Implementation Of Best Management Practices Research Articles

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.

Evaluating Best Management Practice Efficacy Based on Seasonal Variability and Spatial Scales

Implementing best management practices (BMPs) has proven to be an efficient method for reducing non-point source (NPS) pollutants. Agricultural NPS pollution is considered to be a major contributor to water quality impairment. This study aims to assess the variation in hydrologic and water quality outputs at field and watershed scales when BMPs are implemented using modeling approaches. The Yazoo River Watershed (YRW) is the largest watershed basin in the state of Mississippi with approximately 50% agricultural land. Runoff generated from agricultural areas carries sediments and nutrients. The Merigold watershed (MW) is a sub-basin of the YRW and a field-scale watershed with most of the land use being agriculture. It is essential to quantify the streamflow, sediment, total nitrogen (TN), and total phosphorus (TP) when BMPs are implemented. BMPs such as vegetative filter strips (VFS) and cover crops (CC) were tested in this study. The Soil and Water Assessment Tool (SWAT) model was applied to quantify the watershed’s hydrologic and water quality outputs. SWAT model accuracy assessment was performed by calibration and validation process using the Nash and Sutcliffe Efficiency Index (NSE). Model performance was satisfactory for monthly streamflow, with NSE values in the range of 0.62 to 0.81, and for daily sediments, TN, and TP load estimation, with NSE values of 0.21, 0.20, and 0.47, respectively. CC was planted after harvesting the main crop. Therefore, it is essential to quantify the seasonal reduction in pollutants. Water quality was improved after BMP implementation, and an overall decrease in streamflow, sediment, TN, and TP loads was observed for both MW and YRW during dry and wet seasons. Previous studies regarding seasonal assessments with CC implementation in the MW and YRW were limited. Therefore, the results from this study could be a unique addition to the scientific literature.

A stochastic simulation-based chance-constrained programming model for optimizing watershed best management practices for nonpoint source pollution control under uncertainty

In this study, a stochastic simulation-based chance-constrained programming (SSCP) model is developed by integrating soil and water assessment tool (SWAT), generalized likelihood uncertainty estimation (GLUE), chance-constrained programming (CCP) and genetic algorithm (GA) for managing non-point source (NPS) pollution under uncertainty. The SSCP model improves upon conventional simulation-based optimization methods by effectively (i) reflecting the propagation of stochastic uncertainties from the SWAT to the optimization framework by the joint GLUE and CCP (GLUE-CCP) approach, and (ii) identifying the optimal implementation levels of best management practices (BMPs) under different constraint-violation risk levels. The SSCP is solved using a GA with parallel sampling technique after conversion into the corresponding deterministic version. The model is applied to determine the optimal types, sizes and locations of BMPs for NPS pollution control in the Hanjiang River basin, China. The results indicate that, under low-risk conditions, grassed waterways and filter strips should be implemented in the northern part of the basin and larger detention ponds of about 637.8 ∼ 850.4 ha should be installed in the northern and eastern parts of the basin; whereas under high-risk conditions, filter strips should be installed in the northeastern part of the basin and larger detention ponds of about 562.1 ∼ 749.5 ha should be installed in the northern and southwestern parts of the basin. Moreover, as the risk level decreases, stricter control of constraint violations leads to higher BMP implementation costs in order to mitigate the risk of excessive NPS pollution loads. Thus, the proposed model provides valuable insights into the selection of BMP placement schemes at various risk levels, facilitating the reduction of NPS pollution at the outlet of the Hanjiang River basin to acceptable levels while considering the tradeoff between system cost and risk.

Advancing equitable stormwater management: A decision support tool integrating best practices for nutrient removal and environmental justice

