Cost-effective Best Management Practices Research Articles

Farmer adoption-based prompt networking and modeling for targeting optimal agro-conservation practices

Despite the availability of robust agricultural models, the successful on-ground implementation of all Best Management Practices (BMPs) remains elusive due to the lack of consideration for farmers' preferences. This study develops a unique network-based optimization technique coupled with Soil and Water Assessment Tool (SWAT) which delineates combined set of cost-effective BMPs at field-scale based on farmer's conservation identity in Ganges River Basin, India. SWAT was calibrated and validated using 10-year monthly discharge and nitrate data, and the selected BMPs were simulated using sequential uncertainty fitting framework. Farmers belonging to the Shahpur subdistrict were found to have the maximum normalized conservation identity of 90%, whereas the northeastern portion of the watershed contributed a maximum nitrate load of 7.5–9.92 kg/acre to the watershed outlet. An optimized combination of BMPs (riparian buffer-conservation tillage) with an efficiency of 0.28 was obtained through the modified network technique that targeted subbasins of the Morna subdistrict using farmer conservation identities. The results provide valuable guidance for watershed modelers, conservation planners, and researchers in pinpointing regions for targeted farmer training, subsidies, and other initiatives aimed at facilitating prompt field-scale BMP adoption. A flexible feature of the approach is its ability to modify the BMP action plans by replacing even technically feasible, cost-effective combinations based on farmers' preferences.

Strategy for cost-effective BMPs of non-point source pollution in the small agricultural watershed of Poyang Lake: A case study of the Zhuxi River

In recent years, Poyang Lake has been affected by severe agricultural non-point source (NPS) pollution, a global water pollution problem. The most recognized and effective control measure for agricultural NPS pollution is the strategic selection and placement of best management practices (BMPs) for critical source areas (CSAs). The present study employed the Soil and Water Assessment Tool (SWAT) model to identify CSAs and evaluate the effectiveness of different BMPs in reducing agricultural NPS pollutants in the typical sub-watersheds of the Poyang Lake watershed. The model performed well and satisfactorily in simulating the streamflow and sediment yield at the outlet of the Zhuxi River watershed. The results indicated that urbanization-oriented development strategies and the Grain for Green program (returning the grain plots to forestry) had certain effects on the land-use structure. The proportion of cropland in the study area decreased from 61.45% (2010) to 7.48% (2018) in response to the Grain for Green program, which was mainly converted to forest land (58.7%) and settlements (36.8%). Land-use type changes alter the occurrence of runoff and sediment, which further affect the nitrogen (N) and phosphorus (P) loads since sediment load intensity is a key factor affecting the P load intensity. Vegetation buffer strips (VBSs) proved the most effective BMPs for NPS pollutant reduction, and the cost of 5-m VBSs proved the lowest. The effectiveness of each BMP in reducing N/P load ranked as follows: VBS > grassed river channels (GRC) > 20% fertilizer reduction (FR20) > no-tillage (NT) > 10% fertilizer reduction (FR10). All combined BMPs had higher N and P removal efficiencies than the individual measures. We recommend combining FR20 and VBS-5m or NT and VBS-5m, which could achieve nearly 60% pollutant removal. Depending on the site conditions, the choice between FR20+VBS and NT + VBS is flexible for targeted implementation. Our findings may contribute to the effective implementation of BMPs in the Poyang Lake watershed and provide theoretical support and practical guidance for agricultural authorities to perform and direct agricultural NPS pollution prevention and control.

