Best Management Practices Scenarios Research Articles

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

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

Quantification of agricultural best management practices impacts on sediment and phosphorous export in a small catchment in southeastern Sweden

Agricultural activities contribute to water pollution through sediments and nutrient export, negatively affecting water quality and aquatic ecosystems. However, implementing best management practices (BMPs) could help control sediments and nutrient losses from agricultural catchments. This study used the Soil Water Assessment Tool (SWAT) model to assess the effectiveness of four BMPs in reducing sediment and phosphorus export in a small agricultural catchment (33 km2) in southeastern Sweden. The SWAT model was first evaluated for its ability to simulate streamflow, sediment load, and total phosphorous load from 2005 to 2020. Then, the calibrated parameters were used to simulate the agricultural BMP scenarios by modifying relevant parameters. The model performed satisfactorily during calibration and validation for streamflow (NSE = 0.80/0.84), sediment load (NSE = 0.67/0.69), and total phosphorous load (NSE = 0.61/0.62), indicating its suitability for this study. The results demonstrate varying effects of BMP implementation on sediment and phosphorus (soluble and total) export, with no significant change in streamflow. Filter strips were highly effective in reducing sediment (−32%), soluble phosphorus (−67%), and total phosphorous (−66%) exports, followed by sedimentation ponds with −35%, −36%, and −50% reductions, respectively. Grassed waterways and no-tillage were less impactful on pollutant reduction, with grassed waterways showing a slight increase (+4%) in soluble phosphorus and no-tillage having a minimal effect on sediment (−1.3%) and total phosphorus (−0.2%) export. These findings contribute to the ongoing efforts to mitigate sediment and nutrient pollution in Swedish agricultural areas, thereby supporting the conservation and restoration of aquatic ecosystems, and enhancing sustainable agricultural practices.

Assessing effect of best management practices in unmonitored watersheds using the coupled SWAT-BiLSTM approach

In order to enhance the simulation of BMPs (Best Management Practices) reduction effects in unmonitored watersheds, in this study, we combined the physically-based hydrological model Soil & Water Assessment Tool (SWAT) and the data-driven model Bi-directional Long Short-Term Memory (Bi-LSTM), using the very-high-resolution (VHR) Land Use and Land Cover (LULC) dataset SinoLC-1 as data input, to evaluate the feasibility of constructing a water environment model for the Ba-River Basin (BRB) in central China and improving streamflow prediction performance. In the SWAT-BiLSTM model, we calibrated the top five SWAT parameters sorted by P-Value, allowing SWAT to act as a transfer function to convert meteorological data into base flow and storm flow, serving as the data input for the Bi-LSTM model. This optimization improved the Bi-LSTM's learning process for the relationship between the target and explanatory variables. The daily streamflow prediction results showed that the hybrid model had 9 regions rated as "Very good," 2 as "Good," 2 as "Satisfactory," and 1 as "Unsatisfactory" among the 14 regions. The model achieved an NSE of 0.86, R2 of 0.85, and PBIAS of −2.71% for the overall daily streamflow prediction performance during the verification period of the BRB. This indicates that the hybrid model has high predictive accuracy and no significant systematic bias, providing a sound hydrodynamic environment for water quality simulation. The simulation results of different BMPs scenarios showed that in the scenarios with only one BMP measure, stubble mulch had the best reduction effect, with average reductions of 17.83% for TN and 36.17% for TP. In the scenarios with a combination of multiple BMP measures, the combination of stubble mulch, soil testing and formula fertilization, and vegetative filter strip performed the best, achieving average reductions of 42.71% for TN and 50.40% for TP. The hybrid model provides a novel approach to simulate BMPs' reduction effects in regions without measured hydrological data and has the potential for wide application in BMP-related decision-making.

Short-term climate change influence on surface water quality impacts from agricultural activities.

