Evaluation Of Best Management Practices Research Articles

Evaluation of best management practices for mitigating harmful algal blooms risk in an agricultural lake basin using a watershed model integrated with Bayesian Network approach

Lake eutrophication caused by nitrogen and phosphorus has led to frequent harmful algal blooms (HABs), especially under the unknown challenges of climate change, which have seriously damaged human life and property. In this study, a coupled SWAT-Bayesian Network (SWAT-BN) model framework was constructed to elucidate the mechanisms between non-point source nitrogen pollution in agricultural lake watersheds and algal activities. A typical agricultural shallow lake basin, the Taihu Basin (TB), China, was chosen in this study, aiming to investigate the effectiveness of best management practices (BMPs) in controlling HABs risks in TB. By modeling total nitrogen concentration of Taihu Lake from 2007 to 2022 with four BMPs (filter strips, grassed waterway, fertilizer application reduction and no-till agriculture), the results indicated that fertilizer application reduction proved to be the most effective BMP with 0.130 of Harmful Algal Blooms Probability Reduction (HABs-PR) when reducing 40% of fertilizer, followed by filter strips with 0.01 of HABs-PR when 4815ha of filter strips were conducted, while grassed waterway and no-till agriculture showed no significant effect on preventing HABs. Furthermore, the combined practice between 40% fertilizer application reduction and 4815ha filter strips construction showed synergistic effects with HABs-PR increasing to 0.171. Precipitation and temperature data were distorted to model scenarios of extreme events. As a result, the combined approach outperformed any single BMP in terms of robustness under extreme climates. This research provides a watershed-level perspective on HABs risks mitigation and highlights the strategies to address HABs under the influence of climate change.

New paradigm for watershed model development by coupling machine learning algorithm and mechanistic model

The development of watershed models faces double pressure of data requirements and physical interpretation. The simulation of nonpoint source (NPS) pollution is an important application of watershed model, and the best management practices (BMPs) have attracted wide attention as the main control approach of NPS pollution. In this study, a new paradigm was proposed based on the integration of data-driven and mechanistic methods, taking BMP evaluation as an example. Specifically, comprehensive databases were constructed for filter and retention BMPs by collecting, classifying and analyzing published data. Twelve machine learning algorithms were employed for regression analysis between BMPs efficiency and their influencing factors, while the constructed equations were coupled with physical-based models. A case study was performed in a typical catchment of Chaohu Lake Watershed, China. The results demonstrated total interception area, soil type, and vegetation biomass had significant impacts on BMPs performances, while the multilayer perceptron regression (MLPR), K nearest neighbor regression (KNRD), and extremely randomized tree (ETR) methods had the best performances of nutrients removal. The study generated over ten thousand datasets using mechanistic processes, resulting in more efficient and interpretable BMPs evaluator. Compare to traditional methods, this new paradigm has shown advantages in the model application at the watershed scale, enhancing the BMPs evaluator with a higher level of interpretability by coupling the approach with mechanistic models.

Evaluation of best management practices (BMPS) and their impact on environmental flow through SWAT+ model

Evaluation of best management practices (BMPS) and their impact on environmental flow through SWAT+ model

Evaluation of BMPs in Flatland Watershed with Pumped Outlet

The effectiveness of existing and potential best management practices (BMPs) to cropped lands in the Jeannette Creek watershed (Thames River basin, Ontario, Canada) in reducing P loads at its pumped outlets was assessed using the Soil and Water Assessment Tool (SWAT). Existing BMPs consisted of banded, incorporated, and variable phosphorus (P)-rate application, conservation tillage, cover crops, and vegetative buffer strips. Potential BMPs consisted of banded P application, no-till, and a cover crop following winter wheat. Two separately delineated sub-watersheds, J1 and J2, characterized by a flat topography and distinct pumped outlets, were selected for analysis. Despite challenges in delineation, the SWAT model was successfully set up to assess the impact of BMPs in reducing P loads in these sub-watersheds. Each BMP was systematically removed, and the resulting simulated P loads were compared with the baseline scenario. Compared to cover crops or vegetative buffer strips, the implementation of conservation tillage and no-till, along with altering the mode of P application, offered superior effectiveness in reducing the P load. On average, the annual reduction in total P (Ptot) loads under existing BMPs was 9.2% in J1 and 11.3% in J2, whereas, under potential BMPs, this reduction exceeded 60% in both watersheds.

