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Soil erosion and sediment buildup are the factors that speed up the decline in capacity and function of reservoirs, agricultural products, and water resources. In order to simulate sediment and runoff and map high sediment-yielding sub-basins in the Gibe Gojeb catchment in southwest Ethiopia, this study used the Soil and Water Assessment Tool (SWAT) model. Using data on sediment and river flow, calibration and validation were carried out. Between 2003 and 2016, the catchment produced an average annual sediment loading of 62.5 tons ha-1 yr-1, with loading fluctuations ranging from 0.2 to 108.4 tons ha-1 yr-1. The acceptable sediment yield threshold value ranges from 12.3 to 108.4 tons ha-1 yr-1 for 56 sub-basins, and from 0.2 to 10 tons ha-1 yr-1 for 5 sub-basins. The most significant sub-basins with very high to extremely severe sediment yields were sub-basins 1 to 30, 32 to 44, 47, 48, 50, 51, and 53 to 61. After thirteen years of operation, the yearly amount of 58,802 tons of sediment transferred from the catchment and deposited into Gibe One reservoir has decreased the capacity by 5.7 %. The accumulation of sediment in a reservoir has an impact on its functionality, power production, and capacity, affecting the safety of dams and the environment. The study's findings enhanced our comprehension of sediment accumulation in reservoirs and furnished us with the necessary information regarding reservoir safety, integrated soil, and water management.

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The Jinsha River Basin (JRB) contributes a significant amount of sediment to the Yangtze River; however, an imbalance exists between runoff and sediment. The underlying mechanisms and primary factors driving this imbalance remain unclear. In this study, the Shapley Additive Explanation (SHAP) and Geographical Detector Model (GDM) were employed to quantify the importance of the driving factors for water yield (WYLD) and sediment yield (SYLD) using the Soil and Water Assessment Tool (SWAT) model in the JRB. The results indicated that the SWAT model performed well in simulating runoff and sediment, with R2 > 0.61 and NSE > 0.5. Based on the simulated data, SYLD exhibited strong spatiotemporal linkages with WYLD. Temporally, both sediment and runoff showed decreasing trends, with the sediment decrease being more pronounced. Spatially, WYLD and SYLD displayed similar distribution patterns, with low values in the southwest and high values in the northeast. By quantifying the driving factors, we found that climatic factors, including precipitation and potential evapotranspiration, were the main influencing factors for WYLD and SYLD across the entire region, though their contributions to the two variables differed. For WYLD, climatic factors accounted for 70 % of the total influencing factors, whereas their contribution to SYLD was 50 %. Furthermore, soil type and land-use type played significant roles in the SYLD, with importance values of 16 % and 12 %, respectively. Under the influence of surface conditions, the proportion of SYLD in the JRB to the total SYLD in the Yangtze River Basin was greater than that of WYLD. The findings of this study provide scientific evidence and technical support for local environmental impact assessments and the formulation of soil and water conservation plans.

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Balancing environmental protection and social-economic development in agricultural land use management is a dilemma for decision-makers. Based on the modelling of the impacts of land use changes on river water pollution by SWAT model, the tradeoff between tea plantation expansion and river water quality was detected. SWAT model performs well in simulating the non-point source (NPS) pollution in agricultural watershed. The results showed that the tea plantation area expanded dramatically from 44 km2 in 2000 to 169 km2 in 2020 at the high cost of forest land. Consequently, the mean contents of NO3--N and TN have significantly increased by 100% and 91% respectively in the past 20 years. And the NO3--N in river water accounted for over 80% of TN in the tea plantation area. The NO3--N and TN concentrations were positively related with the proportions of tea plantation area (Tea%) at different periods. The high pollution levels of NO3--N and TN are priority control targets for river water quality management. The results indicated that the proportion of tea plantation thresholds lead to abrupt changes in river water quality. When the Tea% exceeded 3.0% in 2000, the probability of N pollution increased sharply. Whereas in 2020, it is suggested that the Tea% should not exceeds 18% to avoid sudden deterioration of water quality. The critical interval value of the Tea% for sudden change in N pollution showed an obvious increase tendency. The accelerating of nutrient pollution in rivers reduced the sensitivity of water quality to tea plantation expansion. Our results can provide new insights and empirical evidence for balancing the tradeoff between agricultural development and river water quality protection by demonstrating the carrying capacity threshold of river water environment for the expansion tea plantation.