Climate change is a global phenomenon that directly affects agriculture by altering crop yield, nutritional quality, pests, and plant diseases. The North Aegean Basin located in Turkey has considerable agricultural importance due to its fertile soils. Agricultural activities have increased significantly and uncontrollably in the last decade, resulting in dramatic changes in nitrate and phosphorus levels in surface water within the watershed. Changes in climatic conditions have the potential to impact the quantity and quality of water resources. Best management practices (BMPs) are presently utilized as a planning tool to enhance the quality of water resources. To develop policies in this regard, it is necessary to evaluate the effectiveness of BMPs. To this end, this study aims to investigate the potential effect of climate change on the surface water quality of the North Aegean Basin. For the period between 2010 and 2030, global climate data retrieved from Concentration Pathway (RCP) scenarios 4.5 and 8.5 and regionally downscaled were used to feed the Soil and Water Assessment Tool (SWAT) model. The various potential BMP scenarios were developed and simulated in the hydrological model by considering the effects of climate change. The RCP4.5 scenario reduced the precipitation by 15.11%, while the RCP8.5 scenario reduced the precipitation by 10.97%. Decreased precipitation also affected the runoff and the nutrient loads and concentrations. As a result of the RCP4.5 simulation, TP and TN concentrations increased by 24.42% and 58.45%, respectively, in the IST_KEN014 station. Improvements were observed in TN and TP concentrations with the effect of applied BMP simulations. Also, the results revealed that the applied BMP scenarios may contribute to considerable reductions in nutrient loads. Considering the RCP4.5 scenario, BMPs reduced TN loads in the basin by 2.42-10.97%, while reducing TP loads by around 3.60-16.81%. Considering the RCP8.5 scenario, the BMPs reduced the TN loads in the basin between 2.21 and 10.04%, while they reduced the TP loads between 3.57 and 16.67%.

Best management practices to reduce soil erosion and change water balance components in watersheds under grain and dairy production

Soil erosion and sedimentation are among the most serious global environmental problems. Soil and water conservation measures have been proven effective ways to reduce soil loss. The objective of this study was to evaluate the impact of three approaches of soil and water conservation measures (soil management, vegetative measures, and structural practices) on soil erosion and water balance of two paired agricultural watersheds located in Southern Brazil. Streamflow and sediment monitoring was carried out from 2016 to 2019 in the two small paired agricultural watersheds; called North watershed (NW) and South watershed (SW). Modeling using Soil & Water Assessment Tool (SWAT) was performed to simulate individual (nine scenarios) and combined (four scenarios) best management practices (BMPs), by including the three approaches. Among the nine individual BMP scenarios, the most effective in reducing soil erosion was crop rotation and cover crop (sediment yield, SY, reduction of 38.4 for NW, and 28.8% for SW). Among the four combined scenarios, the association of all conservation approaches was the most effective in reducing soil erosion (SY reduction of 46 for NW, and 41.5% for SW), followed by the vegetative measures scenario (SY reduction of 43.5 and 34.1% for NW and SW). All combined scenarios increased infiltration and subsurface water components, and decreased surface runoff. The findings of this study can help farmers and policymakers choosing appropriate BMPs to reduce current soil erosion problems and promote water and soil conservation.

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

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

Assessing multivariate effect of best management practices on non-point source pollution management using the coupled Copula-SWAT model

Best management practices (BMPs) have wide application in non-point source (NPS) pollution abatement in agricultural watersheds. Multivariate analysis of BMPs reduction effects taking their randomness and correlations into account is significant to spatial optimization of BMPs configuration. However, quantifying the correlations among high-dimensional random variables of BMPs effects is challenging and remains unexplored thoroughly. This study coupled the SWAT with the Vine Copula model to conduct multivariate analysis of BMPs reduction effects considering their randomness caused by hydro-meteorological variability along with correlations among different indicators (ammonium nitrogen, NH3-N; and total phosphorus, TP) and BMPs. The coupled model was applied to evaluate the multi-indicator effect of individual BMP and combined effect of various BMPs in the upper Boyang River basin, China. Results showed that bivariate copulas and three-dimensional vine copulas can efficaciously describe the dependence of BMPs effects. Simulation results indicate 43–100% probabilities of 45% NH3-N loads reduction, while 0–79% probabilities of 45% TP loads reduction for combined BMPs scenarios. Besides, the joint probabilities of different indicators in combined BMPs scenarios are generally lower than separate probabilities with 0–21% decrease, which is similar to individual BMP. Generally, joint probabilities using copulas can provide more accurate and factual knowledge of the risk and dependability of implementation of BMPs than univariate variables. The proposed model can conduct multivariate analysis of BMPs reduction effects and has great prospect in the future risk-based decision-making of NPS pollution management.