Evaluation of best management practices to reduce sediment yield in the upper Gilo watershed, Baro akobo basin, Ethiopia using SWAT

The increasing sediment yield in the watershed is caused by natural and human activities, which significantly shifts the hydro-meteorological in the watershed. The Modified Universal Soil Loss Equation (MUSLE) equation in the Soil and Water Assessment Tool (SWAT) was used to estimate sediment yields for each hydrological response unit (HRU) based on peak runoff, daily runoff volume, area of hydrological response unit, and other estimated and default hydrological model parameters. The amount of sediment yield from each HRU is then summed to give the total soil erosion for the watershed.The spatio-temporal variations of sediment yield in the Upper Gilo watershed was simulated to identify the hotspot area and select the effective management practices (BMPs) for reducing significant problems. Model calibration and validation were carried out using sediment yield data from 1990 to 2004 and 2005 to 2014. The results indicated that the watershed total sediment yield is 1021.8 tonnes/yr. Furthermore, 17 sub-basins (37.8% of total watershed area) are severely threatened by high soil erosion. According to the simulation results, the filter strips, terraces, and contours reduced the watershed sediment yield by up to 53.2%, 45.4%, and 48%. Overall, the selected BMPs are highly effective in reducing sediment yield in watershed-prone areas.

Simulation of sediment yield and evaluation of best management practices in Azuari watershed, Upper Blue Nile Basin

Abstract This study was conducted to simulate the sediment yield and evaluate best management practices (BMPs) for sediment control in the Azuari watershed, Upper Blue Nile basin, Ethiopia using the Soil and Water Assessment Tool (SWAT) model. As inputs for the model, 30 years (1991–2020) of daily values of meteorological data were used. For model simulation, daily stream flow and sediment data were collected for the periods from 1988 to 2012. The study area was delineated into 19 subwatersheds and the sediment yield was estimated in each subwatershed using the modified universal soil loss equation. The average simulated sediment yield in the watershed was found to be 10.81 t/ha/yr. Six subwatersheds were identified to have high to severe sediment yields and are considered hotspot areas which require prior mitigation measures to control sediment. Four soil and conservation measures were evaluated in SWAT as BMPs namely filter strip, terracing, strip cropping, and contouring. Filter strip was found to reduce sediment by 35.61%, terracing by 20.44%, strip cropping by 44.12%, and contouring by 43.6%. Thus, the implementation of strip cropping resulted in maximum sediment yield reduction. The findings of the study would help to make informed decisions on best watershed management strategies.

Sediment Yield Modeling and Evaluation of Best Management Practices Using the SWAT Model of the Daketa Watershed, Ethiopia

Sediment Yield Modeling and Evaluation of Best Management Practices Using the SWAT Model of the Daketa Watershed, Ethiopia

Evaluation of Best Management Practices for non-point source pollution based on the SWAT model in the Hanjiang River Basin, China

Abstract Taking the Hanjiang River Basin with the Ankang hydrological station as the control section and as the study area, the Soil and Water Assessment Tool (SWAT) model was used to identify the spatial and temporal distribution of non-point source (NPS) pollution and determine the critical source areas (CSA). We set up 11 Best Management Practices (BMPs) in the CSA and evaluated their environmental and comprehensive benefits. The results showed that TN and TP loads in flood season were significantly higher than that in the non-flood season. The distribution of loss intensity of TN and TP load has a strong correlation with runoff and sediment erosion intensity, respectively. Among the eight individual BMPs, the reduction rates of stubble coverage, grassed waterway and returning farmland to forest land were relatively high, and the comprehensive attribute value Z of stubble coverage was the highest. Among the three combined BMPs, the reduction rate of ‘stubble coverage + grassed waterway + returning farmland to forest land (>25°)’ was the highest and the Z value was the largest. Overall, the BMPs such as stubble coverage, grassed waterway, and returning farmland to forest land can be adopted alternately to control NPS pollution in the Hanjiang River Basin.

