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This study focuses on the impacts of climate change on hydrological processes in watersheds and proposes an integrated approach combining a weather generator with a multi-site conditional generative adversarial network (McGAN) model. The weather generator incorporates ensemble GCM predictions to generate regional average synthetic weather series, while McGAN transforms these regional averages into spatially consistent multi-site data. By addressing the spatial consistency problem in generating multi-site synthetic weather series, this approach tackles a key challenge in site-scale climate change impact assessment. Applied to the Jinghe River Basin in west-central China, the approach generated synthetic daily temperature and precipitation data for four stations under different shared socioeconomic pathways (SSP1-26, SSP2-45, SSP3-70, SSP5-85) up to 2100. These data were then used with a long short-term memory (LSTM) network, trained on historical data, to simulate daily river flow from 2021 to 2100. The results show that (1) the approach effectively addresses the spatial correlation problem in multi-site weather data generation; (2) future climate change is likely to increase river flow, particularly under high-emission scenarios; and (3) while the frequency of extreme events may increase, proactive climate policies can mitigate flood and drought risks. This approach offers a new tool for hydrologic–climatic impact assessment in climate change studies. [ABSTRACT FROM AUTHOR]

Understanding responses of stream discharge to precipitation in a watershed is important in gaining insights into watershed hydrology and estimating hydraulic parameters. Transfer functions in the spectral domain are commonly used to quantify the relationship between precipitation and discharge, and estimate watershed hydraulic parameters. However, previous models have not adequately accounted for the impact of the unsaturated zone. To address this, we have developed a novel analytical model that considers the effect of the unsaturated zone to obtain transfer functions within watersheds. These transfer functions are derived by the spectral method and verified through numerical simulations. The results indicate that the transfer functions are influenced significantly by the relative hydraulic conductivity exponent αk in the moisture characteristic curve. A higher αk results in a lower transfer function, indicating more robust filtering of hydrological signals. A thicker unsaturated zone results in lower transfer functions at higher frequencies. The traditional transfer functions, which neglect the retention capacity of the unsaturated zone, tend to overestimate hydrological responses at high frequencies. Our transfer functions agree well with integrated watershed‐scale flow models and are also applied to observed data from four watersheds in Iowa, providing reasonable estimates for the hydraulic parameters. This study contributes to a deeper understanding of watershed behavior and offers an enhanced tool for estimating hydraulic parameters with practical applications. Key Points: Transfer functions are proposed to quantify hydrological signal filtration considering unsaturated flow described by Richards equationThicker unsaturated zones or higher conductivity exponents enhance the filtration of hydrological signalsUnsaturated zone generally possesses a stronger ability to filter watershed hydrological signals than that of saturated zone [ABSTRACT FROM AUTHOR]

Hydrosedimentalogical models contribute to management of water resources, provided they are based on robust monitoring and calibration–validation strategies. The Limburg Soil Erosion Model (LISEM) properly represents runoff and sediment yield from watersheds with deep, clayey, weathered soils intensely occupied with grain production and dairy farming. Runoff and sediment yield in this agricultural environment have significant economic and off-site ecological importance, as the watersheds are connected to a large reservoir responsible for energy production and water supply. The objective of the study was to test whether LISEM is efficient in runoff and sediment yield modeling (calibration and validation) in paired watersheds with clayey weathered soils, under dairy cattle grazing and no-tillage grain production. The LISEM adequately represented runoff and erosion processes in the calibration phase (2018–2019), with Nash and Sutcliffe efficiency coefficient up to 0.94 and 0.92 for surface runoff, and 0.89 and 0.88 for sediment yield, respectively, for NW and SW watersheds. Some model parameters required significant adjustments, e.g., Ksat at 78.5% and 49.1%, initial soil moisture at 5.5% and 2.5%, soil cohesion at 24.1% and 4.6%, and aggregate stability at 21.4% and 4.6%, respectively for NW and SW watersheds. During the validation period (2020–2021), the model exhibited constraints in adequately representing the hydrosedimentological processes, with only a few rainfall events showing accurate results. Thus, for the utilization of a validated LISEM in future climate scenarios, the model still requires thorough scrutiny of the equations governing hydrology and erosion processes, along with continued monitoring and further model parameterization. [ABSTRACT FROM AUTHOR]

The risk of more frequent and intensified extreme events is expected to increase with climate change. In semi-arid regions, particularly, both increased flooding and prolonged droughts pose a threat as the water resources system must be prepared for both types of extremes. To understand how future extremes may be altered, however, past extremes must be understood. For this reason, this study employs three physically based models to simulate the atmospheric, snow, and hydrologic conditions in the American River Watershed: the Weather Research and Forecasting Model and the Watershed Environmental Hydrology Hydro-Climate Model with the addition of a SNOW Module. Each model is individually calibrated and validated against either gauge data or data provided by the Parameter-Elevation Regressions on Independent Slopes Model for two 10-year periods before a full 169-year daily reconstruction is performed for the period from 1852 through 2020. To analyze the model performance under hydrologic extremes, three flood years (1997, 2006, and 2017) and two drought periods (1987-1992 and 2012-2016) are further analyzed. The reconstruction outputs are found to successfully simulate historical conditions at both daily and monthly scales. Results highlight the importance of fully accounting for the role of temperature in snow processes and the subsequent flow conditions. By understanding how the models perform under historical extreme conditions, future extreme events can be compared, and necessary adaptation plans can be conceived to ensure that the watershed is prepared for future wet and dry conditions. Additionally, the created reconstruction dataset is comprehensive, simulating conditions across the hydroclimate, at a finer spatial and temporal scale than is typically available from observation data alone. The dataset can be further analyzed to assess changes in the trends and the potential trajectory of extreme events within the American River Watershed. [ABSTRACT FROM AUTHOR]

Flashiness is a hydrologic signature used to describe the responsiveness of streamflow to precipitation. In practise, flashiness has most often been correlated with rainfall intensity and the presence of urban land cover or imperviousness. However, a number of watershed characteristics can influence flashiness, necessitating further investigation of how this particular watershed behaviour and its associated drivers vary at regional scales. We investigated how ten measurable watershed characteristics are empirically related to flashiness of 195 gauged streams in the Mid‐Atlantic region using linear regression analysis. The selected gauges had drainage areas ranging in size from 15 to 250 km2. To explore multiple quantifications of flashiness, we determined both the Richards‐Baker flashiness index, calculated from the continuous hydrograph, and number of peaks‐over‐threshold, for all watersheds for a 10‐year period. As found in other studies, the percentage of watershed development was strongly correlated with stream flashiness, though significant inverse relationships also existed for forest cover, water and wetlands and carbonate geology. Differences in flashiness values between rural and suburban watersheds were not significant, with a significant increase in flashiness (p < 0.01) occurring at 80% development or ~ 25% imperviousness. In addition, we found significant differences in relationships between watershed characteristics and flashiness when differentiated by physiographic regions. For the study area and each of its five physiographic sub‐regions, we identified the four most important predictors through multiple regression. The overall mid‐Atlantic model suggested that development, wetlands and compactness ratio as the most important predictors (adj R2 = 0.57). Significant predictors of stream flashiness varied among regions; however, wetlands served as a significant buffer of flashiness in four of five sub‐regions demonstrating the importance of wetlands in modulating flash‐flooding. In all physiographic regions, empirical models of flashiness values outperformed the Mid‐Atlantic regional model, underscoring the value of local landscape characteristics in augmenting or modulating flashy watershed responses. Our findings suggest the potential for improvements to operational flash‐flood forecasting using hydrologic characteristics of the landscape. [ABSTRACT FROM AUTHOR]

