Implementation of BMP strategies for adaptation to climate change and land use change in a pasture-dominated watershed

A quantitative approach on environment-food nexus: integrated modeling and indices for cumulative impact assessment of farm management practices

Background

Best management practices (BMPs) are promising solutions that can partially control pollution discharged from farmlands. These strategies, like fertilizer reduction and using filter strips, mainly control nutrient (N and P) pollution loads in basins. However, they have secondary impacts on nutrition production and ecosystem. This study develops a method to evaluate the cumulative environmental impacts of BMPs. It also introduces and calculates food's environmental footprint (FEF) for accounting the total environmental damages per nutrition production.

Methods

This study combines the soil and water assessment tool (SWAT) for basin simulation with the indices of ReCiPe, a life cycle impact assessment (LCIA) method. By these means, the effectiveness of BMPs on pollution loads, production yields, and water footprints (WFs) are evaluated and converted as equivalent environmental damages. This method was verified in Zrebar Lake, western Iran. Here, water consumption, as WFs, and eutrophication are the main indices that are converted into equivalent health and ecological impairments. Two methods, entropy and environmental performance index (EPI), are used for weighting normalized endpoints in last step.

Results

Results showed that using 25-50% less fertilizer and water for irrigation combined with vegetated filter strips reduce N and P pollution about 34-60% and 8-21%, respectively. These can decrease ecosystem damages by 5-9% and health risks by 7-14%. Here, freshwater eutrophication is a more critical damage in ecosystem. However, using less fertilizer adversely reduces total nutrition production by 1.7-3.7%. It means that BMPs can decline total ecological damages and health risks, which threatens nutrition production. FEF presents a tool to solve this dilemma about the sustainability of BMPs. In the study area, a 4-9% decrease in FEF means that BMPs are more environmental friendly than nutrition menacing. Finally, this study concludes that SWAT-ReCiPe with FEF provides a quantitative framework for environment-food nexus assessment. However, due to the uncertainties, this method is recommended as a tool for comparing management strategies instead of reporting certain values.

How climate change and land-use evolution relates to the non-point source pollution in a typical watershed of China

The water quality of Le 'an River Watershed (LRW) is crucial to the water environmental safety of Poyang Lake, especially the concentration of nitrogen and phosphorus. The effect of climate and land use change on watershed water quality has always been under the attention of local managers. More importantly, the lack of detailed studies on climate and land use impact on river water quality has prevented sustainable water security management in the LRW. Therefore, this study aimed to quantify the weight of climate and land use on nutrient loss in the LRW, respectively. We divided the historical period (1990-2020) into six scenarios and a baseline scenario. TN and TP losses in the watershed were simulated using Soil and Water Assessment Tool (SWAT), and the weight of climate and land use were quantified in overall, by period, and by region. The results showed that the weight of climate was greatly higher than land use with values around 90%. However, the weight of land use had a positive cumulative effect in a certain period, and its influence could not be neglected. The climate in all scenarios led to a reduction in nutrient loss, while land use was found to slightly increase the nutrient loss yield. In addition to, unique regional topographic features, urbanization rates, and climatic conditions could cause spatial heterogeneity in the climatic and land use weights.

A review of climate change effects on practices for mitigating water quality impacts

Water quality practices are commonly implemented to reduce human impacts on land and water resources. In series or parallel in a landscape, systems of practices can reduce local and downstream pollution delivery. Many practices function via physical, chemical, and biological processes that are dependent on weather and climate. Climate change will alter the function of many such systems, though effects will vary in different hydroclimatic and watershed settings. Reducing the risk of impacts will require risk-based, adaptive planning. Here, we review the literature addressing climate change effects on practices commonly used to mitigate the water quality impacts of urban stormwater, agriculture, and forestry. Information from the general literature review is used to make qualitative inferences about the resilience of different types of practices. We discuss resilience in the context of two factors: the sensitivity of practice function to changes in climatic drivers, and the adaptability, or relative ease with which a practice can be modified as change occurs. While only a first step in addressing a complex topic, our aim is to help communities incorporate consideration of resilience to climate change as an additional factor in decisions about water quality practices to meet long-term goals.

