ABSTRACT The lower Mahananda–Fulhar basin, located upstream of the Farakka Barrage is prone to annual flooding and the flow diversion of Mahananda towards the Fulhar played a key role intensifying those events. The long–term baseflow and monsoon flow (1940–2024) of the Fulhar and Mahananda channel, analyzed using the Mann–Kendall test statistics and Sen's slope estimator, as well as for the seasonal groundwater level (1996–2021) showed significant fluctuation since the diversion. Additionally, the flow frequency comparison based on the Flow Duration Curve (FDC), depicts the higher probability of exceeding the danger limits in the Fulhar. In the past four decades, more than 13000 hectares (∼47% of the flooded areas) of drylands are converted into seasonally flooded areas along the Fulhar channel and nearly 2000 hectares of seasonal flood cover have squeezed along the older Mahananda course. Presently, the older course largely depends on its eastern tributaries (∼85% of the total flow) even during the monsoon. However, for alleviating flood risk, newly identified seasonally flooded areas provide a basis for prioritizing interventions, including structural measures or community–based preparedness strategies. Overall, channel rearrangement caused contrasting hydrogeomorphic responses in the Mahananda and Fulhar channels, reflecting complex interactions among channel dynamics, groundwater level and flood hazards.

Forests play a key role in sustaining global water cycles by regulating precipitation partitioning, which in turn influences both water yield and ecosystem stability. Thinning is a silvicultural tool used to improve forest plantation productivity, but it is increasingly recognized as a means for water resource management. This study investigated hydrological changes following 40% thinning of tree density with contour-aligned log placement in paired headwater catchments of a Japanese cypress forest. Annual runoff in the treated catchment was 108.7 mm above the pre-thinning baseline in the thinning year (2020), followed by smaller increases of 99.7 mm, 43.7 mm, and 0.4 mm in 2021 to 2023, after which annual yields effectively returned to pre-thinning levels. Despite these temporary increases, peak discharge and storm quickflow metrics remained within the pre-thinning range. Flow duration curve analysis revealed a sustained enhancement of low-flow discharge and baseflow throughout the post-thinning period, indicating improved low-flow resilience without increased stormflow risk. These findings demonstrate that moderate thinning combined with contour felled logs can enhance water availability in plantation forests while maintaining flood protection. They also highlight the need for long-term, multi-site studies to test the persistence and generality of these low-flow benefits under varying forest and climate conditions.

Limited hydrological information in the form of discharge data on a river or watershed can hinder the process of developing water resources in the area. Based on discharge data recorded at the Sidoan Weir, site in Parigi Moutong Regency, the river has the potential to be used for various purposes, such as irrigation, micro-hydro power plants, raw water, and thus. This study aims to determine the similarity between measured discharge data and calculated discharge data on the Sidoan River, as well as to determine the reliable discharge on the Sidoan River. The data used in this study are climatological data, rainfall data, and discharge data (2011-2020), including a map of the Sidoan watershed. Evapotranspiration analysis was performed using the Modified Penman Method. Measured discharge data was used to determine the similarity with calculated discharge, which was analyzed using the F.J. Mock Method. The Flow Duration Curve (FDC) method was used to analyze the amount of reliable discharge. The results of the study show that the average evapotranspiration value ranges from 100 to 150 mm/month. The parameters used in the water availability analysis with the F.J. Mock method were watershed parameters optimized with a correlation coefficient between measured and calculated discharge of 0.78. The results of the study show that the RMSE values before and after optimization of the watershed parameters are 4.16 and 2.76, respectively. The calculation validation was performed using Mean Absolute Error (MAE). The FDC results show that the 80% - 90% reliable discharge is 0.251 m3/second - 0.150 m3/second, while the 50% reliable discharge is 0.860 m3/second. These results can provide an overview of water availability that can be used for water resource development and management