Spatial Variability of Best Management Practices Effectiveness on Water Quality within the Yazoo River Watershed

Best management practices (BMPs) are management operations that reduce pollution and improve water quality. This study assessed the spatial variability of BMPs effectiveness within the Yazoo River Watershed (YRW) using Soil and Water Assessment Tool (SWAT). Two field-scale watersheds, Merigold Watershed (MW) from the Delta and Skuna River Watershed (SRW) in the Bluff Hills, were selected within the YRW. The SWAT model was calibrated and validated for monthly streamflow, and daily total suspended solids (TSS), total nitrogen (TN), and total phosphorus (TP). Monthly evaluated streamflow Nash–Sutcliffe efficiency indices were in the range from 0.60 to 0.86; daily evaluated TSS indices were in the range from 0.11 to 0.15, TN from 0.11 to 0.12, and TP from 0.05 to 0.26 during model calibration and validation periods. BMPs were implemented in MW and SRW to analyze the spatial variability effect on water quality. Cover crops (CC), vegetative filter strips (VFS), and a combination of VFS and CC were applied as BMP scenarios. Overall, a larger reduction in streamflow was about 15%, sediment about 26%, and nutrient loads, which was about 39% (TN) and 50% (TP), was determined in the MW, whereas in the large watershed (YRW) the reductions in streamflow, sediment, TN, and TP loads were about 4%, 5%, 30%, and 24%, respectively. Therefore, the novelty of this research is to compare the efficiency of a BMP in pollutant reduction at two different geographic scales. The results from this study could help farmers, scientific researchers, precision management planning, and implementing agencies select appropriate BMP for field-scale water resources management in minimizing sediment and nutrient quantities in surface water.

Impacts of Best Management Practices on Runoff, Soil Loss, and Sediment Yield in the Megech Watershed, Ethiopia

This study evaluated the best management practices on how to manage soil losses from catchment and reduce sediment load into a dam reservoir. This study aimed to evaluate the relationship of runoff, soil loss, and sediment yield with best management practice (BMP) scenarios in the GeoWEPP environment for the selected three micro-watersheds (hot spot areas) in the Megech watershed, upper Blue Nile Basin. The impacts of four agricultural BMP scenarios, including forest five years old, corn, soybean; wheat, alfalfa (4 yr) no till; corn, soybean, wheat, alfalfa (4 yr) conservation till; and winter wheat mulch till, on soil loss, runoff, and sediment yield were quantified. The results revealed that soil loss ranges between 41.45–66.11 t/ha/year and sediment yield rates ranges between 36.5–54.8 t/ha/year with the baseline situation (conventional tillage condition) were found to be higher than the tolerable soil loss (10 t/ha/year) in the region. Implementing BMPs on the crop land of the micro-watersheds has positive impacts on all variables’ runoff, soil loss, and sediment yield reductions. Among the implemented BMPs, forests with a five-year perennial (agroforestry) option showed the highest rate of reduction for all runoff, soil loss, and sediment yield, but no cost benefit analysis was included in this study to choose among the BMPs. This study also identified that agricultural BMPs play a great role in reducing runoff, soil loss, and sediment yield in the Megech watershed to minimize on- and off-site impacts. In general, it is important to consider how cost benefit analysis will change throughout project’s implementation among the selected BMP scenarios at the watershed level in the future.

