Cost-effectiveness and cost-benefit analysis of BMPs in controlling agricultural nonpoint source pollution in China based on the SWAT model

Can the best management practices resist the combined effects of climate and land-use changes on non-point source pollution control?

Climate and land-use changes have an overlying impact on non-point source (NPS) pollution in river basins. However, the control effect of Best Management Practices (BMPs) for NPS pollution is not yet clear under future scenarios. The Soil and Water Assessment Tool (SWAT) model was coupled with the entropy-weighted method, global climate patterns and land-use data to explore the dynamic variations in total nitrogen (TN) and total phosphorus (TP) loads in the Jing River Basin during the baseline (2000-2020) and future periods (2021-2065), evaluate the pollution reduction effectiveness of individual and combined BMPs, and propose practical BMP configurations. Results indicate that a future trend of urban land expansion, particularly in the economic scenario (LU_SSP585), leads to weakened environmental ecosystems, while the sustainable scenario (LU_SSP126) exhibits more balanced land development. The MIROC-ES2L model demonstrates higher Taylor skill scores, forecasted significant increases in precipitation, maximum, and minimum temperatures under the SSP585 scenario. Spatial heterogeneity in TN and TP loads is notable, showing an upward trajectory in the future. The interaction between land-use and climate change has complex effects on TN and TP loads, with land-use-induced TN changes being relatively small (4.6 %) and TP changes substantial (24.3 %). The spatial distribution, under overlying effects, leans towards the influence of climate change, emphasizing its dominant role in TN and TP load variations. Distinct differences exist in the reduction of NPS pollution loads among different BMPs, with combined BMPs demonstrating superior effectiveness. The environmental-cost effectiveness trends of BMPs remain consistent across various future scenarios. RG (Return agricultural land to grass), RG + TT (Terracing), and RG + FR10 (Fertilizer reduction: 10 %) + GW (Grassed waterway) + FS (Filter strip) + TT emerge as the most effective single, double, and multiple BMP combinations, respectively. The results offer valuable insights for preventing and mitigating future NPS pollution risks, optimizing land-use layouts, and enhancing watershed management decisions.

A spatial optimal allocation method considering multi-attribute decision making and multiple BMPs random combination in sub-watersheds

Best management practices (BMPs) have been extensively employed in effective watershed management for non-point source pollution. The weights of objective functions and the restrictive conditions of combined BMPs are the vital requirements for BMPs allocation. Therefore, it is more beneficial to explore that a spatial optimal allocation method considering multi-attribute decision making and multiple BMPs random combination. Here is the novel framework based on Soil and Water Assessment Tool (SWAT) and the Non-dominated Sorting Genetic Algorithm II (NSGA-Ⅱ), which considers multiple objectives in deriving watershed-scale pollution control practices by considering BMPs cost and combined reduction rates of total nitrogen (TN) and total phosphorus (TP). The framework also integrates combined Entropy Weight method (EWM) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to solve the weights of TN and TP, and considers the attributes of the sub-basin itself, which is more local suitability. Four categories of BMPs, tillage management, nutrient management, vegetative filter strips, and landscape management, were evaluated in the Jing River Basin (JRB) and resulted in reduction rates of 9.77%, 10.53%, 16.40%, and 14.27% averagely, respectively. BMP allocation schemes, derived from multi-objective optimization, are stratified into three financial scenarios. Low-cost scenario, costing up to 2 billion RMB, primarily targets the grain for green program in 28.81% of sub-basins. Medium-cost scenario, between 2 and 6 billion RMB, predominantly utilizes the grain for green in areas with a slope greater than 15°, accounting for 20.00% of sub-basins. High-cost scenario exceeds 6 billion RMB, mainly due to the implementation of multiple combination measures. The three configuration scenarios can provide decision-makers with a trade-off between measure costs and reduction efficiency. Overall, the innovative framework not only facilitates cost-effective implementation but provides a beneficial methodology for selecting cost-effective conservation practices in other regions.

