Large-scale ecological restoration is a critical strategy for combating land degradation, however, its hydrological implications, especially on evapotranspiration (ET), remain uncertain due to complex spatial heterogeneity and non-linear feedback loops between vegetation and water. To address this, a novel attribution framework for identifying the driving mechanisms of ET and its components (transpiration, Ec; soil evaporation, Es) was developed on the Loess Plateau for the periods 2000-2020, which combines the Two-Source Energy Balance (TSEB) model with the Bayesian Ridge Regression. Methodologically, this zoning framework significantly outperformed traditional global modelling, reducing the prediction error for Ec by a median of 24.3% across the heterogeneous transition zones. The results indicate a fundamental shift in the regional water cycle: ET increased by 9.31 mm/yr, primarily driven by the increase in Ec (10.24 mm/yr). Crucially, the driving forces exhibited distinct spatiotemporal divergence: vegetation restoration dominated in the hilly-gully regions (Zones A and B), climatic factors controlled the arid sandy areas (Zone C). Furthermore, two universal non-linear regulation mechanisms have been identified: a "V-shaped" response for Es (shadow vs. interception) and an "Inverted Ushaped" response for Ec (saturation effect). Specifically, the optimal Leaf Area Index (LAI) threshold for transpiration in Zone A has been shifted from 0.47 (2000-2010) to 0.42 (2011-2020), indicating an intensified water stress. These findings challenge the "one-size-fits-all" greening policy and advocate for a paradigm shift towards a management based on a synergy between greening and water. In addition, actionable strategies have been proposed to ensure the sustainability of ecological engineering in water-limited regions globally, including thinning of dense plantations to maintain LAI close to optimal thresholds and prioritization of water-saving agriculture in arid areas. The results obtained in this study could provide scientific reference for the implementation of ecological engineering and effective utilization of water resource in arid areas.

Historically, there has been a dispute over water allocation between users and policymakers in Iran's Zayandeh-Roud Basin (ZRB). In this study, we used the "System of Environmental-Economic Accounting for Water" (SEEAW) framework in combination with the hydrologic model "Soil and Water Assessment Tool" (SWAT) to achieve the water balance in ZRB. We used SEEAW to combine a wide range of water-related statistics across stakeholders and SWAT to evaluate the unknown agricultural water use. The SWAT model is calibrated based on the stream flows and crop yields in the basin. The model assess the renewable water of the basin into two components, about 363 and 70 mm as green and blue water, respectively. Also results from the physical water supply and water use tables demonstrates that the agricultural sector uses 78% of the total renewable freshwater, followed by the residential, 16%, and the industrial sector, 6%. The flows of water from source to services in ZRB are traced based on the water supply and water use tables. The flow diagram shows that 8 MCM of industrial reused water was transferred to the agricultural sector, and 137 MCM and 18 MCM of water from the wastewater treatment plants to the agricultural and industrial sectors, respectively. Furthermore, the results show that the index of the basin dependence on groundwater resources is high (61%), the value of water stress is high (0.88) and the dependence of the basin on transboundary water resources is 30%. Therefore, this method is highly beneficial for achieving a conceptual water balance in disputed basins without enough agricultural water uses data. Schematic summary of physical supply and use tables (green: return flow from agriculture into the environment, purple: return flow from industries into the environment, gold: return flow from electricity into the environment, brown: return flow from services and household into the environment, pink: return flow from ISIC37 into the environment red: flow out of the basin, blue: flow from the environment, cyan: flow to the basin, grey: flow within the economy). image

