Soil And Water Assessment Tool Model Research Articles

SWAT Model Calibration and Validation with Remotely Sensed Evapotranspiration data in Maklang-Tuyungbi-Taret lok Ungauged Basin in Manipur, India

SWAT Model Calibration and Validation with Remotely Sensed Evapotranspiration data in Maklang-Tuyungbi-Taret lok Ungauged Basin in Manipur, India

Spatial and temporal distribution of nitrogen, phosphorus, and heavy metals loads in Guanshan River Basin based on SWAT modeling

ABSTRACT This study takes Guanshan River Basin, a typical inflow river of the Danjiangkou Reservoir, as the research area, and the nonpoint source (NPS) pollution characteristics of nitrogen and phosphorus from 2013 to 2018 were evaluated by establishing a Soil and Water Assessment Tool (SWAT) model. The pollution characteristics of heavy metals were also evaluated by combining the SWAT and simple output coefficient method. The results show that the pollutant load in Guanshan River Basin contributes significantly to the Danjiangkou Reservoir. Temporally, pollutant loads were primarily concentrated in the flood season, which had a significant positive correlation with precipitation, water yield, and sediments in the abundant period. Among them, sediments were the most important driving factor, followed by water yield. Spatially, pollutant loads were mainly concentrated downstream of the basin, where cultivated land is widespread. In this regard, it is suggested that the input of chemical fertilizers, pesticides, and livestock manure in cultivated land should be controlled and soil erosion downstream of the basin should be prevented to mitigate nitrogen, phosphorus, and heavy metal pollution. This research offers a basis for the formulation and implementation of watershed management for the Danjiangkou Reservoir.

Effects of Cascading Dams on Streamflow within the Downstream Areas of the Rufiji River Basin in Tanzania

Despite their popularity, the construction and operation of hydropower reservoirs pose challenges to water resources. This study investigated the impacts of cascading dams on streamflow in Tanzania’s Rufiji River Basin. The SWAT model was developed to represent the entire Rufiji River Basin. The model simulated the streamflow for 41 years, from 1982 to 2022, and developed two main scenarios: with-dam and without-dam. To capture the influence of all dams, the results were emphasized from 2000 to 2022, when all three dams were operating. Calibration and validation were applied at the Rufiji-Stiegler and Kilombero-Swero stations with good performance. The results show that cascading dams annually decrease the streamflow by 1% at Rufiji-Stiegler station. In contrast, individually, the Mtera Dam displayed a 5% decrease while the Kidatu and Kihansi Dams exerted a 1% increase on the annual streamflow downstream at Rufiji-Stiegler. During 2000–2022, the Rufiji River Basin showed an annual reduction in streamflow contribution of 104.97 m3/s. Therefore, the reservoir’s operation significantly impacts the downstream streamflow. The findings are expected to guide policymakers, water resource managers, and environmentalists in mitigating potential adverse effects while optimizing the benefits of hydropower generation and water regulation within the region.

The Effects of Climate Change on Streamflow, Nitrogen Loads, and Crop Yields in the Gordes Dam Basin, Turkey

The Mediterranean region is highly vulnerable to climate change. Longer and more intense heatwaves and droughts are expected. The Gordes Dam in Turkey provides drinking water for Izmir city and irrigation water for a wide range of crops grown in the basin. Using the Soil and Water Assessment Tool (SWAT), this study examined the effects of projected climate change (RCP 4.5 and RCP 8.5) on the simulated streamflow, nitrogen loads, and crop yields in the basin for the period of 2031–2060. A hierarchical approach to define the hydrological response units (HRUs) of SWAT and the Fast Automatic Calibration Tool (FACT) were used to reduce computational time and improve model performance. The simulations showed that the average annual discharge into the reservoir is projected to increase by between 0.7 m3/s and 4 m3/s under RCP 4.5 and RCP 8.5 climate change scenarios. The steep slopes and changes in precipitation in the study area may lead to higher simulated streamflow. In addition, the rising temperatures predicted in the projections could lead to earlier spring snowmelt. This could also lead to increased streamflow. Projected nitrogen loads increased by between 8.8 and 25.1 t/year. The results for agricultural production were more variable. While the yields of poppy, tobacco, winter barley, and winter wheat will increase to some extent because of climate change, the yields of maize, cucumbers, and potatoes are all predicted to be negatively affected. Non-continuous and limited data on water quality and crop yields lead to uncertainties, so that the accuracy of the model is affected by these limitations and inconsistencies. However, the results of this study provide a basis for developing sustainable water and land management practices at the catchment scale in response to climate change. The changes in water quality and quantity and the ecological balance resulting from changes in land use and management patterns for economic benefit could not be fully demonstrated in this study. To explore the most appropriate management strategies for sustainable crop production, the SWAT model developed in this study should be further used in a multi-criteria land use optimization analysis that considers not only crop yields but also water quantity and quality targets.