CalBMP, a web-based modeling tool for evaluating pesticide offsite movement and best management practice scenarios in California agricultural land

Quantitative evaluation of best management practice (BMP) effectiveness can help stakeholders to make better watershed management decisions. However, such evaluations are always challenging as they require complex algorithms to simulate the relevant hydrological processes, crop growth and the corresponding pollutant transport pathways in order to evaluate potential BMPs and select the best one for the specific field conditions. In this study, a web-based interface (CalBMP) was developed to predict BMP effectiveness in California, focusing on pesticide modeling at the field scale. With built-in databases for soil, weather, crop, pesticides, and BMPs, users can run simulations for baseline and BMP scenarios using their site-specific field conditions by simply providing the field information, such as zip code, soil, crop management, and pesticide application data. CalBMP uses PRZM5 + , a USEPA model, to simulate pesticide transport and fate at the field edge. The CalBMP simulations were validated based on measurements from an alfalfa field study. The results indicated that the CalBMP interface could reasonably simulate the runoff and adsorbed pesticide loss leaving the field with default parameters from previously known field parameters or public databases. CalBMP underestimated sediment erosion, possibly due to uncertainties in field measurements or inaccurate simulation of the temporal distribution of flood irrigation. CalBMP is likely to underestimate pesticides with greater solubility, such as diuron, because PRZM5 + uses the simplified instantaneous equilibrium sorption model. In addition, a strawberry field study was adopted to demonstrate the capability of the CalBMP interface for simulating BMP effectiveness (pesticide reduction percentage in the main pathways) with easy-to-understand graphs and tables. The results indicated that users can easily compare and review the results from multiple scenarios, which could facilitate the decision-making process for mitigating the amount of active ingredient bifenthrin leaving the field. The CalBMP tool provides useful information on pesticide runoff potential and BMP selection at the field scale. With increasingly stringent regulations for water quality protection, CalBMP will add to the growers’ toolbox for minimizing the environmental impacts from their inevitable pesticide usage.

Economic Impact of Climate Change on the Implementation of Best Management Practices in the Fort Cobb Watershed

AbstractThis study determines the most cost‐effective selection and location of Best Management Practice (BMP) scenarios for farmlands to reduce soil erosion and the delivery of sediment and phosphorus to the Fort Cobb Reservoir watershed under current and future climate scenarios. Using the Soil and Water Assessment Tool, detailed conservation practices (conservation tillage, contour farming, no‐tillage, and terracing) are simulated to determine crop yields, sediment, nitrogen, and phosphorus loss of three crops (winter wheat, irrigated cotton, and pasture) by each land use unit (hydrologic response units) and location in the watershed. An economic model is used to determine the cost‐minimizing choice of BMP scenarios for each land‐use unit that meets 50%, 75%, and 90% reduction of sediment, nitrogen, and phosphorus loads and the impact of climate change on the net return to farmers. Results indicate that the effective spatial placement of BMP scenarios is not the same under different climatic conditions. The average optimal net return to farmers ranges from 170.39 to 316.32 $/acre for all the scenarios. The shadow prices vary from 2.36 to 17.78 $/ton/acre of sediment abated. Although individual BMP scenario is effective in reducing sediment loads, combined BMP scenarios achieve higher performance. This work will help guide policymakers and farmers in decision‐making for the future regarding water quantity used and water quality downstream in the recreation area of the Fort Cobb Reservoir.

Evaluation of the Impact of Best Management Practices on Streamflow, Sediment and Nutrient Yield at Field and Watershed Scales

Evaluating Best Management Practices (BMPs) in watersheds using hydrologic and water quality models can help to establish an effective watershed water management. Soil and Water Assessment Tool (SWAT) was applied to Big Sunflower River Watershed (BSRW) and the Stovall Sherard Watershed (SSW) to evaluate BMP’s impact at watershed and field scale watersheds respectively. SWAT was calibrated and validated for streamflow, sediment yield, total nitrogen (TN), and total phosphorous (TP) at outlets of three sub-basins of the BSRW, and within the SSW. BMP scenarios of check-dam, tail water pond, vegetative filter strips (VFS), nutrient management, and tillage management were evaluated for their efficacy in reducing streamflow, sediment yield, and nutrient loads at field and watershed scales. The VFS was determined as the most effective BMP in decreasing sediment yield, TN, and TP at both field and watershed scales. At field scale, reduction of sediment yield, TN, and TP by VFS ranged from 8 to 12%, 71% to 98%, and 72% to 99% respectively and at watershed scale, reduction of sediment yield, TN, and TP by VFS ranged from 12 to 38%, 29% to 87%, and 42% to 99% respectively. The application of conservation and zero tillage operation showed reduction in sediment yield by 1% to 2% respectively but increased TN and TP by 2% to 25% at field and watershed scale watersheds. This study will help in managing water at field and watershed scale watersheds regarding BMPs selection and implementation.Graphical

