Water Assessment Tool Research Articles

Soil erosion assessment using SWAT, in relation withLand use, agricultural practices, and future climate change in a semi-arid catchment in Tunisia

Abstract Soil erosion is a severe environmental concern arising from intensive agricultural uses, land degradation, and anthropogenic activities. This problem threatens agricultural productivity and sustainable development, particularly in emerging countries. Therefore, evaluating soil erosion is essential in conservation, planning, and management on a watershed or basin scale. This study aims to assess the erosion of soil loss in the El Gouazine Watershed, central Tunisia, using the Soil and water assessment tool (SWAT). We define the impact of soil and water conservation management implementation combined with climate change scenario. We identified the spatial distribution of erosion rates based on soil properties, topography, and land use. The observed specific erosion rate of the watershed is estimated at 1.6 t.ha−1.yr−1, whereas according to the SWAT model, the average soil loss rate is 1.4 t.ha−1.yr−1. Furthermore, the obtained results highlight importance of the slope factor in affecting the severity of the soil loss rates in the El Gouazine watershed. It was also demonstrated that it’s urgent to prioritize other measures such as contour cropping or conservation agriculture, to enhance and strengthen the soils’ resistance against the detachment due to discharge water. In this context, this research found that these techniques decrease considerably the soil loss by 22% for the strip cropping, 33% for the No-tillage, and 72% for the bench terracing. Moreover, these farming techniques, contribute at the same time to the amelioration of the water balance by reducing the evapotranspiration and enhancing the soil water storage. To go further in this study a soil erosion forecast using the worst-case scenario for climate change RCP 8.5 was conducted. an overview of the future soil erosion patterns is obtained. We noticed then a decrease of the average annual soil loss rate until 2050 and then a prominent increase from 2051 to 2100.

Impacts of LULC changes on runoff from rivers through a coupled SWAT and BiLSTM model: A case study in Zhanghe River Basin, China

Changes in river runoff have a significant impact on the sustainable use of water resources in a watershed, and these changes are closely linked to variations in land use/land cover (LULC). This research explores an innovative approach in the Zhang River Basin (ZRB), China, by coupling a concept-based hydrological model, the Soil and Water Assessment Tool (SWAT), with a deep-learning model, the Bidirectional Long Short-Term Memory Network (Bi-LSTM), to improve the accuracy of river runoff simulations. By analyzing LULC changes in 2002, 2012, and 2022, this study developed three SWAT models and three coupled SWAT-BiLSTM models to quantitatively assess the impacts of these changes on river runoff through eight LULC scenarios. The findings revealed significant LULC changes from 2002 to 2022, with cropland and grassland areas decreasing while forest and urban land areas increased. The total area of grassland, forest, and cropland made up over 93 % of the basin, indicating active land type conversions. Calibration and validation results demonstrated that the SWAT-BiLSTM model outperformed the conventional SWAT model, yielding higher accuracy in runoff simulations. Specifically, the SWAT-BiLSTM model achieved R2 values of 0.89 and 0.90 during calibration and validation, compared to the SWAT model's R2 values of 0.76 and 0.79. Scenario analyses indicated that expansions in farmland, grassland, and urban areas were correlated with increased river runoff, while an expansion in forested areas led to reduced runoff. Notably, urban land changes had the most pronounced impact on runoff, emphasizing the need for careful runoff management and flood risk mitigation in urban planning. By combining SWAT and Bi-LSTM models, this study provides an innovative assessment of the impact of LULC changes on water resources in the ZRB. The results offer valuable insights for water resource management, LULC optimization, and flood risk management, highlighting the potential application of deep learning techniques in hydrological simulation. This research serves as a scientific basis for policy-making and sustainable land use planning in the ZRB and similar regions.