Stormwater runoff is a significant contributor to nutrient pollution, leading to water quality degradation and ecological imbalances. The management of stormwater runoff and nutrient pollution faces significant challenges due to inadequate assessment tools for evaluating nutrient loads across multiple watersheds at the state level and the absence of an open-source tool that can comprehensively assess the effectiveness of stormwater Best Management Practices (BMPs) in nutrient removal while incorporating environmental justice (EJ) considerations. To address these challenges, we developed an innovative online statewide tool that identifies areas where BMP planning needs to be prioritized to address environmental disparities resulting from high pollutant loads intersecting with disadvantaged communities, alongside tracking pollutant loads after various BMP implementations. In doing so, we estimated pollutant loads including total phosphorus (TP), total nitrogen (TN), biochemical oxygen demand (BOD), and total suspended solids (TSS) from urban land use in 1378 HUC-12 watersheds across Florida using EPA's pollutant load estimate tools (PLET), which calculates loads based on factors such as land use, septic systems and wastewater discharge, soil characteristics, and precipitation. To integrate BMP implementation with EJ considerations, a social vulnerability index was developed to identify tiers of sociodemographic disparities using racial/ethnicity metrics (e.g., % black, % Hispanic, etc.) and socioeconomic metrics (e.g., median household income, educational attainment, etc.). We then investigated the effectiveness of 28 urban stormwater BMPs in reducing pollutant loads and estimated post-BMP loads for each watershed. Hotspots of nutrient pollution were primarily identified in coastal areas, with residential land use as the main contributor. Miami-Dade, Broward, and Hillsborough counties had the highest sociodemographic disparities. In addition, central and southern Florida exhibited a disproportionate exposure of disadvantaged communities to pollutant loads. The developed online tool contributes significantly to holistic watershed management by features including visualizing the distribution of nutrient pollution loads across state watersheds, identifying areas with high pollutant loads intersecting with disadvantaged communities, and quantifying pollution load reductions post-BMP implementation. This research promotes equitable outcomes and empowers stakeholders in Florida to adopt sustainable and inclusive practices for water quality improvement.

Evaluating water quality change with hydrologic restoration in the Western Everglades (Florida, USA), an application of WAM

Hydrologic restoration at the watershed scale is a complex process that can influence other processes and conditions within the watershed and downstream systems. Given these interrelated watershed scale processes, tools like models are essential to assess the potential effectiveness of sub-watershed to regional remediation strategies for ecological restoration. The goal of Everglades restoration is to restore the quality, quantity, and timing of water to one of the most ecologically unique and complex systems. This study aimed to evaluate changes to water quality associated with hydrologic restoration efforts within the Feeder Canal Basin as identified by the Western Everglades Restoration Project (WERP) by demonstrating, through simulations the potential effectiveness of implementing water quality remediation measures such as Best Management Practices (BMPs) and Stormwater Treatment Areas (STAs) within the WERP area. Additionally, to understand potential phosphorus sources and pre-develpoement conditions within the basin, a pre-development baseline was developed. Using the Watershed Assessment Model (WAM) various model alternatives including the WERP tentatively selected plan (TSP) were developed for a 22 year period of simulation. The implementation of both moderate and aggressive BMPs significantly reduced total phosphorus concentrations within the canal system at various levels indicating an improvement to near-field conditions. Meanwhile, not until the moderated BMPs and operation of an STA do water quality improvement become realized further downstream. The combined strategy of BMPs and STA demonstrates the integrated nature of nutrient remediation with both near and far-field benefits to the system with hydrologic restoration. This integrated strategy of water quality and hydrologic restoration can lead to a more sustainable and resilient restored ecosystem.

Effectiveness and resilience of BMPs to watershed climate adaptation considering the uncertainty of hydrological model and GCMs

Climate change significantly impacts catchment hydrologic and water quality processes. Best management practices (BMPs) can serve as adaptation strategies to negate the impact of climate change on sediment and total nitrogen (TN) loads. One major controversial issue in climate change adaptation studies is the highly uncertain nature of such changes. Previous studies have rarely focused on the combined impact of the uncertainty in climate change and watershed model parameters, which could be the main sources of uncertainty in climate change adaptation research. In this study, the effectiveness and resilience (defined as continued effectiveness under a changing climate) of BMPs in reducing sediment and TN loads were explored under future climate change in the Shanmei Reservoir watershed (SMW) of Southeast China. Climate change projections provided by 10 general circulation models (GCMs) under the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios from 2031 to 2060 were applied in the Annualized Agricultural Nonpoint Source (AnnAGNPS) model to evaluate the effectiveness and resilience of 4 BMPs (riparian buffers (RB), no-tillage (NT), fertilization reduction (FR), and parallel terraces (PT)). The ensemble average of 10 GCMs and 10 behavior parameter groups were adopted to reduce the uncertainty resulting from the hydrological model parameters and GCMs. The results indicated that the average annual temperature and precipitation in the SMW will increase in the future. On a seasonal scale, the average temperature during all seasons will increase, and precipitation will decrease in summer and autumn but increase in spring and winter. The annual sediment and TN loads will decrease, but the loads in spring and winter will increase. BMPs could be effective as climate adaptation strategies for reducing sediment and TN loads under future climate conditions, with PT as the most effective option. Structural BMPs were more effective in reducing sediment and TN loads in spring and winter, whereas nonstructural BMPs were more effective in reducing loads in summer and autumn. BMPs were more resilient when future watershed runoff changes were slight or climate sensitivity was reduced, with higher BMP resilience in spring and winter than in summer and autumn. This study aimed to provide systematic references for watersheds through the implementation of BMPs for mitigating the effects of climate change and extending the boundaries of the AnnAGNPS model application.