Applying copulas to predict the multivariate reduction effect of best management practices

Best management practices (BMPs) have been widely applied to mitigate non-point source (NPS) pollution in agricultural watersheds. However, a prediction of the multivariate reduction effect of NPS pollutants by BMPs considering its stochastic nature has not been conducted. A new modeling approach combining a hydrological model and copulas was proposed to predict the multivariate effect of BMPs fully considering the stochastic characteristics of BMPs effects and the dependence structure between them. Two levels of reduction effect, i.e., the multi-indicator effect of a single BMP and the combined effect of multiple BMPs, were simulated. The approach was demonstrated in Zhangjiachong watershed, a typical small watershed in the Three Gorges Reservoir area, China. Results show that copulas can effectively simulate the dependence between the univariate effects of BMPs. The approach can accurately predict the probability to achieve the reduction objective for multiple pollutants and multiple BMPs in a watershed. It provides a stochastic way to predict the multivariate effect of BMPs and has great potential to be widely applied in BMPs related decision making.

Hydrologic Responses to Climate Variability and Human Activities in Lake Ziway Basin, Ethiopia

Hydrological impacts of human activities and climate variability on Ketar and Meki watersheds of Lake Ziway basin, Ethiopia were studied using the soil and water assessment tool. Three land-use change and two climate variability scenarios were considered to analyze the separate and combined impacts on annual water balance, monthly streamflow, and spatial distributions of evapotranspiration and water yield. The evaluation showed that changes in land use resulted in an increase in annual surface runoff and water yield for Ketar watershed and an increase in annual ET for Meki. Similarly, the climate variability resulted in a decrease in annual ET, surface runoff, and water yield for Ketar watershed and a decrease in ET for Meki. Overall, climate variability has greater impacts on the monthly streamflow compared to land-use change impacts. Similarly, greater sensitivity in hydrologic response was observed for Ketar watershed compared to Meki watershed.

Can FinTech Development Curb Agricultural Nonpoint Source Pollution?

The green development of FinTech empowerment has become a compelling theme in economic development. In this study, based on the weighted least squares (WLS) and threshold regression methods of cross-sectional data, we empirically examine the impact of FinTech development on agricultural nonpoint source (NPS) pollution, a major cause of impaired surface water quality. Our results show that there is an inverted “U” shape relationship between the development of FinTech and agricultural NPS pollution. That is, after crossing a “threshold value”, the level of FinTech development can curb agricultural NPS pollution. At the structural level, the availability of FinTech services, the FinTech infrastructure, and the agricultural NPS pollution also have an inverted “U” shape relationship. At the threshold effect, in the developing stage of an agricultural economy, the overall level of FinTech development, the use of FinTech services, the availability of FinTech services, and the FinTech infrastructure have an inverted “U” shape relationship with agricultural NPS pollution. On the other hand, in the developed stage of an agricultural economy, the impact of FinTech development and its structure on agricultural NPS pollution is insignificant. Hence, we can conclude that FinTech development can help reduce agricultural NPS pollution in under-developed regions. However, due to the fact that a “U” shape relationship always exists between FinTech service quality and agricultural NPS pollution, the quality of FinTech service should be the main focus to reduce agricultural NPS pollution more effectively.

Evaluation of the effectiveness of conservation practices under implementation site uncertainty

Agricultural nonpoint source pollution is the leading source of water quality degradation in United States, which has led to the development of programs that aim to mitigate this pollution. One common approach to mitigating nonpoint source pollution is the use of best management practices (BMPs). However, it can be challenging to evaluate the effectiveness of implemented BMPs due to polices that limit data sharing. In this study, the uncertainty introduced by data sharing limitations is quantified through the use of a watershed model. Results indicated that BMP implementation improved the overall water quality in the region (up to ∼15% pollution reduction) and that increasing the area of BMP implementation resulted in higher pollution reduction. However, the model outputs also indicated that uncertainty caused by data sharing limitations resulted in variabilities ranging from -160% to 140%. This shows the importance of data sharing among agencies to better guide current and future conservation programs.

Modeling the combined effects of changing land cover, climate, and atmospheric deposition on nitrogen transport in the Neuse River Basin

STUDY REGION

The SWAT model was used to estimate the combined effects of changing land cover, climate and Clean Air Act (CAAA)-related atmospheric nitrogen (N) deposition to watershed nitrogen fate and transport for two watersheds in North Carolina, USA.