Evaluating water balance components in a tropical ecological zone under land use changes

Water availability for domestic, institutional, and agricultural production is threatened by the continuous change in land use land cover (LULC). These changes in LULC features affect the dynamics of the hydrological processes such as surface runoff, infiltration, and evapotranspiration, resulting in variations in water availability especially, for human consumption and crop yield. Therefore, the Soil and Water Assessment Tool (SWAT) hydrological model was deployed to simulate the Pra River Basin (PRB)’s water balance response to changing LULC from 1986 to 2020. Open and closed forests reduced from an area of 11,071 km2 to 5902 km2 and 5125 km2 to 4990 km2 while settlement and cropland increased from 1100 km2 to 2392 km2 and 5303 km2 to 9320 km2 representing an average annual expansion rate of +24.7 km2/yr and +118 km2/yr respectively over the three decades. The growth in settlement and cropland resulted in an upsurge of more than 33 % and 20 % in surface runoff and water yield respectively, but decreases of over 4 % and 17 % in evapotranspiration and baseflow respectively. These changes have resulted in a seasonal increase in surface runoff, baseflow, and evapotranspiration (ET) during the wet season but a decrease during the dry season. The PRB has experienced a dramatic decline in forest areas, chiefly in areas where settlement and farmlands have been expanded. The areas where surface runoff and water yield showed significant upsurge and reduction in ET are the northwestern and southern enclaves of the basin. These findings can aid in effectively planning and managing land use to control the gradually depleting water resources in the basin.

Assessing Future hydrological response of an urban watershed using machine learning based LULC forecasting models

Urbanization in terms of land-use/cover (LULC) change has a long-term significant impact on the hydrological cycle as the LULC is one of the most important influencing parameters to produce curve number (CN). The drastic change in LULC changes the CN. This change directly affects surface water including peak flows. This study aims to assess the change in surface runoff due to changes in LULC. Hydrological modeling is done for the consistent long-term behavioral study of surface runoff. The area focused on the study is the Kharun river, a tributary of the Mahanadi River. For the assessment of the impact of LULC change on the catchment discharge, a daily-step conceptual model soil and water assessment tool (SWAT) was applied. Landuse maps were prepared with the Landsat Thematic Mapper satellite images. The future land use was forecasted with the technique of spatial statistical modeling. The machine learning (ML) tool is used for quantifying the influences on the LULC change dynamics and producing the LULC map for 2024 and 2030. Remote sensing (RS) and geographic information system (GIS) analysis were coupled with hydrological SWAT modeling to investigate the connection between the LULC change and hydrologic regime. The SWAT Model’s calibration efficiency is verified by comparing the simulated and observed discharge time series at the Patharidih gauge and discharge station. The monthly and daily calibrations were quite satisfactory, with Nash-Sutcliffe an efficiency coefficient of 0.86 and 0.67. This modeling provides reliable information for sustainable management of available water resources of the catchment.

Temporal and spatial variations in the effect-based ecotoxicological assessment of streams

BackgroundWater bodies are affected by chemical contamination, including micropollutants, which is not fully captured by conventional chemical monitoring methods. The inclusion of integrative, effect-based in vivo and in vitro methods in standardized assessment procedures offers the possibility of bridging discrepancies between chemical and biological assessments and has already been proposed in several studies. However, there is a need to develop a comparable ecotoxicological assessment system for surface waters as for chemical and ecological status. This study aims to contribute to this discourse by investigating the temporal and spatial variation of ecotoxicological effects by assessing water grab samples of 15 different sites in central Germany over the course of 1 year using different in vitro assays.ResultsThe level of measured estrogenicity and anti-estrogenicity varied between the four measurement campaigns, while baseline toxicity, dioxin-like effects and mutagenicity showed relatively constant detectable effects over the study period. The impact of conventionally treated wastewater appeared to be one of the strongest influencing stressors, as direct comparisons of ecotoxicity upstream and downstream of wastewater treatment plant dischargers showed a significant increase for most of the conducted bioassays. Comparison of the measured estrogenicity with proposed threshold values showed effects within ecotoxicologically relevant ranges.ConclusionsBioassays record ecotoxicological effects on the basis of specific modes of action, allowing whole groups of substances to be identified as pollutants. Recording ecotoxicological status in this way is a useful complement to water assessment tools and can contribute to successful water management. Although most of the assays in this study were very consistent in detecting strong anthropogenic influences, possible temporal variations of individual assays should be taken into account when planning sampling strategies to improve the comparability of results.