Buried bedrock valleys in North America are often filled with coarse-grained deposits that form productive buried-valley aquifers, providing a valuable water source for human use. However, the role of buried-valley aquifers in the hydrology of watersheds, including baseflow generation and supporting ecosystems, is not widely recognized. This study demonstrates that the presence of a buried-valley aquifer influences near-surface hydrology, specifically the interaction of a creek coaligned with the bedrock valley thalweg. We combine synoptic sampling of environmental tracers and geochemistry of the creek during low flow conditions and regional groundwater data to determine downstream variation in groundwater interaction. Modelled downstream variation suggests that the greatest amount of groundwater discharge occurs where the buried-valley aquifer is present beneath, but not necessarily in direct contact with the creek. Further, a shift in baseflow source to the creek occurs depending on the depth to bedrock, indicated by a change in water isotopic and chemical composition similar to that of groundwater located in the sediments above bedrock to a signature similar to groundwater in the underlying bedrock formations. This study demonstrates that buried-valley aquifers can focus groundwater flow to a modern-day creek valley, providing a unique source of baseflow in the Canadian Prairies and midwestern United States. The interaction between buried-valley aquifers and streams has implications for water allocation and land use planning, whereby a critical baseflow source may also be a target aquifer to develop with good quality water. [ABSTRACT FROM AUTHOR]

The frequency and extent of wildfires have increased in recent decades with immediate and cascading effects on water availability in many regions of the world. Precipitation is used as primary input to hydrologic models and is a critical driver of post‐wildfire hydrologic hazards including debris flows, flash floods, water‐quality effects, and reservoir sedimentation. These models are valuable tools for understanding the hydrologic response to wildfire but require accurate precipitation data at suitable spatial and temporal resolutions. Wildfires often occur in data‐sparse, headwater catchments in complex terrain, and post‐wildfire hydrologic effects are particularly sensitive to high‐intensity, short‐duration precipitation events, which are highly variable and difficult to measure or estimate. Therefore, the assessment and prediction of wildfire‐induced changes to watershed hydrology, including the associated effects on ecosystems and communities, are complicated by uncertainty in precipitation data. When direct measurements of precipitation are not available, datasets of indirect measurements or estimates are often used. Choosing the most appropriate precipitation dataset can be difficult as different datasets have unique trade‐offs in terms of spatial and temporal accuracy, resolution, and completeness. Here, we outline the challenges and opportunities associated with different precipitation datasets as they apply to post‐wildfire hydrologic models and modeling objectives. We highlight the need for expanded precipitation gage deployment in wildfire‐prone areas and discuss potential opportunities for future research and the integration of precipitation data from disparate sources into a common hydrologic modeling framework. This article is categorized under:Science of Water > Hydrological ProcessesScience of Water > MethodsScience of Water > Water and Environmental Change [ABSTRACT FROM AUTHOR]

Climate change is intensifying water challenges in the Eastern Himalayas. Bridging climate change and water demand is vital, especially in India's ungauged Himalayan catchments. The proposed novel method aims to differentiate climate change and anthropogenic activity impacts on catchment hydrology. In this study, evaporative demand was assessed by coupling SWAT and Budyko framework at the micro-watershed scale for understanding climate and surface changes in local hydrology. The coupled model considers climate parameters through SWAT to decompose the impacts of climate change and anthropogenic activities on watershed hydrology. The Budyko framework depicted the relationship between precipitation, evapotranspiration (ET), and potential evapotranspiration (PET) resulting in partitioning evaporative demand into green and blue ET. Parameters like d-statistics, responsivity, and elasticity assessed the buffer capacity of catchments against climate change. The study unveiled catchment characteristic (ω) values within the range of 1.70–1.56 from 2005 to 2030, indicative of a discernible shift in hydrological patterns attributed to changes in land use land cover (LULC) and climate variables. The investigation underscored the significant impact of LULC changes, manifesting as a reduction in snow and glacier cover alongside an augmentation in blue ET. The variation in precipitation, LULC, PET, and temperature were identified as primary influencers on hydrological regimes, rendering watersheds increasingly susceptible to climatic variations. Six catchments are unable to cope with or buffer against climate change and have low coping capacity. The study emphasizes the exigency to water resource management in ecologically delicate Eastern Himalayan ecosystem. [ABSTRACT FROM AUTHOR]

Subsurface tile drainage systems are common in agricultural regions of the Midwestern United States. Drainage systems remove excess water from the surface and soil profile of agricultural fields, allowing crop production in previously unsuitable locations. However, these systems impact watershed hydrology and could influence flooding events. Therefore, this study aimed to determine whether tile drainage systems influence downstream flood days in a Midwestern agricultural watershed, specifically the Skunk Creek watershed. The Soil and Water Assessment Tool (SWAT) model was used to simulate the hydrologic processes of the Skunk Creek Watershed for an 18-year period (2004-2021). The model was calibrated and validated using observed daily streamflow data with the SWAT Calibration and Uncertainty Program (SWAT-CUP) software and through the manual modification of missed precipitation data. Three tile drainage scenarios--ranging from 15% to 75% tile-drained agricultural land--were individually incorporated into the model. Results indicated that with increased tile drainage, surface runoff, groundwater flow, deep aquifer recharge, and percolation decreased, whereas lateral soil flow, tile flow, evapotranspiration, and water yield increased. A comparison of tile drainage scenarios suggests that increasing the area of tile-drained agricultural land decreases total flood days. However, the impact of tile drainage systems on downstream peak flood flows varied by event, with large precipitation events initiating flood days across all scenarios. While tile flow decreased flood days on a daily time step, flash floods might have occurred on a subdaily time step but were not captured in this study. Future studies can replicate the approach with a sub-daily time step for simulating hourly flood events with various tile drainage scenarios. [ABSTRACT FROM AUTHOR]

An accurate quantification of flow components and an understanding of water source dynamics are essential for effective water resource and quality management. However, the complexity of hydrological processes and the interference of intensive human activities pose significant challenges in precisely separating water discharge into distinct components such as surface runoff, interflow, and groundwater. The Xinanjiang (XAJ) model, a conceptual watershed hydrological model, has been developed and successfully implemented for rainfall–runoff simulations and hydrograph separations across various Chinese watersheds. While the model framework is robust, it fails to account for agricultural irrigation water withdrawals and the variations in in-stream water travel times across different hydrological regimes, introducing considerable uncertainty in simulating low-flow conditions. This study introduced modifications to the XAJ model by allowing parameter adjustments across different flow regimes and incorporating irrigation withdrawals into the runoff routing process. Utilizing a decade of hydrometeorological data (2013–2022) from the Yongan River watershed in eastern China, the modified model demonstrated improved efficiency metrics in low- and medium-flow regimes compared to the original model, with a Nash–Sutcliffe coefficient improvement from −4.43~−0.49 to 0.40~0.46, R2 from 0.21~0.36 to 0.53~0.63, and BIAS reduction from 7.60~89.08% to 2.06~12.71%. Furthermore, the modified XAJ model provided a more accurate estimation of the spatial and temporal distribution of streamflow components across sub-watersheds. The original model tended to overestimate groundwater contributions (13%) and underestimate interflow (14%), particularly in low-flow conditions. The enhanced XAJ model, thus, offers a more effective tool for identifying streamflow components, providing essential insights into hydrological processes for better management decisions. [ABSTRACT FROM AUTHOR]

Forest fires pose significant environmental challenges globally, profoundly affecting watershed hydrology. As human activities increase and climate change exacerbates, the incidence and severity of forest fires have escalated, leading to profound modifications in watershed hydrological behavior. This review synthesizes findings from numerous studies conducted between 1966 and May 2024, focusing on the short- and long-term effects of forest fires on watershed runoff, peak flow, sediment transport, and water quality. Key findings include significant increases in runoff volume and peak flow, with post-fire runoff in some regions increasing by up to 500 %. Fires also alter soil properties, reducing infiltration and increasing erosion. These changes persist over time, impacting groundwater recharge, baseflow, and water quality. Elevated levels of phosphorus, nitrate, and other pollutants in post-fire runoff present risks to aquatic ecosystems and human health, with potential for eutrophication and contamination of drinking water. The study highlights regional differences in hydrological responses to forest fires, with Mediterranean regions experiencing rapid runoff increases, while boreal forests exhibit more gradual hydrological changes. This review also discusses the methodologies employed, including hydrological models and remote sensing technologies, and outlines future research needs to address gaps in our understanding of fire-watershed interactions. Improved management strategies are essential to mitigate the hydrological impacts of increasing fire activity in forested regions worldwide.