Evaluation of hydrological responses to climate change in the Gibe Gojeb catchment, southwestern Ethiopia

ABSTRACT The expected influences of climate alteration on hydrological responses in the Gibe Gojeb catchment, southwestern Ethiopia, were evaluated using the Soil and Water Assessment Tool (SWAT) model and regional climate models (RCMs). This study emphasizes the evaluation of the climate change impact on hydrological responses. The RCM data were downloaded from CORDEX-Africa. Power transformation and delta change methods were used for bias correction of precipitation and temperature, respectively. The calibration and validation of the SWAT model showed good agreement, and climate change impact was simulated. Accordingly, precipitation, soil water content, percolation, water yield, and groundwater are projected to decrease by 28.18, 7.5, 9.1, 5.4, and 9.2%, respectively, under RCP4.5 in the future (2021–2050). Besides, surface runoff and potential and actual evapotranspiration are projected to increase by 17.4, 11.32, and 5.06%, respectively. Soil water content, percolation, water yield, and precipitation are projected to decrease by 10.51, 5.63, 2.76, and 21.57%, respectively, under RCP8.5 in the future. Rain-fed crop production and hydropower generation in the catchment would be highly vulnerable to the likely effects of climate change. The attained results help to develop effective adaptation measures to reduce the ongoing impacts of climate change and draft long-term water resource management plans in the Gibe Gojeb catchment.

Climate change adaptation for drinking water and ecological flows through sustainable agricultural practices

ABSTRACT Analysing the impacts of climate change on water resources is crucial to identify vulnerabilities and prioritize actions. We investigated climate change impacts on drinking water supply, emphasizing sustainable agriculture as an adaptation strategy, using the SWAT model in the Cávado River basin, Portugal. Our study highlights an increase in months with river discharge below ecological flow post water abstraction due to climate change. Notably, nitrate concentration was more influenced by sustainable agriculture practices than climate change. Our study highlights the vital role of adaptive strategies, especially sustainable agriculture, in securing water resources amidst challenges posed by climate change.

Influence of land use enclave distribution on discharge in a small catchment

Abstract According to many authors, hydrological modelling is one of the fundamental techniques for determining the impacts of various environmental changes on the quantitative characteristics of the aquatic environment. This study examines the effects of landscape changes induced by the need to respond to climate change and the natural urban development of the rural setting on the discharge from the small catchment. The SWAT model was applied to a small catchment of Kopaninsky Stream in the traditional agricultural part of the Czech Republic. According to the results, the most effective approach for reducing the consequences of hydrological extremes in the catchment and retaining more water in the landscape is the properly spaced placement of grassland and forest enclaves in the developing urban structure. In practice, each land use category’s overall percentage of representation is less significant than its relative arrangement.

Assessing hydrological interactions, soil erosion intensities, and vegetation dynamics in Nyabarongo River tributaries: a SWAT and RUSLE modeling approach

Assessing hydrological interactions, soil erosion intensities, and vegetation dynamics in Nyabarongo River tributaries: a SWAT and RUSLE modeling approach

Simulating the land use change effects on non-point source pollution in the Duliujian River Basin.