Towards implementing precision conservation practices in agricultural watersheds: A review of the use and prospects of spatial decision support systems and tools

Agricultural nonpoint source (NPS) pollution leads to water quality degradation. While agriculture is faced with the challenge of feeding a growing population in a changing climate, farmers must also strive to minimize adverse impacts of agriculture on the environment. As a result, policies, and agri-environmental programs to promote agricultural conservation practices for controlling NPS pollution have been emerging. Despite progress, reducing NPS is a complex challenge that requires ongoing innovation and investment. A major challenge is to achieve an optimal spatial trade-off between the economic costs and positive environmental outcomes of conservation practices on complex agricultural landscapes. Geospatial systems and tools can help to address this challenge and enhance the effectiveness and efficiency of conservation efforts. However, using these tools for precision conservation is underexamined. This review paper aims to address this gap through a critical exploration of spatial decision support systems and tools to provide synthesized knowledge for implementing precision conservation practices. This paper proposes a conceptual framework to guide the implementation of precision conservation and identifies areas for further development of geospatial systems and tools on planning and assessment of precision conservation efforts. All of which will be helpful for decision-makers and watershed managers in determining the most effective approaches for precision conservation. Furthermore, this review highlights the need for further research and development towards establishing an integrated spatial decision support system framework, which can improve socio-economic, environmental, and ecological outcomes.

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 E_NS 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.

Contribution of nonpoint source pollution from baseflow of a typical agriculture-intensive basin in northern China

Baseflow is an essential component of total surface runoff that is widely considered one of the most influential factors regarding water quality via nonpoint source (NPS) pollution. Previously, many researchers and policy makers have directed their efforts toward surface runoff pollution, largely ignoring nutrient delivery via baseflow. Taking a typical agriculture-intensive basin of northern China as an example, this study explored the spatiotemporal characteristics of baseflow and pollution load in relation to NPS pollution. Baseflow was quantified using digital filtering techniques, and the results together with observed pollution data were used to validate a physically based hydrological model, i.e., the Soil and Water Assessment Tool. Then, the spatial and temporal distribution characteristics of NPS and baseflow pollution were investigated using the modeling results. Results indicated that baseflow contribution to total runoff accounted for more than 70% during the studied years (2016-2018), and 84.15% of the basin area showed non-point source pollution dominated by baseflow pollution; both baseflow and its pollution load were greater in the nonflood seasons (spring, autumn, and winter) than in the flood season (summer); the spatial distribution of baseflow total nitrogen and total phosphorus pollution intensity showed higher values in the east and lower values in the west; the scaling effects of baseflow and its pollution load was found with increasing basin area. The results of our study highlighted the necessity for management of pollution load via baseflow in the river basin and provided reference information for improvement of NPS pollution management in other similar basins.

Spatially Explicit River Basin Models for Cost-Benefit Analyses to Optimize Land Use

Recently, a wide range of models have been used in analyzing the costs and benefits of land utilization in river basins. Despite these advances, there is not enough information on how to select appropriate models to perform cost-benefit analyses. A literature search in the Web of Science (WOS) online database was implemented and resulted in the selection of 27 articles that utilized models to perform cost-benefit analyses of river basins. The models reviewed in these papers were categorized into five types: process-based, statistical, probabilistic, data-driven, and modeling frameworks or integrated models. Twenty-six models were reviewed based on their data and input variable needs and user convenience. A SWOT analysis was also performed to highlight the strengths, weaknesses, opportunities, and threats of these models. One of the main strengths is their ability to perform scenario-based analyses while the main drawback is the limited availability of data impeding the use of the models. We found that, to some extent, there is an increase in model applicability as the number of input variables increases but there are exceptions to this observation. Future studies should explicitly report on the necessary time needed for data collection, model development and/or training, and model application. This information is highly valuable to users and modelers when choosing which model to use in performing a particular cost-benefit analysis. These models can be developed and applied to assist sustainable development as well as the sustainable utilization of agricultural parcels within a river basin, which can eventually reduce the negative impacts of intensive agriculture and minimize habitat degradation on water resources.

The Effects of Agricultural Conservation Practices on the Small Water Cycle: From the Farm- to the Management-Scale

Reinforcing the small water cycle is considered to be a holistic approach to both water resource and landscape management. In an agricultural landscape, this can be accomplished by incorporating agricultural conservation practices; their incorporation can reduce surface runoff, increase infiltration, and increase the water holding capacity of a soil. Some typical agricultural conservation practices include: conservation tillage, contour farming, residue incorporation, and reducing field sizes; these efforts aim to keep both water and soil in the landscape. The incorporation of such practices has been extensively studied over the last 40 years. The Soil and Water Assessment Tool (SWAT) was used to model two basins in the Czech Republic (one at the farm-scale and a second at the management-scale) to determine the effects of agriculture conservation practice adoption at each scale. We found that at the farm-scale, contour farming was the most effective practice at reinforcing the small water cycle, followed by residue incorporation. At the management-scale, we found that the widespread incorporation of agricultural conservation practices significantly reinforced the small water cycle, but the relative scale and spatial distribution of their incorporation were not reflected in the SWAT scenario analysis. Individual farmers should be incentivized to adopt agricultural conservation practices, as these practices can have great effects at the farm-scale. At the management-scale, the spatial distribution of agricultural conservation practice adoption was not significant in this study, implying that managers should incentivize any adoption of such practices and that the small water cycle would be reinforced regardless.