ABSTRACT In Colombia, 37.8% of land is agriculturally suitable, yet only 6% is irrigated. The Department of Cesar (CD) is experiencing 41.1% household food insecurity. This study assesses irrigated agriculture feasibility in CD by integrating land suitability, water availability, and crop demand under dry, normal, and wet conditions. A geographic information system (GIS)-based methodology combined: (1) land suitability via analytic hierarchy process (AHP), classifying 17.7% as highly suitable and 76.6% as moderately suitable; (2) water availability using the flow duration curve–Terán (FDC-Terán) model, where the 90th percentile low flow (Q90) ranged spatially from 0.01 to 0.61 L s⁻1 ha⁻1; and (3) irrigation demand simulation using AquaCrop for staple crops (maize, beans, rice, cassava). Demand varied from 0.2–1.9 L s⁻1 ha⁻1 (normal/wet years) to 2.9 L s⁻1 ha⁻1 (dry years). Just 30–56% of cultivable land (222 837 ha) is irrigable due to water scarcity, proving its critical role in irrigation planning.

Baseflow separation methods are widely applied in hydrological studies; however, they are rarely implementated in small- to medium-scale catchments in tropical monsoonal climates. Understanding baseflow dynamics in this area is essential for sustainable watershed management, especially under increasing hydrometeorological stress. This study evaluates the performance of three graphical HYSEP algorithms (Fixed Interval, Sliding Interval, and Local Minimum) applied to the Setail Watershed in Banyuwangi Regency, Indonesia. This area experiences recurrent downstream flooding and seasonal drought. Daily streamflow data from Automatic Water Level Recorders (AWLR) in Jambewangi (upstream) and Kradenan (downstream) were used as input. Calibration was performed using a trial-and-error approach in the BFI+ software to obtain the optimal parameters that best fit the observed and estimated baseflow. Model performance was assessed using coefficient of determination (R²), Root Mean Square Error (RMSE), and Flow Duration Curve (FDC) analysis. The Local Minimum algorithm demonstrated the highest R² value (up to 0.98) and the lowest RMSE (0.38) during both the calibration and validation periods, performing best overall. A high Baseflow Index (BFI) indicates that baseflow significantly contributes to total streamflow. This reflects the permeable characteristics of the watershed and its capacity to maintain discharge during the dry seasons. These findings confirm the applicability of the HYSEP method for tropical watersheds and emphasize the importance of local-scale calibration to improve model reliability and support adaptive water resource management under monsoonal climate variability.

Hydrological analysis is crucial in the planning of a Mini-Hydro Power Plant (PLTM). This study aims to examine the hydrological aspects of the Way Besai PLTM, located in Bonglai Village, Way Kanan Regency, Lampung Province. The Way Besai Mini-Hydro Power Plant (PLTM) is a runoff-river PLTM scheme located approximately 242 km north of Bandar Lampung City, Lampung Province, Indonesia. The data used include daily rainfall data from six rainfall stations, climate element data from the Radin Inten II Meteorological Station, and outflow data from the Besai PLTA. The rainfall data were analyzed for consistency using the Mass Curve method, with only three stations deemed consistent. Potential evapotranspiration was calculated using the Modified Penman method. Furthermore, the rainfall data were converted into daily discharge data using the F.J. Mock Rainfall to Runoff hydrological method. The catchment area is 449.14 km2 at the intake site and the average annual rainfall reaches 2,366 mm/year. The analysis results are used to determine the mainstay discharge (plant discharge) and the planned flood discharge through the Flow Duration Curve (FDC). Based on these results, the Way Besai Hydroelectric Power Plant is projected to have a generated power of 9.2 MW and an annual energy of 67.513 GWh resulting from the utilization of an effective water head of 67.45 m and a maximum plant discharge of 16.5 m3/second.