The uncertainty in the generation and formation of non-point source pollution makes it challenging to monitor and control this type of pollution. The SWAT model is frequently used to simulate non-point source pollution in watersheds and is mainly applied to natural watersheds that are less affected by human activities. This study focuses on the Duliujian River Basin (Xiqing section), which is characterized by a dense population and rapid urbanization. Based on the calibrated SWAT model, this study analyzed the effects of land use change on non-point source pollution both temporally and spatially. It was found that nitrogen and phosphorus non-point source pollution load losses were closely related to land use type, with agricultural land and high-density urban land (including rural settlements) being the main contributors to riverine nitrogen and phosphorus pollution. This indicates the necessity of analyzing the impact of land use changes on non-point source pollution loads by identifying critical source areas and altering the land use types that contribute heavily to pollution in these areas. The simulation results of land use type changes in these critical source areas showed that the reduction effect on non-point source pollution load is in the order of forest land > grassland > low-density residential area. To effectively curb surface source pollution in the study area, strategies such as modifying urban land use types, increasing vegetation cover and ground infiltration rate, and strictly controlling the discharge of domestic waste and sewage from urban areas can be implemented.

The structural equation modeling constructed for runoff change attribution analysis outperforms traditional methods

Recently, with the increasing global warming and intensity of human activities, runoff has significantly decreased. This has had a severe impact on water resources development and utilization, as well as ecological and environmental construction. To understand hydrological cycles and promote sustainable utilization of water resources, it is crucial to conduct attribution analysis of runoff changes. This study employed traditional models, including empirical statistics, elasticity coefficients, hydrological modeling, and introduced a simple and efficient model – structural equation modeling (SEM) – to quantify the impact of various factors on runoff changes. The findings revealed a notable decreasing trend in natural runoff in the Shiyang River from 1960 to 2020, while precipitation, snowmelt, potential evapotranspiration (ET0), and temperature exhibited increasing trends. The integrated the results from multiple models highlighted that human activities emerged as the primary driver influencing runoff changes. From 1972 to 2020, the factors contributing to runoff reduction were ranked in the order: water withdrawal (50 %) > LUCC (20 %) > ET0 (16 %) > temperature (8 %). Factors contributing to runoff increase were ranked: precipitation = water diversion project (20 %) > snowmelt (6 %). The impact of reservoir regulation on runoff initially exhibited a negative correlation (impact rate of 10 %) and later turned positive (impact rate of 6 %). The SEM model, employed for runoff change attribution analysis, demonstrated a good fit and was consistent with results obtained from the SWAT model. Compared to traditional methods, SEM not only allowed for quantitative analysis of the factors’ impact on runoff but also explored the interactions between factors and the direct and indirect effects of factors on runoff. This study introduces innovative methods for the attribution analysis of runoff changes, offering valuable insights crucial for the ecological sustainable development of water resources in arid and semi-arid regions.

Spatial and Temporal Changes in Nutrient Source Contribution in a Lowland Catchment Within the Baltic Sea Region Under Climate Change Scenarios

AbstractCurrently, climate change is considered as an important factor affecting nutrient loads introduced through riverine systems into the Baltic Sea. Although the prospect of a large increase in pollution has long seemed very real, it still does not translate into planning of effective remedial actions. One of the factors limiting the development of such activities is the scale of simulations, focusing generally on catchment outlet profiles. To fill this gap and enable a step forward in understanding responses toward future predictions in a higher resolution scale (subcatchment), we assessed nutrient load contribution using calculation profiles localized along a main watercourse and its tributaries. To track spatial and seasonal changes of total nitrogen and phosphorus for the Wełna River (central Poland), we used climate change data and the SWAT model. Having at our disposal a catchment model with a good performance we could follow not only total load changes in particular subcatchments, but also track localization of the pollution sources and their direct impact on load estimations. Our results showed an increase of the loads, especially from the agricultural land use type, up to 34% for TN and 85% for TP, in the most extreme scenario. Moreover, forest areas have been noted as highly reactive to climate change, and through their localisation are able to distinctly alter nutrient outflow. Finally, the contribution of urban areas should be further investigated since the dynamics of nitrogen and phosphorus release from impervious surfaces is noticeably different here than from the other diffuse sources.