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Hydrological models are vital tools in environmental management. Weaknesses in model robustness for hydrological parameters transfer uncertainties to the model outputs. For streamflow, the optimized parameters are the primary source of uncertainty. A reliable calibration approach that reduces prediction uncertainty in model simulations is crucial for enhancing model robustness and reliability. The optimization of parameter ranges is a key aspect of parameter calibration, yet there is a lack of literature addressing the optimization of parameter ranges in hydrological models. In this paper, we introduce a parameter calibration strategy that applies a clustering technique, specifically the Self-Organizing Map (SM), to intelligently navigate the parameter space during the calibration of the Soil and Water Assessment Tool (SWAT) model for monthly streamflow simulation in the Baishan Basin, Jilin Province, China. We selected the representative algorithm, the Sequential Uncertainty Fitting version 2 (SUFI-2), from the commonly used SWAT Calibration and Uncertainty Programs for comparison. We developed three schemes: SUFI-2, SUFI-2-Narrowing Down (SUFI-2-ND), and SM. Multiple diagnostic error metrics were used to compare simulation accuracy and prediction uncertainty. Among all schemes, SM outperformed the others in describing watershed streamflow, particularly excelling in the simulation of spring snowmelt runoff (baseflow period). Additionally, the prediction uncertainty was effectively controlled, demonstrating the SM's adaptability and reliability in the interval optimization process. This provides managers with more credible prediction results, highlighting its potential as a valuable calibration tool in hydrological modeling.

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Escalating climate extreme events disrupt hydrological processes by affecting both water availability and sediment dynamics. However, the interconnection between hydrological variability and climatic extremes remains underexplored, particularly in cold regions under a changing climate. Here, we develop a yield-based dichotomy framework to examine the impact of shifted climatic extreme patterns on hydrological regimes in the Ishikari River Basin (IRB), Hokkaido, Japan, which is a crucial area for local agriculture and urban development. Utilizing a modified Soil and Water Assessment Tool (SWAT) integrated with downscaled CMIP6-GCM climate projections under Shared Socioeconomic Pathways (SSPs) scenarios, we identified significant annual variability in water and sediment yields associated with extreme climate events. Hot-dry conditions correlate with lower water and sediment yields, whereas increased cold extremes may result in higher sediment yields across the IRB. Our findings also indicate that hotter and drier patterns interact with hydrological processes, potentially establishing new hydrologic regimes and shifting climatic extremes-induced thresholds for yield classification within the IRB. Notably, under SSP585, both water availability and sediment transport are projected to intensify, increasing flood risks and exacerbating sedimentation challenges. Our study highlights the urgent need for adaptive water management strategies to address these anticipated changes in hydrological regimes in response to global climate change.

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Neonicotinoid pollution has increased rapidly and globally in recent years, posing significant risks to agricultural areas. Quantifying use and emission, transport and fate of these contaminants, and risks is critical for proper management of neonicotinoids in river basin. This study elucidates use and emissions of neonicotinoid pesticides in a typical large-scale agriculture basin of China, the Pearl River Basin, as well as the resulting agricultural non-point source pollution and related ecological risks using market surveys, data analysis, and the Soil and Water Assessment Tool. Neonicotinoid use in the basin was estimated at 1361 t in 2019, of which 83.1 % was used in agriculture. After application, approximately 99.1 t neonicotinoids were transported to the Pearl River, accounting for 7.2 % of the total applied. Estimated aquatic concentrations of neonicotinoids showed three seasonal peaks. Several distinct groups of neonicotinoid chemicals can be observed in the Pearl River, as estimated by the model. An estimated 3.9 % of the neonicotinoids used were transported to the South China Sea. Based on the present risk assessment result, several neonicotinoids posed risks to aquatic organism. Therefore, the use of alternative products and/or reduced use is deemed necessary. This study provides novel insights into the fate and ecological risks of neonicotinoid insecticides in large-scale watersheds, and underscores the need for greater efficiency of use and extensive environmental monitoring.