Despite the unique hydrological properties exhibited by frozen soil, its characteristics are often oversimplified in most distributed hydrological models, resulting in major errors in material cycle predictions in cold climate regions. This study aims to modify the Soil and Water Assessment Tool (SWAT), a semi-distributed hydrological model that originally assumes no water movement in frozen soil layers, by incorporating the dynamic change of soil permeability based on the degree of soil freezing, and to understand the effect of water movement in frozen soil on watershed hydrology. SWAT with frozen soil permeability (SWAT-FSP) was developed by adding two modules to the original SWAT: a heat conduction equation that considers the phase change of ice and liquid water and a frozen-soil percolation model that considers dynamic decrease in soil permeability due to soil freezing. The original SWAT and SWAT-FSP were set up in the Tokoro River watershed in northern Japan. The river flow and soil water dynamics during the snowmelt period (March–May) simulated using the original SWAT and SWAT-FSP were compared. The modified model significantly alters the soil water dynamics simulation to generate earlier soil water drainage and reduces the soil water content during the snowmelt period in years featuring weak soil freezing. Consequently, the SWAT-FSP estimated an earlier increase in river flow at the beginning of the snowmelt period and a smaller river flow in the middle of the snowmelt period as compared with the original SWAT. The modified model improved the overall performance in river flow simulation for the snowmelt period (March–May) of 2012–2019. The Nash-Sutcliffe efficiency obtained during the calibration period by the original SWAT was 0.602, and during the validation period it was 0.367. For the SWAT-FSP, it was 0.659 during calibration, and 0.639 during validation. Meanwhile, the SWAT-FSP showed unsatisfactory performance in 2014 and 2015, with underestimated snow water equivalent, indicating that improvements in the snowmelt/accumulation module may further enhance its accuracy. Our results showed that the dynamic change of soil permeability governed by the degree of soil freezing is an important factor affecting the water cycle of cold climate watersheds with seasonally frozen soil. [ABSTRACT FROM AUTHOR]

The effects of forest treatments on watershed hydrology have often been studied in isolation from climate change. Consequently, under a warming climate, it is unclear how forest thinning will impact snowpacks, evapotranspiration, and streamflow availability. In this study, we used a distributed hydrologic model to provide insight into the effects of warming and forest treatment on the hydrologic response of the Beaver Creek watershed (∼1,100 km2) of central Arizona. Prior to the numerical experiments, confidence in the hydrologic model performance was established by comparisons to long‐term observations (2003–2018) of snow water equivalent and streamflow using station observations and through spatially distributed estimates. Results indicated that warming during the 21st century could increase mean annual streamflow by 1.5% for warming levels up to +1°C, followed by a −29% decrease for continued warming up to +6°C, due to the varying effects of warming on snow sublimation, soil evaporation, and plant transpiration. On average, forest thinning increased streamflow by +12% (or 7 mm/yr) through lower plant transpiration by −19% (or −18 mm/yr), while also increasing the change in soil water storage by +42% (or 11 mm/yr). Forest thinning delayed the detrimental effects of warming on streamflow until +4°C, as compared to +2°C without forest treatment. Furthermore, model results suggested that forest cover reductions laterally displace water availability and evapotranspiration to downstream sites. These model‐derived mechanisms provide insights on the potential for water resilience toward warming effects afforded through treatment projects in southwestern US ponderosa pine forests. Plain Language Summary: The effects of forest thinning on watershed hydrology have often been studied in isolation from warming. Thus, it is unclear if forest thinning conducted under different warming levels will have hydrologic impacts on snow and streamflow conditions. Here, we used a hydrologic model to study these interactions within the Beaver Creek watershed in Arizona. First, we built confidence in the hydrologic model through comparisons to snow and streamflow observations. Then, we conducted a range of different warming scenarios with and without forest thinning. We found that warming could increase streamflow up to +1°C, but then led to larger decreases in streamflow up to +6°C. In contrast, forest thinning increased streamflow and delayed the negative effects of warming up to +4°C. The application of the hydrologic model with the warming and forest thinning scenarios provides new insights on how warming effects could be reduced through management projects in ponderosa pine forests. Key Points: Distributed simulations in mountainous watershed show good match with warm and cold season hydrologic data over 16‐year periodIndependent and combined scenarios showed that forest thinning reduces the streamflow impact of warming up to a 4°C increaseForest treatment effects propagated downstream by displacing evapotranspiration from forested uplands to near channel regions [ABSTRACT FROM AUTHOR]

To advance understanding of the spatiotemporal variability of the streamflow in the Pearl River Basin (PRB), we used the Soil and Water Assessment Tool model to simulate the water fluxes from 2010 to 2020 and to identify the underlying controlling mechanisms. The streamflow in the PRB is highly variable and controlled by complex land surface processes and atmospheric impacts over the heterogeneous terrain. Two key factors primarily govern the streamflow: (1) the location of the active precipitation zone, which is determined by the interaction between the monsoon path and uplifting effect of the terrain, and (2) the redistributions resulting from land use and soil characteristics. We observe distinct patterns in the different water fluxes across the different regions. Specifically, surface flow exhibits the highest activity within the precipitation zone. Lateral flow and actual evapotranspiration (AET) have the greatest intensity in the forests and in agricultural regions, respectively, and the aquifer flow is more active in areas with coarse soil textures. The land surface processes of the AET and aquifer retention significantly govern the temporal variability of the streamflow, contributing to the precipitation and streamflow being out of phase in the PRB. Based on the underlying mechanisms driving streamflow variability, we classify the PRB into three substreams: a drought-prone upstream, a hydrologically active midstream, and a typhoon-affected downstream, and each substream exhibits distinct spatiotemporal characteristics of streamflow. We find that the time series and probability distributions of the streamflow at different tributaries within each substream are similar. Each probability distribution is multimodal and can be decomposed into three unimodal distributions representing dry, transitional, and wet conditions. Specifically, the PRB features a large and steep dry mode, a flat transitional mode, and a short wet mode. [ABSTRACT FROM AUTHOR]

Seasonal predictions of spring‐summer river flow volume (water supply forecasts, WSFs) are foundational to western US water management. We test a new space‐based remote sensing product, spatially and temporally complete (STC) MODSCAG fractional snow‐covered area (fSCA), as input for the Natural Resources Conservation Service (NRCS) operational US West‐wide WSF system. fSCA data were considered alongside traditional SNOTEL predictors, in both statistical and AI‐based NRCS operational hydrologic models, throughout the forecast season, in four test watersheds (Walker, Wind, Piedra, and Gila Rivers in California, Wyoming, Colorado, and New Mexico). Outcomes from over 200 WSF models suggest fSCA‐enabled accuracy gains are most consistent and explainable for short‐lead, late‐season forecasts (roughly 10%–25% improvements, typically), which in operational practice can be challenging as snowlines rise above in situ measurement sites. Gains are roughly proportional to how thoroughly spring‐summer runoff is dominated by snowmelt, and how poorly in situ networks monitor late‐season snowpack. fSCA also improved accuracy for long‐lead, early‐season forecasts, which are similarly problematic in WSF practice, but not for WSFs issued around the time of peak snow accumulation, when in situ measurements reasonably characterize mountain snowpack available for upcoming spring‐summer snowmelt. The AI‐based hydrologic model generally outperformed the statistical model and, in some cases, better‐capitalized on satellite remote sensing. Additionally, preliminary analyses suggest reasonable WSF skill in many cases using fSCA as the sole predictor, potentially useful in sparsely monitored regions; and that combining satellite and in situ products in data‐driven hydrologic models using genetic algorithm‐based predictor selection could help guide new SNOTEL site selection. Plain Language Summary: Western US operational water supply forecasts (WSFs) are predictions, typically issued at the start of every month from January through spring, of upcoming spring‐summer flow volume for a given point on a river, performed by service‐delivery organizations having strict accountabilities to end users around reliably delivering this information. WSFs use mathematical models of watershed hydrology that heavily leverage on‐the‐ground data on winter mountain snowpack, source of much of the spring‐summer runoff. Past research shows that snow measurements from air and space can improve WSF accuracy, but operational WSF models often don't directly ingest such data for practical reasons. Here, we consider new, NASA satellite‐derived snow data that is uniquely suited to WSF operations, partly because coverage in space and time is gap‐free, and test it in the largest stand‐alone operational WSF system in the American West, run by the US Department of Agriculture. Overall, outcomes demonstrate the benefits of this satellite data in statistical and AI‐based hydrologic models used in standard WSF applications in the western US, and guide scientists and engineers around when and where to use those data. Such WSF improvements will be critical to successful water management going forward in this increasingly water‐stressed region. Key Points: Improvements to operational water supply forecasts (WSFs), based heavily on mountain snow data, are critical to western US water managementWe test a new satellite remote sensing snow product, having no spatial or temporal coverage gaps, for ability to improve USDA WSF modelsResults argue for operational implementation and give practical guidance around when and where such data may provide the most benefit [ABSTRACT FROM AUTHOR]