Spatial calibration and uncertainty reduction of the SWAT model using multiple remotely sensed data

Remotely sensed products are often used in watershed modeling as additional constraints to improve model predictions and reduce model uncertainty. Remotely sensed products also enabled the spatial evaluation of model simulations due to their spatial and temporal coverage. However, their usability is not extensively explored in various regions. This study evaluates the effectiveness of incorporating remotely sensed evapotranspiration (RS-ET) and leaf area index (RS-LAI) products to enhance watershed modeling predictions. The objectives include reducing parameter uncertainty at the watershed scale and refining the model's capability to predict the spatial distribution of ET and LAI at sub-watershed scale. Using the Soil and Water Assessment Tool (SWAT) model, a systematic calibration procedure was applied. Initially, solely streamflow data was employed as a constraint, gradually incorporating RS-ET and RS-LAI thereafter. The results showed that while 14 parameter sets exhibit satisfactory performance for streamflow and RS-ET, this number diminishes to six with the inclusion of RS-LAI as an additional constraint. Furthermore, among these six sets, only three effectively captured the spatial patterns of ET and LAI at the sub-watershed level. Our findings showed that leveraging multiple remotely sensed products has the potential to diminish parameter uncertainty and increase the credibility of intra-watershed process simulations. These results contributed to broadening the applicability of remotely sensed products in watershed modeling, enhancing their usefulness in this field.

Enhancing physically-based hydrological modeling with an ensemble of machine-learning reservoir operation modules under heavy human regulation using easily accessible data

Dams and reservoirs have significantly altered river flow dynamics worldwide. Accurately representing reservoir operations in hydrological models is crucial yet challenging. Detailed reservoir operation data is often inaccessible, leading to relying on simplified reservoir operation modules in most hydrological models. To improve the capability of hydrological models to capture flow variability influenced by reservoirs, this study proposes a hybrid hydrological modeling framework, which combines a process-based hydrological model with a machine-learning-based reservoir operation module designed to simulate runoff under reservoir operations. The reservoir operation module employs an ensemble of three machine learning models: random forest, support vector machine, and AutoGluon. These models predict reservoir outflows using precipitation and temperature data as inputs. The Soil and Water Assessment Tool (SWAT) then integrates these outflow predictions to simulate runoff. To evaluate the performance of this hybrid approach, the Xijiang Basin within the Pearl River Basin, China, is used as a case study. The results highlight the superiority of the SWAT model coupled with machine learning-based reservoir operation models compared to alternative modeling approaches. This hybrid model effectively captures peak flows and dry period runoff. The Nash-Sutcliffe Efficiency (NSE) in daily runoff simulations shows substantial improvement, ranging from 0.141 to 0.780, with corresponding enhancements in the coefficient of determination (R2) by 0.098–0.397 when compared to the original reservoir operation modules in SWAT. In comparison to parameterization techniques lacking a dedicated reservoir module, NSE enhancements range from 0.068 to 0.537, and R2 improvements range from 0.027 to 0.139. The proposed hybrid modeling approach effectively characterizes the impact of reservoir operations on river flow dynamics, leading to enhanced accuracy in runoff simulation. These findings offer valuable insights for hydrological forecasting and water resources management in regions influenced by reservoir operations.

Assessing impact of climate change on streamflow: A case study in Ba River watershed, Gia Lai province, Vietnam

Surface water resources have been impacted by climate change. Due to the Coupled Model Intercomparison Project Phase 6 (CMIP6), the Intergovernmental Panel on Climate Change (IPCC) published its sixth assessment report in recent years. Therefore, this study aimed to evaluate the impact of the latest climate change scenarios on surface resources. The Ba River watershed’s streamflow was simulated under current and climate change conditions utilizing Soil and Water Assessment Tool (SWAT) model. Two shared Socio-economic Pathways 1-2.6 and 5-8.5 from ACCESS-CM2, CanESM5, and HadGEM3-GC31-LL General circulation models were used. The simulated annual discharge showed that surface water resources will increase during the 2030s, 2050s, 2080s, and entire periods for all the climate change scenarios in the watershed. Additionally, surface water resource maps of the watershed were created for each period of the climate change scenarios. The results from this study have indicated the effective application of SWAT model in assessing the impact of climate change on water resources.