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Climate change has diversified negative implications on environmental sustainability and water availability. Assessing the impacts of climate change is crucial to enhance resilience and future preparedness particularly at a watershed scale. Therefore, the goal of this study is to evaluate the impact of climate change on the water balance components and extreme events in Piabanha watershed in the Brazilian Atlantic Forest. In this study, extreme climate change scenarios were developed using a wide array of global climate models acquired from the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Reports (AR6). Two extreme climate change scenarios, DryHot and WetCool, were integrated into the Soil and Water Assessment Tools (SWAT) hydrological model to evaluate their impacts on the hydrological dynamics in the watershed. The baseline SWAT model was first developed and evaluated using different model performance evaluation metrics such as coefficient of determination (R2), Nash-Sutcliffe (NSC), and Kling-Gupta efficiency coefficient (KGE). The model results illustrated an excellent model performance with metric values reaching 0.89 and 0.64 for monthly and daily time steps respectively in the calibration (2008 to 2017) and validation (2018 to 2023) periods. The findings of future climate change impacts assessment underscored an increase in temperature and shifts in precipitation patterns. In terms of streamflow, high-flow events may experience a 47.3 % increase, while low-flows could see an 76.6 % reduction. In the DryHot scenario, annual precipitation declines from 1657 to 1420 mm, with evapotranspiration reaching 54 % of precipitation, marking a 9 % rise compared to the baseline. Such changes could induce water stress in plants and lead to modifications on structural attributes of the ecosystem recognized as the Atlantic rainforest. This study established boundaries concerning the effects of climate change and highlighted the need for proactive adaptation strategies and mitigation measures to minimize the potential adverse impacts in the study watershed.

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Managing landscape change is increasingly challenging due to rapid anthropogenic shifts. A delicate balance must be struck between the environment and change to ensure landscapes can withstand these impacts. This study conducted in the Tunca River sub-basin of Edirne province, aims to assess landscape sensitivity by examining the influence of land use/land cover (LULC) and climate change on landscape function processes. For this purpose, a methodology was developed based on ecosystem services to determine landscape sensitivity. The results revealed a LULC transformation that could lead to a 60% reduction in forest areas and a 5% and 20% increase in urban and irrigated agricultural areas, respectively. Water and erosion emerged as the most affected landscape function processes. Future scenarios from 2050 to 2070 indicate noteworthy changes in landscape sensitivity, showing an increase in sensitivity in the upper regions of the basin. The study identified high sensitivity in forested areas, moderate sensitivity in agricultural zones, and low sensitivity in micro-basins near residential areas. Protection and improvement strategies are recommended for areas with high and moderate sensitivity, while use-oriented strategies are suggested for those with low sensitivity. This study also establishes a scientific foundation for guiding the protection and management of ecologically sensitive basin areas, offering insights into the effects of landscape change processes at the micro-basin level in connection with climate change models.

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The establishment of river water quality monitoring network is crucial for watershed protection. However, the evaluation process of monitoring network layout involves significant subjectivity and has not yet to form a complete indicator system. This study constructed an indicator system based on the DPSR (Driving-Pressure-State-Response) framework in the Liao River Basin, China. SWAT model and ArcGIS were used to quantify the indicators. And the entropy weight-TOPSIS method was employed to rank monitoring points. The results showed that pressure and state indicators had a greater impact on the network layout, with the indicator for proportion of land use in residential areas carrying the largest weight of 0.136. It suggested that the risk of river pollution remained high, and the governance strategies needed to be improved. Priority monitoring points were mainly located in the east and middle of the basin, consistent with the distribution of human activities such as urban areas and farmland. In addition, the redundancy of points should be avoided, and evaluation results should be adjusted based on the actual situation. The study provided an evaluation method for the layout of monitoring points.

