Soil And Water Assessment Tool Research Articles

Groundwater sustainability mapping for managed aquifer recharge in Dwarkeswar River basin: Integration of watershed modeling, multi-criteria decision analysis, and constraint mapping

Groundwater sustainability is a pressing issue in many regions, especially in semi-arid and drought-prone areas, impacting progress towards achieving the Sustainable Development Goals (SDGs). This study addresses this challenge by assessing Managed Aquifer Recharge (MAR) potential in India's Dwarkeswar River basin. The study employs a systematic approach integrating watershed modeling using the Soil and Water Assessment Tool (SWAT), multi-criteria decision analysis (MCDA), and constraint mapping techniques. Initially, the SWAT model evaluates water availability for MAR, followed by an MCDA-AHP method to identify optimal sites based on ten spatial parameters encompassing technical, economic, and environmental criteria. Furthermore, the study employs constraint mapping to refine site suitability assessments and sensitivity analysis to gauge the robustness of the results. The SWAT analysis revealed substantial variation in runoff volumes among the eight sub-basins, ranging from 8.34 m³/s to 136.28 m³/s, indicating significant availability of source water for MAR. Results from the MCDA followed by constraint mapping indicate that 51.57% of the study area is unsuitable for MAR, while 0.12%, 34.59%, and 13.72% are classified as low, moderate, and suitable zones, respectively. Sensitivity analysis reveals that geological attributes, soil thickness, runoff, and slope significantly influence the suitability scores, underscoring their impact on MAR feasibility. Validation with major pond locations confirmed the accuracy of this integrated approach in identifying suitable sites for MAR initiatives. This emphasizes the importance of holistic groundwater management strategies for sustainable water resource utilization and achieving the SDGs.

Assessment and mapping of potential sites for small-scale hydropower in Gidabo River catchment

ABSTRACT This study assessed the small-scale hydropower potential (SHP) of the Gidabo River catchment. The Soil and Water Assessment Tool (SWAT) hydrological model was used to estimate the streamflow in the river networks. The model was calibrated and validated at Messa and Apposto gauging stations, and the results for the coefficient of determination (R2) and Nash-Sutcliffe efficiency (NSE) revealed that the observed and simulated streamflow results agree fairly well at the calibration and validation locations. Thus, the simulated streamflow at the sub-catchment outlets was used to determine design discharge at 50%, 75%, and 95% flow dependability. The potential assessment was conducted under a scenario of 500, 1000 and 2000 m horizontal intervals along the stream networks. The study revealed that the river catchment has the potential to develop run-of-river-type plants at different locations with 50%, 75%, and 95% dependability, though it varies from place to place.

Coupled natural-social water system in a subwatershed of the Tennessee River Basin

Regional water cycle systems are increasingly characterized by the dual effect of natural and social processes, which have profound impacts on global water security. However, accurately interpreting the changes in the coupled natural-social water system and identifying the driving factors pose significant challenges. Here, we attempted to model a coupled natural-social water system in the East Fork Poplar Creek (EFPC) watershed of the Tennessee River, United States. The study area features two social water cycle components: a local water transfer project and the Oak Ridge Wastewater Treatment Facility (ORWTF). We conducted the Soil and Water Assessment Tool (SWAT) modeling in the open-source light-weight QGIS software, with the synthesis of various climate and land use change scenarios in both historical periods (1980–2016) and future periods (2017–2050). We achieved more accurate and realistic model simulations when considering the social water cycle components, indicating that the social water cycle accounted for 13–18 % of the observed streamflow. Climate variation/change dominates natural runoff changes. Though land use and cover change (LUCC) had minimal effect on natural runoff, it had a profound impact on the process of runoff generation, i.e., surface runoff (RS) and subsurface runoff (RSS). Specifically, LUCC would be responsible for 152 % and 45 % of the changes in RS and RSS, respectively, in future periods. This study highlights the significance of artificial water discharge and withdrawal impacts on the water cycle and emphasizes the need for water resources management measures that fully consider natural-social hydrological processes.

