Search Results (70)

High Mountain Asia (25–40° N, 70–100° E) plays a critical role in sustaining water resources for nearly two billion people; however, the accurate estimation of precipitation remains challenging. Numerous gridded products have been developed, yet their performance across the region remains uncertain and is often analyzed only over small areas or short periods. This study provides a comprehensive evaluation of five major gridded precipitation datasets (ERA5, HARv2, GPCC, APHRODITE, and PERSIANN-CDR) over 1983–2007 throughout the entire domain through spatial intercomparison, validation against ground stations, and assessment against observed river discharge. Results show that reanalysis products (ERA5, HARv2) better capture spatial precipitation patterns, particularly along the Himalayas and Kunlun range, with HARv2 more accurately representing elevation-dependent gradients. Gauge-based (GPCC, APHRODITE) and satellite-derived (PERSIANN-CDR) datasets exhibit smoother fields and weaker orographic responses. In catchment-scale evaluations, reanalysis shows a superior performance, with ERA5 achieving the lowest bias, highest Kling–Gupta Efficiency, and best water-balance consistency. GPCC and PERSIANN-CDR underestimate discharge, and APHRODITE performs worst overall. No single dataset is optimal for all applications. Gauge-based datasets and PERSIANN-CDR are suitable for localized climatology in well-instrumented areas, while reanalysis products offer the best compromise between spatial realism and hydrological consistency for large-scale modelling in high-altitude regions where observations are limited. Full article

This study investigates the recent changes in the relationship between annual precipitation, mean annual air temperature, mean annual river discharge, and annual runoff coefficients in two small, neighboring continental catchments in Slovenia and Croatia: the Sutla/Sotla and Krapina River basins. Analyses of discharge, precipitation, and temperature time series were conducted on an annual scale using simple linear regression, multiple linear regression (MLR), and multiple log-linear regression (MLLR). Despite their geographical proximity and similar climatic conditions, the two basins exhibit markedly different runoff coefficients. Lower values observed in the Krapina River at Kupljenovo likely reflect gentle slopes, permeable soils, dense vegetation, and significant infiltration losses, while higher runoff coefficients at the Sutla River near Rakovec suggest more rapid surface runoff, reduced infiltration, and potentially distinct land use. In both basins, a pronounced rise in mean annual air temperatures has been evident since 1992, followed approximately eight years later by a sharp decline in mean annual flows and annual runoff coefficients. Our results show that the influence of air temperature on both discharge and runoff coefficients has become significantly stronger in recent decades, especially since the year 2000, contributing to a notable decline in mean annual discharges as well as annual runoff coefficients. Mean annual discharges have decreased by 19% in the Sutla and 15% in the Krapina basin, coinciding with temperature increases. Regression analyses confirm that air temperature has become a dominant negative predictor of discharge and runoff, with its influence intensifying over the past two decades. The runoff coefficient declined from 0.483 to 0.394 in the Sutla basin and from 0.325 to 0.270 in the Krapina basin during the same period. These findings highlight the importance of catchment-specific assessments for understanding and managing the localized impacts of climate change on hydrological processes. However, future work should incorporate evaporation as a key variable to better attribute the observed runoff reductions. Full article

Despite increasing concerns over recurrent phosphorus (P) pollution, the Ju River—a small tributary of the Yangtze River—has received limited scientific attention. To correct this, the present study integrates field-based observations with the Hydrological Simulation Program—FORTRAN (HSPF) model to comprehensively assess the conjunct effects of urban expansion and changing precipitation patterns on watershed hydrology and phosphorus dynamics at the small-catchment scale. A total of five urban expansion scenarios and three precipitation enhancement scenarios were simulated to capture both seasonal and event-driven variations in daily discharge and total phosphorus (TP) concentrations. The model was calibrated and validated using in situ water quality data, ensuring high reliability of the simulations. The results indicate that agricultural non-point sources are the primary contributor to total phosphorus (TP) loads. During the overlapping period of intensive farming and heavy rainfall (June–July), TP concentrations more than doubled compared to other months, with these two months accounting for over 70% of the annual TP load. Urban expansion significantly amplified hydrological extremes, increasing peak discharge by up to 224% under extreme rainfall, thereby intensifying flood risks. Although increased precipitation diluted TP concentrations, it simultaneously accelerated overall phosphorus export. This study offers a novel modeling–monitoring framework tailored for small watersheds and provides critical insights into how land use transitions and climate change jointly reshape nutrient cycling. The findings support the development of targeted, scenario-based strategies to mitigate eutrophication risks in vulnerable river systems. Full article