Sustainability of cover cropping practice with changing climate in Illinois

Climate change could adversely impact the best management practices (BMPs) designed to build a sustainable agro-ecological environment. Cover cropping is a conservation practice capable of reducing nitrate-nitrogen (NO3–N) loadings by consuming water and nitrate from the soil. The objective of this study was to investigate how climate change would impact the proven water quality benefits of cereal rye as a winter cover crop (CC) over the climate divisions of Illinois using the DSSAT model. Moreover, this study explores the sustainability of the CC with the changing climate conditions by using five regional climate models (RCMs) projections of two warming scenarios-rcp45 (a medium emission scenario - radiative forcing of 4.5 W/m2) and rcp85 (a high emission scenario - radiative forcing of 8.5 W/m2)). The CC impact simulated in the warming scenarios for the near-term (2021–2040) and the far-term future (2041–2060) were compared with the baseline scenario (2001–2020). Our results conclude that the climate change may negatively impact [average of CC and no CC (NCC)] maize yield (−6.6%) while positively affecting soybean yield (17.6%) and CC biomass (73.0%) by the mid-century. Increased mineralization caused by rising temperature could increase the nitrate loss via tile flow (NLoss) and nitrate leached (NLeached) up to 26.3% and 7.6% on average by the mid-century in Illinois. Increasing CC biomass could reduce the NLoss more considerably in all the scenarios compared to the baselines. Nevertheless, the NLoss level in the CC treatment can increase from the near-term to far-term future and could get closer to the baseline levels in the NCC treatment. These results suggest that CC alone may not address nitrate loss goals via subsurface drainage (caused by increasing N mineralization) in future. Therefore, more robust and cost-effective BMPs are needed to aid the CC benefits in preventing nutrient loss from the agricultural fields.

Effectivity and Efficiency of Best Management Practices Based on a Survey and SWAPP Model of the Xiangxi River Basin

A questionnaire survey was conducted among farmers in the Xiangxi River Basin to investigate the local livestock situation and the farmers’ understanding of and attitude towards pollution. The results showed that local farmers lacked environmental awareness and few livestock and poultry pollution treatment measures had been implemented. However, once farmers understood that livestock pollution would greatly influence their lives and interests, they would act to prevent Agricultural non–point source (ANPS) pollution. The farmers’ education level and satisfaction with the environment were the main factors affecting their awareness regarding ANPS pollution. The “Comprehensive Environmental Optimization Tool SWAT–APEX Interface” model (SWAPP) was used to simulate the reduction of ANPS by different best management practices (BMPs) and the construction cost was calculated. The results showed that compound bedding and piping systems and ponds were the most effective and economic measures for reducing ANPS pollution. Spatially, implementing BMPs in the upstream region was better for improving water quality. The nitrate reduction rate in upstream sub–basins reached 90%, which is 30% larger than that in downstream sub–basins with combined bedding and piping systems. Combining the farmers’ awareness of and engagement in livestock pollution with cost–effective BMPs can improve the BMPs’ effectivity and efficiency.

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.

Valuing water quality benefits from adopting best management practices: A spatial approach.

We developed a GIS-based tool that values, in a spatially explicit way, the ecosystem services generated by water quality improvements resulting from adoption of agricultural best management practices (BMPs). The tool is calibrated for watersheds in the Chesapeake Bay drainage and includes the benefits from water quality improvements within targeted watersheds, water quality improvements downstream from targeted watersheds, and reductions in pollutant loadings to Chesapeake Bay. The tool is used to investigate specific BMP scenarios adopted within specific watersheds. The results show that (i) BMP adoption generates large positive net benefits to society, with benefit/cost ratios ranging from 22 to 276; (ii) by selecting cost effective BMPs and placing them in the most appropriate places, the cost of meeting pollutant reduction targets would be reduced by 34-71%; and (iii) net benefits from BMP adoption are higher when they are implemented close to or upstream from population centers.

Multi-Objective Optimization for Selecting and Siting the Cost-Effective BMPs by Coupling Revised GWLF Model and NSGAII Algorithm

Best management practices (BMPs) are an effective way to control water pollution. However, identification of the optimal distribution and cost-effect of BMPs provides a great challenge for watershed policy makers. In this paper, a semi-distributed, low-data, and robust watershed model, the Revised Generalized Watershed Loading Function (RGWLF), is improved by adding the pollutant attenuation process in the river channel and a bank filter strips reduction function. Three types of pollution control measures—point source wastewater treatment, bank filter strips, and converting farmland to forest—are considered, and the cost of each measure is determined. Furthermore, the RGWLF watershed model is coupled with a widely recognized multi-objective optimization algorithm, the non-dominated sorting genetic algorithm II (NSGAII), the combination of which is applied in the Luanhe watershed to search for spatial BMPs for dissolved nitrogen (DisN). Fifty scenarios were finally selected from numerous possibilities and the results indicate that, at a minimum cost of 9.09 × 107 yuan, the DisN load is 3.1 × 107 kg and, at a maximum cost of 1.77 × 108 yuan, the total dissolved nitrogen load is 1.31 × 107 kg; with the no-measures scenario, the DisN load is 4.05 × 107 kg. This BMP optimization model system could assist decision-makers in determining a scientifically comprehensive plan to realize cost-effective goals for the watershed.

