Combination Of 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.

Evaluation of the Best Management Practices for Reducing Phosphorus Load in a Watershed in Terms of Cost and Greenhouse Gas Emissions

Effective management of water quality in watersheds is crucial because it is directly linked to the sustainability of aquatic ecosystems. In conventional watershed management, best management practices (BMPs) have been instrumental in addressing deteriorating water quality issues caused by non-point source pollution. Greenhouse gas (GHG) emissions have emerged as a global concern, necessitating immediate and diverse environmental actions to mitigate their impacts. This study aims to explore BMPs that maximize total phosphorus (TP) load removal efficiencies, while minimizing costs and GHG emissions within watersheds, using the Soil and Water Assessment Tool (SWAT) and non-dominated sorting genetic algorithm III (NSGA-III). The Yeongsan River Watershed between 2012 and 2021 was selected as the study area. Hydrological and BMP data were analyzed. Applying identical BMPs to the watershed showed that the BMPs with high TP removal efficiency may not be effective in terms of cost and GHG emissions. Therefore, the optimal combination of BMPs for the Yeongsan River Watershed was determined using NSGA-III considering TP removal efficiency, cost, and GHG emissions. This study is the first to consider GHG emissions at the watershed level when applying BMPs and is expected to contribute to the development of BMP implementation incorporating GHG emissions.

Effect of varying hydrologic regime on seasonal total maximum daily loads (TDML) in an agricultural watershed

Rising hypoxia due to the eutrophication of riverine ecosystems is primarily caused by the transport of nutrients. The majority of existing TMDL models cannot be efficienty applied to represent nutrient concentrations in riverine ecosystems having varying flow regimes due to seasonal differences. Accurate TMDL assessment requires nutrient loads and suspended matter estimation under varying flow regimes with minimal uncertainty. Though a large database can enhance accuracy, it can be resource intensive. This study presents the design of an innovative modeling strategy to optimize the use of existing datasets to effectively represent streamflow-load dynamics while minimizing uncertainty. The study developed an approach to assess TMDLs using six different flux models and kriging techniques (i) to enhance the accuracy of nutrient load estimation under different hydrologic regimes (flow stratifications) and (ii) to derive an optimal modeling strategy and sampling scheme for minimizing uncertainty. The flux models account for uncertainty in load prediction across varying flow strata, and the deployment of multiple load calculation procedures. Further, the proposed flux approach allows the determination of load exceedance under different TMDL scenarios aimed at minimizing uncertainty to achieve reliable load predictions. The study employed a 10-year dataset (2009–2018) consisting of daily flow data (m3/sec) and weekly data (mg/L) for nitrogen (N), phosphorus (P) and total suspended solids (TSS) concentrations in three distinct agricultural sites in+ the Minnesota River Watershed. The outcomes were analyzed geospatially in a Geographic Information System (GIS) environment using the kriging interpolation technique. The study recommends (i) triple stratification of flows to obtain accurate load estimates, and (ii) an optimal sampling scheme for nitrogen and phosphorous with 30.6 % and 49.8 % datapoints from high flow strata. The study outcomes are expected to contribute to the planning of economically and technically sound combinations of best management practices (BMPs) required for achieving total maximum daily loads (TMDL) in a watershed.

Integrated Agricultural Practices and Engineering Technologies Enhance Synergies of Food-Energy-Water Systems in Corn Belt Watersheds.

Interconnected food, energy, water systems (FEWS) require systems level understanding to design efficient and effective management strategies and policies that address potentially competing challenges of production and environmental quality. Adoption of agricultural best management practices (BMPs) can reduce nonpoint source phosphorus (P) loads, but there are also opportunities to recover P from point sources, which could also reduce demand for mineral P fertilizer derived from declining geologic reserves. Here, we apply the Integrated Technology-Environment-Economics Model to investigate the consequences of watershed-scale portfolios of agricultural BMPs and environmental and biological technologies (EBTs) for co-benefits of FEWS in Corn Belt watersheds. Via a pilot study with a representative agro-industrial watershed with high P and nitrogen discharge, we show achieving the nutrient reduction goals in the watershed; BMP-only portfolios require extensive and costly land-use change (19% of agricultural land) to perennial energy grasses, while portfolios combining BMPs and EBTs can improve water quality while recovering P from corn biorefineries and wastewater streams with only 4% agricultural land-use change. The potential amount of P recovered from EBTs is estimated as 2 times as much as the agronomic P requirement in the watershed, showing the promise of the P circular economy. These findings inform solution development based on the combination of agricultural BMPs and EBTs for the cobenefits of FEWS in Corn Belt watersheds.