Accurate streamflow modeling in data-scarce catchments remains a significant challenge due to the limited availability of historical records. Transfer Learning (TL), increasingly applied in hydrology, leverages knowledge from data-rich catchments (sources) to enhance predictions in data-scarce catchments (targets), providing new possibilities of hydrological predictions. Most existing TL approaches pre-train models on large-scale meteoro-hydrological datasets and show good generalizability across multiple target catchments. However, for a specific target catchment, it remains unclear which source catchments contribute most effectively to the accurate prediction. Including many irrelevant sources may even degrade model performance. In this study, we investigated how source catchment selection affects TL performance by employing similarity-guided strategies based on three key factors, i.e., spatial distance, physical attributes, and flow regime characteristics. Using the CAMELS-GB dataset, we conducted comparative experiments by pre-training the networks with different ranked groups of the source catchments and fine-tuning them on three target catchments representing distinct hydrological environments. The results showed that carefully selected small subsets (fewer than 40, or even as few as 10) of highly similar catchments can achieve comparable or better TL performance than using all 668 available source catchments. All three target catchments yielded better NSE results from source catchments with closer spatial proximity and more consistent flow regimes. The TL performance of physical attribute similarity-based selection varied depending on the attribute combinations, with those related to land cover, climate, and soil properties leading to superior performance. These findings highlight the importance of similarity-guided source selection in hydrological TL. In addition, they demonstrate ways to reduce computational costs while improving modeling accuracy in data-scarce regions. Full article

Accurate streamflow forecasting at fine temporal and spatial scales is essential to manage the diverse hydrological behaviors of individual catchments, particularly in rapidly responding mountainous regions. This study compares three forecasting models ARIMAX, LSTM, and HEC-HMS applied to the Posina River basin in northern Italy, using 13 years of hourly hydrological data. While recent literature promotes multi-basin LSTM training for generalization, we show that a well-configured single-basin LSTM, combined with a rolling forecast strategy, can achieve comparable accuracy under high-frequency, data-constrained conditions. The physically based HEC-HMS model, calibrated for continuous simulation, provides robust peak flow prediction but requires extensive parameter tuning. ARIMAX captures baseflows but underestimates sharp hydrological events. Evaluation through NSE, KGE, and MAE shows that both LSTM and HEC-HMS outperform ARIMAX, with LSTM offering a compelling balance between accuracy and ease of implementation. This study enhances our understanding of streamflow model behavior in small basins and demonstrates that LSTM networks, despite their simplified configuration, can be reliable tools for flood forecasting in localized Alpine catchments, where physical modeling is resource-intensive and regional data for multi-basin training are often unavailable. Full article

Extreme rainstorms are difficult to predict and often result in catchment-scale rainfall flooding, leading to substantial economic losses globally. Enhancing the numerical computational efficiency of flood models is essential for improving flood forecasting capabilities. This study presents an integrated hydrological–hydrodynamic model accelerated using GPU (Graphics Processing Unit) technology to perform high-efficiency and high-precision rainfall flood simulations at the catchment scale. The model couples hydrological and hydrodynamic processes by solving the fully two-dimensional shallow water equations (2D SWEs), incorporating GPU-accelerated parallel computing. The model achieves accelerated rainstorm flooding simulations through its implementation on GPUs with parallel computing technology, significantly enhancing its computational efficiency and maintaining its numerical stability. Validations are conducted using an idealized V-shaped catchment and an experimental benchmark, followed by application to a small catchment on the Chinese Loess Plateau. The computational experiments reveal a strong positive correlation between grid cell numbers and GPU acceleration efficiency. The results also demonstrate that the proposed model offers better computational accuracy and acceleration performance than the single-GPU model. This GPU-accelerated hydrological–hydrodynamic modeling framework enables rapid, high-fidelity rainfall flood simulations and provides critical support for timely and effective flood emergency decision making. Full article

