Soil Water Assessment Tool Model Research Articles

Assessing groundwater drought vulnerability through baseflow separation and index-based analysis under climate change projections

Groundwater is an essential resource, providing drinking water to millions of people globally and supporting agriculture, industry, and ecosystems. It acts as a drought buffer and provides a stable source of water during dry periods. However, groundwater is often underestimated and overexploited, leading to aquifer depletion and other negative impacts. Groundwater is invisible and difficult to measure, which makes it challenging for sustainable management. This study employed the Soil & Water Assessment Tool (SWAT) hydrological model to simulate streamflow in an eastern Afghan watershed using satellite-based and reanalysis data. Variables from five Coupled model intercomparison project phase 6 (CMIP6) general circulation models (GCMs), including minimum and maximum temperature and precipitation, were bias-corrected (downscaled) using Quantile Mapping (QM). The results from these five GCMs were then compared based on statistical criteria to determine the most reliable model, and the selected model was used to derive future data (i.e., 2021 to 2050) under different climate scenarios after applying QM. Using the future climate data and the developed SWAT model, streamflow values were projected for future periods. Considering that there are various methods to estimate groundwater recharge and the most commonly used technique involves baseflow separation procedures, this study used seven baseflow separation methods to estimate groundwater recharge values based on streamflow time series from the baseline period and different climate scenarios. To evaluate the groundwater drought characteristics, a recently proposed index called the Groundwater Recharge Drought Index (GRDI) and the run theory method were used. Results indicated that the SWAT model performed well in simulating and predicting streamflow. The sixth version of the Model for Interdisciplinary Research on Climate (MIROC6) provided the highest accuracy compared to other climate models. Moreover, it was observed that the baseflow separation methods significantly affected the estimation of groundwater recharge, thus the obtained results from all developed methods were considered. The log-normal function was found to provide the best correlation for estimating GRDI. The findings revealed a gradual decrease in drought duration in the coming years. However, the magnitude and severity of droughts are projected to increase, especially under pessimistic climate scenarios.

SWAT‐GL: A new glacier routine for the hydrological model SWAT

AbstractThe hydrological model Soil Water Assessment Tool (SWAT) is widely used in water resources management worldwide. It is also used to simulate catchment hydrology in high‐mountainous regions where glaciers play an important role. However, SWAT considers glaciers in a simplistic way. Although some efforts were done to overcome this limitation, there is no official version available that considers glaciers adequately. This strongly impairs its applicability in glacierized catchments. In this technical note, we propose a novel version of the traditional SWAT, called SWAT‐GL, which introduces (1) a mass balance module and (2) a glacier evolution routine to represent dynamic glacier changes. Mass balance calculations are based on a conceptual degree‐day approach, similar to the snow routine implemented in SWAT. Glacier evolution is realized using the delta‐h (∆h) parameterization, which requires a minimum of data and is thus suitable in data‐scarce regions. The approach allows users to simulate spatially distributed glacier changes. Annual mass balance changes are translated to distributed ice thickness changes depending on the glacier elevation. We demonstrate how SWAT‐GL is technically integrated into SWAT and how glaciers are merged with the existing spatial units. Model code and test data are freely accessible to promote further model development efforts and a wide application. Ultimately, SWAT‐GL aims to make SWAT easily applicable in glacierized catchments without the need of additional tools.

Integrated modeling of snow-covered areas and hydrological processes in the Larji Sub-Basin, Himachal Pradesh, India, using SRM and SWAT models

