Soil And Water Assessment Tool Model Research Articles

Exploring variability in climate change projections on the Nemunas River and Curonian Lagoon: coupled SWAT and SHYFEM modeling approach

Exploring variability in climate change projections on the Nemunas River and Curonian Lagoon: coupled SWAT and SHYFEM modeling approach

Climate change impact on water scarcity in the Hub River Basin, Pakistan

The Hub River Basin (HRB), a critical transboundary water source for Sindh and Baluchistan provinces in Pakistan, may face worsening water scarcity due to climate change and population growth. This study aims to assess the current state of water scarcity in the HRB and assesses its vulnerability to these pressures in future. To evaluate the baseline water scarcity in the HRB, a calibrated and validated Soil and Water Assessment Tool (SWAT) was established. Five General Circulation Models (GCMs) were employed to project the future climate under Representative Concentration Pathways (RCP 4.5 and 8.5) for the HRB. Sector-specific indicators were also used to assess the temporal and altitudinal sensitivity of the basin to climate change. These climate projections were incorporated in the SWAT model to simulate flows for three different periods: Early Future (EF; 2010–2039), Mid Future (MF; 2040–2069), and Far Future (FF; 2070–2099). The SWAT model results indicate significant increase in mean flows simulated by SWAT, ranging from 15.27 to 52.78 m3/s under RCP 4.5 and RCP 8.5 compared to baseline flows at HRB. Additionally, the study examines the temporal variation in basin stress and scarcity levels using Falkenmark and Water scarcity indicators. The findings indicate a general decrease in the basin's stress and scarcity levels, potentially benefiting water users of the HRB, especially under RCP8.5. This study offers crucial insights for shaping policies and strategies to adapt to climate change and population growth, ultimately aiming to minimize their impacts on HRB's water resources. By informing water managers and promoting sustainable water management practices, this research can help prevent future conflicts over water allocation and infrastructure development linked with the HRB.

Evaluation of hydrological models for streamflow prediction: a case study of the Mille River, Lower Awash Basin, Ethiopia

ABSTRACT Accurate prediction of stream flow is essential for effective water resource management, particularly in regions with complex hydrological dynamics. The Mille River, which flows through this basin and has a watershed area of 4,862.3 km², plays a crucial role in the region's water resources. However, selecting the most suitable hydrological model for this task remains a challenge due to varying model performances. This study addresses the problem of identifying the most effective hydrological model for predicting stream flow in the Mille River by evaluating three models: Soil and Water Assessment Tool (SWAT), Hydrologiska Byråns Vattenbalansavdelning (HBV-IHMS), and Artificial Neural Network (ANN). The objectives are to compare these models’ abilities to simulate daily stream flow and to determine their accuracy. The significance of this evaluation lies to guide water management decisions by identifying which model provides the most reliable predictions. The methodology involves using performance metrics, Nash-Sutcliffe Efficiency (NSE) values, to assess the accuracy of each model. The results show that SWAT achieved the highest NSE values of 0.81 and 0.82, indicating the best performance in simulating stream flow. ANN followed with NSE values of 0.79 and 0.81, while HBV-IHMS had lower NSE values of 0.73 and 0.74. Although all models demonstrated potential, SWAT and ANN outperformed HBV-IHMS in capturing the complex hydrological processes of the Mille River. The findings from this study indicate that the choice of model significantly impacts the accuracy and reliability of streamflow predictions. The SWAT and ANN models show strong potential for use in operational streamflow forecasting in the Mille River and similar basins. In conclusion, further research is recommended to refine model calibration and validation processes. Incorporating additional data sources, such as remote sensing and climate projections, could further enhance model accuracy and provide a more comprehensive understanding of the region's hydrological dynamics.