IDENTIFYING EROSION HOT SPOT AREAS AND EVALUATION OF BEST MANAGEMENT PRACTICES IN THE TOBA WATERSHED, ETHIOPIA

Ethiopian highlands have been increasingly exposed to the risk of soil erosion and evaluations of how various management practices can reduce the risk of soil erosion are still limited. Here, the calibrated and validated Soil and Water Assessment Tool (SWAT) is used to estimate soil loss rates, identify erosion hotspot areas and evaluate effective best management practices (BMP) to curb the risk of soil erosion. The annual sediment yield (SY) in Toba watershed varies from 0.09 t ha-1 yr-1 to 44.8 t ha-1 yr-1 with an average SY of 22.7 t ha-1 yr-1. Cultivated lands on steep slopes are the sources of extensive soil loss rate, whereas areas with good vegetation cover have low SY. The increased population pressure, increased cultivation of steep slope and uncontrolled grazing are the causes of high SY in the watershed. 17 sub-basins with SY higher than the tolerable erosion of Ethiopia (2-18 t ha-1 yr-1) are considered for the application of BMP scenarios. Implementing all BMPs could reduce the extent of SY but with varying degrees and combination of the BMPs are more pronounced and desirable. Reforestation with vegetative strips was the most effective management (87.8% reduction) followed by soil/stone bund with vegetative strips (83.7% reduction). These findings are important to ensure sustainable land management and promote sustainable agricultural production in a rapidly changing agricultural watershed. In general, the result highlights the need for regional developments and cooperation to urge for strong BMPs strategies for the rapid land and water resources degradation.

Efficiencies of best management practices in reducing nitrate pollution of the Sebdou River, a semi‐arid Mediterranean agricultural catchment (North Africa)

AbstractA major problem facing the water sector in Algeria is deteriorating water quality, which is strongly influenced by nutrient inputs to agricultural watersheds. To mitigate the effects of agricultural activities and enhance water quality, this study considered the impact of different best management practices (BMPs) in agriculture. The objective of the research was to evaluate the impacts of various agricultural BMPs on nitrate losses in the Sebdou catchment in north‐west Africa using the Soil and Water Assessment Tool (SWAT) model in order to identify and recommend the most appropriate BMP. The study was carried out in two parts: first, the SWAT model was calibrated and validated to simulate discharge and nitrate losses at the outlet of the catchment, and second, the calibrated model was used to assess the effects of BMPs on nitrate losses. The hydrological modelling fitted well with the observed data for the calibration and validation periods (NSE between 0.63 and 0.65 and R2 between 0.80 and 0.92). Nitrate simulation was also satisfactory (NSE = 0.58 and R2 = 0.58), with the average nitrate exports at the outlet varying between 136 and 149 t N year−1. Agricultural tillage practices were the main N input and plant uptake was the main N output. The simulation results of BMP scenarios (contour farming, strip cropping and terracing) showed a significant decrease in nitrate quantity in soil, nitrate yield in surface run‐off and nitrate exports. The maximum reduction was observed from the use of parallel terraces, which reduced nitrate in soil by 17% (41 kg ha−1) and decreased nitrate flux exportation to below 133 t N year−1 (a reduction of about 11%). This study provided useful information for implementation of the most effective agricultural BMPs in the catchment for stakeholders who are interested in soil and water management.