Evidence suggests that climate change will create uncertain regional agricultural production stability in the coming decades. This research investigated the impact of climate change on hydrology and sugar beet yield as one of the main crops in the Urmia lake basin using the Soil and Water Assessment Tool (SWAT). To address this, a baseline SWAT model was setup for 1986-2014. Afterward, the output was calibrated (1989-2004) and validated (2005-2014) in the SWAT-CUP software using the SUFI2 algorithm to simulate streamflow of 23 gauging stations and crop yield. The Nash-Sutcliffe efficiency was 0.43 and 0.53 for calibration and validation periods, sequentially. The Percent Bias was 45% and 16% for calibration and validation periods, respectively. As well as the agreement indices of 0.71 and the little Percent Bias (-6% to 10%) for crop production, verified the model's efficiency. The next step was downscaling and bias-correction of the precipitation and temperature data received from 3 climate models, namely GFDL, HadGEM2, and IPSL under RCP4.5 and RCP8.5 using CCT program. Then, the downscaled data were fed to SWAT, and Finally, hydrological fluxes and sugar beet yield were estimated for 2021-2050. Despite a dispersion of precipitation changes ranging from -12% to +35% in most scenarios, results highlight the pivotal role that the warmer temperature (+2.7°C) increases evaporation, resulting in sharpened pressure on water resources and runoff, especially, at the beginning of crop growth season. Finally, the negative impacts on crop productivity (-45%) is not unexpected. This means that sugar beet may suffer from climate change impacts, and the production of this plant will change over the next period in this region. Keywords: Climate Change, Sugar Beet, Urmia Lake Basin, Sensitivity Analysis, SWAT.

As water quality declines and water resources become scarce, water conservation emerges as the central challenge of water resource management and sustainable development in the watershed ecosystem. The Yellow River, known as the "mother river" of China, of which the water conservation function has received significant public attention in the changing environmental conditions. In the study, the InVEST water yield model was utilized to evaluate the spatiotemporal dynamics of water conservation; the MK trend test and Sen's slope were used to examine the trends of precipitation and water conservation, respectively. Additionally, the response of water conservation to climate, land use, and soil changes during the period 1981–2020 was also discussed. The results showed that under the comprehensive influence of various factors, the water conservation of the YRB showed a decreasing and then increasing trend, which was presumed to be associated with the Grain for Green Project. Water conservation showed an increasing trend in the upstream area of the study area while decreasing in the lower reaches in recent decades. The changes in water conservation function in the YRB resulted from the comprehensive influence of climate factors, soil conditions, and land use types. Besides, woodland and grassland provide the highest water conservation capacity, which initially increased and then decreased with the increase of slope. The spatial analysis emphasized the critical role of water conservation in the Yellow River Basin, particularly highlighting the source area (above Lanzhou Station), the southern tributaries of the Wei River, and the upper reaches of the Yiluo River as significant water conservation zones. These areas should be considered crucial and given priority in regional water resource management and ecological protection efforts. The findings of this study could provide a theoretical foundation for ecological protection and water security in the YRB, which are essential for sustainable development.

Climate change–induced precipitation anomalies during extremely wet years (EWYs) result in substantial nitrogen losses to aquatic ecosystems (Nw). Still, the extent and drivers of these losses, and effective mitigation strategies have remained unclear. By integrating global datasets with well-established crop modeling and machine learning techniques, we reveal notable increases in Nw, ranging from 22 to 56%, during historical EWYs. These pulses are projected to amplify under the SSP126 (SSP370) scenario to 29 to 80% (61 to 120%) due to the projected increases in EWYs and higher nitrogen input. We identify the relative precipitation difference between two consecutive years (diffPr) as the primary driver of extreme Nw. This finding forms the basis of the CLimate Extreme Adaptive Nitrogen Strategy (CLEANS), which scales down nitrogen input adaptively to diffPr, leading to a substantial reduction in extreme Nwwith nearly zero yield penalty. Our results have important implications for global environmental sustainability and while safeguarding food security.

Landuse and climate change are the two main dynamics significantly affecting watershed hydrology. Adequate knowledge about how these changes will alter the hydrologic regime provides valuable information for future water resources planning and management. The current study attempts to analyze the joint consequences of these dynamics on the future hydrological response of the Gorganroud watershed in northern Iran. For landuse, the integrated Markov Chain analysis and Multi-Layer Perceptron Neural Network (MC-MLPNN) algorithm were used to obtain landuse for 2030 and 2050. For climate, we developed future scenarios based on the downscaled data from MPI-ESM-MR for 2021–2040 and 2041–2060. Soil and Water Assessment Tool (SWAT) was used to simulate watershed hydrology. We found that (1) from 1986 to 2050, agriculture and rangeland are likely to expand by 18.6% and 10.7% of the total watershed area, respectively, at the expense of forest covers. (2) Temperature and precipitation are expected to increase by 1.3 °C and 2.5 °C and by 31.7% and 27.1% for Representative Concentration Pathway 8.5 (RCP8.5) during 2021–2040 and 2041–2060, respectively, compared to the baseline of 1976–1995. (3) We found that the integrated landuse and climate change will likely increase annual evapotranspiration during 2021–2040 and 2041–2060 by 113.9% and 11.4%, lateral flow by 14.6% and 7%, baseflow by 166.7% and 77.2%, surface runoff by 54.2% and 41%, water yield by 50.5% and 35.9%, and streamflow by 48.6% and 32.1% for RCP8.5 compared to the baseline of 1976–1995.

