Accurate runoff inversion is essential for watershed hydrology and water resources management, yet traditional single-model approaches often exhibit substantial biases in complex terrain and nonlinear flow regimes. This study presents a fusion modeling framework for the Jialing River Basin, combining three individual methods—the relationship fitting method, the improved Manning’s formula, and the C/M signal method—through weighted averaging, Bagging–AdaBoost, and Stacking ensemble strategies, with linear regression as a meta-learner for multi-source feature integration. Validation using monthly data from 2015–2020 shows that the Stacking-based model achieves superior performance (Nash–Sutcliffe efficiency = 0.981; RMSE = 38.69 m 3/s; RRMSE = 5.09%), outperforming both Bagging–AdaBoost and weighted averaging. The model effectively reduces systematic errors and variance, providing stable predictions across high- and low-flow regimes. These results demonstrate that ensemble-based fusion models significantly enhance runoff reconstruction and capture flow dynamics more accurately than individual approaches. The proposed framework offers a robust, scalable tool for hydrological estimation in complex basins and has important implications for water resources management and flood mitigation.

Field measurements within ice covers during the melting period are scarce, often constrained by safety concerns leading to uncertainty in model parameterizations of ice melt. To address these limitations, a Floating Research Station (FRS) was constructed in a small subarctic lake near Yellowknife, Canada to monitor ice processes year-round. Using the FRS, the objective of this study was to delineate key processes influencing ice melt and decay through evaluating heat budget components over three melt seasons: April 1- May 31 of 2023, 2024, and 2025. Our results show that the decay process was both thermally and mechanically driven, with mechanical decay from ice collapse occurring at internal ice porosities of 0.31-0.35 and accounting for 24 - 48% of total ice loss. Thermal melt at the surface (0.6 - 2.1 cm d -1) was driven by surface heat absorption (13-160 W m -2) and losses via net longwave fluxes (-95.2 - -6.6 W m -2). Bottom melt (0.1- 0.6 cm d -1) was caused by modest mean daily water-to-ice heat fluxes (< 15 W m -2). Melt season lengths varied between 35-49 days, and break-up dates up to 16 days, and were dependent on air temperatures, albedo, and net insolation. Results from this study can be used to improve and constrain melt period parameterizations in ice models while providing needed validation and calibration data in northern, high-latitude environments.

The duration, magnitude, and frequency of heatwaves are predicted to increase in the coming decades, a combination that can reduce the survival of many fish species. Across the world, there is broad interest in identifying thermal refuge for heat-intolerant fish species and exploring opportunities to enhance or protect these areas. Because deeper groundwater maintains a relatively constant temperature, groundwater-influenced areas along streams can provide cool-water refuge for fish during periods of extreme heat. A targeted approach was developed for identifying existing cold-water zones and areas of substantial groundwater discharge in four high priority Lake Ontario tributaries. Our approach included: (1) predicting where groundwater discharge is most likely with a simple geospatial model and (2) using model predictions to select field sites for intensive high-resolution study, including ground-based mapping of groundwater features (springs, seeps, tributaries) as well as drone-based optical and thermal infrared surveys. Results from field sites were used to both verify model performance and map different types and aerial extents of thermal anomalies. Geospatial modeling successfully predicted regions of widespread groundwater upwelling, later verified and mapped by field and drone surveys. Comparison of model and field survey results further highlighted specific geospatial layers, such as soil/bedrock types and topographic wetness index, as being particularly useful for predicting groundwater influence on streams in the study area. In addition, a comparison of geospatial model results with a model of fish abundances along the studied streams showed strong correlations (Spearman’s ρ as high as 0.93) for many heat-intolerant fish species over a wide geographic area. The approach developed in this study can be applied to other watersheds to highlight areas of probable groundwater discharge and could be used by fishery and water resource managers to support cold-water fish habitat management decision-making and resource conservation.

The critical zone (CZ), extending from the vegetation canopy to unweathered bedrock, hosts coupled hydrologic, geochemical, and biological interactions that regulate soil health, water resources, and ecosystem sustainability. The subsurface CZ can extend tens of meters below the surface and is largely inaccessible, except in happenstance exposure from quarries or road cuts through mountain hillsides. Drilling and subsequent borehole sampling, monitoring and imaging reveal the importance of the deep subsurface for CZ evolution and function. However, drilling can be labor-intensive, require expensive, specialized equipment, and can only be done where the equipment can be deployed, limiting the number and placement of boreholes. To empower the next generation of critical zone scientists to employ drilling and downhole techniques, this review synthesizes emerging research objectives and methods commonly used during CZ drilling campaigns over the last 30 years. We focus on three CZ research themes: (1) physical and chemical weathering, (2) subsurface water storage and flow, and (3) solute, microbial, and gas dynamics. For each theme, we evaluate drilling techniques, sampling strategies, downhole logging approaches, long-term monitoring, and analytical methods that collectively enable diverse hypothesis-testing. We conclude by providing a vision for the future of drilling within the CZ, with a focus on novel drilling techniques aimed at recovering saprolitic material as well as borehole designs that can monitor and sample the vadose zone. Additionally, we emphasize that near-surface geophysics and data-model integration efforts are needed to expand borehole observations to the larger scales that are necessary to advance CZ science and inform ecosystem and water resource management.