Modeling the impacts of best management practices (BMPs) on pollution reduction in the Yarra River catchment, Australia

Pollution of a watershed by different land uses and agricultural practices is becoming a major challenging factor that results in deterioration of water quality affecting human health and ecosystems. Sustainable use of available water resources warrants reduction of Non-Point Source (NPS) pollutants from receiving water bodies through best management practices (BMPs). A hydrologic model such as the Soil and Water Assessment Tool (SWAT) can be used for analyzing the impacts of various BMPs and implementing of different management plans for water quality improvement, which will help decision makers to determine the best combination of BMPs to maximize benefits. The objective of this study is to assess the potential reductions of sediments and nutrient loads by utilizing different BMPs on the Yarra River watershed using the SWAT model. The watershed is subdivided into 51 sub-watersheds where seven different BMPs were implemented. A SWAT model was developed and calibrated against a baseline period of 1998–2008. For calibration and validation of the model simulations for both the monthly and annual nutrients and sediments were assessed by using the Nash–Sutcliffe efficiency (NSE) statistical index. The values of the NSE were found more than 0.50 which indicates satisfactory model predictions. By utilizing different BMPs, the highest pollution reduction with minimal costs can be done by 32% targeted mixed-crop area. Furthermore, the combined effect of five BMPs imparts most sediments and nutrient reductions in the watershed. Overall, the selection of a BMP or combinations of BMPs should be set based on the goals set in a BMP application project.

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.

Assessing the effectiveness of potential best management practices for science-informed decision support at the watershed scale: The case of the Mar Menor coastal lagoon, Spain

Coastal lagoons are ecosystems of high environmental importance but are quite vulnerable to human activities. The continuous inflow of pollutant loads can trigger negative impacts on the ecological status of these water bodies, which is contrary to the European Green Deal. One example is the Mar Menor coastal lagoon in Spain, which has experienced significant environmental degradation in recent years due to excessive external nutrient input, especially from non-point source (NPS) pollution. Mar Menor is one of the largest coastal lagoons of the Mediterranean region and a site of great ecological and socio-economic value. In this study, the highly anthropogenic and complex watershed of Mar Menor, known as Campo de Cartagena (1244 km2), was modelled with the Soil and Water Assessment Tool (SWAT) to analyse potential options for recovery of this unique system. The model was used to simulate several best management practices (BMP) proposed by recent Mar Menor regulations, such as vegetative filter strips, shoreline buffers, contour farming, removal of illegal agriculture, crop rotation management, waterway vegetation restoration, fertiliser management and greenhouse rainwater harvesting. Sixteen scenarios of individual and combined BMPs were analysed in this study. We found that, as individual measures, vegetative filter strips and contour farming were most effective in nutrient reduction: approximately 30 % for total nitrogen (TN) and 40 % for total phosphorus (TP). Moreover, waterway vegetation restoration showed the highest sediment (S) reduction at approximately 20 %. However, the combination of BMPs demonstrated clear synergistic effects, reducing S export by 38 %, TN by 67 %, and TP by 75 %. Selecting the most appropriate BMPs to be implemented at a watershed scale requires a holistic approach considering effectiveness in reducing NPS pollution loads and BMP implementation costs. Thus, we have demonstrated a way forward for enabling science-informed decision-making when choosing strategies to control NPS contamination at the watershed scale.

Narrowing maize yield gaps in the rainfed plateau region of Odisha

Abstract Maize is the primary staple crop cultivated during the monsoon season in eastern India. However, yield gaps are large because of multiple factors, including low adoption rates of good agronomic management practices. This study aimed to narrow the maize yield gap using diverse agronomic and varietal interventions through field experiments over 2 years (2013–2014) in the rainfed plateau region of Odisha. As a result, maize yield increased by 0.9, 0.74, and 0.17 Mg ha−1 under optimum plant population, fertilizer management, and herbicide-based weed management, respectively, over farmers’ current practices (Check). Moreover, when all three interventions were combined (‘best’ management practice), grain yields increased by 1.7 Mg ha−1 in conservation tillage and 2.2 Mg ha−1 in conventional tillage. We also observed that the combination of long-duration hybrids and best management practices (BMPs) increased grain yield by 4.0 Mg ha−1 and profitability by $888 ha−1 over farmers’ current practices. In addition, Nutrient Expert decision support tool-based fertilizer management along with BMPs increased grain yield by 1.7 Mg ha−1 and profitability by $314 ha−1 over farmers’ fertilizer practices (Check). These results suggest that the combination of maize hybrids and BMPs can improve the productivity and profitability of rainfed maize in the plateau region of Odisha. However, these entry points for intensification need to be placed in the context of varying investment requirements, input and output market conditions, and matched with farmer preferences and risk.