While hydropower is a cornerstone of global renewable energy strategies, its development in semi-arid regions remains insufficiently explored. Limited and highly variable water availability often discourages comprehensive assessments of its potential. In particular, run-of-river hydropower, despite its environmental and economic advantages, remains largely underexplored in these contexts due to its sensitivity to flow variability. This study evaluates the theoretical hydropower potential of run-of-river schemes within the semi-arid Grou watershed, a major tributary of the Bouregreg river in Morocco, with a focus on optimizing energy production under dry hydrological conditions. Hydrological modeling was applied using the Soil and Water Assessment Tool (SWAT), enabling the generation of flow-duration curves across the river network. These curves were then used to develop energy-duration curves, allowing for the identification of multiple optimal design flows. Consequently, instead of relying on a single turbine, the study explores the deployment of modular turbines per plant, each tailored to specific flow regimes, thereby expanding the range of exploitable run-of-river hydropower. Results indicate an untapped hydropower potential of approximately 32.4 MW per meter of head, with outputs of 31.5 MW, 783.3 kW, and 98.9 kW for high, moderate, and low flows, respectively. These findings highlight the feasibility of run-of-river hydropower in semi-arid regions and underscore the importance of adaptive turbine systems in enhancing sustainable energy production, specifically in water-scarce environments such as Morocco.

In Brazil, an allocation system was implemented in 1994 to regulate the use of water, considering water availability based on the hydrological characteristics of the basins. Knowing these conditions is essential for the planning and sustainable management of water resources, thereby promoting sustainable development. The current system uses minimum reference flows to define the water availability in each basin. This study analyzed different methodologies for calculating reference flows in the Iguaçu River basin, comparing the values obtained by the FDC, AFDC, and 7-day moving averages (Q7), as well as the Weibull equation. The results indicated that the flows obtained by AFDC were higher, while the lowest flow corresponded to Q7.10. The choice between these methods has a direct impact on grant management, since the adoption of Q7.10 or Q95 imposes stricter restrictions, influencing the economy and users in the region. Therefore, defining the appropriate methodology must balance water availability and user needs.

The paper presents the results of investigations into the relationship between selected water quality parameters and hydrological streamflow drought in a small river situated in the Mazovian Lowlands in Poland. As hydrological streamflow drought periods become more frequent in Poland, investigations about the relationship between flow and water quality parameters can be an essential contribution to a better understanding of the impact of low flow on the status of water rivers. Data from a three-year study of a small lowland river along with significant agricultural land management was used to analyze the connection between low flows and specific water quality indicators. The separation of low-flow data from water discharge records was achieved using two criteria: Q90% (the discharge value from a flow duration curve) and a minimum low-flow duration of 10 days. During these periods, the concentration of water quality indicators was determined based on collected water samples. In total, 30 samples were gathered and examined for pH, suspended sediments, dissolved substances, hardness, ammonium, nitrates, nitrites, phosphates, total phosphorus, chloride, sulfate, calcium, magnesium, and water temperature during sampling. The study’s main aim was to describe the relation between hydrological streamflow droughts and chosen water quality parameters. The analysis results demonstrate an inverse statistically significant relationship between concentration and low-flow values for total hardness and sulfate. In contrast, there was a direct relationship between nutrient indicators, suspended sediment concentration, and river hydrological streamflow drought. Statistical tests were applied to compare the datasets between years, revealing statistical differences only for nutrient indicators.

ABSTRACT Rising temperatures and climate change exacerbate water scarcity during dry seasons and intensify floods during wet seasons, underscoring the urgent need for integrated water resources management. One approach to addressing these challenges is to use mathematical models to predict high-and-low flow conditions. The wide variety of daily rainfall-runoff models complicates the selection of the most suitable one for practical use. This study aims to provide insight with four models: HBV-96, NAM, Sacramento, and HEC-HMS. The four models are tested using the Jiangwan River Basin in China as case study. The available hydro-meteorological data are daily rainfall, discharge, and potential evapotranspiration (PET) from 1971 to 1986. Two objective functions were utilised, such as Nash-Sutcliffe (NSE) and Kling-Gupta Efficiency in a logarithmic form (KGE’). Based on the calibration and validation results, all models meet the satisfactory standard of the objective function. Furthermore, high-and-low flow predictions were made using the maximum daily discharges of each month and the flow duration curve, respectively. The results indicate that the HBV-96 model produces the most favourable objective function value and the smallest average deviations among the evaluated models. Hence, the HBV-96 model is the best at simulating daily flow discharge for the Jiangwan River Basin.