Abstract Alpine snow is crucial for the water cycle, as the runoff and environment of arid and semi-arid regions rely entirely on these glaciers. Mountain-fed rivers provides the water for domestic, agricultural irrigation, hydroelectric power, and other uses. Due to climate variability, river catchment flows may shift, causing floods and droughts that will aggravate the economy. This study estimated the SCA using Google Earth Engine (GEE) for the Larji River basin, situated in Himachal Pradesh, from the year 2001 to 2021. The snow cover area (SCA) varies from 0.7–22% in the basin. The present study highlights the effectiveness of cloud computing for assessing trends in snow-cover regions in the basin. Moderate Resolution Imaging Spectroradiometer (MODIS) snow product (MOD10A1 V6 Snow Cover Daily Global 500m product) is utilized for SCA calculation. This study simulates runoff from the Larji river, using Snow-melt Runoff Model (SRM) and Soil Water Assessment Tool (SWAT) for years (2019-2021). Furthermore, the Coefficient of determination (R2) Coefficient of corelation (r), Nash-Sutcliffe Efficiency (NSE) and Kling-Gupta Efficiency (KGE) were used to evaluate the efficacy of models. This study will help the policymakers and stakeholders to carry out the water resource management practices in the study area.

Hydrological investigation of climate change impact on water balance components in the agricultural terraced watersheds of Yemeni highland

AbstractHydrological models serve as valuable instruments for assessing the impact of climate change on water resources and agriculture as well as for developing adaptation measures. In Yemen, climate change and variability are imposing a significant impact on the most important sectors such as agriculture and economy. The current study evaluates the influence of future climate on hydrology and water balance components in Yemen’s highlands using a semi-distributed physical-based hydrologic model Soil Water Assessment Tool (SWAT) and employing high-resolution climate projections. The SWAT was calibrated and verified using observed streamflow data from 1982 to 2000 in three large catchments. Ground data from 24 stations and statistically downscaled future climate data for the period 2010–2100 under RCP2.6 and RCP8.5 are used. SWAT performance was assessed using multiple statistical methods, which revealed the commendable performance of SWAT during the calibration (average NSE = 0.80) and validation (NSE = 0.72) periods. The outcome indicates an increase in future seasonal and annual rainfall, maximum temperature, and minimum temperature in the 2020s and the 2080s under both RCP2.6 and RCP8.5 scenarios. This projected increase in the rainfall and the local temperature will result in increased averages of surface runoff, evapotranspiration, soil water, and groundwater recharge in the representative three catchments up to 6.5%, 21.1%, 7.6%, and 6.4%, respectively. Although, the projected increase in the water balance components will benefit the agriculture and water sector, specific adaptation measures will be crucial to mitigate potential flood impacts arising from the increased precipitations as well as to minimize the consequences of the increased temperature. Likewise, demand for supplementary irrigation is expected to increase to offset the higher evapotranspiration rates in the future.

Improvement of Soil Water Assessment Tool (SWAT) wetland module for modelling of ephemeral pond hydrology

AbstractEphemeral ponds (EPs) are seasonally flooded isolated wetlands that provide a variety of hydroecological benefits, including the provision of breeding habitat for several amphibian and invertebrate species. However, the lack of their explicit representation in hydrological models limits a comprehensive understanding of their interaction with surrounding landscapes and their vulnerability in the context of human interventions and climate change. The purpose of this research was to improve the isolated wetland module of the Soil Water Assessment Tool (SWAT) to better represent EP hydrology. The changes include (1) representation of groundwater and hypodermic flow as the only inflows from the pond drainage surface, due to the intermittent and negligible presence of inflow from surface runoff in forested ponds, (2) revision of how evapotranspiration within EPs is represented and (3) implementation of distinct volume‐area‐depth relationships for ponds based on their geometrical shape. The accuracy of these improvements was assessed against that of a previous isolated wetland formulation in replicating water depth observations of 10 EPs of a portion of the Kenauk forest (68 km2) in the Canadian Shield of the Outaouais region (Québec, Canada). The comparison results show that the revised SWAT model presented here significantly improves the distinct filling and drying water cycle of EPs (average root mean square error of 0.1 m of the revised model vs. 0.23 m for the original model). Besides, the new module allowed to identify that hypodermic flow, evapotranspiration and seepage to the underlying soil are the main EP source and sinks. The new module also allowed to explicitly quantify the differences in filling/drying pattern of the EPs of the Kenauk forest and unlike the original model structure, the new module was able to closely replicate the interannual variation of spring and annual hydroperiod duration.