Stacked conservation practices reduce nitrogen loss: A paired watershed study

Combinations of best management practices (BMPs) are needed to achieve nutrient reduction goals in the Mississippi/Atchafalaya River Basin (MARB), but field results are crucial to encourage stacked adoption of BMPs. A paired catchment-scale study (2015–18) was done to assess the impact of (i) BMPs, (ii) precipitation patterns, and (iii) seasonality on nitrogen (N) export. Flow-weighted samples were collected and analyzed for total ammonia nitrogen (TAN), nitrate (NO3–N), and total nitrogen (TN). Catchments Low-BMP 11 and High-BMP 12 had 27.6% and 87.6% areal coverage of BMPs, respectively. No significant difference (p > 0.05) in TAN concentrations was found between Low-BMP 11 (0.023 mg L−1) and High-BMP 12 (0.020 mg L−1). However, NO3–N and TN concentrations were significantly higher (p < 0.05) at Low-BMP 11 (NO3–N: 26.0 mg L−1, TN: 28.7 mg L−1) than at High-BMP 12 (NO3–N: 8.8 mg L−1, TN: 9.2 mg L−1). Two precipitation factors that affected N export patterns were observed. First, N flushing could continue for several years after a drought as elevated NO3–N concentrations were observed in 2015 (i.e., two years after the 2011–2013 drought). Second, higher annual N export was observed when more precipitation occurred during the pre-planting or early-growing season versus later periods. For both catchments, the highest 50% of flows were responsible for majority of the NO3–N export. We estimated that 33–37%, 61–62%, and 82–85% of the NO3–N loads occurred in the 90th, 75th, and 50th flow percentiles, respectively. As demonstrated in High-BMP 12, stacked BMP application effectively lowered NO3–N and TN loads by 60.3% and 59.1%, respectively, relative to Low-BMP 11. Although 27.6% BMP coverage area in Low-BMP 11 was considered low for this study, this coverage area is higher than many other parts of the MARB. This research highlights the importance of joint efforts between landowners in a watershed to meet downstream water quality goals.

Minimization of Water Use Conflicts in Kunthipuzha River Basin by Use of Water Allocation Tool

Water scarcity and consequent droughts are of serious concern for almost all countries around the world. Since climate change is expected to exacerbate the already existing water stresses, the improvement of water efficiency against water scarcity and drought is very much important. The water stressed areas within the Kunthipuzha river basin were identified by allocating the available water for various demands using the WEAP model. This study aims at suggesting some Best Management Practices (BMPs) for those water stressed areas so as to minimize the water scarcity problems. To contribute towards this goal, Water Evaluation and Planning (WEAP) model is used, which is a decision support system (DSS) to assess water availability and investigate the impacts of different water allocation scenarios (water demand management strategies) aimed at meeting various sectorial water demands. The results from the study revealed that the implementation of BMP’s like improving the irrigation efficiency, changing of planting date, changing of crops etc. could bring in significant reduction in water scarcity problems in the identified hotspots. Moreover, in certain sub basins it was found that it would be possible to completely eliminate water scarcity by implementing combinations of BMPs. Thus, such studies done in an extensive manner will help in finding a balance between what is needed and what is available within the environment which in turn serves as an important step in achieving water resource sustainability.

Impact Assessment of Best Management Practices (BMPs) on the Water Footprint of Agricultural Productions

Agriculture is the main source of diffuse nutrient pollution in surface waters. It requires best management practices (BMPs) for controlling the discharges of pollutants like total nitrogen (TN) and total phosphorous (TP). In addition, these pollutants are accounted in the grey water footprint (GWF) of agricultural productions. This study proposes an integrated methodology with two steps for assessing the impacts of BMPs on the water footprints (WF) of agricultural productions. First, this approach uses the soil and water assessment tool (SWAT) for basin modeling and calculating the required data for WF assessment. In the second step, the WFs of agricultural productions are quantified and compared in different BMP scenarios, including fertilizer and irrigation reduction (FIR) and the application of vegetated filter strips (VFS). The SWAT modeling shows that FIR and VFS are more effective on TN and TP reduction, respectively. It can estimate that the combination of BMPs has the potential of abating 60% of the TN and TP concentrations of lake in 8 years. However, the WFs of agricultural productions may not be significantly reduced by BMPs as the average GWF only constitutes 4.2% of WF in this basin. For instance, the combination of FIR and VFS can reduce the average WF of cereals from 44 to 41 m3/km2. Nevertheless, this practice is relatively more effective for irrigated crops. The WF of rain-fed crops remains constant on 37 m3/km2, while it is reduced 24% (from 91 to 69 m3/km2) for irrigated crops by BMPs. In addition, it is realized that FIR can adversely reduce the production yields up to 32%. All these findings verify that the proposed methodology can integrate BMP and WF assessments by SWAT modeling and is recommended for basins, where farmlands are the dominated land-use.