Water Ecological Security Pattern Based on Hydrological Regulation Service: A Case Study of the Upper Hanjiang River

Water ecological problems involve flood, drought, water pollution, destruction of water habitat and the tense relationship between humans and water. Water ecological problems are the main problems in the development of countries all over the world. In terms of ecological protection, China has put forward the ecological red line policy. Water ecology is an important component of the ecosystem, and the delineation of the water ecological red line is an important basis for ecological protection. Based on ecosystem services, this paper tries to determine the red line of the water ecology space and tries to solve various water problems comprehensively. Based on the ecosystem services accounting method, the SWAT (soil and water assessment tool) model was used to simulate the spatial–temporal dynamic quantities of water purification and rainwater infiltration services in the upper reaches of the Hanjiang River. The basin was divided into 106 sub-basins and 1790 HRUs (hydrological response units). Water quality data taken from 8 sites were used to verify the simulation results, and the verification results have high reliability. The grid scale spatialization of water quality and rainwater infiltration is realized based on HRU. The seasonal characteristics of hydrological regulation and control services were analyzed, the red line of hydrological regulation and control in the upper reaches of the Hanjiang River was defined, and the dynamic characteristics of water ecological red line were analyzed. According to the research results, the water ecological protection strategy of the basin is proposed. The prevention and control of water pollution should be emphasized in spring and summer, the prevention and control of rain flood infiltration in autumn and winter, and the normal monitoring and management should be adopted in the regulation and storage. The results of this study can provide scientific reference for water resources management and conservation policy making.

Combining the digital filtering method with the SWAT model to simulate spatiotemporal variations of baseflow in a mountainous river basin

Study regionGanjiang River Basin, a typical mountainous river basin which located on the south bank of the middle-lower Yangtze River. The Ganjiang River is the seventh largest tributary of the Yangtze River. Study focusBaseflow, a key recharge source for the river streamflow. This study combined the digital filtering method with the SWAT model to examine the temporal and spatial patterns of baseflow across the Ganjiang River Basin, and quantitatively assessed land use change impact on baseflow. New hydrological insights for the regionBaseflow in the Ganjiang River Basin shows a "single peak" intra-annual distribution. Monthly variations of streamflow and baseflow across the basin are different. The variation of baseflow index is generally opposite to that of streamflow. A positive correlation has been noted between the annual baseflow and streamflow, while a negative correlation was found between the annual baseflow index and precipitation. Due to the potential influence of basin topography, river flow direction and rock layer distribution, baseflow and baseflow modulus showed a spatially increasing trend from south to north, with the northwest region having extremely strong groundwater recharge. In comparison to the basic scenario, under extreme land use scenarios of forest, grassland, and cropland, baseflow may experience an increase of 14.7 % and 2.9 %, while witness a decrease of 13.9 %. All results improve the understanding of baseflow spatiotemporal variations in river basins.

Altitude characteristics in the response of rain-on-snow flood risk to future climate change in a high-latitude water tower

Global warming is profoundly impacting snowmelt runoff processes in seasonal freeze-thaw zones, thereby altering the risk of rain-on-snow (ROS) floods. These changes not only affect the frequency of floods but also alter the allocation of water resources, which has implications for agriculture and other key economic sectors. While these risks present a significant threat to our lives and economies, the risk of ROS floods triggered by climate change has not received the attention it deserves. Therefore, we chose Changbai Mountain, a water tower in a high-latitude cold zone, as a typical study area. The semi-distributed hydrological model SWAT is coupled with CMIP6 meteorological data, and four shared socioeconomic pathways (SSP126, SSP245, SSP370, and SSP585) are selected after bias correction, thus quantifying the impacts of climate change on hydrological processes in the Changbai Mountain region as well as future evolution of the ROS flood risk. The results indicate that: (1) Under future climate change scenarios, snowmelt in most areas of the Changbai Mountains decreases. The annual average snowmelt under SSP126, SSP245, SSP370, and SSP585 is projected to be 148.65 mm, 135.63 mm, 123.44 mm, and 116.5 mm, respectively. The onset of snowmelt is projected to advance in the future. Specifically, in the Songhua River (SR) and Yalu River (YR) regions, the start of snowmelt is expected to advance by 1–11 days. Spatially, significant reductions in snowmelt were observed in both the central part of the watershed and the lower reaches of the river under SSP585 scenario. (2) In 2021–2060, the frequency of ROS floods decreases sequentially for different scenarios, with SSP 126 > SSP 245 > SSP 370 > SSP 585. The frequency increments of ROS floods in the source area for the four scenarios were 0.12 days/year, 0.1 d/yr, 0.13 days/year, and 0.15 days/year, respectively. The frequency of high-elevation ROS events increases in the YR in the low emission scenario. Conversely, in high emission scenarios, YR high-elevation ROS events will only increase in 2061–2100. This phenomenon is more pronounced in the Tumen River (TR), where floods become more frequent with increasing elevation.