Evaluating land use and climate change impacts on Ravi river flows using GIS and hydrological modeling approach

The study investigates the interplay of land use dynamics and climate change on the hydrological regime of the Ravi River using a comprehensive approach integrating Geographic Information System (GIS), remote sensing, and hydrological modeling at the catchment scale. Employing the Soil and Water Assessment Tool (SWAT) model, simulations were conducted to evaluate the hydrological response of the Ravi River to both current conditions and projected future scenarios of land use and climate change. This study differs from previous ones by simulating future land use and climate scenarios, offering a solid framework for understanding their impact on river flow dynamics. Model calibration and validation were performed for distinct periods (1999–2002 and 2003–2005), yielding satisfactory performance indicators (NSE, R2, PBIAS = 0.85, 0.83, and 10.01 in calibration and 0.87, 0.89, and 7.2 in validation). Through supervised classification techniques on Landsat imagery and TerrSet modeling, current and future land use maps were generated, revealing a notable increase in built-up areas from 1990 to 2020 and projections indicating further expansion by 31.7% from 2020 to 2100. Climate change projections under different socioeconomic pathways (SSP2 and SSP5) were derived for precipitation and temperature, with statistical downscaling applied using the CMhyd model. Results suggest substantial increases in precipitation (10.9 − 14.9%) and temperature (12.2 − 15.9%) across the SSP scenarios by the end of the century. Two scenarios, considering future climate conditions with current and future land use patterns, were analyzed to understand their combined impact on hydrological responses. In both scenarios, inflows to the Ravi River are projected to rise significantly (19.4 − 28.4%) from 2016 to 2100, indicating a considerable alteration in seasonal flow patterns. Additionally, historical data indicate a concerning trend of annual groundwater depth decline (0.8 m/year) from 1996 to 2020, attributed to land use and climate changes. The findings underscore the urgency for planners and managers to incorporate climate and land cover considerations into their strategies, given the potential implications for water resource management and environmental sustainability.

Ecological flow research in response to hydrological variation: A case study of the Jinsha River Basin, China

Climate change and human activities have altered the natural state of rivers to a certain extent, leading to runoff variation and impacting the stability of riverine ecosystems. The ecological flow has emerged to balance the water relationship between humanity and riverine ecosystems and to safeguard the health and biodiversity of rivers. Presently, the scientific quantification of riverine ecological flow has become a focal point in water resource research. Addressing the quantification of ecological flow under hydrological variation conditions, the cumulative deviation method (CDM) and Pettitt methods were firstly employed to detect breakpoints in the runoff sequences. Then, the natural monthly runoff post-variation was restored using the Soil and Water Assessment Tool (SWAT) model, i.e., natural runoff restoration, and three testing methods were employed to determine the optimal hydrological distribution functions for natural monthly runoff. Subsequently, an improved frequency calculation method was used to calculate the ecological flow. The Jinsha River Basin was selected as the study area, and four crucial sections in the mainstream of the Jinsha River were studied, including Zhimenda (ZMD), Shigu (SG), Xiaodeshi (XDS), and Pingshan (PS). The results indicated: (1) the runoff sequences (1960–2017) at the four crucial sections exhibit different breakpoint times, with breakpoint years being 2004, 1986, 2005, and 1996, respectively; (2) the SWAT model, in simulating runoff at the four crucial sections, exhibited NSE values all exceeding 0.85, and r values all surpassing 0.9, demonstrating its effective ability to restore natural runoff in the Jinsha River basin; (3) the optimal hydrological distribution functions for natural monthly runoff at the four sections varied, and most natural monthly runoff conforms to the Generalized Extreme Value (GEV) distribution; (4) the average annual ecological flows for the ZMD, SG, XDS, and PS sections were 296 m3/s, 992 m3/s, 1238 m3/s, and 2755 m3/s, and the ecological flows derived using the improved frequency calculation method under the optimal hydrological distribution functions were more rational. This study can provide a scientific basis for the optimal allocation of water resources and the protection of riverine ecosystems in the Jinsha River basin.