Application of Soil and Water Assessment Tool (SWAT) to evaluate the fates of nitrogenous fertilizer in subtropical mountainous watershed tea farms

Extensive nutrient loss is one of the most challenging issues faced by agricultural production regions worldwide. However, diffuse pollution in the subtropical mountainous watersheds is rarely simulated. A watershed model with regional parameter values is essential for watershed management. In this study, SWAT, one of the most popular models was applied to simulate daily discharge (years of 2008-2014), NO₃-N flux (2012-2014), and tea yield (2012-2014) in the Ping-Lin watershed (PLW) of Taiwan, as well as to test the effectiveness of a modified fertilization strategy. The results demonstrated that SWAT was capable of simulating daily discharge variation, daily riverine NO₃-N flux, and tea yield in the PLW. NO₃-N yield of the tea farm (47 kg/ha/yr) was 9 times higher than that of the forest (5.1 kg/ha/yr). A significant proportion (~ 50%) of the input nitrogen (including dry/wet deposition and fertilizer) infiltrated into the soil, resulting in a poor fertilizer uptake efficiency of the tea tree. It was demonstrated that the modified fertilization strategy (apply fertilizer in small rainfall event, i.e., daily rainfall < 20 mm/day, and not in a single day) could increase the nitrogen uptake and harvest yield of the tea tree by 14% and 4%, respectively, with a 10% reduction in nitrogen input. Furthermore, this strategy significantly reduced the nitrogen yields from surface flow (75%), lateral flow (36%), percolation (50%), and groundwater (48%). A popular model with verified parameter values could help in developing a win-win strategy for both farmers and regulators, thus realizing the goals of sustainable agricultural practices.

Study of uncertainty of satellite and reanalysis precipitation products and their impact on hydrological simulation

Satellite and reanalysis precipitation products are potential alternatives in hydrological studies, and it is very important to evaluate their accuracy and potential use for reliable simulations. In this study, three precipitation products (Tropical Rainfall Measuring Mission 3B43 Version 7 (TRMM 3B43), spatial interpolation grid data based on 2472 national meteorological observation stations in China (GRID_0.5), and National Centers for Environmental Prediction-Climate Forecast System Reanalysis (NCEP-CFSR)) were evaluated against gauge observations in the Xiangxi River watershed of Hubei Province. The performance results indicated that the results of the three precipitation products were correlated with those of the rain gauges; however, there were differences among the three products. TRMM 3B43 tended to overestimate precipitation with the highest correlation coefficient, while NCEP-CFSR tended to underestimate precipitation with the least satisfactory performance, and the performance of GRID_0.5 ranked between them. However, the annual and monthly mean errors differed, as the errors of most of the results driven by NCEP-CFSR were lowest. The errors varied at different time scales. During years with high precipitation, the results were often underestimated, while the results are often overestimated during years with low precipitation. According to the average monthly results, the GRID_0.5 results were closest to the gauge observations for most months. During the wet season, TRMM 3B43 performed better, while NCEP-CFSR precipitation performed better during the dry season. The errors from precipitation to streamflow, NPS pollution, and water environmental capacity (WEC) driven by the three precipitation products increased gradually, ranging from 10% for precipitation to over 20% for NPS pollution and almost 100% for WEC. The error increase for NCEP-CFSR was lower than that of the other two products. Although the simulation error from precipitation to the WEC results driven by the three precipitation products gradually increased, the degree of overestimation and underestimation became smaller.