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.

Quantifying effects of conservation practices on non-point source pollution in the Miyun Reservoir Watershed, China

Non-point source (NPS) pollution, including fertilizer and manure application, sediment erosion, and haphazard discharge of wastewater, has led to a wide range of water pollution problems in the Miyun Reservoir, the most important drinking water source in Beijing. In this study, the Soil and Water Assessment Tool (SWAT) model was used to evaluate NPS pollution loads and the effectiveness of best management practices (BMPs) in the two subwatersheds within the Miyun Reservoir Watershed (MRW). Spatial distributions of soil types and land uses, and changes in precipitation and fertilizer application, were analysed to elucidate the distribution of pollution in this watershed from 1990 to 2010. The results demonstrated that the nutrient losses were significantly affected by soil properties and higher in both agricultural land and barren land. The temporal distribution of pollutant loads was consistent with that of precipitation. Soil erosion and nutrient losses would increase risks of water eutrophication and ecosystem degradation in the Miyun Reservoir. The well-calibrated SWAT model was used to assess the effects of several Best Management Practices (BMPs), including filter strips, grassed waterways, constructed wetlands, detention basins, converting farmland to forest, soil nutrient management, conservation tillage, contour farming, and strip cropping. The removal rates of those BMPs ranged from 1.03 to 38.40% and from 1.36 to 39.34% for total nitrogen (TN) and total phosphorus (TP) loads, respectively. The efficiency of BMPs was dependent on design parameters and local factors and varied in different sub-basins. This study revealed that no single BMP could achieve the water quality improvement targets and highlighted the importance of optimal configuration of BMP combinations at sub-basin scale. The findings presented here provide valuable information for developing the sustainable watershed management strategies.

Assessment of site-specific agricultural Best Management Practices in the Upper East River watershed, Wisconsin, using a field-scale SWAT model

The Great Lakes “Priority Watershed” effort targeted the Upper East River watershed, a 116.5-km2 tributary watershed to Wisconsin's Green Bay, to reduce its sediment and nutrients loads from agricultural sources. A Soil and Water Assessment Tool (SWAT) model was created to determine the effectiveness of agricultural Best Management Practices (BMPs) funded through the Great Lakes Restoration Initiative. The model was calibrated at the monthly time-step for flow, sediment, dissolved reactive phosphorus (DRP), total phosphorus (TP), nitrate, and total nitrogen (TN). Field- and watershed-scale sediment and nutrient reductions were calculated due to the implementation of 74 BMP combinations on dairy and cash grain rotations. Modeling results indicated that when multiple BMPs were placed on a field, especially those including filter strips and grassed waterways, sediment and nutrient loads generally were reduced more than single BMP implementation. The most effective in-field practice at reducing DRP and TP on dairy fields was a combination of 5 different BMPs: cover crops, crop rotation, nutrient management plan, reduced tillage, and a filter strip. Conservation cover was the single most effective practice at reducing sediment and nutrient yields. Sediment and nutrient loads decreased at the watershed scale as the quantity and coverage of BMPs increased. When all contracted BMPs were simulated at the watershed scale, sediment loads were reduced 2%, while TP, DRP, TN and nitrate loads were reduced 20%, 9%, 24%, and 17%, respectively. Modeling scenarios also indicated that over-winter manure storage was important to keep soluble nutrients out of waterways.