The U.S. Environmental Protection Agency (EPA) developed the concept of Water Quality Volume (WQv) as a Best Management Practice (BMP) to treat the first 25.4 mm of rainfall in urban areas, aiming to capture approximately 90% of annual runoff. However, applying this urban-based standard—designed for areas with over 50% imperviousness—to rural regions with higher infiltration and pervious surfaces may result in overestimated facility capacities. In Korea, a uniform WQv criterion of 5 mm is applied nationwide, regardless of land use or hydrological conditions. This study examines the suitability of this 5 mm standard in rural catchments using the Hydrological Simulation Program–Fortran (HSPF). Eight sub-watersheds in the target area were simulated under varying cumulative runoff depths (1–10 mm) to assess pollutant loads and runoff characteristics. First-flush effects were most evident below 5 mm, with variation depending on land cover. Nature-based treatment systems for constructed wetlands were modeled for each sub-watershed, and their effectiveness was evaluated using Flow Duration Curves (FDCs) and Load Duration Curves (LDCs). The findings suggest that the uniform 5 mm WQv criterion may result in overdesign in rural watersheds and highlight the need for region-specific standards that consider local land-use and hydrological variability.

ABSTRACT Over coal mining catchments, reduced or interrupted river flow is particularly prominent, significantly impacting regional economic development and the environment. However, the impact of coal mining on the characteristics of ecological flows, which is of paramount importance for ensuring the catchment ecosystem sustainability, remains elusive. This study utilized the SIMHYD‐PML model (a coupled framework that combines the simulation of hydrology (SIMHYD) and Penman‐Monteith‐Leuning (PML) models) that incorporates groundwater seepage to assess the impact of coal mining on ecological flow in the Huangfuchuan and Gushanchuan catchments located in the Loess Plateau, where intensive coal mining occured. The results revealed that coal mining caused a reduction of ~40% in the runoff volume and a downward shift in the flow duration curve in both catchments. Besides, after the coal mining, there was a strong decrease in the frequency and the intensity of high‐flow events, while the low‐flow event frequency and intensity markedly increased, resulting in an increase in ecological deficit but a decrease in ecological surplus. Specifically, the occurrence of high‐flow events in the Huangfuchuan and Gushanchuan has decreased from 1825 to 410, and 1825 to 119, respectively, while the number of low‐flow events increased from 2190 to 5169, and 2190 to 6864, respectively. With the increase in coal mining, both the quantity and magnitude of ecological surplus gradually decrease, while those of ecological deficit steadily increase. The ecological health statuses of both catchments were relatively poor and tended to further deteriorate. Specifically, the change in the hydrological indicator due to coal mining activities was moderate (40.2%) in the Huangfuchuan, but became somewhat severe (75.2%) in the Gushanchuan. This study enhances our understanding of the impacts of coal mining on ecological flow, which provides guidelines for sustainable water resources management and utilization of coal resources.

The construction of a dam significantly alters downstream flow characteristics, often analyzed through changes in flow–duration curves before and after construction. Typically, post-dam flow–duration curves exhibit increased probabilities in low-flow zones and decreased probabilities in high-flow zones, primarily influenced by reservoir operation methods (ROMs). This study introduces a Bayesian framework to replace ROM simulations for predicting downstream flow–duration curve changes after dam construction, mainly during the flood season. Within this framework, inflow data are treated as random variables, and the ROM is analogized to a likelihood function in Bayesian analysis. The key challenge lies in deriving a likelihood function that mimics the given ROM. The Rigid ROM, a hybrid of constant rate and constant magnitude ROMs commonly used in the Republic of Korea, is targeted in this study. Using hourly inflow data from the Republic of Korea’s Andong Dam (2010–2019), the proposed Bayesian method produces flow–duration curves closely matching simulation-based results, validating its accuracy. Furthermore, the method’s ability to seamlessly handle multi-dam systems in a series highlights its practical advantage, attributed to the iterative nature of Bayesian updates. This study underscores the Bayesian approach’s potential for efficient and robust flow–duration curve modeling in complex hydrological systems.