In this study, we conducted a comprehensive analysis of surface water area changes in 9235 small and medium-sized reservoirs across China from 1985 to 2021. Using Landsat and Sentinel-2 satellite data, our investigation delved into the spatiotemporal changes in these reservoirs and explored reservoir-based droughts. Using a robust algorithm, we examined the spatial and temporal patterns of surface water area (SWA) change on a national scale. While cumulative SWA remained stable at the national level, our analysis revealed diverse variations in individual catchments. To improve our understanding of reservoir-based hydrological drought, we introduced the Standardized Area Index (SAI). This index serves as a metric for quantifying drought severity and reveals a distinct north–south divide in China. The study shows that water-scarce northern regions experience prolonged and severe droughts, necessitating increased conservation efforts. Conversely, the water-rich southern region prioritizes increasing reservoir capacity. Our findings underscore the importance of small and medium-sized reservoirs in shaping China’s water resources landscape. Furthermore, this study provides valuable insights into the nuanced characteristics of droughts, facilitating the development of regionally tailored water management strategies. Full article

Urban vegetation has an essential role in maintaining the hydrological and energy balance. These processes in urban areas have been long overlooked due to the fragmentation and uneven feature of land use and vegetation distribution. Recent advances in remote sensing and the ease of data acquisition have allowed a more precise mapping of vegetation and land cover, making it possible to simulate the above processes at micro scales. This research selects a small typical residential catchment in Japan as the study area and the purpose of this research is to investigate the impact of urban vegetation on mitigating urban runoff and the heat island effect. The remote-sensed Normalized Difference Vegetation Index (NDVI) data were used to represent vegetation spatial distribution and seasonal variation. A single layer canopy model and the Storm Water Management Model were coupled to simulate interception, evapotranspiration, and runoff generation processes. The effects of vegetation amount and landscape patterns on the above processes were also considered. The results showed that the coupled model had a satisfactory performance in the modeling of these processes. When the vegetation amount was set to 1.4 times its original value, the summer total runoff had a 10.7% reduction and the average surface temperature had a 2.5 °C reduction. While the vegetation amount was 0.8 times its original value, the total runoff increased by 6%, and the average surface temperature in summer increased by 1.5 °C. The combination of green roof and dense street trees showed the best mitigation performance among the different landscape patterns. The results of this study could be used as a reference for future green infrastructure development in areas with similar climate and vegetation characteristics. Full article

Climate change is increasing air temperatures and altering the precipitation and hydrological regime on a global scale. Challenges arise when assessing the impacts of climate change on the local scale for water resource management purposes, especially for low-mountain headwater catchments that not only serve as important water towers for local communities but also have distinct hydrological characteristics. Until now, no low-flow or hydrological drought studies had been carried out on the Lauter River. This study is unique in that it compares the Lauter River, a transboundary Rhine tributary, with a nearby station on the Rhine River just below its confluence at the French–German border. The Lauter catchment is a mostly natural, forested catchment; however, its water course has been influenced by past and present cultural activities. Climate change disturbances cascade through the hydrologic regime down to the local scale. As we are expecting more low-flow events, the decrease in water availability could cause conflicts between different water user groups in the Lauter catchment. However, the choice among different methods for identifying low-flow periods may cause confusion for local water resource managers. Using flow-rate time series of the Lauter River between 1956 and 2022, we compare for the first time three low-flow identification methods: the variable-threshold method (VT), the fixed-threshold method (FT), and the Standardized Streamflow Index (SSI). Similar analyses are applied and compared to the adjacent Maxau station on the Rhine River for the same time period. This study aims at (1) interpreting the differences amongst the various low-flow identification methods and (2) revealing the differences in low-flow characteristics of the Lauter catchment compared to that of the Rhine River. It appears that FT reacts faster to direct climate or anthropogenic impacts, whereas VT is more sensitive to indirect factors such as decreasing subsurface flow, which is typical for small headwater catchments such as the Lauter where flow dynamics react faster to flow disturbances. Abnormally low flow during the early spring in tributaries such as the Lauter can help predict low-flow conditions in the Rhine River during the following half-year and especially the summer. The results could facilitate early warning of hydrological droughts and drought management for water users in the Lauter catchment and further downstream along some of the Rhine. Full article