Addressing the spatial disconnect between national-scale total maximum daily loads and localized land management decisions

Regulatory watershed mitigation programs typically emphasize widespread adoption of best management practices (BMPs) to meet total maximum daily load (TMDL) goals. To comply with the Chesapeake Bay TMDL, jurisdictions must develop watershed implementation plans (WIPs) to determine the number and type of BMPs to implement. However, the spatial resolution of the bay-level model used to determine these load reduction goals is so coarse that the regulatory plan cannot consider heterogeneity in local conditions, which affects BMP effectiveness. Using the Topo-SWAT modification of the Soil and Water Assessment Tool (SWAT), we simulated two BMP adoption scenarios in the Spring Creek watershed in central Pennsylvania to determine if leveraging fine-scale spatial heterogeneity to place BMPs could achieve the same (or better) nutrient and sediment reduction at a lower cost than the state-level WIP BMP adoption recommendations. Topo-SWAT was initialized with detailed land use and management practice information, systematically calibrated, and validated against 12 yr of observed data. After determining individual BMP cost effectiveness, results were ranked to design a cost-effective BMP adoption scenario that achieved equal or greater load reduction as the WIP scenario for 74% of the cost using eight management-based BMPs: no-till, manure injection, cover cropping, riparian buffers, land retirement, manure application timing, wetland restoration, and nitrogen management (15% less N input). Because watersheds of this size typically represent the smallest modeling unit in the Chesapeake Bay Model, results demonstrate the potential to use watershed models with finer inference scales to improve recommendations for BMP implementation under the Chesapeake Bay TMDL.

Best management practices from agricultural economics: Mitigating air, soil and water pollution

Often the several stakeholders involved in the agricultural sector place a greater emphasis on the negative externalities from farming production rather than on the solutions and approaches to mitigate, namely impacts from pollution. The scientific literature, in certain circumstances, follows this tendency leaving a vast chasm of enormous potential left to be explored. It is important to contribute towards the reduction of this gap, highlighting the best management practices implemented across the agricultural sector around the world, specifically to make them more visible and give incentive to the several agents in adopting and spreading their use. In this way, the main objective is to stress the best management practices presented by the global scientific literature from the farming sector. To achieve this objective methodology based on bibliometric analysis-factor-analysis-literature survey approach was considered, applied to 150 documents obtained from the Web of Science (core collection) related with the following topics: best management practice; agricultural economics; air, soil and water pollution. As main insights, it is worth referring the best management practices to deal with problems from agricultural production, such as, for example, the use of agricultural residues as feedstock for renewable energies. With regard to sustainable development in the agricultural sector, concepts such as "sustainable remediation" have their place. On the other hand, the agricultural and environmental policies and the agricultural costs associated with the several farming practices also play a determinant role here. Finally, only fraction of the scientific documents analysed (16 papers) belong to the group of studies related to policies, showing that there are potential subjects to be addressed here in future studies related with these topics. The same happens for cost-benefit analyses (24 documents).

Assessing the Impacts of Best Management Practices on Nonpoint Source Pollution Considering Cost-Effectiveness in the Source Area of the Liao River, China

Agricultural nonpoint source pollution has been a major influential factor on the deterioration of water quality in the Liao River source area. Best management practices (BMPs), as a comprehensive pollution prevention system designed to reduce the impacts of agricultural activities and improve water quality, has been considered one of the most effective solutions for nonpoint source pollution control. However, economic cost has been an important element for screening the implementation of BMPs. Both pollution reduction and capital expenditure need to be resolved with the actual situation. A water quality model such as the Soil and Water Assessment Tool (SWAT) and empirical cost algorithm are important tools to assess the cost-effectiveness of the effects of BMPs on nonpoint source pollution. In this study, BMP scenarios including buffer strips (BSs), fertilizer reduction (FR), forest land increase (FLI), grassland increase (GLI), and their combination were implemented using the SWAT model; furthermore, the efficiency of their pollutants reduction and costs benefit were estimated in the watershed. The results showed that combined BMPs have better control effects than a single BMP, with “BS20 (widths 20 m) + FR15 (fertilization reduction 15%) + FLI (forest land increase)” arriving at the greatest loads reduction in the critical periods. From environmental and economic perspectives, the cost-effectiveness of interception measures is higher than that of the source control measures. The results indicated that BS was the most environmentally friendly practice, and FR was the most economically efficient out of all the BMPs. Regarding land-use changes, FLI was more environmentally friendly, and GLI was more economically efficient. The most economical and effective BMPs can be designated as follows: BS1.5 (widths 1.5 m) and FR15 (fertilization reduction 15%). Therefore, due to possible differences in government policies, it is important to consider an integrated approach for all the relevant actors and seek sustainable environmental and economic development.