Efficiency and feasibility of Best Management Practices to reduce nutrient loads in an agricultural river basin

Excessive use of mineral fertilizers and inappropriate tillage operations are two main drivers of land degradation. The European Green Deal (EUGD) aims to restore the natural functions of ground and surface soil by 2030. EU Member States will be called upon to include mitigation measures in their own management programs. In this context, the current work aimed to evaluate the feasibility of Best Management Practices (BMPs), generally used to counteract soil erosion, in achieving nutrient load reduction, and evaluate their economic convenience in the private and public sector. The Soil and Water Assessment Tool (SWAT) was used to model point and diffuse nutrient sources in the Carapelle basin (Apulia, Italy) and to simulate BMP scenarios. Contour farming (CF), no tillage (NT), reforestation (RF), and two additional scenarios, including the 20% reduction of fertilizers in CF and NT, (CFR) and (NTR), were simulated following the EUGD strategy. For the current land uses, the riverine export of nitrogen (TN) and phosphorous (TP) were ∼49 kg ha-1y-1 and ∼0.044 kg ha-1y-1, respectively. CF and NT increased N-NO3 load both into surface runoff and in terms of leaching. Conversely, RF showed a reduction of N-NO3 losses. CFR and NTR scenarios decreased N-NO3 load both in surface runoff and leached of ∼20%. CFR and NTR represented the best alternative among the analyzed scenarios both for their lower production costs at the farm level and for their savings in terms of nutrient and soil losses. RF was economically profitable in sloped areas, thus representing BMPs that may be implemented in combination with other practices to have a greater impact at the basin scale. BMP implementation requires significant investments (public and private). The results of this study provide the scientific basis for decision-making for agriculture and watershed management.

Evaluating the Effectiveness of Best Management Practices On Soil Erosion Reduction Using the SWAT Model: for the Case of Gumara Watershed, Abbay (Upper Blue Nile) Basin

This study was conducted to evaluate the effectiveness of best management practices (BMPs) to reduce soil erosion in Gumara watershed of the Abbay (Upper Blue Nile) Basin using the Soil and Water Assessment Tool (SWAT) model. The model was calibrated (1995-2002) and validated (2003-2007) using the SWAT-CUP based on observed streamflow and sediment yield data at the watershed outlet. The study evaluated four individual BMP Scenarios; namely, filter strips (FS), stone/soil bunds (SSB), grassed waterways (GW) and reforestation of croplands (RC), and three blended BMP Scenarios, which combines individual BMPS of FS and RC (FS & RC), GW and RC (GW & RC), and SSB and GW (SSB & GW). Mean annual sediment yield at the baseline conditions was estimated at 19.7 t ha-1yr-1, which was reduced by 13.7, 30.5, 16.2 and 25.9% in the FS, SSB, GW, and RC Scenarios, respectively at the watershed scale. The highest reduction efficiency of 34% was achieved through the implementations of the SSB & GW Scenario. The GW & RC, and FS & RC Scenarios reduced the baseline sediment yield by 32% and 29.9%, respectively. The study therefore concluded that the combined Scenarios mainly SSB & GW, and GW & RC can be applied to reduce the high soil erosion in the Gumera watershed, and similar agro-ecological watersheds in Ethiopia. In cases where applying the combined scenarios is not possible, the SSB Scenario can yield significant soil erosion reduction.

Evaluating nitrate and phosphorus remediation in intensively irrigated stream-aquifer systems using a coupled flow and reactive transport model