Assessing the feasibility of sprinkler irrigation schemes and their adaptation to future climate change in groundwater over-exploitation regions

Promoting appropriate water-saving irrigation is an important pathway to alleviate groundwater overexploitation in irrigated agriculture. Whether an alternative irrigation method is feasible relies on quantitative assessments of its impacts on crop yield and hydrological cycle, especially in the groundwater overdraft area that faces a dilemma between water scarcity and food security. Using a groundwater-module-improved SWAT (Soil & Water Assessment Tool) model, five GCMs (General Circulation Models) projections of CMIP6 (Coupled Model Intercomparison Project 6), and a linear programming algorithm, sprinkler irrigation was simulated, evaluated, and optimized in a representative global groundwater mining location, the piedmont plain of the North China Plain. During the historical period (1993–2012), the results showed that, in general, sprinkler irrigation had advantages in benefiting crop transpiration of winter wheat and reducing percolation, hence improving water use efficiency with reference to traditional surface irrigation. Specifically, compared to traditional surface irrigation schemes, winter wheat yields increased by 12%− 14% with a 225 mm irrigation quota; they were stable with a 150 mm irrigation quota; but they decreased by 4% with a 75 mm irrigation quota. The shallow groundwater tables would decline at an average rate of 1.29 m/yr, 0.83 m/yr, and 0.35 m/yr, respectively, under sprinkler irrigation with 225 mm, 150 mm, and 75 mm irrigation quotas. Future climate changes (increased precipitation, air temperatures, and CO2 concentration) would bring effects of improving wheat yield by 6%− 7% and increasing groundwater vertical recharge by 58%− 122% in 2030–2049. The variations of predicted future shallow groundwater tables were − 0.37 m/yr, 0.01 m/yr, and 0.40 m/yr with the 225 mm, 150 mm, and 75 mm irrigation quotas, respectively, in the SSP2–4.5 scenario; and the corresponding results were − 0.45 m/yr, − 0.05 m/yr, and 0.34 m/yr in the SSP5–8.5 scenario. The optimization results showed that sprinkler irrigation could be implemented in approximately 50% of the study area to achieve shallow groundwater equilibrium and stable wheat production simultaneously in the near future. And the dominant sprinkler irrigation schedule after optimization was found to be scheme S3 (irrigation frequency for wheat was 5 times) with a limited irrigation quota of 150 mm. This study provides detailed data for planning sprinkler water-saving irrigation regimes and groundwater pumping strategies in China’s breadbasket, as well as a reference for global irrigated agriculture with over-drafted aquifers to balance groundwater conservation and grain production.

Multi-Station Hydrological Modelling to Assess Groundwater Recharge of a Vast Semi-Arid Basin Considering the Problem of Lack of Data: A Case Study in Seybouse Basin, Algeria

Water resource management scenarios have become more crucial for arid to semi-arid regions. Their application prerequisites rigorous hydrological modelling approaches since data are usually exposed to uncertainties and inaccuracies. In this work, Soil Water Assessment Tool (SWAT), an open source semi-distributed, continuous-time, process-based physical hydrological model is used to model hydrological processes and eventually calculate groundwater recharge estimations in Seybouse basin, Northeast Algeria. The model uses estimated rainfall to calibrate the model with observed discharge from hydrometric stations. Model calibration and validation are performed over four hydrometric stations located in the basin. Uncertainty analysis and sensitivity analysis supported the calibration period. SUFI-2 algorithm is used for uncertainty estimations along with a global sensitivity analysis prior to calibration simulations. Simulated flood hydrographs showed generally good accuracy with few misfits on the peaks. The model obtained satisfactory and consistent calibration and validation results for which the Nash score varied from 0.5 to 0.7 for calibration and from −0.1 to 0.6 for validation and R2 from 0.6 to 0.7 for calibration and 0.03 to 0.8 for validation. Moreover, estimated water budget values show strong similarities with the observed values found in the literature. The present work shows that the rigorously calibrated and validated SWAT model can simulate hydrological processes as well as major high and low flows using estimated rainfall data.