Enhancing ecohydrological simulation with improved dynamic vegetation growth module in SWAT

The Soil and Water Assessment Tool (SWAT) model has been widely used for simulating ecohydrological processes such as streamflow and evapotranspiration (ET) under different land use and climate conditions. The growth of vegetation is a crucial link in the ecohydrological process. However, the model uses a simplified Environmental Policy Impact Climate (EPIC) model, which has limitations in simulation of dynamic vegetation growth. Therefore, this study aims to enhance SWAT by incorporating the forest aging data and optimizing the dormancy and forest vegetation growth modules. The application of this modified model with a case study shows that the accuracy of leaf area index (LAI) simulation has significantly improved (coefficient of determination (R2) increased by 0.16, the Nash-Sutcliffe efficiency (NSE) increased from −0.18 to 0.87, and the absolute value of percent bias (PBIAS) decreased by 50.99%), and with moderate improvement in streamflow simulation (NSE increased by 0.03, PBIAS decreased by 4.60%). Furthermore, optimizing the dynamic growth model of vegetation led to significant increases in LAI (151.58%) and ET (5.25%) values in the forest area, while streamflow and water yield decreased by 4.28% and 4.16%, respectively, across the watershed. The results indicate that dynamic vegetation growth led to increased ET, resulting in a decrease in streamflow and water yield. Overall, our results suggest that the modified SWAT model effectively simulated the process of forest growth from young forest to mature stages, significantly improving the accuracy of simulated hydrological processes. This methodology can be applied to other watersheds to simulate ecohydrological processes and can be valuable in management of ecosystems and water resources at watershed scale.

Estimation of Freshwater Discharge from the Gulf of Alaska Drainage Basins

The freshwater discharge from catchments along the Gulf of Alaska, termed Alaska discharge, is characterized by significant quantity and variability. Owing to subarctic climate and mountainous topography, the Alaska discharge variations may deliver possible impacts beyond the local hydrology. While short-term and local discharge estimation has been frequently realized, a longer time span and a discussion on cascading impacts remain unexplored in this area. In this study, the Alaska discharge during 1982–2022 is estimated using the Soil and Water Assessment Tool (SWAT). The adequate balance between the model complexity and the functional efficiency of SWAT suits the objective well, and discharge simulation is successfully conducted after customization in melting calculations and careful calibrations. During 1982−2022, the Alaska discharge is estimated to be 14,396 ± 819 m3⋅s−1⋅yr−1, with meltwater contributing approximately 53%. Regarding variation in the Alaska discharge, the interannual change is found to be negatively correlated with sea surface salinity anomalies in the Alaska Stream, while the decadal change positively correlates with the North Pacific Gyre Oscillation, with reasonable time lags in both cases. These new findings provide insights into the relationship between local hydrology and regional climate in this area. More importantly, we provide rare evidence that variation in freshwater discharge may affect properties beyond the local hydrology.

Unravelling the impact of climate change and anthropogenic activities on streamflow: the benefit of newly developed evapotranspiration data

ABSTRACT To separate the contributions of climate change and human activities to alterations in flow for the Ahar Chay watershed in Iran, change points of the normalized difference vegetation index (NDVI) and evapotranspiration (ET) were distinguished before and after significant alterations. The Budyko model and Soil and Water Assessment Tool (SWAT) were used to find the reduction in runoff. New Penman-Monteith-Leuning (PML) ET data was used to consider plant types. Results revealed an increase in NDVI coinciding with the change point in 1998, as well as ET in 1999. The significance of the Sattarkhan Dam became evident when distinguishing the impacts upstream versus downstream of the dam. Results also indicated that climate change contributed significantly to upstream flow reduction (83.5%), whereas downstream reductions were primarily linked to human-related impacts (59.7–82.5%). Assuming no dam interception, 2007 became the change point, signifying a 37.5% reduction in average flow from before to after this point due to the increased vegetation cover.