The combined impact of climate change scenarios and land use changes on water resources in a semi-arid watershed

This study proposes a combined approach involving climate change scenarios and varied land use and land cover (LULC) projections in a semi-arid watershed (El Grou) located in Morocco. The Soil and Water Assessment Tool (SWAT) model was coupled with land use scenarios generated using the Cellular Automata-Markov model for three dates (2030, 2040, and 2050) and future climate projections from the CMIP5 model under RCP 4.5 and 8.5 scenarios. Future precipitation and temperature projections indicate a decrease in annual precipitation by 5 % to 34 % and an increase in average temperatures, particularly during the summer months. LULC changes reveal a significant decline in agricultural lands and forests, with an expansion of bare soil by 2050. These changes, analyzed through three SWAT models representing different time periods, indicate a decrease in surface runoff by 41 % to 73 %, a reduction in total water yield by 21 % to 53 %, and a decline in groundwater recharge, posing significant challenges for water resource management and ecosystem health. The study underscores the need for integrated land and water management strategies, incorporating climate change adaptation measures, to ensure sustainable water resource utilization and build resilience in the El Grou watershed and similar semi-arid regions.

Assessment of climate change on river streamflow under different representative concentration pathways

Climate change and excessive greenhouse gas emissions profoundly impact hydrological cycles, particularly in arid and semi-arid regions, necessitating assessments of their effects on water resource management, agriculture, soil fertility, nutrient transport, hydropower generation, and flood risk. This study investigates climate change repercussions on streamflow in the Zarrineh River Basin, Iran, across three decadal intervals (2020–2029, 2055–2064, and 2090–2099) aiming to develop effective adaptation and mitigation strategies. Four General Circulation Models (GCMs), chosen based on distinct Representative Concentration Pathways (RCPs) determined by the annual mean temperature gradient, are employed. These models generate daily maximum (Tmax) and minimum (Tmin) temperatures along with precipitation data. Subsequently, these variables are integrated into the Soil and Water Assessment Tool (SWAT) model to analyze river flow alterations for each decadal timeframe. Comparison between future projections and observed climate data reveals a gradual decline in precipitation and Tmax, coupled with a substantial increase in Tmin. The average precipitation diminishes from 0.77 mm in the period 1985–1994 to a range of 0.42–0.28 mm in 2090–2099. The simulated flow at the basin outlet highlights that the GCM with the highest annual mean temperature gradient yields the lowest streamflow, while conversely, the model with the lowest gradient generates the highest. Consequently, streamflow experiences a decline from 52 m3/s in 1985–1994 to a range of 41–20 m3/s in 2090–2099.

Quantifying the impacts of climate change and human activities on runoff and suspended sediment load in the Lhasa River Basin, Tibetan Plateau

AbstractQuantifying the attribution of climate change and human activities on runoff and suspended sediment load is crucial for formulating future watershed management measures, especially in the ecologically fragile alpine region, which is more susceptible to climate change and human activities. In this study, the temporal changes in runoff‐suspended sediment load and the potential impact factors (i.e., precipitation, potential evapotranspiration (PET), land use/land cover change (LULC) and reservoir operation) were investigated in the Lhasa River Basin (LRB) from 1956 to 2020. In addition, the contributions of those factors to the changes in runoff and suspended sediment load were quantitatively evaluated based on physically‐based Soil and Water Assessment Tools (SWAT). The results indicated that annual runoff and suspended sediment load showed an increasing but insignificant trend during 1956–2020, while annual precipitation and PET showed a significant increasing trend at a rate of 0.94 and 1.07 mm/yr, respectively. LULC mainly presented an increase in forestland area followed by a decrease in grassland and bare land area due to the implementation of ecological projects. Runoff and suspended sediment load changed abruptly at approximately 1995 and 2005 based on three abrupt change identification methods, thus, the study period was further divided into three substages: baseline period (P0, 1956–1994), dramatically increased period (P1, 1995–2004) and slightly decreased period (P2, 2005–2020). The attribution analysis showed that climate change was the dominant contributor to runoff and suspended sediment load increments during P1. LULC caused the decline in runoff and suspended sediment load in both P1 and P2, with their contribution increasing significantly from 0.40% and 4.73% in P1 to 50.24% and 51.79% in P2, respectively. Reservoir operation was the second key factor in runoff and suspended sediment load reduction in P2, contributing 42.07% and 43.72%, respectively. These findings provide the scientific foundation for reasonably allocating water resources and statistical support for the benefit evaluation of implementing ecological projects in the basin.