Performance of LSTM over SWAT in Rainfall-Runoff Modeling in a Small, Forested Watershed: A Case Study of Cork Brook, RI

The general practice of rainfall-runoff model development towards physically based and spatially explicit representations of hydrological processes is data-intensive and computationally expensive. Physically based models such as the Soil Water Assessment tool (SWAT) demand spatio-temporal data and expert knowledge. Also, the difficulty and complexity is compounded in the smaller watershed due to data constraint and models’ inability to generalize hydrologic processes. Data-driven models can bridge this gap with their mathematical formulation. Long Short-Term Memory (LSTM) is a data-driven model with Recurrent Neural Network (RNN) architecture, which is better suited to solve time series problems. Studies have shown that LSTM models have competitive performance in watershed hydrology studies. In this study, a comparative analysis of SWAT and LSTM models in the Cork Brook watershed shows that results from LSTM were competitive to SWAT in flow prediction with NSE of 0.6 against 0.63, respectively, given the limited availability of data. LSTM models do not overestimate the high flows like SWAT. However, both these models struggle with low values estimation. Although interpretability, explainability, and use of models across different datasets or events outside of the training data may be challenging, LSTM models are robust and efficient.

Quantification of agricultural best management practices impacts on sediment and phosphorous export in a small catchment in southeastern Sweden

Agricultural activities contribute to water pollution through sediments and nutrient export, negatively affecting water quality and aquatic ecosystems. However, implementing best management practices (BMPs) could help control sediments and nutrient losses from agricultural catchments. This study used the Soil Water Assessment Tool (SWAT) model to assess the effectiveness of four BMPs in reducing sediment and phosphorus export in a small agricultural catchment (33 km2) in southeastern Sweden. The SWAT model was first evaluated for its ability to simulate streamflow, sediment load, and total phosphorous load from 2005 to 2020. Then, the calibrated parameters were used to simulate the agricultural BMP scenarios by modifying relevant parameters. The model performed satisfactorily during calibration and validation for streamflow (NSE = 0.80/0.84), sediment load (NSE = 0.67/0.69), and total phosphorous load (NSE = 0.61/0.62), indicating its suitability for this study. The results demonstrate varying effects of BMP implementation on sediment and phosphorus (soluble and total) export, with no significant change in streamflow. Filter strips were highly effective in reducing sediment (−32%), soluble phosphorus (−67%), and total phosphorous (−66%) exports, followed by sedimentation ponds with −35%, −36%, and −50% reductions, respectively. Grassed waterways and no-tillage were less impactful on pollutant reduction, with grassed waterways showing a slight increase (+4%) in soluble phosphorus and no-tillage having a minimal effect on sediment (−1.3%) and total phosphorus (−0.2%) export. These findings contribute to the ongoing efforts to mitigate sediment and nutrient pollution in Swedish agricultural areas, thereby supporting the conservation and restoration of aquatic ecosystems, and enhancing sustainable agricultural practices.

Modeling rainfall-runoff estimation and assessing water harvesting zone for irrigation practices in Keleta watershed, Awash river basin, Ethiopia

The world’s water demand is increasing twice as quickly as the world’s population. Contrarily, the greatest problem facing humanity in the twenty-first century is the supply of food. During dry seasons, when water collecting is a crucial survival strategy, the communities in the study area experience water deficit for agricultural production. In this study, socioeconomic and biophysical parameters were considered to evaluate the water harvesting zone for irrigation practices. With the aid of this technology, water harvesting sites can be found in acceptable sites, and water resource management can be improved to address water shortages during the dry season when crops are at key stages of growth and filling. The integrated geographical information system/Remote Sensing (GIS/RS), Soil Water Assessment Tool (SWAT), fuzzy logic, and analytic hierarchy process (AHP) model were used to carry this out. Rainfall, drainage density, surface runoff, percentage of clay content, land use land cover, slope, lithology, lineament, and Euclidian distance to settlement and road were the criteria utilized to choose the Rainwater Harvesting (RWH) sites. The run-off was estimated using the SWAT model, weights for each influential component were determined using AHP, the input factor was standardized using fuzzy membership, and factors were combined using gamma fuzzy (ℽ= 0.9) overlay weighting. The model’s statistical performance was demonstrated by R2 values of 0.79 and NSE values of 0.77 for monthly calibration periods and R2 values of 0.81 and NSE values of 0.75 for monthly validation periods. The study area’s Rainwater Harvesting potential suitability classes covered very highly suitable (16.91%), extremely suitable (27.6%), moderately suitable (20.23%), low suitable (13.1%), and not suitable (6.43%), and restrictions (15.73%). The study’s findings could help decision-makers identify more lucrative and long-lasting irrigation investment options in the Keleta watershed and make better decisions regarding the development of irrigation projects there.