Estimation of Runoff at Shetrunji River Basin using SWAT Hydrological Modelling

The researchers and scientists have realized that this is the high time to act in accordance to the impact of change of climate. Because of climate change problem, various effects occur, one of them is hydrological extremes. This leads to the emergence of hot-spots and vulnerable areas causing difficult adaptation. The current analysis intends to estimate the influence of change in climate on the hydrological parameter on one of the most important tributaries of Saurashtra region of Gujarat, Western India. Out of number of methods available to perform this task, simulation (hydrological modelling) which is the most widely used techniques available at this time, has been adopted. Here in this research the SWAT (Soil and Water Assessment Tool) model which happens to be a semi-distributed model and integrates the GIS information with the attribute database of the River has been utilized. The watershed delineation has been done using AWD (Automatic Watershed Delineation) which is available as a plugin in ArcSWAT. It has classified the catchment into 28 subbasins. From Esri Sentinel-2 landuse map has been used and the soil map is extracted from FAO Raster world soil map. Moreover, we can classify the sub basins into 173 HRUs (Hydrological Response Unit) by the model. The weather files from 1982 to 2019 has been used from the global weather source as a seed to the model. The successful run of the model gives elucidate fluctuating runoff volumes over time, spanning from a lowest of 2.56 mm to a extreme of 503.78mm. Notably, the annual average runoff stands at 190.82 mm, representing approximately 28.34% of the cumulative rainfall experienced within the river basin. The estimation of runoff is helpful in allocating water for agriculture, household demands, and industrial requirements.

Model-based analysis of the impact of climate change on hydrology in the Guayas River basin (Ecuador)

ABSTRACT Worldwide climate change will most likely lead to drastic changes in hydrology and food production. In this study, the impact of climate change on the hydrological regime and the fate of pesticides in the Guayas River basin is investigated using the Soil and Water Assessment Tool. Four general circulation models and three representative concentration pathways (RCP 4.5, RCP 6.0 and RCP 8.5) for three future periods were used to assess impact of climate change. Future projections showed a maximum increase in the average monthly precipitation of 40% in June, as well as an increase in an average minimum temperature of 3.85°C for July and an average maximum temperature of 4.5°C for August in 2080s. The model simulations based on RCP 8.5 scenario predict an increase in potential evapotranspiration by 11%, surface runoff of 39% and water yield of 33% in 2080s. The pesticide simulation showed the highest water concentrations during the wet season. Projections of trends in pesticide concentration indicate a similar trend to the current situation given the application rate remains the same. The results can be beneficial for the management and planning of the basin to mitigate flood and water quality-related impacts of food production and climate change.

Investigating Hydrological Drought Characteristics in Northeastern Thailand in CMIP5 Climate Change Scenarios

In this study, we analyzed the predictions of hydrological droughts in the Lam Chiang Kri Watershed (LCKW) by using the Soil and Water Assessment Tool (SWAT) and streamflow data for 2010–2021. The objective was to assess the streamflow drought index (SDI) for 5-, 10-, 25-, and 50-year return periods (RPs) in 2029 and 2039 in two representative concentration pathway (RCP) scenarios: the moderate climate change scenario (RCP 4.5) and the high-emission scenario (RCP 8.5). The SWAT model showed high accuracy (R2 = 0.82, NSE = 0.78). In RCP4.5, streamflow is projected to increase by 34.74% for 2029 and 18.74% for 2039, while in RCP8.5, a 37.06% decrease is expected for 2029 and 55.84% for 2039. A historical analysis indicated that there were frequent short-term droughts according to SDI-3 (3-month-period index), particularly from 2014 to 2015 and 2020 to 2021, and severe droughts according to SDI-6 (6-month-period index) in 2015 and 2020. The RCP8.5 projections indicate worsening drought conditions, with critical periods from April to June. A wavelet analysis showed that there is a significant risk of severe hydrological drought in the LCKW. Drought characteristic analysis indicated that high-intensity events occur with low frequency in the 50-year RP. Conversely, high-frequency droughts with lower intensity are observed in RPs of less than 50 years. The results of this study highlight an increase in severe drought risk in high emission scenarios, emphasizing the need for water management.