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This study focuses on the impacts of climate change on hydrological processes in watersheds and proposes an integrated approach combining a weather generator with a multi-site conditional generative adversarial network (McGAN) model. The weather generator incorporates ensemble GCM predictions to generate regional average synthetic weather series, while McGAN transforms these regional averages into spatially consistent multi-site data. By addressing the spatial consistency problem in generating multi-site synthetic weather series, this approach tackles a key challenge in site-scale climate change impact assessment. Applied to the Jinghe River Basin in west-central China, the approach generated synthetic daily temperature and precipitation data for four stations under different shared socioeconomic pathways (SSP1-26, SSP2-45, SSP3-70, SSP5-85) up to 2100. These data were then used with a long short-term memory (LSTM) network, trained on historical data, to simulate daily river flow from 2021 to 2100. The results show that (1) the approach effectively addresses the spatial correlation problem in multi-site weather data generation; (2) future climate change is likely to increase river flow, particularly under high-emission scenarios; and (3) while the frequency of extreme events may increase, proactive climate policies can mitigate flood and drought risks. This approach offers a new tool for hydrologic–climatic impact assessment in climate change studies.

The Soil and Water Assessment Tool (SWAT) model was used to simulate the impacts of LULC changes on streamflow and sediment yields of Migori River watershed. The Nash – Sutcliffe Efficiency (NSE), co-efficient of determination (R2), and percent bias (PBIAS) of the monthly streamflow and sediment outflow simulation for the calibration and validation showed good model performance. From 1980 to 2020, the results show a decrease of 40.63% in shrublands, 84.86% in grasslands, and 52.90% in forests. Additionally, there was an 82.03% reduction in water areas and a 38.44% decline in wetlands. In contrast, cultivated land, bare land, and built-up areas all experienced growth during this same time frame, expanding by 34.25%, 132.28%, and 461.20%, respectively. These LULC changes have contributed to the decline of annual actual evapotranspiration by 2.83%, annual potential evapotranspiration by 5.38%, and annual groundwater flow by 19.06%; whereas annual surface runoff, water yield, and sediment yields have increased over the same period by 32.57%, 4.82%, and 84.58% respectively. The negative impacts of LULC changes between 1980 and 2020 on the hydro-sedimentological processes are the main cause of flooding problems within the watershed. The study recommends addressing the sedimentation and flooding with comprehensive soil and water conservation interventions. [ABSTRACT FROM AUTHOR]

Spring constitutes one of the primary water resources in some parts of the world, such as the Indian Himalayas. However, these remain imperfectly surveyed and delineated far and wide in most areas worldwide. Due to natural and anthropogenic factors, the springs are under great threat. All over the globe, springs have left as data deficit and have not relatively gained considerable attention in comparison to other systems like rivers, streams, lakes, and wetlands. This is also true for India, where most of the research is usually centered on groundwater, rivers, lakes and wetlands. This manuscript presents an overview of studies carried out on various themes of spring water systems, such as characteristics, classification schemes, and different empirical and analytical methods at international and national levels. A comprehensive overview of the literature identified the demand for an integrated approach of different empirical and analytical methods to strengthen the understanding of spring hydrology in the Himalayan region and elsewhere. Research highlights: Springwater system protection needs a forewarning of imminent contamination and thus, an integrated approach of conceptual and management-related groundwater models should be developed in India on a large scale. Empirical and analytical approaches should be used to attain an inclusive understanding of springwater hydrology and water quality. Himalayan springs should be studied considering the current updated classification schemes to obtain a comprehensive understanding of them. Monitoring of data and simulation models should be developed to establish an integrated and comprehensive understanding of Himalayan spring hydrogeology and hydrology. [ABSTRACT FROM AUTHOR]

South Fork Quantico Creek (SFQ; 19.8 square kilometre (km2), forested) and Fourmile Run (4MR; 32.4‐km2, urban) are small watersheds in northern Virginia, United States. Precipitation and streamflow data for both watersheds were examined from water year (WY) 1952 through 2022. Temporal changes in hydrologic metrics were identified by calculating trends in annual precipitation, annual peak flow, mean daily flow, minimum daily flow, stream flashiness, and the runoff ratio. The impact of climate and urbanization on watershed hydrology was assessed by computing trends on both raw and precipitation‐adjusted data. Despite increasing precipitation in both watersheds, increasing monotonic trends in most hydrologic metrics were observed only in 4MR. At 4MR, the long‐term trend in annual peak flow was non‐linear, thus trends were calculated on separate periods. Annual peak flow increased from WY 1952 through 1968, coinciding with a period of rapid urbanization. During WY 1969 through 1981, annual peak flows decreased, coinciding with construction of a flood channelization project. Trends for both periods were robust to precipitation adjustment. From WY 1982 through 2022, no change in the precipitation‐adjusted annual peak flows occurred, suggesting annual peak flows increased due to climate factors during this period. Comparison of area‐normalized hydrologic metrics between the two watersheds revealed higher flows in 4MR than SFQ across all flows, not just high flows. Runoff ratio and stream flashiness also were higher in 4MR. Differences in hydrologic metrics between the two watersheds were driven primarily by differences in land use, land cover, and modifications to the water balance related to urbanization. Climate change has altered watershed hydrology at both sites, but extensive urbanization in 4MR has altered the hydrology more than that of SFQ. We conclude that urban watersheds are likely at greater risk of increased flooding than less developed areas as the climate intensifies. [ABSTRACT FROM AUTHOR]

Landfalling atmospheric rivers (LARs) are important drivers of mid-latitude climate; however, our understanding of the water vapour sources, storm trajectories, and receiving waters of ARs is limited. This study aims to characterize LARs in southwest British Columbia by their isotopic composition and storm track trajectories and to better understand how AR-derived precipitation is manifested in watershed waters. ARs were depleted (−11.71‰ δ18O, −85.80‰ δ2H, n = 19) compared to non-ARs (−9.47‰ δ18O, −69.58‰ δ2H, n = 32) (p = 0.03); however, the difference is minimal. LAR storm tracks did not show any obvious correlation to their isotopic composition, despite the large variability in their source regions across the Pacific Ocean. The lack of correlation is attributed to mixing air parcels, thereby incorporating moisture with different isotopic compositions into the main transport mechanism. D-excess values for ARs and non-ARs were statistically similar, although seasonal differences were observed. ARs with higher d-excess were sourced from the central Pacific, whereas ARs with lower d-excess had storm tracks through the northern Pacific. Watershed water d-excess values (mean = 8.58 ± 2.97‰) were more similar to winter precipitation (mean = 10.1 ± 5.1‰), compared to summer (mean = 2.8 ± 4.3‰), likely due to their source of winter precipitation at high elevation. A greater range in AR d-excess winter values relative to summer values (3.6–16.6‰, −0.3–6.0‰, respectively) is attributed to storm track variability. [ABSTRACT FROM AUTHOR]