Effectiveness of physical soil and water conservation measures under simulated and observed dataset in Ethiopia: Meta‐analysis

AbstractTo combat land degradation through conserving soil and water resources, Ethiopia has undergone vigorous implementation of soil and water conservation (SWC) measures, predominantly physical structures. To evaluate the effectiveness of these implemented structures, various researches have been conducted through using both measured and simulated approaches. This study was initiated to analyze the reliability of SWAT‐based simulated studies results on the effectiveness of SWC measures toward erosion reduction potential against the measured dataset using unpaired t‐test statistical analysis. In this study, 123 published papers were downloaded, of which 70 were found to be more related to the objective of the review. After applying four refining criteria, only 43 were found more compatible with the study objective and used for data analysis. Studies conducted by different scholars show up to 98% and 93.50% soil loss reduction effectiveness by SWC measures in measured and simulated approaches, respectively. The simulated SWC measure efficiency output was also evaluated with respect to the ground‐measured data of the same structure within the same agroecology class. Finally, the unpaired t‐test results indicated that the grass strip in the mid‐highland agroecology showed a significant difference from the measured one at a 95% significance level. However, none of the other measures showed significant differences between the measured and simulated datasets. Hence, the SWAT model can effectively simulate the effectiveness of physical SWC measures on soil loss reduction if it is well‐calibrated and validated with sediment yield data. Refining model parameters that can be sufficiently captured and represent biological measures (grass strip), incorporating additional field data for calibration and validation coupled with exploring alternative modeling approaches that efficiently simulate biological SWC was set as a recommendation to obtain an effective biological measure simulation.

Spatial Layout of Vegetation Buffer Zones around Water Bodies to Avoid Non-Point Source Pollution in a Mining Area

The riparian vegetation buffer zone plays an important role in the prevention and control of non-point source pollution, and consideration should be given to selecting one with a lower cost and better effect. The SWAT model was used to simulate the regulation ability of riparian vegetation buffer zone layout on runoff, nitrogen, and phosphorus in the Jiawang Basin, and five different vegetation buffer zone layout scenarios were set up. The results showed that (1) the SWAT model has good applicability in simulating runoff and water quality in the Jiawang Basin; (2) the reduction rates of runoff, total nitrogen, and total phosphorus in continuous forest riverbank buffer zones reached 2.46%, 6.63%, and 9.18%, and their regulatory effects were better than those in grasslands; (3) there is not much difference in the inhibitory effect of forest and grassland on total nitrogen, but the discontinuous forest buffer zone has a better reduction effect on total phosphorus than grassland. Therefore, in the actual arrangement of vegetation buffer zones, it should be tailored to local conditions to achieve ideal non-point source pollution prevention and control effects at a lower cost.