A coupled model system to optimize the best management practices for nonpoint source pollution control

Agricultural nonpoint source pollution (NPS) is the main water-use impairment in the upper watershed of the Miyun Reservoir in Beijing, China. Selection and placement of best management practices (BMPs) in heterogeneous watersheds, requires a multi-objective optimization framework to identify the most cost-effective conservation strategy to achieve desired water quality goals. In this paper, a novel optimization methodology was developed, utilizing a BMP database that includes BMP reduction efficiencies and costs, using a multi-objective sorting genetic algorithm (NSGA-II, nondominated sorting genetic algorithm-II) combined with the Soil Water and Assessment Tool (SWAT) served as the NPS watershed model. Cost-effectiveness curves (optimal fronts) between pollutant reduction and total net cost input were obtained for the upper watershed of Miyun Reservoir. The optimal combination of BMP, which include a combination of conservation tillage, careful timing of 30% less fertilizer application, contour planting, and use of a 10-m edge-of-field buffer strip, indicate that the least costly scenario reduced total nitrogen (TN) and total phosphorus (TP) loads by 33% at a cost of 1.02 × 106 China Yuan. The cost-effective scenario reduced TN and TP loads 44% and 68% at a cost of 2.52 × 107 and 5.64 × 107China Yuan. The greatest reduction scenario reduced TN and TP loads 55% and 76%, respectively, at a cost of 2.01 × 108 and 2.48 × 108 China Yuan. Watershed with poultry operations, required a 30% reduction in number of birds, along with a 30% reduction in the amount of manure applied was needed to achieve water quality goals. Use of the coupled BMP optimization model can assist the policy makers achieve a cost-effective implementation of best management practices to mitigate agricultural nonpoint sources at a watershed scale.

Assessing the Impact of Site-Specific BMPs Using a Spatially Explicit, Field-Scale SWAT Model with Edge-of-Field and Tile Hydrology and Water-Quality Data in the Eagle Creek Watershed, Ohio

The Eagle Creek watershed, a small subbasin (125 km2) within the Maumee River Basin, Ohio, was selected as a part of the Great Lakes Restoration Initiative (GLRI) “Priority Watersheds” program to evaluate the effectiveness of agricultural Best Management Practices (BMPs) funded through GLRI at the field and watershed scales. The location and quantity of BMPs were obtained from the U.S. Department of Agriculture-Natural Resources Conservation Service National Conservation Planning (NCP) database. A Soil and Water Assessment Tool (SWAT) model was built and calibrated for this predominantly agricultural Eagle Creek watershed, incorporating NCP BMPs and monitoring data at the watershed outlet, an edge-of-field (EOF), and tile monitoring sites. Input air temperature modifications were required to induce simulated tile flow to match monitoring data. Calibration heavily incorporated tile monitoring data to correctly proportion surface and subsurface flow, but calibration statistics were unsatisfactory at the EOF and tile monitoring sites. At the watershed outlet, satisfactory to very good calibration statistics were achieved over a 2-year calibration period, and satisfactory statistics were found in the 2-year validation period. SWAT fixes parameters controlling nutrients primarily at the watershed level; a refinement of these parameters at a smaller-scale could improve field-level calibration. Field-scale modeling results indicate that filter strips (FS) are the most effective single BMPs at reducing dissolved reactive phosphorus, and FS typically decreased sediment and nutrient yields when added to any other BMP or BMP combination. Cover crops were the most effective single, in-field practice by reducing nutrient loads over winter months. Watershed-scale results indicate BMPs can reduce sediment and nutrients, but reductions due to NCP BMPs in the Eagle Creek watershed for all water-quality constituents were less than 10%. Hypothetical scenarios simulated with increased BMP acreages indicate larger investments of the appropriate BMP or BMP combination can decrease watershed level loads.

Calibration of a Field-Scale Soil and Water Assessment Tool (SWAT) Model with Field Placement of Best Management Practices in Alger Creek, Michigan

Subwatersheds within the Great Lakes “Priority Watersheds” were targeted by the Great Lakes Restoration Initiative (GLRI) to determine the effectiveness of the various best management practices (BMPs) from the U.S. Department of Agriculture-Natural Resources Conservation Service National Conservation Planning (NCP) Database. A Soil and Water Assessment Tool (SWAT) model is created for Alger Creek, a 50 km2 tributary watershed to the Saginaw River in Michigan. Monthly calibration yielded very good Nash–Sutcliffe efficiency (NSE) ratings for flow, sediment, total phosphorus (TP), dissolved reactive phosphorus (DRP), and total nitrogen (TN) (0.90, 0.79, 0.87, 0.88, and 0.77, respectively), and satisfactory NSE rating for nitrate (0.51). Two-year validation results in at least satisfactory NSE ratings for flow, sediment, TP, DRP, and TN (0.83, 0.54, 0.73, 0.53, and 0.60, respectively), and unsatisfactory NSE rating for nitrate (0.28). The model estimates the effect of BMPs at the field and watershed scales. At the field-scale, the most effective single practice at reducing sediment, TP, and DRP is no-tillage followed by cover crops (CC); CC are the most effective single practice at reducing nitrate. The most effective BMP combinations include filter strips, which can have a sizable effect on reducing sediment and phosphorus loads. At the watershed scale, model results indicate current NCP BMPs result in minimal sediment and nutrient reductions (&lt;10%).