Large-scale implementation of the Grain for Green Project since 1999, which took the Yellow River Basin (YRB) as the core ecological restoration area, has had an important impact on the hydrological processes and ecological environment. Whether such forest restoration construction is conducive to achieving land degradation neutrality as well as improving water conservation capacity has become a hot research topic. The Yiluo River basin (YLRB), one of the most important water conservation areas in the YRB, was selected as the study area. Firstly, the transfer matrix was used to analyze the changes in the two land use maps in 1990 and 2015 and to determine the transformation relationship between different land use types. Furthermore, land degradation was also investigated for further exploration of the correlation between land degradation neutrality and water conservation. The effects of land use and cover changes (LUCC) on the water conservation capacity across the YLRB were investigated by combining the Soil and Water Assessment Tool (SWAT) model, water conservation assessment method and land use change scenarios method. The results showed that the land degradation area was mainly located in the residential area and agricultural land in the downstream of the YLRB, and the execution of the Grain for Green Project is beneficial in promoting land degradation neutrality and increasing the water conservation capacity. The water conservation capacity across the YLRB approximately increased by 19.30 mm yr−1 as every 10% of agricultural land converted to forest, showing a greater increase in the upstream than that in the downstream. Rainfall, Normalized Difference Vegetation Index (NDVI), and temperature were the primary factors affecting water conservation in the YLRB, while geological lithology also affects the spatial distribution of water conservation. The findings of this study could provide a theoretical basis for water resources and ecological environment protection.

A predictive understanding of the source-specific (e.g., point and diffuse sources) land-to-river heavy metal (HM) loads and HM dynamics in rivers is essential for mitigating river pollution and developing effective river basin management strategies. Developing such strategies requires adequate monitoring and comprehensive models based on a solid scientific understanding of the watershed system. However, a comprehensive review of existing studies on the watershed-scale HM fate and transport modeling is lacking. In this review, we synthesize the recent developments in the current generation of watershed-scale HM models, which cover a wide range of functionalities, capabilities, and spatial and temporal scales (resolutions). Existing models, constructed at various levels of complexity, have their strengths and weaknesses in supporting diverse intended uses. Additionally, current challenges in the application of watershed HM modeling are covered, including the representation of in-stream processes, organic matter/carbon dynamics and mitigation practices, the issues of model calibration and uncertainty analysis, and the balance between model complexity and available data. Finally, we outline future research requirements regarding modeling, strategic monitoring, and their combined use to enhance model capabilities. In particular, we envisage a flexible framework for future watershed-scale HM models with varying degrees of complexity to accommodate the available data and specific applications.