Evaluation of SWAT Model in Runoff Simulation Using Rainfall and Temperature Derived From Satellite Images

Evaluation of SWAT Model in Runoff Simulation Using Rainfall and Temperature Derived From Satellite Images

Assessing the sustainability of small hydropower sites in the Citarum Watershed, Indonesia employing CA-Markov and SWAT models

ABSTRACT This study investigates the sustainability of potential small hydropower sites within the Citarum Watershed in West Java, Indonesia. The Citarum River, with a catchment area of 6,090 km2, plays a crucial role in regional water supply and hydroelectric power generation. However, environmental challenges such as deforestation, land use changes, and sedimentation pose significant risks. We employed the CA-Markov model integrated with IDRISI TerrSet software and the Soil and Water Assessment Tool to predict future land use changes and assess water supply, soil erosion, and sedimentation impacts for 2030 and 2040. The analysis revealed diverse trends in water yield across different catchment areas, with some regions showing increased water availability and others facing declines. High erosion and sedimentation rates were identified as critical issues affecting hydropower efficiency. The study highlights the need for comprehensive watershed management strategies, including reforestation, sustainable land management practices, and sediment management, to enhance the sustainability of small hydropower projects. Our findings underscore the importance of integrating environmental considerations into hydropower development to ensure the ecological integrity of the Citarum Watershed.

Spatiotemporal variability of streamflow under current and projected climate scenarios of Andit Tid watershed, central highland of Ethiopia

This study examined the impact of climate change on streamflow in the Andit Tid watershed using climate models of dynamically downscaled Ethiopia’s CORDEX. The Arc SWAT and ArcGIS 10.5 software assessed the spatial and temporal distribution of streamflow, incorporating geospatial data like land use maps, digital elevation models, soil maps, and climate data. The SWAT model was calibrated and validated using SWAT-CUP with the SUFI-2 algorithm. The Canadian Centre for Climate Modeling and Analysis, Canada (CCCma (RCA4) model was selected for future projections after validation. From 1991 to 2021, the average streamflow rate was 0.0374 m3/s (247 mm), with R2 values of 0.83 for calibration and 0.72 for validation. Hotspots with active gullies and slopes over 20% were identified mainly in cultivated lands. Future projections indicated a comparable streamflow rate to current conditions at 0.0322 m3/s (212.6 mm). A decline in streamflow is projected: 7.2% and 30.2% decreases in the near and far future under RCP 4.5, and 32.3% decreases and 5% increases under RCP 8.5 scenarios. These variations were attributed to differences in catchment characteristics and climate variability. Further research is needed to validate these findings by incorporating additional biophysical variables. This study provides insights into hydrological planning and management in the Andit Tid watershed and similar regions facing climate variability.