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Pesticides are a major source of pollution for ecosystems. In agricultural catchments, ponds serve as buffer areas for pesticide transfers and biogeochemical hotspots for pesticide dissipation. Some studies have highlighted the specific impact of ponds on the dynamics of pesticides, but knowledge of their cumulative effect at the watershed scale is scarce. Hence, using a modelling approach, we assessed the cumulative role of ponds in pesticide transfer in an agricultural basin (Southwest of France, 1110 km2). The Soil and Water Assessment Tool (SWAT) model was used to model the Save basin, including 197 ponds selected with a Multi-Criteria Decision Aiding Model based on their pesticide interception capacities. The daily discharge, the suspended sediment loads and two herbicide loads (i.e. S-metolachlor and aclonifen) in dissolved and particulate phases were accurately simulated from January 2002 to July 2014 at a daily time step. The presence of ponds resulted in a yearly mean reduction at the watershed outlet of respectively 61 % and 42 % of aclonifen and S-metolachlor fluxes compared to the simulations in the absence of ponds. Sediment-related processes were the most efficient for pesticide dissipation, leading to a mean dissipation efficiency by ponds of 51.0 % for aclonifen and 34.4 % for S-metolachlor. This study provides a first quantification of the cumulative role of ponds in pesticide transfer at the catchment scale in an intensive agricultural catchment.

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The hydrological regimes of watersheds might be drastically altered by climate change, a majority of Pakistan's watersheds are experiencing problems with water quality and quantity as a result precipitation changes and temperature, necessitating evaluation and alterations to management strategies. In this study, the regional water security in northern Pakistan is examined about anthropogenic climate change on runoff in the Kunhar River Basin (KRB), a typical river in northern Pakistan using Soil and Water Assessment tool (SWAT) and flow durarion curve (FDC). Nine general circulation models (GCMs) were successfully utilized following bias correction under two latest IPCC shared socioeconomic pathways (SSPs) emission scenarios. Correlation coefficients (R2), Nash-Sutcliffe efficiency coefficients (NSE), and the Percent Bias (PBIAS) are all above 0.75. The conclusions demonstrate that the SWAT model precisely simulates the runoff process in the KRB on monthly and daily timescales. For the two emission scenarios of SSP2-4.5 and SSP5-8.5, the mean annual precipitation is predicted to rise by 3.08 % and 5.86 %, respectively, compared to the 1980-2015 baseline. The forecasted rise in mean daily high temperatures is expected to range from 2.08 °C to 3.07 °C, while the anticipated increase in mean daily low temperatures is projected to fall within the range of 2.09 °C-3.39 °C, spanning the years 2020-2099. Under the two SSPs scenarios, annual runoff is estimated to increase by 5.47 % and 7.60 % due to climate change during the same period. Future socioeconomic growth will be supported by a sufficient water supply made possible by the rise in runoff. However, because of climate change, there is a greater possibility of flooding because of increases in both rainfall and runoff. As a result, flood control and development plans for KRB must consider the climate change's possible effects. There is a chance that the peak flow will move backwards relative to the baseline.