Prioritization of Sub-Watersheds to Sediment Yield and Evaluation of Best Management Practices in Highland Ethiopia, Finchaa Catchment

Excessive soil loss and sediment yield in the highlands of Ethiopia are the primary factors that accelerate the decline of land productivity, water resources, operation and function of existing water infrastructure, as well as soil and water management practices. This study was conducted at Finchaa catchment in the Upper Blue Nile basin of Ethiopia to estimate the rate of soil erosion and sediment loss and prioritize the most sensitive sub-watersheds using the Soil and Water Assessment Tool (SWAT) model. The SWAT model was calibrated and validated using the observed streamflow and sediment data. The average annual sediment yield (SY) in Finchaa catchment for the period 1990–2015 was 36.47 ton ha−1 yr−1 with the annual yield varying from negligible to about 107.2 ton ha−1 yr−1. Five sub-basins which account for about 24.83% of the area were predicted to suffer severely from soil erosion risks, with SY in excess of 50 ton ha−1 yr−1. Only 15.05% of the area within the tolerable rate of loss (below 11 ton ha−1yr−1) was considered as the least prioritized areas for maintenance of crop production. Despite the reasonable reduction of sediment yields by the management scenarios, the reduction by contour farming, slope terracing, zero free grazing and reforestation were still above the tolerable soil loss. Vegetative contour strips and soil bund were significant in reducing SY below the tolerable soil loss, which is equivalent to 63.9% and 64.8% reduction, respectively. In general, effective and sustainable soil erosion management requires not only prioritizations of the erosion hotspots but also prioritizations of the most effective management practices. We believe that the results provided new and updated insights that enable a proactive approach to preserve the soil and reduce land degradation risks that could allow resource regeneration.

A Soil Water Assessment Tool (SWAT) Modeling Approach to Prioritize Soil Conservation Management in River Basin Critical Areas Coupled With Future Climate Scenario Analysis

About 44% of the Indian landmass experiences the adverse impact of land degradation. This loss of sediments caused by soil erosion reduces the water quality of local water bodies and decreases agricultural land productivity. Therefore, decision-makers must formulate policies and management practices for sustainable management of basins that are cost-effective and environment friendly. Application of the best management practices (BMPs) to properly manage river basins is difficult and time-consuming. Its implication under various climate change scenarios makes it more complicated but necessary to achieve sustainable development. In this study, the soil and water assessment tool (SWAT) model was employed to prioritize the Tons river basin’s critical areas in the central Indian states coupled with future climate scenario analysis (2030–2050) using Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios. The SWAT model was calibrated and validated for simulation of streamflow and sediment yield for daily and monthly scales using the sequential uncertainty fitting (SUFI-2) technique. The values of coefficient of determination ( R2), Nash–Sutcliffe efficiency (NSE), percent bias (PBIAS), and root mean square error (RMSE)-observations standard deviation ratio (RSR) were .71, .70, −8.3, and .54, respectively during the calibration period, whereas for validation the values were .72, .71, −3.9, and .56, respectively. SWAT model underestimated the discharge during calibration and overestimated the discharge during validation. Model simulations for sediment load exhibited a similar trend as streamflow simulation, where higher values are reported during August and September. The average annual sediment yield of the basin for the baseline period was 6.85 Mg ha−1, which might increase to 8.66 Mg ha−1 and 8.79 Mg ha−1 in the future years 2031–2050 and 2081–2099, respectively. The BMPs such as recharge structure, contour farming, filter strip 3 and 6 m, porous gully plugs, zero tillage, and conservation tillage operations have been considered to evaluate the soil and water conservation measures. Recharge structure appeared to be the most effective measure with a maximum reduction of sediment by 38.98% during the baseline period, and a 37.15% reduction in the future scenario. Sub-watersheds, namely SW-8, SW-10, SW-12, SW-13, SW-14, SW-17, SW-19, SW-21, SW-22, and SW-23, fall under the high category and are thus considered a critical prone area for the implementation and evaluation of BMPs. Compared to the baseline period, the effectiveness of BMPs is slightly decreasing in the 2040s, increasing in the 2070s and decreasing in the 2090s. Recharge structure and filter strip 6 m have been found to nullify the high soil erosion class completely. Overall, SWAT model simulations under the RCP 8.5 scenarios were observed to be reliable and can be adopted to identify critical areas for river basins having similar climatic and geographical conditions.