Application of SWAT Model for Hydrological Simulation of Rapti River Basin

This study aimed at application of SWAT model for hydrological simulations of Rapti River Basin (RRB) water systems. The Rapti River originates from Nepal and then it comes in India. SWAT (Soil and Water Assessment Tool) model was used for hydrological simulation of the RRB surface and sub surface water systems. SWAT is a comprehensive, semi-distributed river basin model that requires a large number of input parameters, which complicates model parameterization and calibration. The RRB was discretised into 4 sub-basins and 630 hydrological response units (HRUs) and calibration and validation was carried out at Bagasoti using monthly flow data of 11 years, respectively. We first calibrated the model in SWAT-CUP which is a decision-making framework that incorporates a semi-automated approach (SUFI2) using manual calibration and incorporating sensitivity and uncertainty analysis. Parameter sensitivity analysis helps focus the calibration and uncertainty analysis and is used to provide statistics for goodness-of-fit. In this study Calibration has been done between simulated and observed discharge data (1974-1985) for 50 simulations with 6 parameters that is Curve number (CN2 = 0.945), Groundwater delay (GW_DELAY = 50), Baseflow alpha factor (ALPHA_BF = 0.58), Manning's "n" value for the main channel (CH_N2 = 0.15), Effective hydraulic conductivity in main channel alluvium (CH_K2 = 10.20) and Available water capacity of the soil layer (SOL_AWC = 0.28). The results were analysed and compared with the observational data. The model performance evaluation showed acceptable ranges of values (i.e., Nash Sutcliff was 0.75 and R2 was 0.71). After model calibration, in order to predict water balance, the model was validated by using the best parameter.

Assessment of the effects of climate change on water balance components in the upper Erer subbasin, Ethiopia

Eastern Ethiopia watersheds are located in transition zone from Arid to semi-humid climate and in expanding to westwards the west annual rainfall is highly declining. This paper explains future hydrological response impacts under changing climate using ensemble average of the CORDEX RCMs for historical (1979–2014) and future (2024–2070) periods. The result revels the monthly average temperature varies (0.04–6.25°C) for RCP-4.5, while it varies (0.03–6.59°oC) for RCP-8.5. The monthly average rainfall to be decline by 90.71 mm and rise by 211. 22 mm for RCP-4.5, while it is going to decline by 84.97 mm and rise by 235.62 mm for RCP-8.5. The adjusted SWAT model was used to detect the changes of projected hydrological response from reference period. Balance components of the baseline period was compared to future period. The result shows the change in decrease of annual mean surface flow (4.98 %–5.63 %), groundwater flow (5.63 %–6.68 %), evapotranspiration (2.45 %–2.57 %) and water yield (5.54 %–5.21 %) to be expected from RCP-4.5 to RCP-8.5. The findings of this paper provide valuable assistance to water resource planners by enhancing their comprehension of change in climate effects at local level.

Evaluating Best Management Practice Efficacy Based on Seasonal Variability and Spatial Scales

Implementing best management practices (BMPs) has proven to be an efficient method for reducing non-point source (NPS) pollutants. Agricultural NPS pollution is considered to be a major contributor to water quality impairment. This study aims to assess the variation in hydrologic and water quality outputs at field and watershed scales when BMPs are implemented using modeling approaches. The Yazoo River Watershed (YRW) is the largest watershed basin in the state of Mississippi with approximately 50% agricultural land. Runoff generated from agricultural areas carries sediments and nutrients. The Merigold watershed (MW) is a sub-basin of the YRW and a field-scale watershed with most of the land use being agriculture. It is essential to quantify the streamflow, sediment, total nitrogen (TN), and total phosphorus (TP) when BMPs are implemented. BMPs such as vegetative filter strips (VFS) and cover crops (CC) were tested in this study. The Soil and Water Assessment Tool (SWAT) model was applied to quantify the watershed’s hydrologic and water quality outputs. SWAT model accuracy assessment was performed by calibration and validation process using the Nash and Sutcliffe Efficiency Index (NSE). Model performance was satisfactory for monthly streamflow, with NSE values in the range of 0.62 to 0.81, and for daily sediments, TN, and TP load estimation, with NSE values of 0.21, 0.20, and 0.47, respectively. CC was planted after harvesting the main crop. Therefore, it is essential to quantify the seasonal reduction in pollutants. Water quality was improved after BMP implementation, and an overall decrease in streamflow, sediment, TN, and TP loads was observed for both MW and YRW during dry and wet seasons. Previous studies regarding seasonal assessments with CC implementation in the MW and YRW were limited. Therefore, the results from this study could be a unique addition to the scientific literature.

Assessing impacts of irrigation on flows frequency downstream of an irrigated agricultural system by the SWAT model

Assessing impacts of irrigation on flows frequency downstream of an irrigated agricultural system by the SWAT model