In irrigated semi-arid watersheds, over-fertilization often leads to nitrogen (N) and phosphorus (P) contamination in aquifers and river systems. Modelling tools often are used to evaluate the effect of management practices on nutrient contamination levels. In this study, we assess a suite of best management practices (BMPs) for N and P in a regional irrigated stream-aquifer system using a new numerical model. As it is necessary to consider the interaction of flow in the stream and aquifer, SWAT-MODFLOW model that couples surface and groundwater flow was used. The reactive processes were modelled using RT3D that simulate the reactive groundwater transport. The model is based on the coupled flow model SWAT-MODFLOW, with the groundwater reactive transport model RT3D included to simulate the reactive groundwater transport of NO3 and soluble P and their interactions within the soil-aquifer-stream system. The assessment is performed for a highly managed 732 km2 region in the Lower Arkansas River Valley (south-eastern Colorado), with model results compared to observed groundwater nutrient concentration, in-stream nutrient concentration and loading, and crop yield. A total of 28 BMPs scenarios are evaluated regarding their impact on NO3 and soluble P contamination in the aquifer and river system. The most effective individual BMP in most areas is to decrease fertilizer by 30%, resulting in NO3 and soluble P reduced by 20% and 2% for groundwater concentrations, 25% and 10% for river concentrations, and 27% and 6% for mass loadings into surface water, respectively. Combinations of using 30% irrigation reduction, 30% fertilization reduction, 60% canal seepage reduction, and conservation tillage yield the greatest overall impact to lower NO3 and soluble P concentrations up to 41% and 8% in groundwater, 52% and 40% in river, and 63% and 49% for mass loadings. Targeting BMPs on localized problem areas shows great promise in reducing contamination while maintaining region-wide crop yield. The study demonstrates the SWAT-MODFLOW-RT3D modelling code is a useful tool to examine NO3 and P transport and quantify BMP effects in groundwater-driven watersheds.

Soil erosion prediction in Cilebak – Cirasea Micro Watershed, Indonesia

Soil erosion impact on land degradation could threaten soil and water quality. In the mountainous area, soil erosion resulted in losses of topsoil, which containing high nutrients. The study area was located in Cilebak-Cirasea Micro Watershed, Bandung Regency, Indonesia. Landuses in this area were secondary forest (12%), upland agriculture (84%), and paddy field (4%). The objectives of this study were to assess soil erosion and study best management practices (BMP) effect to reduce soil erosion. Universal Soil Loss Equation (USLE) was used to estimate soil erosion with support from Geographic Information System (GIS). USLE parameters, which consist of erosivity, erodibility, slope length, steepness, crop, and soil management, were used to estimate soil erosion. BMP scenarios consist of application raised bed that parallel to contour lines and combination of raised bed that parallel to contour lines and straw mulch addition of 3 and 6 Mg ha−1 year−1. The result indicated that soil erosion rate under current condition was 45.4 Mg ha−1 year−1, which exceeding the tolerable soil loss. All BMP scenarios showed their effectiveness in reducing soil erosion. Proposed BMP to minimize soil erosion rate could probably be able to support government in arranging policies for maintaining or restoring crop productivity for sustainable agriculture.

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.

Evaluating the performance of BAM-based blanket filter on nitrate reduction in a karst spring

Understanding the effects of best management practices (BMPs) on nitrate reduction in karst aquifers is critical for spring restoration. In this study, Conduit Flow Process (CFPv2) and Conduit Mass Three-Dimensional (CMT3D) models were applied to evaluate nitrate removal for Silver Springs in Florida using blanket filters composed of biosorption-activated media (BAM). As the inputs of the model, the spatial and temporal variability of nitrate-N concentration in groundwater recharge was estimated as a function of population and land use, reflecting both point and non-point sources of nitrate. Additionally, the spatial heterogeneity of nitrate removal efficiency in the soil was considered in the evaluation. The model estimates that conduit flow accounts for 48% of spring discharge and 47% of nitrate-N mass transport on average, and the contributions of conduit to flow and nitrate mass transport are higher during wet years. The net effect of nitrate reduction in spring discharge was evaluated for two BMP scenarios, i.e., implementing BAM-based blanket filters in 26 stormwater retention basins and 50% of the urban area. The net effect of the BMP on nitrate reduction for Scenario 1 is limited; whereas, for Scenario 2, the nitrate-N concentration will be reduced to 1.08 mg/L in 2026 for a nitrate removal efficiency of 74% (i.e., a 4.9% reduction relative to the baseline condition). This study suggests that the BAM-based blanket filters benefit is likely to scale with penetration (i.e. greater water quality benefits can be expected with greater BMP implementation). Further, this study shows that whether BAM-based blanket filters leads to net water quality improvements or degradation depends on whether BAM removes more or less nutrients from stormwater than the unaltered soil profile. The simulated effects of the BMP on nitrate reduction may serve as an additional guidance for water resources managers to make decisions on investments in nutrient reduction technologies for spring restorations in karst systems.