Rain gardens are used to solve urban problems related to the negative impact of stormwater. (1) Scientific contributions from different countries provide general guidelines for the design and operation of rain gardens in different geographical areas. Given the small spatial scale of rain gardens, the use of existing infiltration models often leads to design errors. (2) The purpose of this paper is to develop a hydrological model by introducing a system of equations that extends the ability to calculate the rate, flow rate and time of saturation of layers with moisture and rainwater leakage from the rain garden system. (3) The results obtained allow us to describe the dynamic processes of passage and saturation of layers of the rain garden at a certain point in time, which extends the ability to calculate the flow rate. It was established that the smaller the area of the rain garden compared to the area of the catchment basin, the faster it reaches its full saturation. Increasing the thickness of the rain garden layers allows for an increase in the efficiency of water retention at a lower value of the area ratio. (4) The practical significance of the results obtained is especially important for the correct description of hydrodynamics in the system and determining the optimal conditions for the effective functioning and management of the rain garden structure for any climatic region. Full article

Sustainable rainwater management may counteract the effects of climate change and significantly improve the distorted water balance in urbanized catchments. However, despite the hydrologic advantages of rainwater management, acceptance and willingness-to-pay in the local society are required. This paper presents an assessment of the financial aspects, i.e., the cost-efficiency and economic feasibility, of various designs of rainwater management for a small-scale urban housing community in Lublin, Poland. The research was performed for a housing community covering approx. 1.38 ha and five multi-family residential buildings. The proposed designs covered rainwater harvesting systems, supported with extensive green roofs, with rainwater retained in underground or above-ground reservoirs, used with variable demand for watering the green areas and for underground parking lot flushing. For each designed variant, the investment as well as operation and maintenance costs were estimated. The assessment of the cost-efficiency and profitability of the proposed rainwater management systems was based on three indicators: Dynamic Generation Costs, Payback Period and Benefits–Costs Ratio. The performed calculations showed that only two designs, utilizing above-ground rainwater reservoirs, could be assessed as economically profitable. Thus, local communities may be unable to financially sustain investments in sustainable rainwater management, so it seems that financial support is required. Full article

This paper analyzes the temporal evolution of streamflow for different rivers in Argentina based on information quantifiers such as statistical complexity and permutation entropy. The main objective is to identify key details of the dynamics of the analyzed time series to differentiate the degrees of randomness and chaos. The permutation entropy is used with the probability distribution of ordinal patterns and the Jensen–Shannon divergence to calculate the disequilibrium and the statistical complexity. Daily streamflow series at different river stations were analyzed to classify the different hydrological systems. The complexity-entropy causality plane (CECP) and the representation of the Shannon entropy and Fisher information measure (FIM) show that the daily discharge series could be approximately represented with Gaussian noise, but the variances highlight the difficulty of modeling a series of natural phenomena. An analysis of stations downstream from the Yacyretá dam shows that the operation affects the randomness of the daily discharge series at hydrometric stations near the dam. When the station is further downstream, however, this effect is attenuated. Furthermore, the size of the basin plays a relevant role in modulating the process. Large catchments have smaller values for entropy, and the signal is less noisy due to integration over larger time scales. In contrast, small and mountainous basins present a rapid response that influences the behavior of daily discharge while presenting a higher entropy and lower complexity. The results obtained in the present study characterize the behavior of the daily discharge series in Argentine rivers and provide key information for hydrological modeling. Full article