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Stream flow forecasting is a crucial aspect of hydrology and water resource management. This study explores stream flow forecasting using two distinct models: the Soil and Water Assessment Tool (SWAT) and a hybrid M5P model tree. The research specifically targets the daily stream flow predictions at the MH Halli gauge stations, located along the Hemvati River in Karnataka, India. A 14-year dataset spanning from 2003 to 2017 is divided into two subsets for model calibration and validation. The SWAT model's performance is evaluated by comparing its predictions to observed stream flow data. Residual time series values resulting from this comparison are then resolved using the M5P model tree. The findings reveal that the hybrid M5P tree model surpasses the SWAT model in terms of various evaluation metrics, including root-mean-square error, coefficient of determination (R2), Nash-Sutcliffe efficiency, and degree of agreement (d) for the MH Halli stations. In conclusion, this study shows the effectiveness of the hybrid M5P tree model in stream flow forecasting. The research contributes valuable insights into improved water resource management and underscores the importance of selecting appropriate models based on their performance and suitability for specific hydrological forecasting tasks.

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Assessing the spatiotemporal patterns of watershed water conservation under the influence of the South Asian monsoon climate and its response to precipitation is essential for revealing the evolving patterns of water conservation under different temporal scales. Following the principles of water balance and using the Soil and Water Assessment Tool (SWAT) model, we investigated the spatiotemporal patterns of water conservation and its response to precipitation in the Fangcheng River Basin of Beibu Gulf. The results showed that water conservation in Fangcheng River Basin calculated by SWAT model were 1637.4 mm·a-1, accounting for 50.7% of the mean annual precipitation. The variation of water conservation in different sub-basins was obviously different. Sub-basins with high forest coverage and steep slopes exhibited higher water conservation, while sub-basins with other land use types (such as cropland and grassland), gentle slopes, and intense human activities showed lower water conservation. At the monthly scale, both water conservation and its variation showed similar response characteristics to precipitation in the basin. The response of water conservation variation to sub-precipitation events could be classified into two types. For the short-term rainfall events (duration≤2 days), water conservation variation showed a linear relationship. For the medium to long-term rainfall events (2 days

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Watershed water quality modeling is a valuable tool for managing ammonium (NH4+) pollution. However, simulating NH4+ pollution presents unique challenges due to the inherent instability of NH4+ in natural environment. This study modified the widely-used Soil and Water Assessment Tool (SWAT) model to simulate non-point source (NPS) NH4+ processes, specifically incorporating the simulation of land-to-water NH4+ delivery. The Jiulong River Watershed (JRW) is the study area, a coastal watershed in Southeast China with substantial sewage discharge, livestock farming, and fertilizer application. The results demonstrate that the modified model can effectively simulate the NPS NH4+ processes. It is recommended to use multiple sets of observations to calibrate NH4+ simulation to enhance model reliability. Despite constituting a minor proportion (5.6 %), point source inputs significantly contribute to NH4+ load at watershed outlet (32.4∼51.9 %), while NPS inputs contribute 15.3∼17.3 % of NH4+ loads. NH4+ primarily enters water through surface runoff and lateral flow, with negligible leaching. Average NH4+ land-to-water delivery rate is about 2.35 to 2.90 kg N/ha/a. High delivery rates mainly occur at agricultural areas. Notably, proposed NH4+ mitigation measures, including urban sewage treatment enhancement, livestock manure management improvement, and fertilizer application reduction, demonstrate potential to collectively reduce the NH4+ load at watershed outlet by 1/4 to 1/3 and significantly enhance water quality standard compliance frequency. Insights gained from modeling experience in the JRW offer valuable implications for NH4+ modeling and management in regions with similar climates and significant anthropogenic nitrogen inputs.

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The study investigated the impact of climate and land cover change on water quality. The novel contribution of the study was to investigate the individual and combined impacts of climate and land cover change on water quality with high spatial and temporal resolution in a basin in Turkey. The global circulation model MPI-ESM-MR was dynamically downscaled to 10-km resolution under the RCP8.5 emission scenario. The Soil and Water Assessment Tool (SWAT) was used to model stream flow and nitrate loads. The land cover model outputs that were produced by the Land Change Modeler (LCM) were used for these simulation studies. Results revealed that decreasing precipitation intensity driven by climate change could significantly reduce nitrate transport to surface waters. In the 2075-2100 period, nitrate-nitrogen (NO3-N) loads transported to surface water decreased by more than 75%. Furthermore, the transition predominantly from forestry to pastoral farming systems increased loads by about 6%. The study results indicated that fine-resolution land use and climate data lead to better model performance. Environmental managers can also benefit greatly from the LCM-based forecast of land use changes and the SWAT model's attribution of changes in water quality to land use changes.