A Comparison of Forest Biomass and Conventional Harvesting Effects on Estimated Erosion, Best Management Practice Implementation, Ground Cover, and Residual Woody Debris in Virginia

Expanding markets for renewable energy feedstocks have increased demand for woody biomass. Concerns associated with forest biomass harvesting include increased erosion, the applicability of conventional forestry Best Management Practices (BMPs) for protecting water quality, and reduced woody debris retention for soil nutrients and cover. We regionally compared the data and results from three prior independent studies that estimated erosion, BMP implementation, and residual woody debris following biomass and conventional forest harvests in the Mountains, Piedmont, and Coastal Plain of Virginia. Estimated erosion was higher in the Mountains due to steep slopes and operational challenges. Mountain skid trails were particularly concerning, comprising only 8.47% of the total area but from 37.9 to 81.1% of the total site-wide estimated erosion. BMP implementation varied by region and harvest type, with biomass sites having better implementation than conventional sites, and conventional Mountain sites having lower implementation than other regions. Sufficient woody debris remained for BMPs on both harvest types in all regions, with conventional Mountain sites retaining twice that of Coastal Plain sites. BMPs reduced the estimated erosion on both site types suggesting increased implementation could reduce potential erosion in problematic areas. Therefore, proper BMP implementation should be ensured, particularly in Mountainous terrain, regardless of harvest type.

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.

Contrasting Impacts of Agricultural Intensification and Urbanization on Lake Phosphorus Cycling and Implications for Managing Eutrophication

AbstractSediment core and water quality data, together with historical information on land use/land cover (LULC), were used to reconstruct changes in phosphorus (P) loading and cycling in Lake Wilcox, Ontario, Canada, since the early 1920s. After first being cleared for farming, the originally forested watershed subsequently underwent urbanization. The large increase in P loading accompanying agricultural intensification after World War II caused the eutrophication of the lake. However, improved soil conservation since the 1980s and urban stormwater management since the 1990s have brought watershed P loading and sediment accumulation down to levels comparable to the early 1900s. Yet, the lake continues to exhibit eutrophication‐like symptoms, especially the intensification of hypoxia in the hypolimnion. Post‐2000 water quality data indicate that the latter is not driven by external P loading from the watershed, but rather by rapid salinization that strengthens the lake's summer stratification and enhances internal P loading. Salinization is caused by the increasing application of deicing agents in the expanding urban area. Curbing salt inputs will therefore be essential to restore the lake. Overall, our results provide new insights into the shifts in lake biogeochemistry associated with LULC changes and the implementation of best management practices. The approaches and findings of our case study have broad applicability for the large number of freshwater ecosystems worldwide that are experiencing salinization.

A spatial dependence approach to assessing the impacts of Sustainable Forestry Initiative’s Fiber Sourcing certification on forestry Best Management Practices in Georgia, United States

Understanding the effectiveness of the Sustainable Forestry Initiative Fiber Sourcing (SFI-FS) standard in increasing/sustaining a high forestry Best Management Practices (BMP) implementation rate is critical for the overall sustainability of southern forestlands. We analyze the impacts of SFI-FS standard on the forestry BMP implementation rate in Georgia, United States, by considering the locations of certified and non-certified mills between 2002 and 2019. The results show each increasing non-certified sourcing area overlap reduces BMP rates by 0.15%, while the same rate goes up by 0.08% overall with each increasing certified sourcing overlap. Moreover, the results of the spatial analyses indicate that neighbors' certified overlaps have a negative effect on average forestry BMP rates associated with a sourcing mill, even though the overall effect is positive. An increase in own harvesting area and mill size reduces BMP rates by 0.056%, but an increase for neighboring sourcing mills increases them by 0.063%, showing an overall positive effect of these two variables. These findings reflect the supply chain inefficiency brought on by concurrent contracting behavior between small mills and their larger certified neighbors. BMP rates are higher in the mill sourcing area by 0.023%, with each increase in the presence of perennial streams, further indicating that loggers are adequately following BMPs in areas that have perennial streams. Our overall results show that spatial dependence is an essential mechanism for ascertaining the effectiveness of SFI-FS standard at large spatial scales.