Hydrological simulation using the SWAT model in a semi-arid region in the southern part of Zacatecas, Mexico

Hydrological simulation using the SWAT model in a semi-arid region in the southern part of Zacatecas, Mexico

Evaluating the dynamics of climate and anticipated snow cover changes on the hydrological response of rivers in the Hindu Kush Himalaya region

ABSTRACT The research aims to assess the interplay between climate dynamics and snow cover changes, informing water resource management. Utilizing the SWAT model with historical and future data, hydrological responses in the Marshyangdi River Basin are examined. The model's performance confirms its ability to simulate runoff components effectively. Projections indicate a concerning decrease in snow cover area for 2030, 2050, and 2090, with declines of 2.03, 4.03, and 14.20%, respectively, attributed to global warming and human activities. Isolating climate change reveals substantial increases in stream flow, notably pre-monsoon surges under different scenarios, with projected increments of 84 and 130% under SSP245 and SSP585, respectively. Analysis of snow cover impact shows a slight increase in annual stream flow, with a 3.54% anticipated decrease during the post-monsoon period, raising concerns for water availability in the dry season. Comparing both impacts reveals no significant differences in stream flow or precipitation. Annual stream flow increases under different scenarios, driven by precipitation, with varying impacts. Climate change emerges as the dominant driver, affecting surface runoff, groundwater, and evapotranspiration. This research unravels complex relationships between climate change, snow cover, and hydrological responses, providing valuable insights for water resource management in mountainous regions like the Hindu Kush Himalaya.

Estimation of suspended sediment load to the Volta Lake under changing climate using empirical discharge-sediment equations

ABSTRACT Reliable estimates of sediment fluxes into rivers provide valuable information for current and future water resource development and management. In this study, empirical equations relating discharge to suspended sediment loads were developed for the three major tributaries (Black Volta, White Volta, and Oti) of the Volta Lake. The empirical equations were fed with projected future river discharges for the three tributaries, to estimate the suspended sediment fluxes into the Volta Lake for the future (2051–2080) relative to a baseline period (2014–2016). The Soil and Water Assessment Tool (SWAT) was used to model the projected discharges. The SWAT model was driven by downscaled climate projections from two regional climate models (RCA4 and RACMO22 T) forced by two emission scenarios (RCP 4.5 and RCP 8.5) from the IPCC Fifth Assessment. Compared to the baseline, the estimated future sediment fluxes show average increments of about 19% and 28%, respectively under RCP 4.5 and RCP 8.5. This has negative consequences as less water is stored for hydropower generation and the lake water becomes more turbid, which inhibits zooplankton and fishery production. The result underscores the need to improve the management of the Lake's watershed by ensuring proper landcover/use planning, afforestation and enforcing regulations on land degradation and general environmental conservation.

Enhancing hydrological model efficiency through satellite image classification

ABSTRACT This paper aims to evaluate the performance of a hydrological model by using satellite image classification (SIM) to extract Land Use (LU) information. Four methods, namely Naive Bayes (NB), Classification and Regression Trees (CART), Support Vector Machine (SVM), and Random Forest (RF), are assessed for SIM using satellite images. CART demonstrated the highest Overall Accuracy (OA) of 0.996, followed by RF (OA=0.994), SVM (OA=0.797), and NB (OA=0.543). The Soil and Water Assessment Tool (SWAT) model was employed in this study to construct and refine the hydrological model for simulating the streamflow in the basin. For this purpose, the ground-based layer was replaced by LU generated from the classification algorithms. Integrating the four classification approaches yielded a significant improvement in Nash-Sutcliffe efficiency of the SWAT model, increasing it from 0.37 to approximately 0.76. These findings highlight the effectiveness of using satellite image classification in enhancing the efficiency of hydrological models.

Surface Runoff Estimation in Kubaisa Watershed Using SWAT, Western Desert, Iraq

Surface runoff significantly impacts the region's ecosystem and is closely linked to sustainable development and human well-being. The mathematical model SWAT running in an ArcGIS environment was used to estimate surface runoff in the Kubaisa watershed. The period simulated in this model is 31 years, sufficient to give good results regarding surface runoff volume and water yield contribution from each sub-watershed. The Kubaisa watershed has an area of 2485.50 km2 and comprises six sub-watersheds. The watershed consists of 172 HRUs distributed among sub-watersheds depending on the variation in soil layers, land use, vegetation, and slope. The volume of water calculated from the annual surface runoff rate for the simulation period was about 2699 million cubic meters, and its value was higher than the volume of water calculated from surface runoff due to lateral flow, groundwater discharge, and the contribution of each sub-watershed to the water yield. The highest value in water yield was in 2012, and the largest contribution was made by the sixth sub-watershed; thus, the difference is temporal and spatial in terms of water yield. Finally, through the analysis of multiple scenarios, the difference in hydrological response units is controlled by the difference in surface runoff, discharge, and water yield to the watershed. For this purpose, the SWAT model divides the watershed into many different units and starts the simulation on their basis.