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This study establishes a calibrated SWAT (Soil and Water Assessment Tool) model for the Huntai Basin, driven by SSP126, SSP245, SSP585, and multi-model ensemble (MME) models in CMIP6 (Coupled Model Intercomparison Project-6), to investigate the effects of climate change on hydrological processes and pollution load in the Huntai Basin. The results show that the annual mean temperature and the annual precipitation will gradually increase. The nitrogen and phosphorus pollution loads in the basin exhibit a trend of decreasing-increasing-decreasing. The correlation between the nitrogen-phosphorus pollution load and the hydrological process strengthens with increasing radiative forcing. In the four scenarios, CO2 is a primary driving factor that contributes greatly to nitrogen and phosphorus pollution. The main differences are in the total driving factors, and SSP126 and SSP245 are less than those of other models. The total phosphorus and total nitrogen pollution in different climate models were higher than the average level during the benchmark period, except for ammonia nitrogen pollution, which was lower. The nitrogen and phosphorus pollution in SSP126 and SSP245 modes will reach the maximum in 2040s, and the pollution in other periods will be lower than that in SSP585 and MME scenarios. In the long run, the development state between SSP126 and SSP245 may be better appropriate for the Huntai Basin's future sustainable development. This paper analyzes the occurrence and influencing factors of nitrogen and phosphorus pollution under climate change to provide reference to the protection of water environment under changing environments.

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Land use/land cover (LULC) is a crucial factor that directly influences the hydrology and water resources of a watershed. In order to assess the impacts of LULC changes on river runoff in the Danjiang River source area, we analyzed the characteristics of LULC data for three time periods (2000, 2010, and 2020). The LULC changes during these periods were quantified, and three Soil and Water Assessment Tool (SWAT) models were established and combined with eight LULC scenarios to quantitatively analyze the effects of LULC changes on river runoff. The results revealed a decrease in the cropland area and an increase in the forest, grassland, and urban land areas from 2000 to 2020. Grassland, forest, and cropland collectively accounted for over 94% of the total area, and conversions among these land types were frequent. The SWAT models constructed based on the LULC data demonstrated good calibration and validation results. Based on the LULC data in three periods, the area of each LULC type changed slightly, so the simulation results were not significantly different. In the subsequent LULC scenarios, we found that the expansion of cropland, grassland, and urban areas was associated with increased river runoff, while an increase in forest area led to a decrease in river runoff. Among the various LULC types, urban land exerted the greatest influence on changes in river runoff. This study establishes three SWAT models and combines multiple LULC scenarios, which is novel and innovative. It can provide scientific basis for the rational allocation of water resources and the optimization of LULC structure in the Danjiang River source area.

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Grazing management is an important factor affecting the delivery of ecosystem services at the watershed scale. Moreover, characterizing the impacts of climate variation on water resources is essential in managing rangelands. In this study, the effects of alternative grazing management scenarios on provisioning, regulating, and supporting services were assessed in two watersheds with contrasting climates; the Lower Prairie Dog Town Fork Red River (LPDTFR) Watershed in North Texas and the Apple Watershed in South Dakota. The impacts of heavy stocking continuous grazing, light stocking continuous grazing, Adaptive Multi-Paddock (AMP) grazing, and an ungrazed exclosure were compared using the Soil and Water Assessment Tool (SWAT) model. Our results indicate that the quantity of snow and timing of snow melt substantially influenced grazing management effects on ecosystem services in the Apple Watershed. In contrast, precipitation was the main factor influencing these effects in the LPDTFR Watershed because it highly affected the variation in water cycling, streamflow, sediment, and nutrient controls. Simulated results indicated that AMP grazing was the optimal grazing management approach for enhancing water conservation and ecosystem services in both watersheds regardless of climatic conditions. The Apple Watershed, which is a snow-dominated watershed, exhibited greater ecosystem service improvements under AMP grazing (50.6%, 58.7%, 74.4%, 61.5% and 72.6% reduction in surface runoff, streamflow, and sediment, total nitrogen (TN) and total phosphorus (TP) losses, respectively as compared to HC grazing) than the LPDTFR Watershed (46.0%, 22.8%, 34.1%, 18.9% and 38.4% reduction in surface runoff, streamflow, and sediment, TN and TP losses, respectively). Our results suggest that improved grazing management practices enhance ecosystem services and water catchment functions in rangeland-dominated areas, especially in colder climates.