Abortion and fetal death in sows.

Abortion in sows or the expulsion of foetuses between days 35 and 109 of gestation results in major financial losses. Abortion is the result of maternal failure due to factors interfering with either the endocrine control of pregnancy or causing endometrial damage. In addition, causes of fetal origin, due to infections with a special affinity for the fetus, can also lead to abortion. Many different non-infectious and infectious factors may be involved. Non-infectious risk factors include inappropriate ambient temperature, seasonal effects, different stress factors, and toxic substances. Microorganisms that may cause abortion can be classified as facultative pathogenic and specific pathogenic microorganisms. The first category includes mostly bacteria that are endemic in many pig farms and that are normally harmless commensals. They can cause abortion only in case of decreased immunity or other predisposing factors. Different specific pathogenic microorganisms, especially viruses and bacteria, can cause fetal death and abortion. Some may have a special affinity for the reproductive tract and the foetuses (e.g. Aujeszky's disease virus, parvovirus, Leptospira sp.), while others may cause clinical disease or fever in sows (e.g. swine influenza viruses, Erysipelothrix rhusiopathiae), subsequently leading to abortion. Diagnosis of fetal death and abortion is challenging due to the broad array of processes that may be involved, and the fact that the inciting cause may happen well in advance of the abortion. The diagnostic process should start with a thorough evaluation of the clinical problem and the farm. In case an infectious cause is suspected, proper samples should be collected, preferably from different sows and foetuses, for the detection of specific pathogens. Prevention of abortion mainly relies on the implementation of good management practices, hygiene and biosecurity measures, and for some pathogens also on vaccination.

Evaluating the feasibility and potential of unmanned aerial vehicles to monitor implementation of forestry best management practices in the coastal plain of the southeastern United States

Compared to undisturbed areas, timber harvest activities, including road construction, skid trails, and stream crossings, exhibit the potential for causing erosion and sedimentation if forestry best management practices (BMPs) are not implemented. Forestry BMP monitoring serves as a tool to evaluate BMP implementation status. Conventional on-the-ground BMP monitoring has contributed substantially to assessing BMP implementation. However, conventional on-the-ground surveys can be time consuming. Unmanned aerial vehicles (UAVs) have been rapidly emerging as a new tool for local-scale monitoring. In this study, we evaluated the feasibility and potential of UAVs for monitoring forestry BMPs in the coastal plain of southeastern United States. We compared the performance of UAV-live feed surveys and UAV-created map surveys with conventional on-the-ground surveys across major BMP categories on 30 study sites using BMP guidelines and implementation survey questions from Alabama, Georgia, and Florida for the sites specific to that state (10 sites in each state). The UAV-live feed surveys involved real-time assessments conducted using the live feed function, enabling on-the-spot evaluations. Whereas the UAV-created map surveys entailed autonomous UAV flight to collect imagery specifically for generating maps and facilitating subsequent assessments.We found that using a UAV for monitoring BMPs efficiently provided an overview of a timber harvest area from above. UAV-live feed surveys were as effective as conventional on-the-ground surveys across all major BMP categories. Specifically, the Cramer's V correlation between the responses from UAV-live feed and conventional on-the-ground surveys for all BMP categories, was 0.95 (p < 0.0001) for detecting implemented BMPs and 0.86 (p < 0.0001) for detecting when BMPs were not implemented but needed to be. UAV-created map survey results vs. conventional on-the-ground surveys were not as effective (V of 0.79 for detecting implemented BMPs and 0.46 for detecting BMPs not implemented but needed). Waste and stream crossing BMP implementation were the most difficult to verify using the map surveys, which was not an issue with the live feed surveys due to the capability to evaluate those BMPs at different camera angles. While UAV-created map surveys may be less effective, they provide an observation record that includes a map of the site. This project also developed a standardized framework for using UAVs to monitor forestry BMPs, including instructions and procedures for conducting UAV-live feed and map surveys. In conclusion, a UAV using the live feed function in the field is a feasible option to monitor forestry BMPs.

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.

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.