Analysis of the efficacy and cost-effectiveness of best management practices for controlling sediment yield: A case study of the Joumine watershed, Tunisia

Soil erosion can be reduced through the strategic selection and placement of best management practices (BMPs) in critical source areas (CSAs). In the present study, the Soil Water Assessment Tool (SWAT) model was used to identify CSAs and investigate the effectiveness of different BMPs in reducing sediment yield in the Joumine watershed, an agricultural river catchment located in northern Tunisia. A cost-benefit analysis (CBA) was used to evaluate the cost-effectiveness of different BMP scenarios. The objective of the present study was to determine the most cost-effective management scenario for controlling sediment yield. The model performance for the simulation of streamflow and sediment yield at the outlet of the Joumine watershed was good and satisfactory, respectively. The model indicated that most of the sediment was originated from the cultivated upland area. About 34% of the catchment area consisted of CSAs that were affected by high to very high soil erosion risk (sediment yield >10t/ha/year). Contour ridges were found to be the most effective individual BMP in terms of sediment yield reduction. At the watershed level, implementing contour ridges in the CSAs reduced sediment yield by 59%. Combinations of BMP scenarios were more cost-effective than the contour ridges alone. Combining buffer strips (5-m width) with other BMPs depending on land slope (> 20% slope: conversion to olive orchards; 10-20% slope: contour ridges; 5-10% slope: grass strip cropping) was the most effective approach in terms of sediment yield reduction and economic benefits. This approach reduced sediment yield by 61.84% with a benefit/cost ratio of 1.61. Compared with the cost of dredging, BMPs were more cost-effective for reducing sediment loads to the Joumine reservoir, located downstream of the catchment. Our findings may contribute to ensure the sustainability of future conservation programs in Tunisian regions.

Analysis of field-scale spatial correlations and variations of soil nutrients using geostatistics

Spatial correlations and soil nutrient variations are important for soil nutrient management. They help to reduce the negative impacts of agricultural nonpoint source pollution. Based on the sampled available nitrogen (AN), available phosphorus (AP), and available potassium (AK), soil nutrient data from 2010, the spatial correlation, was analyzed, and the probabilities of the nutrient's abundance or deficiency were discussed. This paper presents a statistical approach to spatial analysis, the spatial correlation analysis (SCA), which was originally developed for describing heterogeneity in the presence of correlated variation and based on ordinary kriging (OK) results. Indicator kriging (IK) was used to assess the susceptibility of excess of soil nutrients based on crop needs. The kriged results showed there was a distinct spatial variability in the concentration of all three soil nutrients. High concentrations of these three soil nutrients were found near Anzhou. As the distance from the center of town increased, the concentration of the soil nutrients gradually decreased. Spatially, the relationship between AN and AP was negative, and the relationship between AP and AK was not clear. The IK results showed that there were few areas with a risk of AN and AP overabundance. However, almost the entire study region was at risk of AK overabundance. Based on the soil nutrient distribution results, it is clear that the spatial variability of the soil nutrients differed throughout the study region. This spatial soil nutrient variability might be caused by different fertilizer types and different fertilizing practices.

Abatement vs. treatment for efficient diffuse source water pollution management in terrestrial-marine systems

Marine ecosystems are affected by water pollution originating from coastal catchments. The delivery of water pollutants can be reduced through water pollution abatement as well as water pollution treatment. Hence, sustainable economic development of coastal regions requires balancing of the marginal costs from water pollution abatement and/or treatment and the associated marginal benefits from marine resource appreciation. Water pollution delivery reduction costs are, however, not equal across abatement and treatment options. In this paper, an optimal control approach is developed and applied to explore welfare maximizing rates of water pollution abatement and/or treatment for efficient diffuse source water pollution management in terrestrial-marine systems. For the case of diffuse source dissolved inorganic nitrogen water pollution in the Tully-Murray region, Queensland, Australia, (agricultural) water pollution abatement cost, (wetland) water pollution treatment cost and marine benefit functions are determined to explore welfare maximizing rates of water pollution abatement and/or treatment. Considering partial (wetland) treatment costs and positive water quality improvement benefits, results show that welfare gains can be obtained, primarily, through diffuse source water pollution abatement (improved agricultural management practices) and, to a minor extent, through diffuse source water pollution treatment (wetland restoration).