Reforestation often occurs when the economy shifts from agriculture to industry and services such as tourism. However, there is a lack of coherent knowledge and investigation about the impact of reforestation in the tropics on hydrological variability as well as flood risks. It is unclear how changes in forest cover and pattern will affect flood risks and watershed response to future altered rainfall intensity. This study uses the Soil Water Assessment Tool (SWAT+) to simulate the impact of reforestation, the locality of forest, and the concentrated rainfall on the hydrology of the largest watershed in Puerto Rico. SWAT+ is a computer model simulating watershed hydrology driven by meteorological input and the characteristics of soils and land use. We hypothesized that increased forest cover, especially at low elevation range, would reduce flood risk and that reduced rain days while maintaining the mean annual rainfall invariant would increase stream discharge variability. We found that reforestation significantly reduced large discharges but increased small discharges; that forest at low elevation tended to reduce large and extreme discharges in comparison with forest at high elevation; and that more concentrated rainfall not only increased the rainfall variability but also increased the discharge variability. However, both the impact of shifting forest locality and the response of watershed to altered rainfall intensity strongly depended on geophysical factors such as ranges of elevation and slope. Moving forests to lower elevation in subbasins with steeper slopes showed a stronger reduction in extreme discharges than in subbasins with flatter slopes. On the other hand, subbasins with steeper slopes tended to response more strongly to more concentrated rainfall with greater increase in discharge variability than subbasins with flatter slopes. To cope with future increased climate variability, our results favor reforestation at lower elevation for watershed with large elevation ranges and steep slopes. [ABSTRACT FROM AUTHOR]

The aim of this study was to simulate the runoff in the upstream of Chehlgezi hydrometery station in the Gheshlagh Dam watershed, Kurdistan province using SWAT hydrological model. In addition, the results have been evaluated using selected efficiency criteria in the calibration and validation stages, then the performance of the SWAT model is evaluated in simulating the monthly runoff in upland of Gheshlagh Dam. The input model parameters were optimized using the SWAT-CUP optimizer. The calibration and validation of the model was done using SUFI-2 algorithm during 1989-2016 and 2016-2018 periods, respectively. The sensitivity analysis shows that the SCS runoff curve number, Manning’s "n" value for overland flow, minimum and maximum yearly rate of snowmelt, minimum water depth in the shallow aquifer for "revap" were sensitive parameters in flow simulation. The Nash-Sutcliffe and R2 values were 0.62 and 0.65 in the calibration stage, and 0.61 and 0.68 in validation stage, respectively. The results proved the efficiency of the SWAT in monthly flow simulating. According to the results, 55% of the total rainfall entering the watershed has been converted to evapotranspiration, 30% infiltrated into soil and stored as soil moisture, and 15% converted into surface flow component. The results provide useful information on watershed water balance. Flow simulation in different climatic conditions and land-use scenarios in the future can help to sound water resources management.

Rainfall-runoff modeling plays a crucial role in determining the regular water balance. Modifications in land use and land cover (LULC) significantly impact on the hydrological response of watersheds. The study aims to analyze the effect of land use change on river runoff with the use of hydrological modeling in the Wadi Ouahrane watershed in northwestern Algeria. The study was conducted for the period from 1987 to 2017. According to the LULC change study, cultivated land and built-up areas have increased, whereas forest and grassland areas have decreased. Sensitivity evaluation has shown that the CN (curve number) is the most important factor affecting the watershed hydrology. The Nash–Sutcliffe (NSE) and efficiency values for the Wadi Ouahrane watershed were 0.76–0.82 and 0.86–0.91 for the calibration period and 0.72–0.74 and 0.81–0.83 for the validation one, respectively. The assessment of the HEC-HMS response to the LULC change showed that the peak discharge for 2017 increased by 68% relative to the 1987 peak discharge. This research has improved the knowledge of the relationship between land use change and hydrological regimes in the Wadi Ouahrane watershed. [ABSTRACT FROM AUTHOR]

Understanding the spatiotemporal distribution of extreme rainfall and meteorological drought on a watershed scale could be beneficial for local management of any water resources system that supports dam operation and river conservation. This study considered the watershed of Angat as a case, given its economic importance in the Philippines. A series of homogeneity tests were initially conducted on each rainfall dataset from monitoring stations in and near the watershed, followed by trend analysis to determine the rate and direction of change in the annual and seasonal rainfall extreme indices in terms of intensity, duration, and frequency. Three indices, using the rainfall deviation method (%DEV), percent of normal rainfall index (PNRI), and Standardized Precipitation Index (SPI), were also used to identify meteorological drought events. Generally, rainfall in the watershed has an increasing annual PCPTOT (4–32 mm/year), with increasing frequency and intensity in heavy rainfall and wet days. A significant increasing trend (α = 5%) in the seasonal PCPTOT (7–65 mm/year) and R10mm (1.7–10.0 days/decade) was particularly observed in all stations during the Amihan Monsoon Season (Dec–Feb). The observed increasing rainfall intensity and frequency, if it continues in the future, could have an implication both for the water resources operation to satisfy the multiple objectives of Angat Reservoir and for the flood operation that prevents damage in the downstream areas. The effect of each ENSO (El Niño- Southern Oscillation) phase on the rainfall is unique in magnitude, intensity, and duration. The seasonal reversal of the ENSO in the extreme rainfall and meteorological drought signals in Angat Watershed was also evident. The identified meteorological drought events in the watershed based on SPI-12 persisted up to 12–33 months, could reduce more than 60% (PNRI < 40%) of the normal rainfall. Insights from the study have implications for the hydrology of the watershed that should be considered for the water resources management of the Angat Reservoir. [ABSTRACT FROM AUTHOR]

Low-inflow estuaries are subject to inconsistent seasonal and interannual variability in precipitation and watershed influences on hydrology, complicating understanding and prediction of water quality and phytoplankton dynamics. We quantified variability in environmental conditions and phytoplankton biomass over an 8-year period in a eutrophying lagoonal estuary (Baffin Bay, Texas) that experiences prolonged low inflow conditions punctuated by episodic high inflow events, resulting in a large interannual salinity range (20–62 in this study). Using a 90th percentile threshold of chlorophyll a concentration to classify blooms, we observed a higher frequency of blooms at high salinity conditions (20% of high salinity observations were blooms) compared to intermediate (5%) and low (6%) salinity. The conditions and composition of blooms varied at different salinities, with blooms at high salinities dominated by the ecologically damaging "brown tide" Aureoumbra lagunensis, whereas lower salinity blooms were dominated by a variety of phytoplankton groups. The distinct bloom communities that developed under different salinities suggest that complex drivers of community dynamics are at play in Baffin Bay and provide insight into what we can anticipate during future periods of prolonged drought, as well as following sporadic heavy rainfall events, both of which are expected to increase in frequency with climate change. [ABSTRACT FROM AUTHOR]

Context: Quantifying the interactions between land disturbances and energy and water balances, particularly evapotranspiration (ET), is helpful for understanding the land-atmospheric interactions and assessing the effects of urbanization on local climate and hydrological processes at a landscape scale. Objectives: To investigate the mechanisms of ecohydrological response to urbanization from the perspectives of ET or energy balances in a distributed fashion at the watershed scale. To identify spatial 'hot spots', in which ET, and thus watershed hydrology, are most pronounced in response to land use change so that limited watershed landscape management resources can be applied efficiently. Methods: This process-based research quantified spatial patterns of ET and other energy fluxes in a rapidly urbanizing rice paddy-dominated watershed, Qinhuai River Basin (QRB), using a spatially explicit land surface energy balance model (SEBAL). Results: The QRB experienced a rapid land use change in urban–rural interface (URI) area, resulting in a significant reduction in actual ET (− 9.4 mm yr−1) but a significant increase in sensible heat (3.71 W m−2 yr−1) and soil heat fluxes (0.85 W m−2 yr−1) during the growing season from 2001 to 2019. The change in energy partitioning at the watershed scale was dominated by URI area identified as the 'hot spots' of ecohydrological change within a heterogeneous basin. Conclusions: Knowledge gained from this study improves parameterizing distributed watershed ecohydrological models (e.g., ET processes) to guide urban planning. Effective watershed landscape management and planning that aims at mitigating the negative impacts of urbanization should focus on URI by preserving vegetation and local wetlands (e.g., rice paddies). [ABSTRACT FROM AUTHOR]