Evaluation of Best Management Practices by using Hydrologic and Hydraulic Modeling

The urban areas within India are increasing rapidly and resulting into a major land use change. This gives rise to changed runoff patterns which are high in peak flows and can result into flash floods. Flooding is considered as the most costly type of natural disaster in terms of human casualties and damages. An attempt has been made to study the various aspects of the flooding in complex urban environment. Conventional flood mitigation strategies were studied along with the sustainable ways of dealing with runoff in urban areas. Resilient measures have also been studied. A case study in the City of Mumbai Mithi river sub catchment is considered for this thesis. The catchment is divided into number of basin and it is modeled by using SWMM based on different land use in the catchment. A number of features within the catchment were studied and their suitability with respect to Best Management Practices management is checked. Impact of the proposed systems was checked on the peak flow and runoff volume at various locations within the catchment. It was found that the conventional solutions work out to be very costly. Amongst the BMP’S solutions, rain garden system implementation appeared promising with reuse benefit along with runoff control. To achieve a better level of service and also deal with extreme events, a new way of design would need to be considered, which would involve assessing risks and use of sustainable and resilient measures.

Identification of critical areas and evaluation of best management practices using SWAT for sustainable watershed management

Identification of critical erosion-prone areas and selection of best management practices (BMPs) for watersheds are necessary to control their degradation by reducing sediment yields. The current research assesses and proposes a combination of potential BMPs for the Baitarani catchment in India using the Soil and Water Assessment Tool (SWAT). After the successful calibration and validation of the SWAT model developed for this catchment, the model was applied to evaluate the efficacy of eight agricultural and structural management practices and their combinations (three scenarios) for controlling sediment yields at watershed and sub-watershed levels as well as to assess the impacts of combined BMPs on water balance components. A combination of BMPs was found more effective in reducing sediment yields than individual BMPs. Comparative evaluation revealed that structural BMPs (0.66–70%) are better than agricultural BMPs (2–7%) in minimizing sediment yields at watershed level. The costly measures like grade and streambank stabilization structures can reduce the sediment yield up to 70% at the watershed level. The modeling results of the impacts of different combinations of BMPs (three scenarios) indicated that if all the eight BMPs are implemented, the reduction of sediment yields is increased by 76% and 80% at sub-watershed and watershed levels, respectively compared to the Base Scenario. Based on funds availability, a suitable combination of BMPs can be adopted by the concerned decision-makers to effectively reduce sediment yields in the study area. Further, the simulation results of BMPs impacts on water balance components revealed that the annual average surface runoff reduces by 4–14% in the three scenarios, while aquifer recharge (6.8–8.7%), baseflow (8–10.5%), and percolation (1.2–3.9%) increase due to implementation of BMPs. Overall, the findings of this study are very useful for ensuring sustainable management of land and other resources at a catchment scale.

Evaluation of best management practices with greenhouse gas benefits for salt-affected paddy soils in South Asia

Anthropogenic climate change has caused increased soil salinity in South Asia due to saltwater intrusion caused by sea level rise, input of fertilizers with high salt index, and irrigation malpractices, etc. Salinity has a multitude of impacts on plant and soil processes, leading to alterations in gas fluxes and rice productivity. The remedial measures adopted on salt-affected soils to reduce the salinity effect could enhance future climate change if they cause an increase in greenhouse gas (GHG) emissions. This study was conducted to find the best agricultural management practices (BMPs) for salt-affected soils in rice cropping systems (i.e. the major cropping system in Asia) in four South Asian countries (Sri Lanka, India, Bangladesh and Pakistan) considering net GHG emissions and other socioeconomic benefits associated with the adopted measures. The salinity-affected sites were selected based on available information (e.g. agricultural statistics and maps). Site-level measurements on soil parameters and GHG emissions were made in control- and managed plots and farmer surveys were conducted. Although organic amendments ameliorated salinity, it could cause a net increase in carbon dioxide or methane emissions depending on the soil conditions, particularly during the initial stages. This impact could be ameliorated by combining organic amendments with other management practices. In the Indo-Gangetic region, poor soil drainage causing anaerobic conditions favoured nitrous oxide emission under low to medium salinity. Yield losses and emissions in high salinity sites were controlled through organic amendment, irrigation and rice-fallow cropping sequence. The combination of transplanting of rice seedlings, the addition of organic matter, and intermittent irrigated water levels was identified as the BMP for Sri Lankan farmers. The outcome of this project will be used to raise awareness among farmers and policymakers.