Effects of Climate Change and Human Activities on Runoff in the Upper Reach of Jialing River, China

In recent years, the runoff of numerous rivers has experienced substantial changes owing to the dual influences of climate change and human activities. This study focuses on the Lixian hydrological station’s controlled basin, located in the upper reaches of the Jialing River in China. The objective is to assess and quantify the impacts of human activities and climate change on runoff variations. This study analyzed runoff variations from 1960 to 2016 and employed the Soil and Water Assessment Tool (SWAT) model, the long short-term memory (LSTM) model, and eight Budyko framework formulations to assess factors influencing runoff. Additionally, it used the patch-generating land use simulation (PLUS) and SWAT models to simulate future runoff scenarios under various conditions. The results indicate the following. (1) The study area has witnessed a significant decline in runoff (p < 0.01), while potential evapotranspiration shows a significant upward trend (p < 0.01). Precipitation displays a nonsignificant decreasing trend (p > 0.1). An abrupt change point in runoff occurred in 1994, dividing the study period into baseline and change periods. (2) The Budyko results reveal that human activities contributed 50% to 60% to runoff changes. According to the SWAT and LSTM models, the contribution rates of human activities are 63.21% and 52.22%, respectively. Human activities are thus identified as the predominant factor in the decline in runoff. (3) Human activities primarily influence runoff through land cover changes. Conservation measures led to a notable increase in forested areas from 1990 to 2010, representing the most significant change among land types. (4) Future land use scenarios suggest that the highest simulated runoff occurs under a comprehensive development scenario, while the lowest is observed under an ecological conservation scenario. Among the 32 future climate scenarios, runoff increases significantly with a 10% increase in precipitation and decreases substantially with a 15% reduction in precipitation. These findings underscore the significant impact of human activities and climate change on runoff variations in the upper reaches of the Jialing River, highlighting the importance of incorporating both factors in water resource management and planning.

A distributed modeling approach to water balance implications from changing land cover dynamics in permafrost environments

There is 78 % permafrost and seasonal frozen soil in the Yangtze River’s Source Region (SRYR), which is situated in the middle of the Qinghai-Xizang Plateau. Three distinct scenarios were developed in the Soil and Water Assessment Tool (SWAT) to model the effects of land cover change (LCC) on various water balance components. Discharge and percolation of groundwater have decreased by mid-December. This demonstrates the seasonal contributions of subsurface water, which diminish when soil freezes. During winter, when surface water inputs are low, groundwater storage becomes even more critical to ensure water supply due to this periodic trend. An impermeable layer underneath the active layer thickness decreases GWQ and PERC in LCC + permafrost scenario. The water transport and storage phase reached a critical point in August when precipitation, permafrost thawing, and snowmelt caused LATQ to surge. To prevent waterlogging and save water for dry periods, it is necessary to control this peak flow phase. Hydrological processes, permafrost dynamics, and land cover changes in the SRYR are difficult, according to the data. These interactions enhance water circulation throughout the year, recharge of groundwater supplies, surface runoff, and lateral flow. For the region’s water resource management to be effective in sustaining ecohydrology, ensuring appropriate water storage, and alleviating freshwater scarcity, these dynamics must be considered.

An ecohydrological approach to assess water provisioning and supporting ecosystem services in the Budhabalanga River Basin, India.

Rivers are vital and complex natural systems that provide a wide range of ecosystem services. This study presents a methodology for assessing the riverine provisioning and supporting ecosystem services, whose applicability has been demonstrated over the Budhabalanga River Basin of India. The Soil and Water Assessment Tool (SWAT) is used to generate streamflow time series at various ungauged sites, and then the streamflow is characterized for the evaluation of provisioning services. Further, the diversity and abundance of macroinvertebrates, along with the Lotic-invertebrate Index for Flow Evaluation (LIFE), is used to study the riverine supporting ecosystem services. The streams show intermittent behavior and strong seasonality for low flows, which limits the water availability, particularly during pre-monsoon season. The Baseflow Index (BFI) is greater than 0.6, indicating that groundwater contributes more than 60% of the total streamflow. Interestingly, despite the high BFI, the streams did not conform to the prevailing opinion that a greater baseflow contribution results in a later commencement of the low-flow period in the hydrological year. Furthermore, the study depicts significant variations in the diversity and abundance of the macroinvertebrates across the various sampling sites. However, the LIFE score across the sites remained consistent within a narrow range, i.e., 8 to 9, suggesting a steady supply of supporting ecosystem services. The results of the study can help the policymakers towards an informed decision making and the simplistic methodology proposed in this study can be replicated in other river basins for identifying vulnerable watersheds and prioritizing management actions.