Green infrastructure (GI) practices improve stormwater quality and reduce urban flooding, but as urban hydrology is highly controlled by its associated gray infrastructure (e.g., stormwater pipe network), GI's watershed‐scale performance depends on its siting within its associated watershed. Although many stormwater practitioners have begun considering GI's spatial configuration within a larger watershed, few approaches allow for flexible scenario exploration, which can untangle GI's interaction with gray infrastructure network and assess its effects on watershed hydrology. To address the gap in integrated gray‐green infrastructure planning, we used an exploratory model to examine gray‐green infrastructure performance using synthetic stormwater networks with varying degrees of flow path meandering, informed by analysis on stormwater networks from the Minneapolis‐St. Paul Metropolitan Area, MN, USA. Superimposed with different coverage and placements of GI (e.g., bioretention cells), these gray‐green stormwater networks are then subjected to different rainfall intensities within Environmental Protection Agency's Storm Water Management Model to simulate their hydrological benefits (e.g., peak flow reduction, flood reduction). Although only limited choices of green and gray infrastructure were explored, the results show that the gray infrastructure's spatial configuration can introduce tradeoffs between increased peak flow and increased flooding, and further interacts with GI coverage and placement to reduce peak flow and flooding at low rainfall intensity. However, as rainfall intensifies, GI ceases to reduce peak flow. For integrated gray‐green infrastructure planning, our results suggest that physical constraints of the stormwater networks and the range of rainfall intensities must be considered when implementing GI. Key Points: Stormwater flow path meandering results in tradeoff between increase in peak flow versus inland floodingRainfall intensity modulates the effects of green infrastructure (GI) coverage and placement on hydrological outcomesThe effects of gray infrastructure's flow path meandering dominates over the effects of GI in high rainfall intensities [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In the eastern region of the North American Continental Divide in the upper Colorado Rockies, this study demonstrates that enhancing streamflow predictability from May to July in the Yellowstone River Basin is enabled. This streamflow improvement is achieved by employing a land surface hydrology model in the watershed, coupled with an updated winter precipitation weather forcing dataset. Utilizing 13 snowpack telemetry stations from the US Department of Agriculture in the Yellowstone River Basin, the paper calculates ratios between a baseline simulated snowpack from the initial land surface model application and the observed snowpack. The average ratio serves as a constant multiplier for the existing snowfall weather forcing applied in the second land surface model simulation. As a result of the second simulation, the streamflow predictability reaches a Nash-Sutcliffe Efficiency (NSE) of 0.91, in contrast to the baseline simulation's 0.73 NSE during peak streamflow periods. The study also explores cold land hydrological processes, particularly those related to snowmelt-driven streamflow. In addition to streamflow, two land surface variables such as snowpack and soil moisture are assessed against in-situ snowpack and satellite-based soil moisture observations in the Yellowstone River Basin. The comparisons reveal that the peak of soil moisture is mainly driven by springtime snowmelt and diminishes in the summer. The findings are confirmed by both land surface model simulations and satellite-borne soil moisture observations. Another noteworthy discovery is that soil infiltration properties in the Yellowstone River Basin are wetter than the western Continental Divide in North America, resulting in amplified streamflow in the eastern side despite similar levels of snowmelt runoff on either side of the Continental Divide in the upper Colorado Rockies in the United States. [ABSTRACT FROM AUTHOR]

Obtaining precise and detailed precipitation data is crucial for analyzing watershed hydrology, ensuring sustainable water resource management, and monitoring events such as floods and droughts. Due to the complex relationship between precipitation and geographic factors, this study divides the entire country of China into eight vegetation zones based on different vegetation types. Within each vegetation zone, we employ a seasonally adjusted Extreme Random Trees approach to spatially downscale GPM (Global Precipitation Measurement) satellite monthly precipitation data. To validate the effectiveness of this method, we compare it with kriging interpolation and traditional global downscaling methods. By increasing the spatial resolution of the GPM monthly precipitation dataset from 0.1° to 0.01°, we evaluate the downscaled results and validate them against ground-level rain gauge data and GPM satellite precipitation data. The results indicate that the partitioned area prediction method outperforms other approaches, resulting in a precipitation dataset that not only achieves high accuracy but also offers finer spatial resolution compared to the original GPM precipitation dataset. Overall, this approach enhances the model's capability to capture complex spatial features and demonstrates excellent generalization. The resulting higher-resolution precipitation dataset enables the creation of more accurate precipitation distribution maps, providing data support for regions lacking hydrological information. These data can be used to analyze seasonal precipitation patterns and reveal differences in precipitation across different seasons and geographic regions. [ABSTRACT FROM AUTHOR]

The Hydrology of a watershed, encapsulated within the biogeophysical characteristics of upstream, midstream, and downstream regions, governs the peak discharge. Notable flooding issues have been observed in the downstream region of the Buleleng Watershed, largely attributed to land use transitions from vegetative to built-up areas. This study seeks to delineate the flood overflow zone within the Buleleng River Basin, influenced by factors such as rainfall, land use, and soil texture. Data employed in this study encompass land use maps, an 8-meter resolution Digital Elevation Model, annual rainfall records, soil texture information, and river network maps. The adopted methodology involved field survey data collection, satellite image analysis, and hydrological approach computations. Peak discharge values for the Buleleng Watershed, derived for periods of 5, 10, 25, and 5-100 years, were determined to be 426334.44, 568445.88, 603035.31, and 617379 m³/s respectively, set against a river capacity of 312748.13 m³/s. Given the substantial overflow discharge from the Buleleng River, the watershed is susceptible to flooding. The study findings indicate a progressive annual increase in flood overflow predictions, necessitating targeted interventions such as drainage management, surface runoff control, and a review of spatial permits for settlement usage, particularly within watershed conservation areas. [ABSTRACT FROM AUTHOR]

Copyright of Engineer Military Bulletin / Muszaki Katonai Közlöny is the property of National University of Public Service and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Understanding controls on the delivery of dissolved organic matter (DOM) from terrestrial to aquatic systems is key for constraining carbon balances and fluxes in boreal headwater catchments. The largest export of DOM generally occurs during intense periods of water delivery to the landscape (e.g., rain events); however, the timing and magnitude of DOM is complicated by geomorphological, hydrometeorological, and biogeochemical variability. To better assess mechanisms controlling the delivery of DOM to boreal streams, DOM was investigated in two morphologically distinct catchments of an experimental forest watershed in western Newfoundland, one dominated by low relief wetlands and the other by steep hillslopes. The DOM was compared during two fall storms of similar magnitude but contrasting moisture conditions during the autumn transition. Variable concentrations and optical character highlighted antecedent conditions are important for the delivery of DOM to boreal streams. Concentration‐discharge relationships with stream hydrograph separation analysis suggest preferential flowpaths through shallow mineral horizons as a key pathway for delivery of DOM in the hillslope dominated catchment compared to rapid input from near‐stream wetlands in the low relief catchment. Loss of DOM via preferential pathways suggests an additional mechanism for surface soil carbon loss not directly informed by lateral flow and soil hydrology, which has important implications for our conceptualization and modeling of carbon fluxes in boreal systems. These results suggest watershed scale responses of DOM in boreal headwater catchments are complex, and better linkages between catchment scale hydrology and landscape hydrobiogeochemistry are required to constrain terrestrial to aquatic carbon fluxes in boreal landscapes. Key Points: Watershed scale responses of dissolved organic matter are heterogeneic and controlled by spatially distinct and moisture dependent hydrobiogeochemical processesAntecedent conditions are important for the quality and quantity of dissolved organic matter (DOM) delivered to boreal headwatersDifferences in water routing between geomorphologically distinct boreal catchments control pathways for delivery of DOM in boreal systems [ABSTRACT FROM AUTHOR]