Analyzing the impact of agricultural BMPs on stream nutrient load and biotic health in the Susquehanna-Chemung basin of New York

Despite the widespread use of agricultural best management practices (BMPs) to reduce watershed scale nutrient loads, there remain few studies that use directly observed data – instead of models – to evaluate BMP effectiveness at the watershed scale. In this study, we make use of extensive ambient water quality data, stream biotic health data, and BMP implementation data within the New York State portion of the Chesapeake Bay watershed to assess the role of BMPs on reducing nutrient loads and modifying biotic health in major rivers. The specific BMPs considered were riparian buffers and nutrient management planning. A simple mass balance approach was used to evaluate the role of wastewater treatment plant nutrient reductions, agricultural land use changes, and these two agricultural BMPs in matching observed downward trends in nutrient load. In the Eastern nontidal network (NTN) catchment – where BMPs have been more widely reported – the mass balance model suggested a small but discernible contribution of BMPs in matching the observed downward trend in total phosphorus. Contrastingly, BMP implementations did not show clear contributions towards total nitrogen reductions in the Eastern NTN catchment nor for the total nitrogen and phosphorus in the Western NTN catchment, where BMP implementation data are more limited. Assessment of the relationship between stream biotic health and BMP implementation using regression models found limited connection between extent of BMP implementation and biotic health. In this case, however, spatiotemporal mismatches between the datasets and the relatively stable biotic health, typically of moderate to good quality even before BMP implementation, may reflect the need for better monitoring design to assess BMP effects at the subwatershed scale. Additional studies, perhaps using citizen scientists, may be able to provide more suitable data within the existing frameworks of the long-term surveys. Given the preponderance of studies that rely only on modeling to understand nutrient loading reductions achieved by implementation of BMPs, it is essential to continue to collect empirical data to meaningfully evaluate whether there are actual measurable changes due to BMPs.

Best Management Practices Affect Water Quality in Coastal Watersheds

Coastal ecosystems are vulnerable due to watershed sediment and nutrient loads. In this study, the hydrology and water quality of two coastal watersheds, Wolf River watershed (WRW) and Jourdan River watershed (JRW), were assessed using the Soil and Water Assessment Tool (SWAT). Model performance evaluation was performed using the coefficient of determination (R2) and the Nash–Sutcliffe Efficiency (NSE). After model calibration and validation, the effectiveness of ponds, wetlands, riparian buffers, and their combination as best management practices (BMPs) were analyzed. Total suspended solids (TSS) was reduced by 31.15% in the pond scenario and 30.37% in the wetland in WRW. In addition, mineral phosphorous (MinP) was reduced by 11.84% and 9.63% in ponds and wetlands, respectively. Similarly, in JRW, TSS was reduced by 74.89% in ponds and 74.90% in wetlands. Likewise, ponds and wetlands reduced MinP by 8.05% and 13.40%, respectively. Among four riparian buffer scenarios, the 30 m buffer prompted the estimation of higher reductions such as TSS by 28.36% and MinP by 29.77% in WRW, whereas a 13.14% TSS and 22.89% MinP reduction in JRW. In addition, combined BMP, TSS was reduced by 30.37% and MinP by 52.09% in WRW, followed by a 74.92% reduction in TSS and 27.37% in MinP in JRW. All BMP implementations were effective in reducing TSS and MinP. This study suggests that ponds and wetlands were effective in reducing TSS and riparian buffers were effective in reducing MinP. These findings could be insightful in coastal watershed management.

Short-term response of soil aggregate stability and labile carbon to contour tillage, diversion terrace, grassed waterway, and tile drainage implementation

Soil degradation has been of great concern for New Brunswick's potato farmers, especially on sloped land and shallow soils. In this study, we evaluated the initial response of labile soil carbon (C) fractions (permanganate oxidizable C (POXC) and particulate organic C (POC)) and aggregate stability to two integrated best management practices (BMPIs) composed of the following individual practices: diversion terraces (DT), grassed waterways (GW), and contour tillage (CT) (i.e., DTGW) and DT, GW, CT, and tile drainage (TD) (i.e., DTGW + TD), relative to CT that served as a control. The more water was regulated in the field, the greater the increase in labile C; where DTGW and DTGW + TD gained 19.8% and 50.6% of POXC, respectively, while CT lost 11.2% of POXC. There was an increase in mineral associated organic matter C in the terraced BMPIs, despite the high amount of tillage events that took place during potato cultivation. Two BMPIs had no effect on aggregate stability, most likely due to the short duration of this initial monitoring study that spanned just over two growing seasons. Even though there were no improvements in soil structure, our findings showed that some stabilization of soil C is possible even during the initial two seasons following BMPI implementation.