Effects of input data accuracy, catchment threshold areas and calibration algorithms on model uncertainty reduction

AbstractLow resolution of input data and equifinality in model calibration can lead to inaccuracy and insufficient reflection of spatial differences, thereby increasing model errors. However, the impact of input data accuracy, catchment threshold area, and calibration algorithm on model uncertainty reduction has not yet been well understood. The sequential uncertainty fitting version 2 (SUFI‐2) that is linked with the Soil and Water Assessment Tool (SWAT) in the package called SWAT Calibration Uncertainty Programs (SWAT‐CUP) was introduced to quantify the effects of different input data resolutions on parameter sensitivity and model uncertainty in the Jinghe River watershed, and the effects of different sub‐basin delineations and other two calibration algorithms on model uncertainty were also comparatively analysed. (i) USLE_C, EPCO, ALPHA_BNK, and CN2 are the most sensitive parameters among all SWAT projects. When the change of digital elevation model (DEM) resolution is small, the sensitivity of parameters does not change obviously. When the DEM resolution changes significantly, BIOMIX, LAT_SED, USLE_K, and CH_N1 become highly sensitive parameters by replacing OV_N, SMTMP, SURLAG, and USLE_P. However, the change in land use resolution has little impact on parameter sensitivity, with only a slight change in the sensitivity ranking of specific parameters. (ii) Model uncertainty responded to changes in the resolution of DEM more than land use. Most of the runoff simulations had smaller uncertainties (P factor, R factor, percentage of bias [PBIAS]) than sediment. High resolution DEM data reduced model uncertainty, but the models with 2000 m DEM resolution also achieved small uncertainty. Small catchment threshold area leads to high uncertainty of the model, and large catchment threshold areas decrease the model uncertainty. The model has relatively good simulation effects in runoff and sediment when the catchment threshold area was 2000 km2. (iii) The SWAT model has different simulation deviations and uncertainties in different calibration algorithms, the SUFI‐2 and generalized likelihood uncertainty estimation (GLUE) algorithms show better applicability than particle swarm optimization (PSO). The NSE indicators of the three algorithms are in the following order: SUFI‐2 > GLUE > PSO for runoff, and GLUE > SUFI‐2 > PSO for sediment. This study helps us understand the cause, knowledge of which moves from the particular to the general by the comprehension of essence, power, and nature in reducing model uncertainty.

Hydrological responses of the Brahmaputra river basin using CMIP6 GCM projections for supporting climate resilient infrastructure design

ABSTRACT The central northern region of Bangladesh has a low density and quality of sustainable rural infrastructures, and it is frequently affected by climate change-induced seasonal flooding and associated river erosion. This study used the Soil and Water Assessment Tool (SWAT) hydrological model to simulate future discharges under moderate and extreme Shared Socio-economic Pathway (SSP) scenarios, utilizing 13 bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6) General Circulation Models (GCMs). Using these flow projections, the 1D HEC-RAS hydrodynamic model was then simulated to assess future water level fluctuations in six major rivers in the study region. The results indicate that the dry season will experience a more notable flow increase (up to 45%) than the wet season (up to 42%) compared to the baseline under the extreme scenario by 2100. The subsequent rises in water levels will also be significant in the major rivers in the Brahmaputra-Teesta River system. Based on these future water level changes, the study has prepared a guideline for building climate-resilient infrastructures in the study area.