STUDY FOCUS

Two different model simulation scenarios were applied: one included CAAA-related atmospheric N deposition, climate and land cover (CAAD+C+L) and the other only included CAAA-related N deposition (CAAD) in simulation.

NEW HYDROLOGICAL INSIGHTS FOR THE REGION

Results show both scenarios generated overall decreasing trends for nearly all N outputs between 2010 and 2070 which resulted primarily from CAAA-related reductions in oxidized N deposition. In both watersheds, including climate and land cover change in simulation resulted in a relative 30% higher NO3 load, 30% higher denitrification, 10% higher organic N load and a 20% smaller level of plant N uptake in year 2070 compared to not including climate and landcover changes in simulation. The increases in N transport for both watersheds indicates the combined impacts from climate and land cover change may offset benefits provided by the CAAA regulations; however, future NO3 loads for the Little River watershed were small relative to current N loading rates. Conversely, the increasing NO3 and organic N loads for the nearby Nahunta watershed were significant compared to current rates demonstrating that watershed nutrient responses to climate and land cover changes may vary significantly over relatively small spatial scales.

Assessing the impacts of Best Management Practices on nitrate pollution in an agricultural dominated lowland catchment considering environmental protection versus economic development

Water quality is strongly affected by nitrate inputs in agricultural catchments. Best Management Practices (BMPs) are alternative practices aiming to mitigate the impacts derived from agricultural activities and to improve water quality. Management activities are influenced by different governmental policies like the Water Framework Directive (WFD) and the Renewable Energy Sources Act (EEG). Their distinct goals can be contrasting and hamper an integrated sustainable development. Both need to be addressed in the actual conjuncture in rural areas. Ecohydrological models like the SWAT model are important tools for land cover and land use changes investigation and the assessment of BMPs implementation effects on water quality. Thus, in this study, buffer strip, fertilization reduction and alternative crops were considered as BMPs and were implemented in the SWAT model for the Treene catchment. Their efficiency in terms of nitrate loads reduction related to implementation costs at the catchment scale was investigated. The practices correspond to the catchment conditions and are based on small and mid areal changes. Furthermore, the BMPs were evaluated from the perspective of ecologic and economic policies. The results evidenced different responses of the BMPs. The critical periods in winter were addressed by most of the BMPs. However, some practices like pasture land increase need to be implemented in greater area for better results in comparison to current activities. Furthermore, there is a greater nitrate reduction potential by combining BMPs containing fertilization reduction, buffer strips and soil coverage in winter. The discussion about efficiency showed the complexity of costs stipulation and the relation with arable land and yield losses. Furthermore, as the government policies can be divergent an integrated approach considering all the involved actors is important and seeks a sustainable development.

Composition and design of vegetative filter strips instrumental in improving water quality by mass reduction of suspended sediment, nutrients and Escherichia coli in overland flows in eastern escarpment of Mau Forest, Njoro River Watershed, Kenya

This study assessed the effect of vegetative filter strip (VFS) in removal of suspended sediment (SS), total nitrogen, total phosphorus and Escherichia coli (E. coli) in overland flow to improve receiving water quality standards. Four and half kilograms of cowpat manure was applied to the model pasture 14 m beyond the edge of vegetated filter strip (VFS) comprising 10-m Napier grass draining into 20-m Kikuyu grass (VFS II), 10-m Kikuyu grass draining into 20-m Napier grass (VFS III) and native grass mixture of Couch-Buffel (VFS I-control). Overland flow water samples were collected from the sites at positions 0, 0.5, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25 and 30 m along the length of VFSs. E. coli removal by Napier grass VFS was on the order of log unit, which provided an important level of protection and reduced surface-flow concentrations of E. coli to below the 200 (CFU 100 mL^-1) recommended water quality standards, but not for nutrients and SS. The Napier grass showed highest efficiency (99.6 %), thus outperforming both Kikuyu grass (85.8 %) and Couch-Buffel grasses VFS (67.9 ± 4.2 %) in removing E. coli from overland flow. The low-level efficiency of native Couch-Buffel grasses in reducing E. coli in overland flow was because of preferential flow. Composition and design of VFS was instrumental and could be applied with a high potential of contracting the uncertainty in improving water quality standards through mass reduction of SS, nutrients and E. coli load in watersheds.