Cadmium (Cd) is a toxic trace element that threatens ecosystem and human health worldwide. Quantitative understanding of land-to-river Cd fluxes and riverine Cd loads in response to various watershed management measures is essential for developing effective mitigation strategies for large river systems. However, detailed analyses of watershed Cd dynamics under different management scenarios are lacking. Here, we investigated the effects of four management scenarios by combining point and nonpoint source control measures with a previously developed watershed Cd model that was validated with site-specific measurements. The Soil and Water Assessment Tool-Heavy Metal (SWAT-HM) model was applied to simulate the Xiang River Basin's (XRB, similar to 90,000 km(2)) baseline hydrology, soil erosion, and Cd transport processes in China. Using scenario simulations, we found that smelting emissions reduction was the most influential measure for controlling dissolved Cd (DCd) and particulate Cd (PCd) loads at the basin scale. Elimination of 50% emissions from the smelting sector could significantly (p < 0.05) decrease the monthly mean loads of DCd from 940 to 720 kg and of PCd from 2150 to 1760 kg at the XRB outlet. In contrast, reduction in mining emissions had no influence on the Cd load at the XRB outlet because most mining Cd emissions occurred upstream and midstream of the XRB, and the natural attenuation processes in the river limit the transportation of Cd downstream. The effectiveness of management practices for reducing total Cd (TCd) and DCd loads was not always mutually beneficial. For example, soil erosion control may decrease the PCd flux via erosion but increase the subsurface DCd flux to rivers due to greater lateral flow. In addition, increasing soil pH could be a practical and effective measure to reduce nonpoint DCd and PCd fluxes. Such effects may be caused by the declined upward migration of Cd through soil evaporation owing to the decreased Cd concentration in the soil pore water after pH increases. In conclusion, effective watershed management of Cd pollution in large basins requires an integrated plan that combines multiple mitigation measures; strategic modeling experiments could provide valuable insights into the design of such plans.

In 2011, China invested US$9.8 billion to combat the severe heavy metal pollution in the Xiang River basin (XRB), aiming to reduce 50% of the 2008 industrial metal emissions by 2015. However, river pollution mitigation requires a holistic accounting of both point and diffuse sources, yet the detailed land-to-river metal fluxes in the XRB remain unclear. Here, by combining emissions inventories with the SWAT-HM model, we quantified the land-to-river cadmium (Cd) fluxes and riverine Cd loads across the XRB from 2000 to 2015. The model was validated against long-term historical observations of monthly streamflow and sediment load and Cd concentrations at 42, 11, and 10 gauges, respectively. The analysis of the simulation results showed that the soil erosion flux dominated the Cd exports (23.56-80.14 Mg yr-1). The industrial point flux decreased by 85.5% from 20.84 Mg in 2000 to 3.02 Mg in 2015. Of all the Cd inputs, approximately 54.9% (37.40 Mg yr-1) was finally drained into Dongting Lake; the remaining 45.1% (30.79 Mg yr-1) was deposited within the XRB, increasing the Cd concentration in riverbed sediment. Furthermore, in XRB's 5-order river network, the Cd concentrations in small streams (1st order and 2nd order) showed larger variability due to their low dilution capacity and intense Cd inputs. Our findings highlight the need for multi-path transport modeling to guide future management strategies and better monitoring schemes to restore the small polluted streams.

Non-point source (NPS) pollution has gradually become the main source of water environmental pollution with the rapid economic development during the recent decades, especially for the economically developed Yangtze River Basin of China. Due to rapid urbanization, the pressure of the water environment in the Poyang Lake basin (PYLB) has been increasing. In this study, the spatial and temporal variations of NPS pollution loads including total nitrogen (TN) and total phosphorus (TP) in the PYLB during the period 2003-2012 were firstly investigated by using the SWAT; then the changes in NPS pollution loads under different land use types were identified by using the SWAT, land use transition matrix, statistical analysis and scenario analysis methods; finally, the NPS pollution risk assessment were achieved by means of the grey water footprint theory. The results showed that the NPS pollution loads in the PYLB were concentrated from April to June with a large inter-annual variability. The Gan River basin contributed the largest proportion of pollutants entering into the Poyang lake while the Xiu River basin produced the smallest pollution loads. Under the background of the policy of "Grain for Green Project" since 2002, the areas of cultivated land, grassland and bare land decreased during the period 2000-2010, while those of forest land and settlement increased. As the main source of NPS pollution, the area of cultivated land has decreased, while the unit load intensity under cultivated land has significantly increased. By calculating the annual GWF of TN and TP loads and their corresponding WPL, which all showed an upward trend. The results obtained in this study have practical significance for reducing the NPS pollution loads in the PYLB and controlling the environmental pollution in the Yangtze River.