Exploring the future hydropower production of a run-of-river type plant in the source region of the Tigris Basin (Türkiye) under CMIP6 scenarios

This assessment presents a framework for exploring the changing climate impacts on the energy production capacity of a run-of-river type plant, using the Basoren Weir and Hydropower Plant (HPP) as a case study. The Basoren Project is planned considering historical streamflow records in the source region of the Euphrates-Tigris River Basin (ETRB), which is a prominent hotspot warming at nearly double the global average rate. The quantification is built on precipitation and maximum/minimum temperature datasets from 24 Global Climate Models (GCMs) belonging to the sixth phase of the Coupled Model Intercomparison Project (CMIP6) under the moderate- and high-end Shared Socioeconomic Pathway (SSP) scenarios of SSP2-4.5 and SSP5-8.5, as well as the CMIP6 historical experiment (HEXP) scenario. The distribution mapping method is employed to adjust the raw GCM datasets for systematic biases. The Soil and Water Assessment Tool (SWAT) is preferred in producing daily runoff time series for the bias-adjusted simulations of each GCM over the historical (1988-2009) and three future (2025-2049, 2050-2074, and 2075-2099) periods. The ramifications of the changing climate on the Basoren HPP's energy production capacity are assessed based on the medians of the operational results reached for each GCM under the future societal development scenarios of SSP2-4.5 and SSP5-8.5, considering the medians achieved under the HEXP scenario as the reference case. The results indicate potential reductions in the mean yearly energy production of the Basoren HPP by 7.9%, 5.5%, and 5.3% under the SSP2-4.5 scenario, and by 5.8%, 8.0%, and 17.3% under the SSP5-8.5 scenario for the periods 2025-2049, 2050-2074, and 2075-2099, respectively. While declining spillway releases are expected to partly offset the impact of decreasing streamflow rates on energy production, the shift from a snow-dominated to a rain-dominated hydrologic regime necessitates re-optimizing the power capacities of the ETRB plants to maintain effective use of hydropower potential.

Using surface runoff to reveal the mechanisms of landscape patterns driving on various forms of nitrogen in non-point source pollution

Non-point source (NPS) pollution directly threatens river water quality, constrains sustainable economic development, and poses hazards to human health. Comprehension of the impact factors on NPS pollution is essential for scientific river water quality management. Despite the landscape pattern being considered to have a significant impact on NPS pollution, the driving mechanism of landscape patterns on NPS pollution remains unclear. Therefore, this study coupled multi-models including the Soil and Water Assessment Tool (SWAT), Random Forest, and Partial Least Squares Structural Equation Modeling (PLS-SEM) to construct the connection between landscape patterns, NPS pollution, and surface runoff. The results suggested that increased runoff during the wet season enhances the link between landscape patterns and NPS pollution, and the explained NPS pollution variation by landscape pattern increased from 59.6 % (dry season) to 84.9 % (wet season). Furthermore, from the impact pathways, we find that the sink landscape pattern can significantly and indirectly influence NPS pollution by regulating surface runoff during the wet season (0.301*). Meanwhile, the sink and source landscape patterns significantly and directly impact NPS pollution during different seasons. Moreover, we further find that the percentage of paddy land use (Pad_PLAND) and grassland patch density (Gra_PD) metrics can significantly predict the dissolved total nitrogen (DTN) and nitrate nitrogen (NO3−-N) variation. Thus, controlling the runoff migration process by guiding the rational evolution of watershed landscape patterns is an important development direction for watershed NPS pollution management.