Enhancing human resilience against climate change: Assessment of hydroclimatic extremes and sea level rise impacts on the Eastern Shore of Virginia, United States

Coastal regions face climate-induced threats that have likely increased over the past four decades. In this work, we quantify the future climate impacts on hydroclimatic extremes in the risk-prone, 15-m-above-sea-level Eastern Shore of Virginia (ESVA) region, utilizing the Sixth International Coupled Model Intercomparison Project (CMIP6) Assessment Report 6 (AR6) and General Circulation Models (GCMs). We incorporate historical data on demographics and disasters, land use land cover (LULC), Landsat imagery, and sea level rise (SLR) to better understand and highlight the correlation between hydroclimatic extremes and societal components in this region. The hydrological model Soil and Water Assessment Tool (SWAT), Standardized Precipitation Index (SPI), Normalized Difference Water Index (NDWI), and Interquartile Range (IQR) method have been used to evaluate the intensity and frequency of projected climate extremes, in which SLR projections under different greenhouse gas emission pathways are temporally and spatially quantified. Our findings include (1) a trend towards wetter conditions is found with an increase in the number of flood events and up to an 8.9 % rise in the severity of flood peaks compared to the 2003–2020 period; (2) current coastal high-risk regions, identified using historical data of natural disasters, demographics, and LULC, are projected to be more susceptible to future climate impacts; and (3) low-lying coastal towns and regions are identified as currently vulnerable to coastal and SLR-induced flooding and are projected to become even more susceptible by 2100. This is the first effort that provides a valuable scientific basis for anticipated shifts in future climate patterns, essential for natural hazard prevention in ESVA. It highlights the need for authorities and decision-makers to plan and implement adaptive strategies and sustainable policies for the ESVA region and other coastal areas across the United States.

Groundwater drought risk assessment in the semi-arid Kansai river basin, West Bengal, India using SWAT and machine learning models

Increasing concerns over groundwater drought risks, which threaten water availability and adversely impact ecosystems, agriculture, and human activities, underscore the necessity of comprehensive evaluation methods. This research introduces a meticulous approach to evaluating groundwater drought risk (GWDR) in the semi-arid expanse of the Kansai River Basin, West Bengal, India. It intricately amalgamates the Soil and Water Assessment Tool (SWAT) model with three distinct machine learning algorithms namely, Support Vector Machine (SVM), Random Forest (RF), and Neural Networks (NN). The assessment relies on a diverse array of 26 thematic datasets encompassing hydrological, meteorological drought risk, and socioeconomic conditioning variables. The SWAT model has been used to derive hydrological parameters including groundwater recharge, lateral flow, base flow, surface runoff, evapotranspiration, return flow, and soil water content. Simultaneously, a pre-monsoonal water level dataset from 503 well locations is adhered to an impartial sampling strategy, maintaining a 70:30 ratio for training and testing datasets. The ensuing GWDR maps, derived through SVM, RF, and NN models, reveal four discerning risk classes across the study area. High-risk zones conspicuously predominate in upper catchment areas, while low-risk zones find their strategic position in the lower catchment regions. The area under the receiver operating characteristic curve (AUC-ROC) for the RF model, showcases an impressive 91% success rate, surpassing its counterparts SVM and NN models, which attained success rates of 88.4% and 80.7%, respectively. The Mann–Kendall test with Sen's slope analysis confirms a noticeable decline in groundwater levels within high to moderately high GWDR zones, supporting the study's findings. These findings significantly impact water resource management in semi-arid regions, emphasising the need for proactive measures to address evolving groundwater drought risks.

Multivariate Validation at Multistation of Distributed Watershed Hydrological Modeling Based on Multisource Data on Chinese Loess Plateau