Modelling Flow Duration Curve for Upper Cauvery Basin

In the Amazon, nearly one million people remain without reliable access to electricity. Moreover, the rural electricity grid is a mostly single-phase, ground-return type, with poor energy quality and high expenses. This study examines very low-head micro-hydropower (MHP) sites in the Amazon, emphasizing the integration of multiple axial-flow turbines. It includes an analysis of flow duration curves and key curves, both upstream and downstream, to design an MHP plant with multiple units targeting maximized energy yield. The presence of multiple turbines is crucial due to the substantial annual flow variation in the Amazon rivers. One contribution of this work is its scalable framework for ultra-low-head and high flow variability in small rivers, which is applicable in similar hydrological configurations, such as those typical of the Amazon. The design applies the minimum pressure coefficient criterion to increase turbine efficiency. Computational Fluid Dynamics (CFD) simulations forecast turbine efficiency and flow behavior. The CFD model is validated using experimental data available in the literature on a similar turbine, which is similarly used in this study for cost reasons, with discrepancies under 5%, demonstrating robust predictions of turbine efficiency and head behavior as a function of flow. This study also explores the implications of including inlet guide vanes (IGVs). We use a case study of a small bridge in Vila do Janari, situated in the southeastern part of Pará state, where heads range from 1.4 to 2.4 m and turbine flow rates span from 0.23 to 0.92 m3/s. The optimal configuration shows the potential to generate 63 MWh/year.

ABSTRACT Long-term hydrological information is essential for planning and monitoring of water resources, especially given the challenges posed by the low density and insufficient spatial coverage of hydrometeorological networks. The goal of this study is to delineate homogeneous regions and predict the flow duration curve (FDC) at ungauged basins by applying regionalization approaches to assess streamflow. A current study introduced an application of the simple Tyler skill score (STSS) technique to ensemble the output of regionalization approaches, i.e., artificial neural network (ANN), inverse distance weightage (IDW) and stepwise regression (SWR) for better predication of hydrological information. The results indicate that the STSS ensemble approach outperforms individual methods, achieving the highest accuracy with a Nash–Sutcliffe Efficiency (NSE) of 0.78, R2 of 0.89, and PBIAS of −3.5%. The RMSE-observations Standard deviation Ratio (RSR) value of 0.40 confirms its superior predictive capability compared to ANN (RSR = 0.53), SWR (RSR = 0.67), and IDW (RSR = 0.80). Furthermore, the Volume Error (%) was lowest for STSS (−2.0%), demonstrating its effectiveness in streamflow volume accuracy. These results establish STSS as a robust, model-independent regionalization technique suitable for hydrological estimation in data-scarce regions. The findings are highly relevant for water resource management, flood prediction, and hydropower planning in ungauged basins.