Impacts of climate and land-use change on flood events with different return periods in a mountainous watershed of North China

Study regionLuanhe River Basin in North China Study focusGlobal warming exacerbates hydrological cycles, leading to increased intensity and frequency of floods. Regional studies on the impacts of climate change and land cover changes on flood events in recent decades are particularly important for flood prevention and risk assessment. In this study, the Peak Over Threshold- Generalized Pareto Distribution (POT-GPD) method is used to fit extreme runoff values in the Luanhe River Basin from 1961 to 2018 to identify floods with different return periods. Six flood behavior indicators are adopted to analyze the flood characteristics and extreme climate indices are also used for breakpoint testing and trend analysis. Various scenarios are established as the input of the SWAT model to study the impacts of climate change and land-use change on the flood events. New hydrological insights for the regionThe results indicate that the 2-year and 20-year return period floods are primarily rapid-rise single-peak floods, dominated by short-duration intense precipitation. The 5-year and 10-year return period floods are mainly multi-peak floods, primarily caused by long-duration precipitation. Floods in the Luanhe River Basin are primarily influenced by climate change, however, flood events do not directly correspond to the return periods of precipitation events. Forest is the most effective land-use type for flood retention. It could reduce flood magnitudes, especially for the 20-year return period floods. However, increasing forest cover does not effectively reduce the occurrence of the 5-year or 10-year floods, i.e. multi-peak floods. With more extreme rainfall events triggered by future climate change, particular attention should be paid to long-duration precipitation events, which may result in more severe disasters and economic losses.

Sensitivity analysis of SWAT streamflow and water quality to the uncertainty in soil properties generated by the SoLIM model

Hydrological models are essential tools for understanding natural processes, yet they often encounter with uncertainties due to limited input data and simplified assumptions. Soil data is a crucial input parameter for hydrological models, but it faces cartographic challenges due to lack of standardized soil mapping methods. To explore the applicability of soil datasets derived from the Third Law of Geography in hydrological models, the Soil Landscape Inference Model (SoLIM) based on this principle is used to generate a soil dataset. This dataset is then utilized as input data for a semi-distributed hydrological model (Soil and Water Assessment Tool, SWAT) to assess the impact of soil dataset uncertainty on performance of the hydrological model. This study, utilized the Fengyu River Watershed in Yunnan Province, China as an example, showed that: 1) Although the integration of SoLIM-generated soil data into the SWAT model introduces sensitivity in sediment yield, the overall results remain reliable. This suggests that soil datasets based on the Third Law of Geography can serve as input for semi-distributed hydrological models. 2) Uncertainty introduced by SoLIM-generated soil data affects parameters such as evaporation, total porosity of the soil layer (Φd), and groundwater infiltration coefficient (Ksat). These variations influence the sensitivity of SWAT’s predictions regarding streamflow and water quality. 3) Factors influencing model outcomes include steeper slopes in certain areas, which enhance streamflow velocity and flow rates, resulting in more dynamic and non-linear responses. Additionally, soil water dynamics exhibit higher temporal and spatial variability in forests compared to pasture and rice paddy fields, where vegetation tends to be more uniform, maintaining stable soil water loss pathways and reducing uncertainty in streamflow predictions. The study provides a foundation for studies addressing the difficulties in acquiring high-precision soil datasets for such models.