As an erosion dynamic index considering the three elements of flood, runoff erosion power (REP) can better reflect the influence of precipitation, underlying surface, and other factors on the erosion and sediment transport (ST) of flood events. Therefore, it is of great significance to study the variation characteristics of the REP and its relationship with ST in the basin for soil erosion control. In this paper, the Fujiang River Basin (FRB) was selected to analyze the characteristics of runoff and ST at four hydrological stations in the basin from 2009 to 2018, including Santai, Jiangyou, Shehong, and Xiaoheba. Combined with the concept of the REP, six kinds of water–sediment relationship were compared and analyzed. Furthermore, by constructing the SWAT model, the spatial distribution characteristics of runoff, ST, and REP in the FRB were analyzed in depth, and the spatial scale effect of the REP in the basin was explored. The conclusions are as follows: (1) The power function relationship between REP and sediment transport modulus (STM) is better than the other five kinds of water–sediment relationship. (2) Based on the SWAT model, the evaluation indexes of the monthly runoff and ST of the four hydrological stations are credible, good, and excellent in the rating period (RP) and the validation period (VP). (3) The annual REP in the main stream from upstream to downstream is mostly a single change trend, while in each primary tributary, the overall value is larger than that of the main stream and the interannual difference is obvious. The average annual REP generally shows the distribution characteristics of ‘large at the junction of the upper and middle reaches and small in the rest of the area’. With the increase in the control area, the multi-year average REP has a decreasing trend, especially when the catchment area above the sub-watershed is >7318 km²; the change of the multi-year average REP is single and obviously slows down, with an average value of 23.8 mm·m³·s⁻¹·km⁻². Full article

Event flow characteristics were evaluated based on temperature and level of stream water in 22 forested catchments (area: 13.2–281.4 ha) to investigate sustainable flood management measures. Temperature and stream water levels were during 346 rainfall events in the summer season (July–September) from 2020 to 2022. Rising stream water levels responded to falling stream water temperature between ≤100 and >100 ha forested catchments in two types of time of concentration. Stream water temperature decreased by 3.0 °C when the stream water level increased by up to 0.9 m during rainfall events. Falling stream water temperature at two types of time of concentration was negatively correlated with total precipitation and rising stream water level. Based on the relatively high value of regression and cumulative frequency distribution, the estimated rising stream water level was appropriate in small catchments (≤100 ha) when the stream water temperature decreased, and the stream water level increased during rainfall events. Rising stream water levels and falling stream water temperatures are responses to catchment-scale effects, which are influenced by the nature and rapidity of the hydrological responses. Therefore, the results of the present study indicate that spatial and temporal differences in thermal responses of stream water temperature to water levels were controlled by catchment-scale effects under rapidly changing rainfall. Full article

On the Korean Peninsula, the Imjin River is a transboundary river that flows from North Korea into South Korea. Therefore, human intervention activities in the upstream region can have a substantial impact on the downstream region of South Korea. In addition to climate impacts, there are increasing concerns regarding upstream man-made activities, particularly the operation of the Hwanggang dam located in the territory of North Korea. This study explored the feasibility of using the publicly available global hydrological model and satellite remote sensing imagery for monitoring reservoir dynamics and assessing their impacts on downstream hydrology. “Naturalized” streamflow simulation was obtained from the Group on Earth Observation (GEO) Global Water Sustainability (GEOGloWS) European Centre for Medium-Range Weather Forecasts (ECMWF) Streamflow Services (GESS) model. To correct the biases of the GESS-based streamflow simulations, we employed quantile mapping using the observed streamflow from a nearby location. This method significantly reduced volume and variability biases by up to 5 times on both daily and monthly scales. Nevertheless, its effectiveness in improving temporal correlation on a daily scale in small catchments remained constrained. For the reservoir storage changes in the Hwanggang dam, we combined multiple remote sensing imagery, particularly cloud-free optical images of Landsat-8, Sentinel-2, and snow-free Sentinel-1, with the area–elevation–volume (AEV) curves derived from the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM). In assessing its hydrological impacts, the study found that overall impacts within the downstream catchment in Pilseung bridge of South Korea were generally less significant compared to the upstream Hwanggang catchment. However, there was a higher probability of experiencing water shortages during wet months due to the upstream dam’s operations. The study highlights the potential benefits of utilizing the publicly available hydrological model and satellite remote sensing imagery to supplement decision makers with important information for the effective management of the transboundary river basin in ungauged regions. Full article