Estimation of standardized flow Duration curve for gauged and ungauged basins

Mapping and understanding the hydrological dynamics of non-perennial rivers (NPRs) is critical for their conservation and management, yet current methodologies often fail to capture the spatial and temporal complexities of flow intermittency and dry riverbed extension. Leveraging advancements in satellite remote sensing, the RIVERTEMP Erasmus+ project develops an innovative web platform that analyzes Sentinel-2 multispectral imagery to classify NPR hydrological conditions. These data allow for the analysis of rivers with an active channel width larger than 40 m and not covered by vegetation. Through the visual interpretation of false-color images, derived from the SWIR, NIR, and RED bands, the platform allows users to identify the hydrological condition of the river, distinguishing between three main hydrological condition a NPR can present: the ‘Flowing (F)’ condition, characterized by continuous surface flow; the ‘Ponding (P)’ condition, characterized by ponds of water that are not connected to each other; and the Dry (D)’ condition, in which the river is completely without surface water. the ‘Flowing (F)’ condition, characterized by continuous surface flow; the ‘Ponding (P)’ condition, characterized by ponds of water that are not connected to each other; and the Dry (D)’ condition, in which the river is completely without surface water. This methodology makes it possible to generate time series that measure the frequency and duration of each condition, allowing a monitoring of rivers with an average time resolution of approximately 3-5 days in the absence of cloud cover. The tool, which is available free of charge, also includes user manuals and training material for university students. The project further integrates hydrological modeling with satellite observations, using the karst SWAT hydrological model in the Keritis River basin (Chania, Greece) as a case study. The hydrological model fills in gaps in the satellite data, providing information on flow conditions on days without imagery or when cloud cover exists. Satellite imagery classified approximately 60% of the river as "flowing" and around 40% as "ponding," with a small percentage of observations from 2023 identifying "dry" conditions. By combining modelled flow rates and satellite-derived classifications, a flow duration curve for 2019–2023 reveals significant overlap between the three hydrological conditions (Fig. 1), underscoring strong interannual variability in the relationship between modelled flow rate and the hydrological condition. Therefore, an annual basis approach was preferred to determine the threshold flow values representing the transition from one hydrological condition to another. Time-series analyses highlight notable annual variability in hydrological behavior, further supported by ternary plots showing hydrotype classifications. Both hydrological modeling and satellite observations consistently place the river reaches within the intermittent-fluent area, demonstrating strong agreement between methods. The analysis reveales a clear temporal pattern transitioning from intermittent-fluent hydrotype to intermittent-stagnant one, indicating significant changes in the river's hydrological regime (Fig. 2). This integration demonstrates that satellite-derived classifications effectively validate hydrological model predictions, while models can extrapolate hydrological conditions in the absence of satellite data. The research highlights the potential of combining remote sensing and hydrological modeling to enhance the monitoring and management of NPRs, offering robust tools to address existing data limitations.

Accurate high-resolution runoff predictions are essential for effective flood mitigation and water planning. In hydrology, conceptual models are preferred for their simplicity, despite their limited capacity for accurate predictions. Deep-learning applications have recently shown promise for runoff predictions; however, they usually require longer input data sequences, especially for high-temporal resolution simulations, thus leading to increased model complexity. To address these challenges, this study evaluates the robustness of two novel approaches using Long Short-Term Memory (LSTM) models. The first model integrates the outputs of a simple conceptual model with LSTM capabilities, while the second model is a stand-alone model that combines coarse and fine temporal inputs to capture both long and short dependencies. To ensure accuracy and reliability, we utilized a century-long meteorological dataset generated from a sophisticated physics-based model, eliminating any influence of measurement errors. The training phase employed multiple sub-periods ranging from 7- to 50-year, with a separate 50-year subset for validation. Our findings highlight the consistent improvement of both LSTM models with increasing training dataset lengths, while conceptual models show no notable enhancement beyond 15 years of training data. Both LSTM models demonstrate superior performance in capturing the reference flow duration curve, offering a promising pathway for more computationally efficient models for runoff predictions.

ABSTRACT Globally, human-induced hydrological alterations have impacted the transport of hydrological fluxes. These hydrological modifications have changed the amount, frequency, and duration of natural river flows. This study examines the impacts of human activities, specifically the development and operation of large-scale infrastructures, in the Godavari basin, India’s largest peninsular basin. We used 50-year annual water discharge and suspended sediment load in hydrological data analysis, e.g. percentage changes in mean values and flow duration curve analysis. Our findings indicate that dam construction in central Godavari areas is the leading cause of a substantial reduction in suspended sediment load (−62.1%). In addition, undammed smaller tributaries have greatly mitigated the adverse effects of dams and reservoirs during high flows. In addition, continuous constructions of barrages in the downstream regions between Perur and Polavaram have substantially reduced the amount of suspended sediment transport to the downstream deltaic regions.