Assessing the climate change adaptability of sustainable land management practices regarding water availability and quality: A case study in the Sorraia catchment, Portugal

In Mediterranean catchments, such as the Sorraia catchment in Portugal, it is expected that climate change will increase drought stress and the deterioration of water quality in reservoirs. Sustainable land management (SLM) practices are seen as an adaption measure for those problems, but the effectiveness on improving climate change impacted water availability and quality on catchment scale is still poorly understood. Therefore, this study aims to evaluate the effectiveness of SLM practices in adapting the impacts of climate change on water availability and quality of the Montargil and Maranhão reservoirs in the Sorraia catchment. A well-calibrated Soil Water Assessment Tool model is used to simulate four scenarios (2041–2071 and 2071–2100; representative climate pathways 4.5 and 8.5), to investigate the effects of climate change on total phosphorus load (TP) in streams, reservoir volume, irrigation use and water exploitation index (WEI). Results showed that WEI will not exceed any water stress level while reservoir water quality will worsen. In particular since the TP load in streams flowing into the reservoirs increases and the volume decreases, it is likely that the existing P limitation for eutrophication will be counteracted. Nevertheless, tested SLM practices were able to decrease the TP load in those streams and increase the reservoir volume under future climates. Overall, this study shows that the SLM practices are effective in adapting to the climate change effects regarding reservoir water quality, without worsening the water availability; thus, it is a promising tool that should be investigated further for application by e.g. local land-users and decision makers.

Runoff Simulation under the Effects of the Modified Soil Water Assessment Tool (SWAT) Model in the Jiyun River Basin

Few studies have been conducted to simulate watersheds with insufficient meteorological and hydrological information. The Jiyun River watershed was selected as the study area. A suitable catchment area threshold was determined by combining the river network density method with the Soil and Water Assessment Tool (SWAT) models, which was driven using the CMADS dataset (China Meteorological Assimilation Driving Datasets for the SWAT model). Monthly runoff simulations were conducted for the basin from 2010 to 2014, and the calibration and validation of model parameters were completed with observed data. The results showed that the final expression for the density of the river network in the Jiyun River basin as a function of density (y) and the catchment area threshold (x) was obtained as y = 926.782x−0.47717. The “inflection point” of the exponential function was the optimal catchment area threshold. The catchment area threshold had an upper and lower limit of the applicable range and was related to the percentage of the total basin area. The simulation results would be affected if the threshold values were outside the suitable scope. When the catchment area was 1.42% of the entire watershed area, increasing the threshold value had less effect on the runoff simulation results; decreasing the threshold value would cause the simulation results to be unstable. When the catchment area reached 1.42% to 2.33% of the total watershed area, the simulation results were in good agreement with the observed values; the coefficient of determination (R2) and Nash–Sutcliffe efficiency coefficient (NSE) were more significant than 0.79 and 0.78 for the calibration periods evaluation index. Both were greater than 0.77 and 0.76 for the validation period, which met the evaluation requirements of the model. The results showed that the CMADS-driven SWAT model applied to the runoff simulation and the river network density method adoption to determine the catchment area threshold provided a theoretical basis for a reasonable sub-basin division in the Jiyun River basin.