Environmental factors influencing cattle's water consumption at offstream watering points in rangeland beef cattle

Agricultural best management practices (BMP) are of global importance to protect and promote sustainable food supplies and natural resources. Providing an offstream watering point (OSWP) is a functional and cost-effective BMP recommended to assist in maintaining or improving riparian areas and instream water quality. Understanding which factors contribute to cattle's use of OSWPs may enhance the decision making process for graziers when they consider implementing the use of an OSWP. This study's objective were to understand how cattle utilise OSWPs where they have access to an OSWP as the only drinking source compared to where a choice exists between drinking from an OSWP and a river. Choices were determined across a range of environmental factors, including water quality represented by total dissolved solids, climatic factors such as temperature humidity index, the number of rainfall days and wind speed, OSWP distance to stream, stocking density and vegetation greenness within 100 m from the OSWP. The results indicated that 1) cattle consume approximately half of their daily water from the OSWP when they have access to both an OSWP and the river (p = 0.023), with the number of rainfall days being a significant contributing factor (p = 0.037) with cattle consuming less water from OSWP during rain events and 2) Rainfall events influence WC consumption at OSWPs which may alter both vegetation and OSWP water quality and in turn influence how cattle select for water sources, but how cattle select for water sources will need of further researched. Furthermore, vegetation greenness around OSWPs may be of less importance where cattle have river access.

New framework for optimizing best management practices at multiple scales

The optimal design of best management practices (BMPs) is of vital importance for the control of nonpoint source (NPS) pollutants, but proper methods for multiple-scale BMP design are still lacking, especially for large-scale watersheds. In this study, a new framework (MS-BMPs) was proposed for multiscale BMP design by combining multiscale design ideas, hydrological models, cost estimators and shuffled frog leaping algorithms. In addition, the computation efficiency of BMP design was improved by modifying the memetic evolution process. This new framework was then tested in the Daning River Watershed, Three Gorges Reservoir Region, China. Based on the results, the new framework could provide more powerful convergence and optimization ability, while the rationality of BMP configuration was increased by four times. From the Pareto front of the MS-BMPs, the maximum removal of TN and TP improved by 19.42% and 14.36%, indicating a more cost-effective BMP design. This study also highlighted the priority of fertilization management in the regulation of NPS pollution. This new framework can be easily extended to any watershed to assist managers with the optimal design of BMPs.

Impacts of climate change on watershed systems and potential adaptation through BMPs in a drinking water source area

Climate change, in terms of changes in temperature and patterns of precipitation, has significant impacts on water resources and watershed ecosystems. Adapting to climate change is becoming an important strategy for watershed management. The goal of this study was to quantify the impacts of climate change on watershed hydrological processes and water quality, to evaluate the efficiency of Best Management Practices (BMPs) and the possible effects of a changing climate, and to configure cost-effective BMPs at sub-basin scale using a multi-objective optimization method to mitigate climate effects on water resource. The Soil and Water Assessment Tool (SWAT) model was used to simulate the possible effects of changing climate on watershed hydrological and water-quality processes and adaptation options in the Miyun Reservoir Watershed (MRW). Climate change had significant impacts on water balance components such as precipitation, runoff, and evapotranspiration (ET) and on water-quality components such as sediment and nutrient loads. A substantial decreasing trend of runoff indicated that the Miyun Reservoir faced a more acute challenge of insufficient water-supply capacity. Compared with baseline climate, climate change represented by precipitation and temperature regimes resulted in substantial increases in sediment load (12.95%) and nutrient losses (7.26% for TN and 9.56% for TP) on average all sub-basins. Climate variability had significant effects on BMP efficiency through effects on watershed hydrology, soil erosion, and nutrient losses. Results highlight the importance of optimal configuration of site-specific BMPs at sub-basin scale for adaptation to climate change. The methods and findings presented here hold promise to enhance the resilience of the watershed system to current and future climate change.