Cost-effectiveness analysis of different watershed management scenarios developed by simulation–optimization model

The effort to control sediment yield at watershed scale is an ongoing challenge that needs to take into account trade-offs between two conflicting objective functions, i.e. economic and hydrologic criteria. Therefore, researchers have coupled hydrologic and multi-objective optimization models to find Pareto-optimal solutions. However, very limited studies have been conducted to analyse the cost-effectiveness (C/E) of scenarios obtained in the Pareto-front optimal. This could provide new information leading to effective watershed management. Therefore, in the present study, the Soil and Water Assessment Tool (SWAT) was used to simulate sediment yield under different combinations of best management practices (BMPs) and was coupled with the Non-dominated Sorting Genetic Algorithm (NSGA-II). The model attends to providing the Pareto-optimal solutions by minimizing the costs of BMPs and maximizing sediment reduction. The results of the application of the cost-effective optimization model in Mehran watershed, Iran, showed that the solutions in the Pareto-optimal front reduce sediment yield between 2% and 40.5% from baseline at costs of between $6,500 and $72,100, respectively. Finally, comparison of four sediment reduction solutions (i.e. 10%, 20%, 30%, and 40%) showed that the total cost and C/E ratio of solutions increased as the sediment reduction criteria increased.

Evaluation of executable best management practices in Haean highland agricultural catchment of South Korea using SWAT

This study is to evaluate the reduction of high level nonpoint source (NPS) pollution discharges in Haean highland agricultural catchment (62.8km2) by applying best management practices (BMPs) of vegetation filter strip installation (VFS), fertilizer control (FC), and rice straw mulching (RSM) in uplands above 600m of elevation using SWAT (Soil and Water Assessment Tool). From the modeling results, the VFS BMP showed the best performance to reduce sediment (SS) of 16.0% for 1m strip width up to 34.8% for 5m strip width and total phosphorus (T-P) discharge loads of 5.1% to 21.3% from highland crop areas. The FC BMP showed the discharge loads reduction of 4.9% for 10% fertilizer reduction up to 16.4% for 30% fertilizer reduction. The RSM BMP results showed the sediment reduction of 3.0% for 6.0% runoff reduction up to 14.1% for 17.0% runoff reduction and T-P reduction of 1.3% for 6.0% runoff reduction up to 6.8% for 17.0% runoff reduction by showing negative effect of total nitrogen (T-N) up to −3.7% for 12.0% runoff reduction. However, because of the difficulties to install vegetation filter strip by farmers unwillingness in South Korea, the BMPs combination of fertilizer reduction and rice straw mulching (FC+RSM) was suggested as an executable BMP to obtain positive removal efficiency for all nutrient discharge loads. The FC+RSM BMP showed sediment, T-P, and T-N reductions up to 9.7%, 8.1%, and 9.2% respectively.

Methodology for Selecting Best Management Practices Integrating Multiple Stakeholders and Criteria. Part 1: Methodology

The implementation of stormwater Best Management Practices (BMPs) could help re-establish the natural hydrological cycle of watersheds after urbanization, with each BMP presenting a different performance across a range of criteria (flood prevention, pollutant removal, etc.). Additionally, conflicting views from the relevant stakeholders may arise, resulting in a complex selection process. This paper proposes a methodology for BMP selection based on the application of multi-criteria decision aid (MCDA) methods, integrating multiple stakeholder priorities and BMP combinations. First, in the problem definition, the MCDA methods, relevant criteria and design guidelines are selected. Next, information from the preliminary analysis of the watershed is used to obtain a list of relevant BMPs. The third step comprises the watershed modeling and analysis of the BMP alternatives to obtain performance values across purely objective criteria. Afterwards, a stakeholder analysis based on survey applications is carried out to obtain social performance values and criteria priorities. Then, the MCDA methods are applied to obtain the final BMP rankings. The last step considers the sensitivity analysis and rank comparisons in order to draw the final conclusions and recommendations. Future improvements to the methodology could explore inclusion of multiple objective analysis, and alternative means for obtaining social performance values.