Sensitivity Analysis of SWAT Model in a Tropical Watershed, East Java

Brantas watershed has approximately 14,103 km2 and play an essential role in supplying water for about 30% of the East Java population. Management of water resources in this watershed has become a challenging issue. Conformity of modeling processes and result to mimic the existing hydrological processes is still in question. This study aims to analyze the sensitive parameters of the Soil Water Assessment Tool (SWAT) model on the watershed. Hydrological processes are observed both monthly and annually. Sensitivity analysis using the SWAT-CUP tool show 18 sensitive parameters. 9 parameters have more than a 50% sensitivity level. 4 are correlated to the soil layer’s runoff generation and water movement. Then, 8 parameters correlated to baseflow calculation. Simulation results illustrate the strong effect of climate change (especially rainfall) on water yield and sedimentation.

Determination of Spatially-Distributed Hydrological Ecosystem Services (HESS) in the Red River Delta Using a Calibrated SWAT Model

The principles of Integrated Water Resources Management (IWRM), conservation of natural capital, and water accounting requires Hydrological Eco-System Services (HESS) to be determined. This paper presents a modeling approach for quantifying the HESS framework using the Soil Water Assessment Tool (SWAT). SWAT was used–after calibration against remote sensing data–to quantify and spatially identify total runoff, natural livestock feed production, fuelwood from natural forests, dry season flow, groundwater recharge, root zone storage for carrying over water from wet to dry season, sustaining rainfall, peak flow attenuation, carbon sequestration, microclimate cooling, and meeting environmental flow requirements. The environmental value of the current land use and vegetation was made explicit by carrying out parallel simulations for bare soil and vegetation conditions and reporting the incremental ecosystem services. Geographical areas with more and fewer HESS are identified. The spatial and temporal variability of annual HESS services is demonstrated for the Day Basin—which is part of the Red River delta (Vietnam)—for the period 2003 to 2013. The result shows that even though the basin is abundant with HESS, e.g., 7482 m3/ha of runoff, 3820 m3/ha of groundwater recharge, the trend for many HESS values, e.g., micro-climate cooling, meeting environmental flow requirements, and rootzone storage, are declining. It is found and proven that quantified HESS indicators highlighted the provisioning and regulating characters of ecosystem services, as well as geographical hotspots across the basin. The SWAT model shows the capability of simulating terrestrial eco-hydrological processes such as climate, soil, and current land use. The methodology illustrates how eco-hydrologists can benchmark ecosystem values and include HESS in exploring river basin management scenarios, climate change studies, and land use planning.

Potential Impacts of Climate Change on Surface Water Resources in Arid Regions Using Downscaled Regional Circulation Model and Soil Water Assessment Tool, a Case Study of Amman-Zerqa Basin, Jordan

Water scarcity, aggravated by climate change impacts, threatens all sectors in arid regions and hampers sustainable development plans. This work aims to assess the potential impacts of climate change on surface water resources of Amman-Zerqa Basin, Jordan, using the Soil Water Assessment Tool model (SWAT) and outputs from the Downscaled Regional Circulation Model. Future scenarios were developed based on combining two Representative Concentration Pathways (RCPs 4.5 and 8.5). A reference scenario from 1973 to 2015 was used to compare the current climate with future climates and their impacts on hydrological processes. Hydrologic modeling outputs showed very good performance ratings for calibration and validation periods. Statistical bias correction of the Downscale Regional Circulation Model (GCM) indicated that linear scaling for precipitation data was the best-performing bias correction method, along with variance scaling and distribution mapping methods for minimum and maximum temperature, respectively. The coupled future model simulations indicated a reduction in crucial water balance components under all modeled scenarios. The simulated reductions range between 3.7% and 20.7% for precipitation, 22.3–41.6% for stream flow, 25.0–47.0% for surface runoff, 0.5–13.4% for evapotranspiration, and 21.5–41.4% for water yield, from conservative to the severe scenario, respectively. In conclusion, spatial analyses indicated the presence of three zones of impact. Thus, future climate and hydrological adaptation measures should focus on the provided zoning.