Best Management Practices Optimization at Watershed Scale: Incorporating Spatial Topology among Fields

Best management practices (BMPs) are widely used to reduce nonpoint source pollutions. In order to obtain cost-effective BMPs configurations, optimization methods are introduced. Recent studies show that knowledge on BMP placement can be used to improve existing algorithms for BMPs optimization. However, some important knowledge has not been fully utilized yet, one of which is about the spatial topology among fields and BMPs interactions. In this paper, a new method for BMPs optimization was proposed, which incorporated knowledge of BMPs interactions into a multi-objective genetic algorithm (i.e., e-NSGAII) based on spatial topology among fields. Then this method was applied to the BMPs optimization in a small agricultural watershed in Southern Manitoba of Canada, and the performance was compared with those of conventional method. In order to make a comprehensive comparison, experiments were conducted under different population sizes (i.e., 60, 100, and 200) and different numbers of fields (i.e., 29, 52, and 79). The results showed that the proposed method was superior to conventional method on the aspect of greater sediment reductions (2% - 17%) at the same cost, and the Pareto curves obtained by the proposed method were more complete. This study demonstrated that incorporating spatial topology among fields into BMPs optimization can lead to better results and this finding could provide valuable references to similar studies.

한강수계 비점오염원 저감시설의 생애주기비용 평가

환경부는 비점오염원 관리를 위해 시범사업으로 12개의 비점오염 저감시설을 경안천 유역에 설치하였으며, 2006년부터 모니터링이 시작되었다. 본 연구는 비점오염 저감시설의 오염부하량, 저감효율, 유지관리 활동 등의 장기간 수행된 모니터링 결과를 바탕으로 각 시설의 경제성을 평가하기 위해 수행되었으며, 생애주기비용(Lifecycle cost, LCC)을 분석하였다. 비점오염 저감시설의 유지관리는 시설경관을 향상시키기 위한 심미적 관리가 중점적으로 수행된 것으로 나타났으며, 저류형 시설(Retention Pond, RP)이 년간 8,483$, 침투형 시설(Infiltration System, IS)이 8,888$로 대부분 비슷한 비용이 발생한 것으로 분석되었다. LCC는 인공습지(Constructed Wetland, CW)가 가장 높은 것($418,324)으로 나타났으며, 반면에 식생형 시설(Vegetated System, VS)이 가장 낮은 것($210,418)으로 분석되었다. 본 연구에서 조사된 비점오염 저감시설의 LCC와 하수처리장 등 수질처리시설의 LCC를 비교한 결과 비점오염 저감시설이 낮은 것으로 나타났다. 한편, 처리용량 대비 생애주기비용이 높아질수록 TSS와 TN의 저감효율은 높아지는 것으로 나타났다. 이러한 연구결과는 비용효율적인 비점오염 저감시설을 설계하는데 유용하게 활용될 것으로 기대되며, 향후 LCC 모델의 기초자료에도 활용될 수 있을 것으로 판단된다. Diffuse pollution management in Korea initiated by the Ministry of Environment (MOE) resulted to the construction of pilot facilities termed Best Management Practices (BMPs). Twelve BMPs installed for the diffuse pollution management in the Kyung-An Stream were monitored since 2006. Data on the mass loading, removal efficiency, maintenance activities, etc. were gathered and utilized to conduct the evaluation of long-term performance of BMPs. The financial data such as actual construction, design and maintenance cost were also collected to evaluate the lifecycle cost (LCC) of BMPs. In this study, most of the maintenance activity was focused in the aesthetic maintenance that resulted to the annual maintenance cost of the four BMP types was closely similar ranging from 8,483 $/yr for retention pond to 8,888 $/yr infiltration system. The highest LCC were observed in constructed wetland ($418,324) while vegetated system had the lowest LCC ($210,418). LCC of BMPs was not so high as compared with the conventional treatment facility and sewage treatment plant. On the other hand, the relationship of removal efficiency on unit cost for TSS and TN was significant. This study will be used to design the cost effective BMP for diffuse pollution management and become models for LCC analysis.