Earlier, hydrological simulation calibration and validation relied on flow observations at hydrological stations, but multisource observations changed the basin hydrological simulation from single-flow validation to multivariate validation, including evaporation, soil water, and runoff. This study used the Soil and Water Assessment Tool (SWAT) distributed hydrological model to simulate and investigate hydrological processes in the Jinghe River Basin in China. After a single-station, single-variable calibration using flow observation data at the Zhangjiashan Hydrological Station, multisource data were used to validate actual evaporation, soil water, and runoff. Using the flow station data from Zhangjiashan station for parameter calibration and validation, the simulated values of R2, NSE, and KGE were all above 0.64, the PBIAS was within 20%, and the values of all the metrics in the calibration period were better than those in the validation period. The results show that the model performed satisfactorily, proving its regional applicability. Qingyang, Yangjiaping, and Zhangjiazhan stations had R2, NSE, and KGE values above 0.57 and PBIAS within 25% during regional calibration, considering spatial variability. Additionally, simulation accuracy downstream increased. R2, NSE, and KGE were above 0.50, and PBIAS was within 25% throughout validation, except for Qingyang, where the validation period was better than the calibration period. The Zhangjiashan station monthly runoff simulation improved after regional calibration. Runoff validation performed highest in the multivariate validation of evaporation–soil water–runoff, followed by actual evaporation and soil water content in China. The evaluation results for each hydrological variable improved after additional manual calibration. Multivariate verification based on multisource data improved the hydrological simulation at the basin scale.

PixelSWAT: A user-friendly ArcGIS tool for preparing inputs to run SWAT in a distributed discretization scheme

This paper documents the development of PixelSWAT, a Graphical User interface (GUI) python toolbox developed with the motive of creating gridded watershed and stream features to run the Soil and Water Assessment Tool (SWAT) in a distributed discretization scheme thus allowing optimum utilization of gridded weather datasets. Additionally, the tool also aims to automate the preparation of SWAT weather input files from Network Common Data (NetCDF) files for any SWAT user along with the option to interpolate the weather files for each grid. A case study was conducted in the Mago basin of Tawang, Arunachal Pradesh, using gridded weather datasets for hydrological simulation. Three SWAT models were prepared – a conventional SWAT model; a 500 m and a 1000 m gridded watershed PixelSWAT models. Statistical indices Nash Sutcliffe (NSE), Coefficient of Determination (R2) and Percent Bias (PBIAS) showed that the PixelSWAT projects performed marginally better than the conventional model and also incorporated the weather data more meaningfully.

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.

SWAT model to simulate hydrological responses to land use and land cover changes in a tropical catchment: A study in Sri Lanka

A significant concern is the modification and conversion of the land cover in river basins as a consequence of different influences on ecosystems. A hydrological investigation was performed in the Kelani River basin in Sri Lanka using the Soil and Water Assessment Tool (SWAT) to analyze the impact of changes in land use and land cover (LULC) on the hydrological response. In order to calibrate (2003–2012) and validate (2013–2020) the model, input data from four hydrological stations, namely Glencose, Hanwella, Norwood, and Kitulgala, were utilized. Three distinct LULC scenarios were analyzed and compared to the existing urban land pattern. Scenario I involves the conversion of urban land into pasture, Scenario II comprises the conversion of urban land into rubber plantations, and Scenario III entails the conversion of urban land into bare soil. In accordance with the study, the SWAT model's calibration in the Kelani River was successful. The evaluation indices for both the calibration and validation periods were satisfactory at Norwood (R2 = 0.76, NE = 0.88), Hanwella (R2 = 0.83, NE = 0.57), Glencourse (R2 = 0.78, NE = −0.32), and Kitulgala (R2 = 0.69, NE = 0.59). This finding suggests that the SWAT model demonstrated better accuracy in predicting streamflow at a station with high flow compared to stations with low or medium flow conditions. However, the calibrated model did not perform as expected when used to forecast daily streamflow at Glencourse, where the evaluation indices showed an R2 of 0.78 and NE of −0.32. Compared to the current urban land cover, scenario III had the greatest impact on runoff, potential evapotranspiration (PET), and sediment yield, with increases of 14.1%, 15.2%, and 26.3%, respectively. As a consequence of the significant degree of land degradation that was observed throughout the duration of the study, regions in the northern and western parts of the basin have been highlighted as requiring immediate attention for the establishment of vegetation.