In our era, the rapid increase of parallel programming coupled with high‐performance computing (HPC) facilities allows for the use of two‐dimensional shallow water equation (2D‐SWE) algorithms for simulating floods at the "hydrological" catchment scale, rather than just at the "hydraulic" fluvial scale. This approach paves the way for the development of new operational systems focused on impact‐based flash‐floods nowcasting, wherein hydrodynamic simulations directly model the spatial and temporal variability of measured or predicted rainfall on impacts even at a street scale. Specifically, the main goal of this research is to make a step to move toward the implementation of an effective flash flood nowcasting system in which timely and accurate impact warnings are provided by including weather radar products in the HPC 2D‐SWEs modelling framework able to integrate watershed hydrology, flow hydrodynamics, and river urban flooding in just one model. The timing, location, and intensity of the street‐level evolution of some key elements at risk (people, vehicles, and infrastructures) are also discussed considering both calibration issues and the role played by the spatial and temporal rainfall resolution. All these issues are analyzed and discussed having as a starting point the flood event which hit the Mandra town (Athens, Greece) on the 15 November 2017, highlighting the feasibility and the accuracy of the overall approach and providing new insights for the research in this field. Plain Language Summary: In this study, we try to investigate if there is a potentiality for using a flood simulator, which usually requires a lot of time to give the final results, in order to predict, in real‐time, the flood hazard at the roads of a city. For this reason, we exploited the use of supercomputers, which significantly quickened the simulations and the meteorological forecasting given by a weather radar. According to our findings, there is merit for the proposed approach which can shift the flood awareness from generic instructions to more specific predictions, regarding the place and the time of the flood peak. Key Points: The potential of radar data and high‐performance computing two‐dimensional shallow water equation solvers at the watershed scale for impact‐based flash‐flood nowcasting system is highlightedReliable prediction of water depths within the urban area, with run time 30 times faster than real‐time using a high‐resolution gridRain resolution can affect simulated arrival times, peak and time‐to‐peak values, and street‐level prediction of the effects on a specific target [ABSTRACT FROM AUTHOR]

An accurate quantification of flow components and an understanding of water source dynamics are essential for effective water resource and quality management. However, the complexity of hydrological processes and the interference of intensive human activities pose significant challenges in precisely separating water discharge into distinct components such as surface runoff, interflow, and groundwater. The Xinanjiang (XAJ) model, a conceptual watershed hydrological model, has been developed and successfully implemented for rainfall–runoff simulations and hydrograph separations across various Chinese watersheds. While the model framework is robust, it fails to account for agricultural irrigation water withdrawals and the variations in in-stream water travel times across different hydrological regimes, introducing considerable uncertainty in simulating low-flow conditions. This study introduced modifications to the XAJ model by allowing parameter adjustments across different flow regimes and incorporating irrigation withdrawals into the runoff routing process. Utilizing a decade of hydrometeorological data (2013–2022) from the Yongan River watershed in eastern China, the modified model demonstrated improved efficiency metrics in low- and medium-flow regimes compared to the original model, with a Nash–Sutcliffe coefficient improvement from −4.43~−0.49 to 0.40~0.46, R2 from 0.21~0.36 to 0.53~0.63, and BIAS reduction from 7.60~89.08% to 2.06~12.71%. Furthermore, the modified XAJ model provided a more accurate estimation of the spatial and temporal distribution of streamflow components across sub-watersheds. The original model tended to overestimate groundwater contributions (13%) and underestimate interflow (14%), particularly in low-flow conditions. The enhanced XAJ model, thus, offers a more effective tool for identifying streamflow components, providing essential insights into hydrological processes for better management decisions.

In the humid tropics, forest conversion and climate change threaten the hydrological function and stationarity of watersheds, particularly in steep terrain. As climate change intensifies, shifting precipitation patterns and expanding agricultural and pastoral land use may effectively reduce the resilience of headwater catchments. Compounding this problem is the limited long-term monitoring in developing countries for planning in an uncertain future. In this study, we asked which change, climate or land use, more greatly affects stream discharge in humid tropical mountain watersheds? To answer this question, we used the process-based, spatially distributed Soil Moisture Routing model. After first evaluating model performance (Ns = 0.73), we conducted a global sensitivity analysis to identify the model parameters that most strongly influence simulated watershed discharge. In particular, peak flows are most influenced by input model parameters that represent shallow subsurface soil pathways and saturation-excess runoff while low flows are most sensitive to macropore hydraulic conductivity, soil depth and porosity parameters. We then simulated a range of land use and climate scenarios in three mountain watersheds of central Costa Rica. Our results show that deforestation influences streamflow more than altered precipitation and temperature patterns through changes in first-order hydrologic hillslope processes. However, forest conversion coupled with intensifying precipitation events amplifies hydrological extremes, reducing the hydrological resilience to predicted climate shifts in mountain watersheds of the humid tropics. This finding suggests that reforestation can help mitigate the effects of climate change on streamflow dynamics in the tropics including impacts to water availability, flood pulses, channel geomorphology and aquatic habitat associated with altered flow regimes. [ABSTRACT FROM AUTHOR]

The common feature of streams in steep sloping watersheds is that there is a significant change from base-flow to flash-flood; sometimes two or three orders of magnitude. In Hungary, these streams are usually ungauged, with lack of available data, and models. The watershed features both urban and natural land use conditions, but the main area is quite homogenic. This paper evaluates the impact of different model parameterizations, and rainfall duration on flash-flood events in the Morgó-creek watershed. The goal is to find the main parameters that can represent the uncertainty of a flash-flood sensitive area, and how the calibrated and determined parameters take effect on a model if these values are shifted on given intervals. [ABSTRACT FROM AUTHOR]

Climate change strongly influences the available water resources in a watershed due to direct linkage of atmospheric driving forces and changes in watershed hydrological processes. Understanding how these climatic changes affect watershed hydrology is essential for human society and environmental processes. Coupled Model Intercomparison Project phase 6 (CMIP6) dataset of three GCM's (BCC-CSM2-MR, INM-CM5-0, and MPI-ESM1-2-HR) with resolution of 100 km has been analyzed to examine the projected changes in temperature and precipitation over the Astore catchment during 2020–2070. Bias correction method was used to reduce errors. In this study, statistical significance of trends was performed by using the Man- Kendall test. Sen's estimator determined the magnitude of the trend on both seasonal and annual scales at Rama Rattu and Astore stations. MPI-ESM1-2-HR showed better results with coefficient of determination (COD) ranging from 0.70–0.74 for precipitation and 0.90–0.92 for maximum and minimum temperature at Astore, Rama, and Rattu followed by INM-CM5-0 and BCC-CSM2-MR. University of British Columbia Watershed model was used to attain the future hydrological series and to analyze the hydrological response of Astore River Basin to climate change. Results revealed that by the end of the 2070s, average annual precipitation is projected to increase up to 26.55% under the SSP1–2.6, 6.91% under SSP2–4.5, and decrease up to 21.62% under the SSP5–8.5. Precipitation also showed considerable variability during summer and winter. The projected temperature showed an increasing trend that may cause melting of glaciers. The projected increase in temperature ranges from - 0.66°C to 0.50°C, 0.9°C to 1.5°C and 1.18°C to 2°C under the scenarios of SSP1–2.6, SSP2–4.5 and SSP5–8.5, respectively. Simulated streamflows presented a slight increase by all scenarios. Maximum streamflow was generated under SSP5–8.5 followed by SSP2–4.5 and SSP1–2.6. The snowmelt and groundwater contributions to streamflow have decreased whereas rainfall and glacier melt components have increased on the other hand. The projected streamflows (2020–2070) compared to the control period (1990–2014) showed a reduction of 3%–11%, 2%–9%, and 1%–7% by SSP1–2.6, SSP2–4.5, and SSP5–8.5, respectively. The results revealed detailed insights into the performance of three GCMs, which can serve as a blueprint for regional policymaking and be expanded upon to establish adaption measures. [ABSTRACT FROM AUTHOR]