The current state of knowledge on the interaction of Escherichia coli within vegetative filter strips as a sustainable best management practice to reduce fecal pathogen loading into surface waters

Agro-pastoral operations have the potential to threaten public health with loading of diverse pathogens into surface waters through overland flow; increasing awareness of the limitations of fecal indicators has led to development of a number of advancements in detection, source tracking and predictive modeling of public health risk. These tools and techniques are beginning to be integrated into management strategies. The objective of this review was to determine the status of current knowledge and challenges of the fate and transport of Escherichia coli in overland flow and their interaction within vegetative filter strip (VFS) as one of these implemented best management practices and to critically evaluate its use in that setting as an indicator organism. With few studies directly focusing on VFS removal of E. coli from overland flow, we critically evaluated the available data on movement of E. coil from fecal source loading to retention and decay or re-release for potential contamination of water ways and pointed out potential limitations in both pathogen-specific removal and its use as an indicator organisms within overland flow and VFS. Critical areas of focus for future studies to reduce gaps in knowledge were identified, and the integration of newer approaches in source tracking, alternative indicators and the use of non-pathogenic surrogates for field testing of existing VFS models was encouraged. With VFS as a growing field of interest as an economical conservation practice and as an avenue for conservation of resources for small-scale agro-pastoral operations, management strategies to reduce initial fecal load from either applied manure constituents or shedding from free-range animals will continue to test the limits in the applications of models to overland flow and VFS management strategies. Further studies at the microscale in understanding discrepancies between low and high pathogenicity strains of E. coil and between E. coil and other fecal pathogens in the context of VFS will be critical. However, nuanced studies are needed to understand either biological or environmental differences in the fate and transport of the diverse types of fecal pathogens within these settings.

Comparing the selection and placement of best management practices in improving water quality using a multiobjective optimization and targeting method

Suites of Best Management Practices (BMPs) are usually selected to be economically and environmentally efficient in reducing nonpoint source (NPS) pollutants from agricultural areas in a watershed. The objective of this research was to compare the selection and placement of BMPs in a pasture-dominated watershed using multiobjective optimization and targeting methods. Two objective functions were used in the optimization process, which minimize pollutant losses and the BMP placement areas. The optimization tool was an integration of a multi-objective genetic algorithm (GA) and a watershed model (Soil and Water Assessment Tool—SWAT). For the targeting method, an optimum BMP option was implemented in critical areas in the watershed that contribute the greatest pollutant losses. A total of 171 BMP combinations, which consist of grazing management, vegetated filter strips (VFS), and poultry litter applications were considered. The results showed that the optimization is less effective when vegetated filter strips (VFS) are not considered, and it requires much longer computation times than the targeting method to search for optimum BMPs. Although the targeting method is effective in selecting and placing an optimum BMP, larger areas are needed for BMP implementation to achieve the same pollutant reductions as the optimization method.

Assessing the influence of land use and land cover datasets with different points in time and levels of detail on watershed modeling in the North River Watershed, China

Land use and land cover (LULC) information is an important component influencing watershed modeling with regards to hydrology and water quality in the river basin. In this study, the sensitivity of the Soil and Water Assessment Tool (SWAT) model to LULC datasets with three points in time and three levels of detail was assessed in a coastal subtropical watershed located in Southeast China. The results showed good agreement between observed and simulated values for both monthly and daily streamflow and monthly NH(4)+-N and TP loads. Three LULC datasets in 2002, 2007 and 2010 had relatively little influence on simulated monthly and daily streamflow, whereas they exhibited greater effects on simulated monthly NH(4)+-N and TP loads. When using the two LULC datasets in 2007 and 2010 compared with that in 2002, the relative differences in predicted monthly NH(4)+-N and TP loads were -11.0 to -7.8% and -4.8 to -9.0%, respectively. There were no significant differences in simulated monthly and daily streamflow when using the three LULC datasets with ten, five and three categories. When using LULC datasets from ten categories compared to five and three categories, the relative differences in predicted monthly NH(4)+-N and TP loads were -6.6 to -6.5% and -13.3 to -7.3%, respectively. Overall, the sensitivity of the SWAT model to LULC datasets with different points in time and levels of detail was lower in monthly and daily streamflow simulation than in monthly NH(4)+-N and TP loads prediction. This research provided helpful insights into the influence of LULC datasets on watershed modeling.