–14% for sediment, 0.3–10% for TP and 0.3–9% for TN. Relatively higher reductions were observed at the subwatershed level, flow reductions ranged 0–51%, sediment reductions −1 to 79%, TP −1 to 65% and TN −0.37 to 66% depending on BMP type, placement scenario, and watershed characteristics. The results from this study provide the data to help prioritize monitoring needs for collecting watershed response data in LCPR and BMP implementation evaluations, which could be used to inform decisions in similar studies.

Optimizing Agricultural Best Management Practices in a Lake Erie Watershed

AbstractImplementing agricultural best management practices (BMPs) is influenced by a balance of desired environmental outcomes, economic feasibility, and stakeholder familiarity, the latter taken to be related to BMP acceptability. To explore this balance, we developed a multi‐objective decision support system for allocating BMP type and placement by coupling the Soil and Water Assessment Tool with a nondominated sorted genetic algorithm that minimizes total phosphorus (TP) yields from agricultural hydrologic response units (HRUs) and costs, while using stakeholder BMP familiarity as a constraint; conventional tillage, no tillage, nutrient management, riparian buffers, and contour cropping were explored. Using constraints representing current conditions, the optimization resulted in 59.6 to 81.0% reduction in agricultural TP yield from HRUs at costs ranging between US $0.8 and US $5.3 million. The constrained optimization tended to select mostly single BMPs or at most two BMPs for a given HRU due to these BMPs having higher acceptability to stakeholders. In contrast, the unconstrained case, representing full familiarity, selected 2‐ and 3‐BMP applications. There was little difference in costs between the constrained and unconstrained cases below an 80% TP yield reduction; however, significant differences were found at larger reductions, supporting the value of stakeholder education and extension efforts. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.

BMP Optimization to Improve the Economic Viability of Farms in the Upper Watershed of Miyun Reservoir, Beijing, China

Best management practices (BMPs) are being implemented to reduce non-point sources pollution in China and worldwide. There are many types of agricultural BMPs, but their effectiveness differs from farm to farm, depending on where they are applied, how they are applied, and how they are impacted by weather. Two farms (village Nan Wayao, VNWY and village Liu Jianfang, VLJF) with differing farm systems (crop-based mixed farm and dairy-based farms) located in the upper watershed of Miyun reservoir, Beijing, China were selected. We used the Integrated Farming System Model (IFSM) based on these two farms information to estimate total phosphorus (TP) and total nitrogen (TN) loss from 2000 to 2014, to identify (1) causes of farm nutrient imbalances, (2) key factors causing the imbalances, and (3) viable BMPs to reduce source and TN runoff at the farm scale. Results indicated that these farms had TP losses ranging from 8.2 to 160 kg/ha/year and TN losses from 73.7 to 1391.6 kg/ha/year. Using IFSM, physical (i.e., soil bulk density, available water content, and soil-P) and economic (i.e., diesel and farm loan interest rates) factors are more influential in determining nutrient loss from VNWY than VLJF. Rainfall patterns had a little effect on nutrient use and loss on the dairy farm in VLJF. Changes in available water content and soil bulk density had greater impact on the return for VNWY than VLJF, while changes in loan interest rates were more influential on VLJF. Maximum reductions in nutrient loss were obtained with implementation of the BMPs conservation tillage, reduced fertilizer and manure applications, buffer strips, and storage of poultry manure.

Simulation of targeted pollutant-mitigation-strategies to reduce nitrate and sediment hotspots in agricultural watershed

About 50% of U.S. water pollution problems are caused by non-point source (NPS) pollution, primarily sediment and nutrients from agricultural areas, despite the widespread implementation of agricultural Best Management Practices (BMPs). However, the effectiveness of implementation strategies and type of BMPs at watershed scale are still not well understood. In this study, the Soil and Water Assessment Tool (SWAT) ecohydrological model was used to assess the effectiveness of pollutant mitigation strategies in the Raccoon River watershed (RRW) in west-central Iowa, USA. We analyzed fourteen management scenarios based on systematic combinations of five strategies: fertilizer/manure management, changing row-crop land to perennial grass, vegetative filter strips, cover crops and shallower tile drainage systems, specifically aimed at reducing nitrate and total suspended sediment yields from hotspot areas in the RRW. Moreover, we assessed implications of climate change on management practices, and the impacts of management practices on water availability, row crop yield, and total agricultural production. Our results indicate that sufficient reduction of nitrate load may require either implementation of multiple management practices (38.5% with current setup) or conversion of extensive areas into perennial grass (up to 49.7%) to meet and maintain the drinking water standard. However, climate change may undermine the effectiveness of management practices, especially late in the 21st century, cutting the reduction by up to 65% for nitrate and more for sediment loads. Further, though our approach is targeted, it resulted in a slight decrease (~5%) in watershed average crop yield and hence an overall reduction in total crop production, mainly due to the conversion of row-crop lands to perennial grass. Such yield reductions could be quite spatially heterogeneously distributed (0 to 40%).