Assessment of climate change impact on hydrological components of Ponnaiyar river basin, Tamil Nadu using CMIP6 models

AbstractThis study aims to assess the climate change impacts on the hydrological components in the Ponnaiyar river basin using the Soil Water Assessment Tool (SWAT) model. This study used 13 Global Climate Models (GCM) from Coupled Model Inter-comparison Project Phase 6 (CMIP6). Based on the performance evaluation of 13 CMIP6-GCMs, the best GCMs selected for future projections were EC-Earth3, MPI-ESM1-2-LR and MPI-ESM1-2-HR. SWAT-CUP (SWAT – Calibration and Uncertainty Programs) successfully calibrated and validated the SWAT model. The SWAT model simulated the hydrological components of the basin for the future period under SSP245 and SSP585 emission scenarios. The results indicated increased streamflow over the projected period due to increased rainfall in the basin. The annual surface runoff varied from −20.41 to −15.46%, −10.51 to 18.34% and 73.88 to 134.56% under the SSP585 scenario for the 2020s, 2050s and 2080s, respectively. For the future 2020s, the water yield varied from −7.02 to 11.36% and −1.41 to 6.15% for SSP245 and SSP585. During the 2050s and 2080s, there was an increase in water yield (7.89–21.18% and 36.12–115.25%) under SSP245 and SSP585 future climate scenarios. This study could help policymakers and stakeholders to develop adaptive strategies for the Ponniyar river basin.

Impact of Climate Change on the Hydrological Regimes of the Midstream Section of the Yarlung Tsangpo River Basin Based on SWAT Model

Water resources and the water cycle in high mountain areas are significantly impacted by climate change. In this study, the midstream section of the Yarlung Tsangpo River basin, situated in the southern part of the Tibetan Plateau, was chosen as the target area, and the Soil Water Assessment Tool (SWAT) was used to assess how climate change may affect hydrological processes. The SWAT model proved effective for runoff and snow cover area simulation. Surface runoff, interflow, and groundwater accounted for 47.2%, 24.4%, and 28.4% of the total runoff, respectively. The spatial distribution of runoff was mainly influenced by precipitation and glacier distribution, whereas the spatial distributions of individual runoff components were mainly influenced by soil properties. Overall, the total runoff as well as its components (surface runoff, interflow, and groundwater) increased at a rate of 0.03–0.83%/10 yr (p > 0.05) in the study area during 1983–2017, which could be attributed to the increase in precipitation. Surface runoff peaked earlier (August) than interflow and groundwater (September), owing to the longer convergence time of interflow and groundwater. Future predictions showed a warming and wetting trend (p < 0.05) in the study area from 2020 to 2100 under the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios. The total runoff was projected to increase at a rate of 0.92–3.56%/10 yr, and the change of total runoff mainly came from the increase of surface runoff.

Subbasin Spatial Scale Effects on Hydrological Model Prediction Uncertainty of Extreme Stream Flows in the Omo Gibe River Basin, Ethiopia

Quantification of hydrologic model prediction uncertainty for various flow quantiles is of great importance for water resource planning and management. Thus, this study is designed to assess the effect of subbasin spatial scale on the hydrological model prediction uncertainty for different flow quantiles. The Soil Water Assessment Tool (SWAT), a geographic information system (GIS) interfaced hydrological model, was used in this study. Here, the spatial variations within the sub-basins of the Omo Gibe River basin in Ethiopia’s Abelti, Wabi, and Gecha watersheds from 1989 to 2020 were examined. The results revealed that (1) for the Abelti, Wabi, and Gecha watersheds, SWAT was able to reproduce the observed hydrograph with more than 85%, 82%, and 73% accuracy in terms of the Nash-Sutcliffe efficiency coefficient (NSE), respectively; (2) the variation in the spatial size of the subbasin had no effect on the overall flow simulations. However, the reproduction of the flow quantiles was considerably influenced by the subbasin spatial scales; (3) the coarser subbasin spatial scale resulted in the coverage of most of the observations. However, the finer subbasin spatial scale provided the best simulation closer to the observed stream flow pattern; (4) the SWAT model performed much better in recreating moist, high, and very-high flows than it did in replicating dry, low, and very-low flows in the studied watersheds; (5) a smaller subbasin spatial scale (towards to distributed model) may better replicate low flows, while a larger subbasin spatial scale (towards to lumped model) enhances high flow replication precision. Thus, it is crucial to investigate the subbasin spatial scale to reproduce the peak and low flows; (6) in this study, the best subbasin spatial scales for peak and low flows were found to be 79–98% and 29–42%, respectively. Hence, it is worthwhile to investigate the proper subbasin spatial scales in reproducing various flow quantiles toward sustainable management of floods and drought.