Flood disaster is considered a significant natural hazard due to their devastating effects. The 2019 flood in Northern Iran drastically affected the lives of Indigenous Turkmen pastoralists. This work assesses the vulnerability of the pastoral families living in flood regions. We used the Geographical Information System, Multi‐Criteria Decision Analysis, and semi‐structured interviews to analyze the flood vulnerable areas. Initially, we interviewed 20 individuals and then formulated a questionnaire completed by 69 pastoralists in rangelands affected by floods in Golestan province. Result showed that 91% of the participants thought road networks and 76% thought livestock were the most affected components of the rangeland ecosystems in the 2019 flood. Moreover, we found supplementary feeding, watering costs, and forage quantity to be the most affected items in the economy of pastoral families. The main rangeland degrading factors were overgrazing, climate change, drought, and water shortages. The main reasons for overgrazing were the high prices of supplementary feeding, low forage productivity of the rangelands, and financial difficulties of pastoralists. We indicated that pastoral communities in the semi‐arid rangeland of Northern Golestan were highly vulnerable to flood. Hence, proper management of rangelands and building pastoral family resilience requires the attention of nature conservationists and management organizations at the national level.

The Soil and Water Assessment Tool (SWAT) is one of the most widely used and well-tested eco-hydrological models. However, parameter calibration, sensitivity analysis and uncertainty analysis remain among the most challenging tasks. Existing SWAT parameter calibration, sensitivity analysis, and uncertainty analysis tools are either commercial products or free tools with limited options. This study demonstrates an interactive graphical user interface tool in the R environment for SWAT parameter calibration, sensitivity and uncertainty analyses, and visualization, called R-SWAT. Different R functions/packages for parameter calibration, sensitivity analysis, and uncertainty analysis have been incorporated into R-SWAT. Third-party packages can be integrated into R-SWAT with minimum effort. The application of R-SWAT for a test case study demonstrates its functionalities. In general, R-SWAT (1) is a potential platform for developing and testing new sensitivity or optimization packages, and (2) promotes the understanding of hydrological processes with open-source SWAT and R.

Identification of critical source areas (CSAs) for non-point source (NPS) pollution is of great significance for environment governance and prevention. However, the CSAs are generally characterized as great spatial dispersion, and spatially heterogeneous precipitation has a great influence on the spatial distribution of nutrient yields. Therefore, we identify the CSAs for nutrient yields in an agricultural watershed of Northeast China at hydrological response units (HRUs) scale based on the Soil and Water Assessment Tool (SWAT), assess the impacts of spatially heterogeneity of precipitation on the identification of the CSAs, analyze the sensitivity of nutrient yields to precipitation by scenarios analysis method, and further identify priority management areas (PMAs) that have poor ability to retain nutrients. The results showed that the CSAs for nutrient yields identified by uniform precipitation showed greater fluctuation range and coverage area than actual precipitation; the major prevention areas of total nitrogen (TN) yield were mainly distributed in regions nearby main stem of lower reaches, while that of total phosphorus (TP) yield were mostly located in urban area nearby outlet of the watershed; the identification of the PMAs significantly decreased the CSAs for TN yield, whereas that for TP yield was no significant difference with the CSAs. This study could provide scientific guidance for the NPS pollution governance and prevention.

Using the parameters associated with the best-fit simulation (i.e., the simulation with the highest objective function value) to represent a calibrated hydrological model is inadequate. The reason is that the calibrated models best objective function value is usually not significantly different from the next best value or the values after that. This non-uniqueness of the objective function values causes a problem because the best solution's parameters are often significantly different from the next best set of parameters. Therefore, only using the best simulation parameters as the calibrated model's sole parameters to interpret the watershed processes or perform further modeling analyses could produce misleading results. Furthermore, the lack of pristine watersheds makes the task of watershed-scale calibration increasingly challenging. Subjective thresholds of acceptable performance criteria suggested by some researchers, based on comparing the measured and the best solution signals, are often not achievable. Hence, to obtain a satisfactory fit, researchers and practitioners are often forced to compromise the science behind their work. This article discusses the fallacy in using the best-fit solution in hydrologic modeling. A two-factor statistic to assess the goodness of calibration/validation is discussed, considering model output uncertainty.