Decadal hydrological impact assessment of evolving land use and land cover in an Indian river basin: a multi-model approach

ABSTRACT All river basins have ever-evolving land use and land cover (LULC) attributes. The impact of these changes may not be significant on short time scales (i.e., monthly, seasonal, yearly), but over a decadal scale, they can substantially alter the hydrological processes of the basin. This study comprehensively quantifies the impacts of LULC changes over Cauvery basin in India using LULC maps from four decades spanning from 1980 to 2020. Simulations were performed using the Soil and Water Assessment Tool (SWAT) with various datasets. To isolate the effects of LULC changes, two sets of SWAT models were developed: A-set models for calibration and validation to establish basin parameters and B-set models to examine LULC change impacts while isolating other factors such as terrain and climate changes. Key findings include a significant increase in urban areas (0.87% in 1985 to 5.54% in 2015), a decline in vegetation cover (25.34% in 1985 to 21.32% in 2015), and an increase in the Curve Number and average annual surface runoff, highlighting the impact of LULC changes on hydrological processes. The A-set models achieved R-squared values of 0.831, 0.728, 0.715, and 0.757, while the B-set models showcased significant changes in hydrological parameters due to LULC changes.

Hydrological simulation and evaluation of drought conditions in the ungauged watershed Parishan lake Iran, using the SWAT model

ABSTRACT ke Parishan has experienced significant water scarcity, leading to its complete disappearance. This study utilized the SWAT model to assess the impact of changes in vegetation, precipitation, temperature, and evaporation on runoff and the lake's surface. Two strategies were employed: analyzing runoff variations based on land use and land cover (LULC) changes and evaluating the effects of precipitation, temperature, and humidity on runoff during the simulation period. A key challenge was the lack of runoff statistics, which was addressed by using data from donor watershed stations and Copernicus satellite information to improving simulation processes and calibration. The findings reveal that environmental changes, particularly land use, have increased evaporation and temperature fluctuations which results in reducing runoff. While Copernicus satellite data proved useful, runoff statistics from the neighboring Chamchit station provided more accurate simulations. The study finding suggests that the LULC strategy is an effective management approach, as in this case Parishan Lake's historical conditions with less urbanization and agriculture correlated with higher runoff and lake levels. Finally, meteorological and hydrometric drought and its impact on lake area changes were measured to reach a more comprehensive conclusion.

Evaluating the Spatiotemporal Distributions of Water Conservation in the Yiluo River Basin under a Changing Environment

Water conservation is a crucial indicator that measures the available water resources needed for maintaining regional ecological services and socioeconomic development. The Yiluo River Basin plays an essential role in water conservation in the Yellow River Basin, which is one of the most important river basins with vulnerable ecological conditions and a large population in China. However, previous studies have a limited understanding of the distribution of water conservation in the Yiluo River Basin. To address this knowledge gap, we developed a SWAT model to evaluate water conservation in the Yiluo River Basin with high spatial and temporal details on a monthly scale. From a monthly perspective, water conservation accumulation primarily took place in July (54.6 mm), August (23.5 mm), and September (33.2 mm), which are in the flood season. From 1966 to 2018, we found a significant 47% reduction in basin-wide water conservation, and the reduction was primarily influenced by meteorological conditions and underlying surface dynamics. The results of the temporal correlation analysis identified precipitation as the most significant factor influencing water conservation, while the spatial correlation analysis revealed that potential evapotranspiration, vegetation, and elevation had the highest spatial correlation with water conservation. By combining SWAT outputs on the HRU (hydrological response unit) scale with the spatial distribution of HRUs, the study achieved the visualization of the spatial distribution of water conservation, identifying Luonan County, Luanchuan County, and Luoning County as the key regions that experienced water conservation decline over the past decades. These findings advance our understanding of the distributions of water conservation and their key driving factors in the study area and provide valuable policy implications to support ecological protection and water resource management in the Yellow River Basin.

Spatiotemporal evolution of runoff and sediment and their dominant driving factors in the Lower Jinsha River basin

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.