REVIEW AND COMPARATIVE STUDY OF HYDROLOGICAL MODELS FOR RAINFALL-RUNOFF MODELLING

Water is considered as an important resources for human existence on the earth. In order to simulate or optimized hydrological data for various water resources management, several hydrological models are very useful to attain this aim for water resources management and as a decision support tools. A rainfall-runoff model is a quantitative prototype explaining the rainfall-runoff interactions at basin scale. The hydrological models have peculiarities in terms of capabilities for various water resources management. This paper tends to reviewed over fifty (50) papers that are peculiar to hydrological models as applicable to rainfall-runoff modeling. It involved evaluating and comparing different hydrological models used in simulating rainfall process converting into surface runoff for water use efficiency. Several runoff models such as Hydrologic Engineering Center - Hydrologic Modeling System (HEC-HMS), Soil and Water Assessment Tool (SWAT), Precipitation-Runoff Modeling System (PRMS), Variable Infiltration Capacity model (VIC), LISt-based Erosion Model (LISEM), MIKE Surface Water - Groundwater Hydrology (MIKE SHE) and Runoff Prophet were critically assessed. Rainfall-runoff models are globally utilized for different applications to enhance water use efficiency across different sectors. However, types of hydrological models by examining various hydrological models, model accuracy by evaluating the accuracy and reliability of each model in predicting runoff from rainfall data, scope of applications by determining the adequacy of the models for numerous geographical regions and climatic circumstances, complexity and usability by assessing the complexity of the models, their data requirements, ease of use and computational efficiency, also the models advantages and limitations in capturing the dynamics of the rainfall-runoff process were critically assessed. This was to aid modeling objectives. It was inferred that HEC-HMS is widely applied for modelling precipitation-runoff processes in watersheds of various sizes, aiding in flood forecasting, reservoir operation, and water management for agricultural and urban water use efficiency. SWAT is used for assessing the impact of land management practices (e.g., crop rotation, irrigation, land use changes) on water resources, including runoff generation and water quality, thus optimizing water use efficiency in agriculture. PRMS is applied to model the transport of water via complex hydrological systems, aiding in watershed management and water use efficiency assessments. In conclusion, this comparative review seeks to guide water scientists, the users of hydrological models and hydrological engineers in selecting the most suitable models for their specific modelling needs for sustainable water resources management.

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.

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.

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.

Spatio-Temporal Distribution of Water Availability in Marshyangdi Basin: Hydrological Model Development

This Study has developed a hydrological model for the Marshyangdi river basin in Western Nepal, showing considerable potential for developing water resources and overall national prosperity. The model is also used to characterise hydrology and assess the availability of water resources across different spatial and temporal dimensions, hence improving our comprehension of water availability and its possible applications. The newly developed hydrological model in the Soil and Water Assessment Tool (SWAT) replicates the mean flows, hydrological pattern, and flow duration curve at the basin and 54 sub-basin outputs. Additionally, the model undergoes calibration and validation, employing Sufi-2 to fine-tune hydrological parameters. Based on the data generated by the model, the annual average precipitation (P) in the Marshyangdi basin is projected to be 1843 mm. Approximately 17.88% of the average yearly rainfall is lost via evapotranspiration; however, this varies significantly across different locations and time periods. Contrasting the two, the mountains have a higher moisture level than the Himalayan regions. The predicted average annual flow volume at the basin outflow is 9467.423 million cubic metres (MCM). Examining water shortages, finding regions with excess water, and developing solutions to address the competing needs of agriculture, industry, urban areas, and ecosystems are advantageous. Therefore, this method may improve the effectiveness of strategic planning and the long-term management of water resources.