The legacy of intensive agricultural history on the soil health of (sub)tropical landscapes

Soil health conceptualized as a measurable ecosystem property provides a powerful tool for monitoring progress in restoration projects or implementation of best management practices to improve degraded lands and promote sustainable agroecosystems. We surveyed soils collected from a range of land uses (i.e., protected native and non-native forest, managed pasture, unmanaged previously intensive agricultural lands, organic cropland, and conventional cropland) across a range of soil orders (Oxisol, Mollisol, Andisol, Inceptisol, and Vertisol) on three Hawaiian Islands. Forty-six soil health indicators encompassing biological, chemical, and physical properties were measured. In this multivariate survey, the most distinct group was the unmanaged, previously intensive agriculture lands, which was significantly different from all other land uses even when considering differences in mineralogy. Importantly, the soil health indicators of well-managed pastures in Hawaiʻi were not different from protected forests, suggesting that well-managed grazing lands may be as healthy and resilient as protected forests. A suite of 11 readily measured indicators emerged out of a first-principle approach to determining a holistic indication of soil health across a range of soils and systems in Hawaiʻi encompassing much of the diversity in the tropics and subtropics. Every land use may improve its soil health status within a reasonable range of expectations for a soil’s land use history, current land use, and mineralogy. Key drivers of inherent differences in the soil health indicators, including intensive land use history, current land use practices, and mineralogy, must be interwoven into the soil health index, which should set minimum and maximum benchmarks and weight indicators according to equitable standards.

Optimization and multi-uncertainty analysis of best management practices at the watershed scale: A reliability-level based bayesian network approach

Best management practices (BMPs) have been widely adopted to mitigate diffuse source pollutants, and the simulated processes of its pollutant reduction effectiveness suffer from manifold uncertainties, such as watershed model parameters and climate change. We presented a novel Bayesian modeling framework for BMPs planning, integrating process-based watershed modeling and Bayesian optimization algorithm to reveal the impact of multiple uncertainties. The proposed framework was applied to a BMPs planning case study in the Erhai watershed, the seventh-largest freshwater lake in China. Firstly, priority management areas (PMAs) were identified for BMPs siting using a simulation-optimization approach. Bayesian networks were subsequently embedded to reveal the multiple uncertainty sources in the optimal planning and the reliability level (RL) is introduced to represent the probability to meet the water quality target with BMPs implementation. The results suggest that ENS of discharge and nutrients concentration simulation by LSPC are both greater than 0.5, which displays satisfactory performance. The identified PMAs account for 0.8% of the total watershed areas while contribute to more than 15% of nutrient loadings reduction. The analysis of multiple uncertainty sources reveals that precipitation is the most influential source of uncertainties in BMP effectiveness. The construction of hedgerows plays an important role in the nutrient reduction. With the improvement of the reliability levels, the cost increases sharply, indicating that the implementation of BMPs has a marginal utility. The study addressed the urgent need for effective and efficient BMPs planning by identifying PMAs and addressing multi-source uncertainties.

Planning of best management practices for watershed-scale pollution control: A simulation-based inexact fractional programming approach

The implementation of best management practices (BMPs) is crucial for protecting and restoring watersheds from nonpoint source (NPS) pollution. BMP placement plans with a high pollution reduction to cost ratio are highly desired by decision makers. Nevertheless, few studies tackled such a ratio optimization problem in their efforts to identify BMP placement plans. BMP planning also faces challenges in handling inherent uncertainties and estimating NPS pollution loads. To address these gaps, a simulation-based inexact credibility-constrained mixed-integer fractional programming (SICMFP) model was proposed for supporting the placement of BMPs. This model was developed by integrating the export coefficient model (ECM), compound topographic index (CTI), inexact programming, and mixed-integer programming within a fractional programming framework. SICMFP extends the capability of previous BMP placement models by optimizing the ratio of conflicting objectives and handling uncertain parameters based on interval theory and credibility measure. It can also conveniently simulate the spatiotemporal distribution of pollution loads through the ECM, and efficiently identify potential wetland sites using CTI. SICMFP was applied to plan BMP placement in the Luan River Basin, located in northern China. The results showed that SICMFP could provide BMP placement plans with the optimal system efficiency between pollution reductions and cost savings under different credibility levels. These plans could help decision makers gain in-depth insights into the tradeoffs between expected system efficiency and the risk of constraint violation. As the credibility level rises from 0.6 to 0.9, the optimal ratio between pollution reduction and cost declined from [0.88, 1.66] kg/103 yuan to [0.70, 1.15] kg/103yuan, whereas the costs and pollution reductions increased. Compared with the least-cost single-objective model, SICMFP could lead to more pollution reductions and higher system efficiency. The developed SICMFP approach can also be extended to address the ratio optimization problems of water pollution management in other watersheds.