A hybrid SWAT-ANN model approach for analysis of climate change impacts on sediment yield in an Eastern Himalayan sub-watershed of Brahmaputra

The current study focuses on analyzing the impacts of climate change and land use/land cover (LULC) changes on sediment yield in the Puthimari basin, an Eastern Himalayan sub-watershed of the Brahmaputra, using a hybrid SWAT-ANN model approach. The analysis was meticulously segmented into three distinct time spans: 2025–2049, 2050–2074, and 2075–2099. This innovative method integrates insights from multiple climate models under two Representative Concentration Pathways (RCP4.5 and RCP8.5), along with LULC projections generated through the Cellular Automata Markov model. By combining the strengths of the Soil and Water Assessment Tool (SWAT) and artificial neural network (ANN) techniques, the study aims to improve the accuracy of sediment yield simulations in response to changing environmental conditions. The non-linear autoregressive with external input (NARX) method was adopted for the ANN component of the hybrid model. The adoption of the hybrid SWAT-ANN approach appears to be particularly effective in improving the accuracy of sediment yield simulation compared to using the SWAT model alone, as evidenced by the higher coefficient of determination value of 0.74 for the hybrid model compared to 0.35 for the standalone SWAT model. In the context of the RCP4.5 scenario, during 2075-99, the study noted a 29.34% increase in sediment yield, accompanied by simultaneous rises of 42.74% in discharge and 27.43% in rainfall during the Indian monsoon season, spanning from June to September. In contrast, under the RCP8.5 scenario, for the same period, the increases in sediment yield, discharge, and rainfall for the monsoon season were determined to be 116.56%, 103.28%, and 64.72%, respectively. The present study's comprehensive analysis of the factors influencing sediment supply in the Puthimari River basin fills an important knowledge gap and provides valuable insights for designing proactive flood and erosion management strategies. The findings from this research are crucial for understanding the vulnerability of the Puthimari basin to climate and land use changes, and by incorporating these findings into policy and decision-making processes, stakeholders can work towards enhancing resilience and sustainability in the face of future hydrological and environmental challenges.

Evaluating the hydrological regime alteration under extreme climate scenarios in Southeast China

Study regionThe Shanmei Reservoir Watershed (SRW), Southeast China. Study focusThis study investigated the climate and hydrological regimes alterations in a subtropical coastal watershed (SRW) during the 21st century in extreme scenarios. The extreme scenarios, i.e., warm-wet and cold-dry climates, were constructed using 18 global climate models (GCMs) from CMIP6 under shared socioeconomic pathways (SSP1–2.6, SSP2–4.5, SSP3–7.0 and SSP5–8.5). The Soil and Water Assessment Tool (SWAT) model and Indicators of Hydrologic Alteration (IHA) were applied to quantify the impacts of climate change on the eco-hydrological regimes during the projected period (2041–2100) compared to the base period (1980–2014). New hydrological insights for the regionThe results show that the average temperature rises by 0.6–3.8 ℃, and the average annual precipitation changes by −21.4 % - 32.4 % by the end of the 21st century under extreme scenarios. Contrasting hydrological regimes are expected in the SRW under extreme scenarios. Under the extreme warm-wet scenarios, the monthly runoff is lower during spring and higher during summer, the minimum flows are significantly higher, and the maximum and minimum flows occurs earlier. Water resource utilization and ecosystem health are expected to improve. However, the opposite holds true in the cold-dry scenarios. The hydrologic regime alteration under future extreme climate scenarios can guide local water planning and ecological restoration strategies.

Simulation and attribution analysis of runoff–sediment in the Upper Basin of Fenhe River, China

ABSTRACT High-precision simulation of runoff–sediment is a significant challenge due to the combined impacts of climate change and human activities. In this paper, runoff–sediment processes were simulated, and their impact attribution was analyzed using the Soil and Water Assessment Tool (SWAT) model in the upper Fenhe River basin of the Loess Plateau, China. A SWAT model was constructed to assess its applicability during the historical baseline period, which reflects low human activity. However, the simulation results for the comprehensive impact period, using the calibrated historical baseline model, were unsatisfactory. Consequently, a method was proposed to enhance the accuracy of simulation results by considering the presence of soil-retaining dams. This method incorporates large and small soil-retaining dams as reservoirs and ponds, respectively, into SWAT. The results indicate that the accuracy of runoff and sediment simulation reaches a satisfactory level. The attribution analysis results show that human activities have a greater impact on runoff and sediment than climate change, with land use change and soil-retaining dams being particularly significant. The construction of soil-retaining dams plays a more significant role in reducing runoff and sediment. These findings provide valuable insights into the management and utilization of runoff and sediment in river basins.