Application of the Soil and Water Assessment Tool (SWAT) at Field Scale: Categorizing Methods and Review of Applications

HighlightsThis review study identified five different ways of setting up a SWAT model for field-scale analysis.Model setup for each field-scale modeling method and examples of application are discussed.Benefits and limitations of each method are discussed.Abstract. Although the Soil and Water Assessment Tool (SWAT) has been widely used as a watershed/basin scale model, recently there has been considerable interest in applying it at the field scale, especially for evaluation of best management practices and for building stakeholder confidence. In this study, a thorough review of the literature on field-scale application of SWAT was conducted. It was determined that there is more than one way of setting up a field-scale SWAT model depending on the spatial scale of the research as well as the research question to be answered. This article provides a detailed review of the methods used for field-scale SWAT modeling along with a summary of applications. This article also discusses the limitations and advantages of each method along with future research needs. The overarching goal of this article is to provide a valuable and time-conserving resource for future researchers interested in field-scale SWAT modeling. Keywords: Arc-SWAT, Field level, Field-scale resolution, Field-scale SWAT, SWAT.

Deep learning for compute-efficient modeling of BMP impacts on stream- aquifer exchange and water law compliance in an irrigated river basin

Inefficient irrigation practices in the alluvial Lower Arkansas River Basin (LARB) of Colorado are contributing to salinization, waterlogging, reduced crop yields, and harmful concentrations of pollutants in the stream-aquifer system. Intensive data collection and modeling efforts in the LARB over the past 20 years have resulted in development of the GIS-based basin-scale decision support system River GeoDSS. Parallel efforts in regional-scale calibration and application of the MODFLOW-SFR2-RT3D-OTIS stream-aquifer system model permit evaluation of best management practices (BMPs) designed to mollify adverse environmental impacts. Since BMP implementation is allowable only if water laws are not violated, a deep learning model is developed to serve as an accurate, compute-efficient surrogate of MODFLOW-SFR2 and is imbedded in River GeoDSS for assessing basin-scale impacts of BMP implementations on stream-aquifer exchange and water rights. It is shown that BMPs can be implemented while maintaining reasonable water law compliance with development of a new reservoir storage account.

Evaluation of best management practices for sediment and nutrient loss control using SWAT model

The intensive study of an individual watershed is required to develop effective and efficient watershed management plans. Identification of critical erosion-prone areas of the watershed and implementation of best management practices (BMPs) is necessary to control the watershed degradation by reducing the sediment and nutrient losses. The present study evaluates and recommends the BMPs in an agriculture-based Marol watershed (5092 km2) of India, using a hydrologic model, Soil and Water Assessment Tool (SWAT). After successful calibration and validation, the model simulated daily/monthly discharge and sediment were found satisfactory throughout the simulation period. The model was then applied with a calibrated set of parameters for evaluating the effectiveness of various management practices for sediment and nutrient loss control. Keeping in mind the existing agricultural practices, socio-economic aspects and geography of the study area, the management practices were focused on four crops (Maize, Rice, Soybeans and Ground nut), three fertilization levels (high, medium and low), four tillage treatments (Field cultivator, Conservation tillage, Zero tillage and Mould board plough), and two conservation operations (Contour farming and Filter strips). The simulated annual average sediment yield from the watershed was found to be 12.2 t.ha−1yr−1. The water balance analysis revealed that, the evapo-transpiration is predominant over the watershed (approximately 46.3% of the annual average rainfall). Reduction in sediment yield and nutrient loss was observed with alternate cropping treatments of Groundnut and Soybean, as compared to Paddy and Maize cultivation. Overall, based on simulated results, the field cultivator tillage practice and conservation practices viz., contour farming and filter strips, could be adopted to reduce sediment yield and nutrient losses in the critical sub-watersheds of the study area and in other watersheds with similar hydro-climatic conditions.

Identification of Critical Source Areas (CSAs) and Evaluation of Best Management Practices (BMPs) in Controlling Eutrophication in the Dez River Basin

Best Management Practices (BMPs) are commonly used to control pollution in the river basins. Prioritization of BMPs helps improve the efficiency and effectiveness of pollution reduction, especially in Critical Source Areas (CSAs) that produce the highest pollution loads. Recently, the Dez River in Khuzestan, Iran, has become highly eutrophic from the overuse of fertilizers and pesticides. In this basin, dry and irrigated farming produce 77.34% and 6.3% of the Total Nitrogen (TN) load, and 83.56% and 4.3% of the Total Phosphorus (TP) load, respectively. In addition, residential, pasture, and forest land uses together account for 16.36% of the TN and 12.14% of the TP load in this area. The Soil and Water Assessment Tool (SWAT) was implemented to model the Dez River basin and evaluate the applicability of several BMPs, including point source elimination, filter strips, livestock grazing, and river channel management, in reducing the entry of pollution loads to the river. Sensitivity analysis and calibration/validation of the model was performed using the SUFI-2 algorithm in the SWAT Calibration Uncertainties Program (SWAT-CUP). The CSAs were identified using individual (sediment, TN, TP) and combined indices, based on the amount of pollution produced. Among the BMPs implemented, the 10 m filter strip was most effective in reducing TN load (42.61%), and TP load (39.57%).