A Web-Based Model to Estimate the Impact of Best Management Practices

The Spreadsheet Tool for the Estimation of Pollutant Load (STEPL) can be used for Total Maximum Daily Load (TMDL) processes, since the model is capable of simulating the impacts of various best management practices (BMPs) and low impact development (LID) practices. The model computes average annual direct runoff using the Soil Conservation Service Curve Number (SCS-CN) method with average rainfall per event, which is not a typical use of the SCS-CN method. Five SCS-CN-based approaches to compute average annual direct runoff were investigated to explore estimated differences in average annual direct runoff computations using daily precipitation data collected from the National Climate Data Center and generated by the CLIGEN model for twelve stations in Indiana. Compared to the average annual direct runoff computed for the typical use of the SCS-CN method, the approaches to estimate average annual direct runoff within EPA STEPL showed large differences. A web-based model (STEPL WEB) was developed with a corrected approach to estimate average annual direct runoff. Moreover, the model was integrated with the Web-based Load Duration Curve Tool, which identifies the least cost BMPs for each land use and optimizes BMP selection to identify the most cost-effective BMP implementations. The integrated tools provide an easy to use approach for performing TMDL analysis and identifying cost-effective approaches for controlling nonpoint source pollution.

Cost-effectiveness analysis of stormwater best management practices (BMPs) in urban watersheds

This study demonstrates a cost-effectiveness analysis of stormwater BMPs to answer questions, such as what type to place and how large it should be. Cost-effective analysis showed that for the basin considered, a porous pavement was the most effective means of controling runoff, which was able to bring the peak runoff down to the predevelopment level with the least budget. A storage basin was the second best, which was able to bring the peak runoff down to the predeveloped conditions, but with a higher budget. The effectiveness of a green roof in reducing the peak runoff plateaued beyond a certain budget, and was unable to bring the peak runoff down to the predeveloped level, regardless of cost. It is thought that a porous pavement would be a cost-effective BMP in a severely urbanized setting.

BMP Analysis System for Watershed-Based Stormwater Management

Best Management Practices (BMPs) are measures for mitigating nonpoint source (NPS) pollution caused mainly by stormwater runoff. Established urban and newly developing areas must develop cost effective means for restoring or minimizing impacts, and planning future growth. Prince George's County in Maryland, USA, a fast-growing region in the Washington, DC metropolitan area, has developed a number of tools to support analysis and decision making for stormwater management planning and design at the watershed level. These tools support watershed analysis, innovative BMPs, and optimization. Application of these tools can help achieve environmental goals and lead to significant cost savings. This project includes software development that utilizes GIS information and technology, integrates BMP processes simulation models, and applies system optimization techniques for BMP planning and selection. The system employs the ESRI ArcGIS© as the platform, and provides GIS-based visualization and support for developing networks including sequences of land uses, BMPs, and stream reaches. The system also provides interfaces for BMP placement, BMP attribute data input, and decision optimization management. The system includes a stand-alone BMP simulation and evaluation module, which complements both research and regulatory nonpoint source control assessment efforts, and allows flexibility in the examining various BMP design alternatives. Process based simulation of BMPs provides a technique that is sensitive to local climate and rainfall patterns. The system incorporates a meta-heuristic optimization technique to find the most cost-effective BMP placement and implementation plan given a control target, or a fixed cost. A case study is presented to demonstrate the application of the Prince George's County system. The case study involves a highly urbanized area in the Anacostia River (a tributary to Potomac River) watershed southeast of Washington, DC. An innovative system of management practices is proposed to minimize runoff, improve water quality, and provide water reuse opportunities. Proposed management techniques include bioretention, green roof, and rooftop runoff collection (rain barrel) systems. The modeling system was used to identify the most cost-effective combinations of management practices to help minimize frequency and size of runoff events and resulting combined sewer overflows to the Anacostia River.