Assessment of Future Land Use/Land Cover Scenarios on the Hydrology of a Coastal Basin in South-Central Chile

Land use and land cover (LULC) change is one of the clearest representations of the global environmental change phenomenon at various spatial and temporal scales. Chile is worldwide recognized to have areas dedicated to non-native forest plantations that specifically in coastal range show high environmental and economic deterioration, questioning the sustainability of the forestry industry. Currently, there are no studies in Chile that reveal the real effects of the LULC change on the water balance at basin or sub-basin scales associated with future scenarios, which might contribute to territorial decision-making and reveal the real magnitude of the effects of these dynamics. In this study, in order to study LULC dynamics in a coastal basin in South-Central Chile, we assessed and analyzed the effects of future LULC change scenarios on the hydrological processes by generating future synthetic land cover maps from Landsat (Landsat 5 TM and Landsat 8 OLI) image datasets. The hydrological model Soil Water Assessment Tool (SWAT) was calibrated and validated, using hydroclimatic time series, to simulate discharges and other hydrological components over those future LULC scenarios. The LULC future scenarios were projected using combined Markov chain analysis (CA–Markov) and cellular automata algorithms for the near (2025), middle (2035) and far (2045) future. The results revealed that the effects on the different components of the water balance of the basin are not as significant except in the soil water transfer in percolation (increase 72.4%) and groundwater flow (increase 72.5%). This trend was especially observed in sub-basins with non-native forest plantations that dominated land cover in the year 2035, in which an increase of 43.6% in percolation and groundwater flows resulted in increased aquifer recharge and water storage, mainly offset by a decrease of 27% in the evapotranspiration. This work demonstrates the importance of evaluating the impacts of the dynamics of LULC on the hydrological response of a coastal basin, and also on how the land use governance and policy are closely linked to that of water resources.

Analysis of spatiotemporal variation in dissolved organic carbon concentrations for streams with cropland-dominated watersheds

It remains a challenge to understand how dissolved organic carbon (DOC) is cycled from farmlands to rivers due to the complex interaction between farming practices, the baseflow hydrology of predominantly flat lowlands, and seasonal environmental influences such as snowpack. To address this, field DOC concentrations were measured monthly throughout the year at sub-basin scales across the Chippewa River Watershed, which falls within the Corn Belt of the Midwestern United States. These DOC dynamics in stream water from croplands were benchmarked against the data sampled from hilly forested areas in the Connecticut River Watershed. The Soil Water Assessment Tool (SWAT) simulation was applied to provide potential predictive variables associated with daily baseflow. Our study outlines a framework using the combination of primary field data, hydrological modeling, and knowledge-based reclassification of Land Use/Land Cover (LULC) data to analyze the viability of modeling the spatial and temporal variations of cropland stream DOC concentrations. Calibration of the SWAT model resulted in the overall daily Nash–Sutcliffe model efficiency coefficient (NSE) of 0.67 and the corresponding R2 = 0.89. Our main results show: 1) baseflow DOC concentrations from croplands were substantially higher throughout the year relative to other landcover areas, especially for spring runoff/snowmelt scenarios, 2) an empirical analysis explained ~82 % of the spatial gradient of annual mean observed DOC concentrations, and 3) with the addition of hydrological simulated variables, a linear model explained ~81 % of monthly and 54 % of daily variations of observed DOC concentrations for cropland sub-basins. Our study identified key factors regulating the spatiotemporal DOC concentrations in cropland streamflow; the contribution here promotes to strengthen future analytical models that link watershed characteristics to carbon cycling processes in a large freshwater ecosystem.