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In this study, we employed the random forest model to identify the riparian buffer zone in the upper and middle reaches of the Ziwu River, used the Soil and Water Assessment Tool (SWAT) to simulate and calculate the nonpoint source pollution load in the riparian buffer zone, and used empirical formulas to estimate the pollutant concentration when surface runoff passes the edge of the riparian buffer zone. Moreover, through correlation analysis, we identified the main factors that affect the safe width of the riparian buffer zone. By combining these factors with the characteristic parameters of the riparian buffer zone and the water quality demand, we analyzed and calculated the safe width of the riparian buffer zone. Our findings are as follows: ① the simulated values of the SWAT model were highly consistent with the measured values. Specifically, the calibration and verification results of the hydrological station achieved Ens ≥ 0.65, RE < ± 15%, and R2 ≥ 0.85, while the overall total nitrogen and total phosphorus loads achieved Ens ≥ 0.65, RE < ± 15%, and R2 > 0.65. ② We found that the total nitrogen (TN) and total phosphorus (TP) loads in the riparian buffer zone gradually increased from upstream to downstream. Among these loads, the normal season had the largest TN and TP concentrations reaching the edge of the riparian buffer zone, while the dry season had the minimum concentrations. ③ The factors affecting the safe width of the riparian buffer zone included the connectivity, slope of the buffer zone, cultivated land area, and regional population density. For the effective protection of water quality, it is recommended that the upstream, midstream, and downstream buffer zones be at least 77.9 m, 33.37 m, and 60.25 m wide, respectively.

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Ecosystem health of the Chishui River Basin (CRB, a crucial ecological barrier in the upper reaches of the Yangtze River) is vital for the ecological security and sustainability of the Yangtze River Basin. We used RUSLE model, SWAT model, Fragstats and geographic detectors to construct a theoretical framework of ecosystem health assessment for CRB, and examined the spatiotemporal variations and driving factors of ecosystem health in CRB under ecological restoration from 2010 to 2020. The results showed that ecosystem service in the CRB decreased and then increased during 2010-2020 and the overall trend was downward. The overall ecosystem service function was higher in the Danxia (non-karst) area than that in the karst area. The ecosystem health was generally subhealthy, with the Danxia area being mostly extremely healthy and healthy, whereas the karst area mostly subhealthy and unhealthy. There were differences in the dominant drivers of ecosystem health between karst and Danxia areas. Vegetation, precipitation, and bedrock bareness rate were the dominant drivers in the karst area, while vegetation, land use, and precipitation were the dominant factors in Danxia area. After interaction detection, the explanatory power of impact factors increased, and the dominant interaction factor combinations in different geomorphological type regions had shown great differences. Among them, precipitation∩normalized difference vegetation index (NDVI), precipitation∩digital elevation model (DEM) and precipitation ∩ bedrock bareness rate were the dominant interaction factor combinations in the karst area, and NDVI∩precipitation, NDVI∩land use and NDVI∩DEM were the dominant interaction factor combinations in Danxia area. These results would provide scientific support for health maintenance and conservation of CRB ecosystem.

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