Assessment of water quality and evaluation of best management practices in a small agricultural watershed adjacent to Coral Reef area in Japan

The predominantly agricultural coastal watershed located in tropical–subtropical Island has served as a pathway for nonpoint source (NPS) pollution loading into the downstream coastal ecosystems. The present study aims to assess watershed hydrology and water quality by applying a watershed model to long–term high–resolution monitoring data, and to evaluate the reduction of nonpoint–source pollution by implementing best management practices (BMPs) in a small agricultural watershed located in southwestern Japan. The Soil Water and Assessment Tool (SWAT) was coupled to a groundwater model (MODFLOW) and applied to simulate stream flow, sediment, and nutrients discharges. The results revealed that the model successfully predicted hourly stream flow, sediment, and nutrients concentrations in the study watershed and that the model could be further used to evaluate BMP scenarios. This is the first attempt to quantify the impacts of multiple agricultural mitigation measures on long-term water quality for sediment, nitrate, and phosphate at an hourly resolution. From the model results, the land cover conversion and mulching scenarios achieved a significant reduction in sediment, followed by the cover crop, alternative tillage, and filter strip scenarios. Moreover, conversion of all summer sugarcane to pasture farmland and fertilizer control scenarios gave the superior reduction in nitrate load, while other scenarios were minimally effective. On the other hand, most of the scenarios significantly achieved the reduction of phosphate load. The results further indicated that the BMPs recommended in this study are appropriately combined scenarios, which achieved the significant reduction in all NPS loads. Although this study revealed some effective mitigation measures to improve the water quality in the study watershed, actual implementation of correct ones may be practically challenging unless other environmental and economic risks (e.g. the increase of other pollutants and reduction in agricultural productivity) are also taken into considerations.

Design and development of a web-based interface for the Agricultural Policy Environmental eXtender (APEX) model

The diffuse nature of nonpoint source (NPS) pollution as well as that of the effectiveness of best management practices (BMP) to control NPS pollution necessitates BMP evaluation at the field scale. In this study, a web interface was developed for application of the Agricultural Policy Environmental eXtender (APEX) model at the field scale. The interface contains background databases for field location, soil, agricultural management and climate across the contiguous United States. Users can specify properties to run the model for an individual field and compare the results under various land management and conservation practice choices. A case study was conducted to demonstrate the capability of the web interface for simulating various land management scenarios. This tool can help provide on-site information for NPS pollution management related policies and serve as a communication tool among scientists, engineers, and stakeholders.

An Open Source GIS‐Based Decision Support System for Watershed Evaluation of Best Management Practices

AbstractEconomic costs, water quantity/quality benefits, and cost effectiveness of agricultural best management practices (BMPs) at a watershed scale are increasingly examined using integrated economic‐hydrologic models. However, these models are typically complex and not user‐friendly for examining the effects of various BMP scenarios. In this study, an open source geographic information system (GIS)‐based decision support system (DSS), named the watershed evaluation of BMPs (WEBs), was developed for creating BMP scenarios and simulating economic costs and water quantity/quality benefits at farm field, subbasin, and watershed scales. This DSS or WEBs interface integrated a farm economic model, the Soil and Water Assessment Tool (SWAT), and an optimization model within Whitebox Geospatial Analysis Tools (GAT), an open source GIS software. The DSS was applied to the 14.3‐km2 Gully Creek watershed, a coastal watershed in southern Ontario, Canada that drains directly into Lake Huron. BMPs that were evaluated included conservation tillage, nutrient management, cover crop, and water and sediment control basins. In addition to assessing economic costs, water quantity/quality benefits, and cost effectiveness of BMPs, the DSS can be also used to examine prioritized BMP types/locations and corresponding economic and water quantity/quality tradeoffs in the study watershed based on environmental targets or budget constraints. Further developments of the DSS including interface transfer to other watersheds are also discussed. 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.