Changes in land cover (LC) are the major factors influencing the hydrological processes within a watershed. Understanding the impacts of LC on watershed hydrology is crucial for planning and predicting land resource utilization, water resources, and sustaining hydrological balance. This study assesses the hydrological responses of LC changes in the Muger watershed located in the Upper Blue Nile River Basin (UBNRB) from 1986 to 2020. We used the Soil and Water Assessment Tool (SWAT) hydrological model to investigate the effects of LC on the hydrological process. The simulations were driven by several datasets, such as watershed elevations, mean climatology, hydrology and soil datasets, and LC satellite maps for three time periods (i.e., satellite imagery taken in 1986, 2003, and 2020). We found that the key LC changes that affected hydrological parameters in the Muger watershed are changes in cultivation land, forest land, and settlement. The expansion of cultivation land and shrinkage of forest and shrub lands triggered surface runoff and a reduction in groundwater between 1986 and 2003. Additionally, settlement was identified as the primary factor contributing to increases in evapotranspiration (ET) and surface runoff. The LC changes that occurred between 1986 and 2020 reduced the average annual, wet season, and dry season streamflow. Between 2003 and 2020, surface runoff decreased by 3.71% due to the effect of land landscape restoration interventions. The outcome of the study can assist decision-makers and planners in preparing adaptable strategies under changing LC conditions within a watershed. [ABSTRACT FROM AUTHOR]

Groundwater is the primary source of water supply in Ethiopia. The study area was challenged due to increasing water demand, uneven water resource distribution, and noticeable changes in groundwater levels. The study focused on the examining of existing abstraction and future water demand scenarios on groundwater balance in the Weyib watershed using the WetSpass-M and MODFLOW-2005 models. The input datasets, such as aquifer properties, observed groundwater heads, hydrogeology, groundwater recharge, the Digital Elevation Model (DEM), and hydrological data were used. Datasets were prepared to better represent subsurface hydrology and its future demand effects evaluated using calibrated steady-state numerical groundwater modeling. The WetSpass-M and MODFLOW-2005 models depicted good performances during the simulations of groundwater recharge and groundwater budget under existing abstractions and estimated demand scenarios, respectively. The mean annual groundwater recharge estimated was 177.66 mm/year. The existing groundwater abstraction was 34,686.39, estimated short-term and long-term water demand scenarios were 72,113.61 and 93,795.57 m3/day, respectively. The upstream area has the highest groundwater head and recharge, while decreasing as it approaches the Weyib watershed outlet. During the outflow groundwater budget, the groundwater abstractions increased as expenses of river leakage and head dept. bounds increased. Moreover, the increasing groundwater withdrawal would reduce groundwater heads, and the estimated future water demand scenarios would substantially impact the groundwater budget, which would also have an impact on the watershed hydrology and ecosystem. [ABSTRACT FROM AUTHOR]

The average annual temperature, precipitation, and evaporation patterns are some of the characteristics which indicate to a globe where climate is rapidly changing. It remains uncertain regarding how this rapid climate change will impact freshwater biota; however the consequences could be absolutely catastrophic. It is urgently needed to better adapt and maintain the fragile system that comprises the Mediterranean ecosystems. Water shortages and changes in the land use can impact water quality and the watershed's ecosystem. Changes in temperature and precipitation trends can increase the intensity of land use, the increase of water depletion, and the degradation of water quality. The effects of climate change on eco hydrology change runoff, evaporation, surface storage, and soil moisture, that all have immediate effects on the biota and biodiversity of region. It is supported by studies on eco hydrological impacts on local watersheds. The spatial pattern and surface water dynamics of watershed systems are utilized as a perspective using which to examine the hydrologic consequences. The impacts of climate change on rainfall, evaporation, soil humidity, lakes level, and quality of water, habitats, species migration, biodiversity, and economies have been investigated. The potential climatic impacts on watershed ecosystems are determined by a spatiotemporal assessment of variations in temperature and precipitation projections from a multimodal ensemble. The susceptibility of a watershed changed depending over its geographic region, terrain, and human influence. As such a manner of dealing with climate change, improving watershed systems could be beneficial. Various techniques have been proposed which can protect watersheds against by the consequences of climate and land use change. Strengthening ecosystem vulnerability requires knowledge of the Eco hydrological processes. This review anticipated effects of climate change on the Eco hydrology of watershed systems in the Mediterranean and implies strategies for adaptation to create the mechanisms more responsive. [ABSTRACT FROM AUTHOR]

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Climate change affects ecosystems, agriculture, human health, forestry, and water resource availability. This study is mainly aimed at assessing the climate change effect on the water resources of the Kessie Watershed in the Upper Blue Nile Basin, Ethiopia. The updated Coupled Model Intercomparison Project Phase 6 (CMIP-6) data outputs were used. The three climate model outputs: ACESS_ESM1-5, FGOALS_g3, and GFDL_ESM4 with two shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5) scenarios, were used. The climate model output rainfall and temperature data were downscaled to the station level through bias correction. The catchment hydrology was represented by the SWAT—Soil and Water Assessment Tool—through calibration and validation. Future temperatures and rainfall change were evaluated by the Mann–Kendall trend test and Sen's slope estimator. Future climate change trend analysis and streamflow simulation were done on two time horizons: the 2050s (2041–2070) and the 2080s (2071–2100). The baseline streamflow data (1985–2014) were used as a reference. The global climate model projection data indicated mean annual precipitation and temperatures show a slight increase for the future in both scenarios for all climate model outputs. According to the SSP2-4.5 and SSP5-8.5 scenarios, respectively, mean annual precipitation is expected to increase by 5% and 4.89% in the 2050s and 10.13% and 6.8% in the 2080s based on ACCESS_ESM1-5; 4.7% and 3.8% in the 2050s and 4.3% and 4.84% in the 2080s based on FGOALS_g3; and 4.67% and 3.81% in the 2050s and 4.67% and 3.81% based on GFDL_ESM4 models data. Yearly average maximum temperature may increase by 3.62 °C and 1.87 °C in the 2050s and 3.31 °C and 2.99 °C in the 2080s based on ACCESS ESM1-5, 1.76 °C and 1.25 °C in the 2050s and 3.44 °C and 2.61 °C in the 2080s based on FGOALS-g3, and 2.15 °C and 3.83 °C in the 2050s and 1.37 °C and 2.66 °C in the 2080s based on GFDL-ESM4 model data. Similarly, the mean annual minimum temperature is also expected to increase by 2.73 °C and 1.90 °C in the 2050s and 5.63 °C and 4.52 °C in the 2080s based on ACCESS ESM1-5, 3.04 °C and 2.43 °C in the 2050s and 3.55 °C and 4.36 °C in the 2080s based on FGOALS-g3, and 2.31 °C and 3.29 °C in the 2050s, and 3.16 °C and 3.87 °C in the 2080s based on GFDL-ESM4 model data. The streamflow is also expected to increase. In the 2050s, simulated annual streamflow is expected to increase from 12.1 to 21.8% and 9.8 to 15.4% in SSP2-4.5 and SSP5-8.5, respectively, whereas in the 2080s, the change is expected to increase from 15.14 to 24.08% and 13.08 to 41% in SSP2-4.5 and SSP5-8.5, respectively. Future water resource potential of the case study watershed seems able to support irrigation and other projects. [ABSTRACT FROM AUTHOR]