In this study, contributions of climate change and human activity to streamflow changes were estimated to enable decision makers to develop adaptation strategies for management of regional water resources. Flow trends and climate variables were analysed with the Mann-Kendall method. The year 1986 was selected to perform the Pettitt test to identify the change point of the runoff time series. Then, three methods were used for impact differentiation: climatic elasticity, least-squares support-vector machine (LS-SVM), and the soil and water assessment tool (SWAT). The results showed that climate change (38-67%) and human activities (33-62%) influence runoff reduction. Thus three management scenarios are introduced to reduce the effects of climate change and human activity: (1) adjusting wheat and barley cultivation levels; (2) maintaining wheat and barley cultivation levels and replacing other crops with potatoes; (3) increasing irrigation efficiency. All scenarios showed an increase in runoff, but the first scenario had the most impact.

The impact of climate change on water availability has become a significant cause for concern in the Zayandeh-Roud Reservoir in Iran and similar reservoirs in arid regions. This study investigates the climate change impact on water supply and availability in the Zayandeh-Roud River Basin. For better management, the Soil & Water Assessment Tool (SWAT) was used to develop a hydrologic model of the basin. The model was then calibrated and validated for two upstream stations using the Sequential Uncertainty Fitting (SUFI-2) algorithm in the SWAT-CUP software. The impact of climate change was modeled by using data derived from five Inter-Sectoral Impact Model Intercomparison Project general circulation models under four Representative Concentration Pathways (RCPs). For calibration (1991–2008), the Nash–Sutcliffe efficiency (NSE) values of 0.75 and 0.61 at the Ghaleshahrokh and Eskandari stations were obtained, respectively. For validation (2009–2015), the NSE values were 0.80 and 0.82, respectively. The reservoir inflow would probably reduce by 40–50% during the period of 2020–2045 relative to the base period of 1981–2006. To evaluate the reservoir's future performance, a nonlinear optimization model was used to minimize water deficits. The highest annual water deficit would likely be around 847 MCM. The lowest reservoir reliability and the highest vulnerability occurred under the extreme RCP8.5 pathway.

Landuse change and climate change are the main drivers of hydrological processes. The purpose of this study was to analyse the separate and combined future effects of climate and landuse changes on water balance components on different spatial and temporal scales using the integrated hydrological Soil and Water Assessment Tool model. The study focused on the changes and relationship between water yield (WYLD) and sediment yield (SYLD) in the heterogeneous Taleghan Catchment in Iran. For future climate scenarios, RCP 4.5 and RCP 8.5 of GFDL-ESM2M GCM were used for 2020–2040. A Markov chain model was used to predict landuse change in the catchment. The results indicated an increase in precipitation and evapotranspiration. The findings also showed that the relationship between WYLD and SYLD is direct and synergic. Climate change has a stronger effect on WYLD than landuse change, whereas landuse change has a stronger effect on SYLD. The conversion of rangelands to barren land is the most critical landuse change that could increase SYLD. The highest increase in WYLD and SYLD in scenario RCP4.5 resulted from the combined effects of climate and landuse change. We estimated WYLD of about 295 mm and SYLD of around 17 t/ha. The proposed methodology is universal and can be applied to similar settings to identify the most vulnerable regions. This can help prioritize management strategies to improve water and soil management in watersheds.

Conservation of natural resources is vital for sustainable management, especially in fragile semi-arid ecosystems. Forest plantations can provide a wide range of ecosystem services and deliver a measure of protection for soil and water resources. This study proposes a novel framework (Optimum Land Suitability Score, OLSS) to prioritize the most suitable areas with high priority for restoring degraded lands and protecting erosion-prone areas. We applied OLSS to the Latian watershed located in Tehran, Iran. The Latian watershed was divided into 56 sub-basins, where we studied the importance of each sub-basin for afforestation. We used a multicriteria analysis using the Fuzzy Analytical Network Process to bridge the gap between previous studies for determining suitable areas for afforestation in which 21 factors of environmental variables, morphometric characteristics, and topographical indices were considered. Finally, sub-basins were divided into four classes based on the fuzzy theory. The evaluated result indicated that 9 sub-basins showed the highest priority for afforestation. The identified sub-basins were mostly located in areas of depleted plant coverage due to overgrazing and human interventions. We proposed afforestation with proper species adapted to the environmental characteristics of prioritized sub-basins as ecological management. The measure should decrease erosion and flood risk and sustain the Latian reservoir storage capacity. OLSS offers valuable information for watershed managers and decision-makers to invest in soil conservations.