Mountain catchments are key freshwater suppliers to lowland urban populations, sustaining key ecosystem services, particularly in seasonally semiarid environments where potential evapotranspiration (PET) exceeds precipitation (P) for most of the year. However, the biophysical controls that enable snow-free mountains to maintain year-round positive water yields remain poorly understood. In this study, we analyze the water yield of 25 mountain catchments along a climatic gradient of central Argentina, where monsoonal precipitation ranges from 350 to 850 mm/year. We combine long-term hydrometric records with catchment biophysical descriptors of climate, topography, land cover, morphometry and lithology to identify the main drivers of water yield and related hydrologic signatures. Observed water yields varied widely across catchments (7 to 674 mm/year) and often surpassed estimates from extensively used theoretical and empirical hydrological models (i.e. 1974 Budyko´s envelope and 2001 Zhang´s watershed synthesis, respectively), highlighting the key role of local biophysical mountain features, beyond climate, generating flow. Generalized linear models identified mean annual precipitation and the fraction of exposed rock as the strongest positive predictors of water yield, while the aridity index (PET/P), woody vegetation cover, and drainage density were negatively associated with water yield. Hydrologic signatures offered further insight into underlying processes with altitude range and herbaceous vegetation appearing to support higher baseflows. Catchments with higher aridity and woody vegetation cover showed greater dry-season water yield fractions, highlighting the importance of low flows in these systems. By contrast, in more subhumid catchments, topographic attributes such as steep slopes and valley extent emerged as dominant drivers of runoff generation, in clear contrast to the fraction of flatlands. Comparisons with adjacent lowland systems evidenced that the topography, rocky outcrops, and vegetation of the studied mountain landscapes promote the generation of significant water yields, underscoring their critical hydrological and ecological role in the region.

The Upper Minjiang River basin (UMR) is a water resource area for over 20 million inhabitants in the downstream Chengdu Plain and ecological barrier for the Yangtze River Basin in China. The recently decreasing runoff in the UMR poses serious challenges to regional water resource security, but thus to partition the contributions of climate variation and vegetation restoration on runoff variation is of great significance for regional water resource management and ecological restoration. This study utilized two Budyko-based models (Choudhury-Yang equation and Fu equation) to quantify the influences of climate variation and vegetation restoration on runoff changes in two adjacent forested watersheds in the UMR from 1982 to 2010. Our results showed that annual runoff had significant decreasing trends ( p<0.05) from 1982 to 2010 in the both watersheds, with an abrupt change point identified in 1995. Compared with the period I (1982–1994), mean annual runoff in the period II (1995–2010) decreased by 11.7% (-72.7 mm) and 17.9% (-72.1 mm) in the Heishui (HS) watershed and Zhenjiangguan (ZJG) watershed, respectively. Both models indicated that the changes in the underlying surface were the dominant factor contributing to runoff reduction in the two watersheds, followed by decreased precipitation. The changes in Ep had negligible influences on runoff declines. The two watersheds experienced vegetation restoration and exhibited greening trends from 1982 to 2010. Compared with the period I, the forest areas in the HS and ZJG during the period II increased by 10.5% and 18.9%, respectively. The changes in the underlying surface and the reduction of precipitation contributed to 60.8%–69.9% and 29.0%–38.7% of the runoff decline, respectively. This study contributes to an in-depth understanding of the mechanisms of runoff alteration in forested watershed under climate variation and vegetation restoration, and supports regional water resource management.

Surface flooding from rising sea levels is widely recognized as a coastal threat, but coastal subsurface (groundwater) flooding is often overlooked. Coastal water table rise due to sea-level rise can accelerate contaminant flow from onsite wastewater treatment systems (OWTS), decrease roadway performance, corrode below-ground infrastructure, and intensify surface flooding. The few related, existing studies were primarily local, leaving important gaps for regional coastal risk assessments. In this study, we employed existing analytical solutions for coastal water table rise within a new geospatial framework to facilitate regional risk assessments. An ArcGIS toolbox was developed to classify coastal aquifers as recharge-or topography-limited and perform the analytical calculations along a regional coastline using publicly available geospatial datasets. The analysis was conducted for Nova Scotia (13,300 km shoreline), an Atlantic Canadian province characterized by high sea-level rise and reliance on private wells and OWTS. Results highlight coastal regions expected to experience shallow groundwater and possessing vulnerable infrastructure (water table depth < 1.5 m) before and after (year 2099) projected sea-level rise. The model revealed that the most southwestern county (Yarmouth) will experience the highest percent of coastal land with groundwater flooding before (5.7%) and after (7.1%) sea-level rise. Because of differences in coastal infrastructure distribution, the Bay of Fundy (Annapolis County) coastline had the highest fraction of compromised OWTS and roadways (up to 12.8%), while the highest relative increase in compromised OWTS by 2099 was in the southeast (+115%, Shelburne County). This novel hybrid analytical-geospatial approach serves as a first-order assessment and can be used to prioritize localities for further site-specific research and inform targeted coastal development polices.

Tracer hydrology in Latin America and the Caribbean has made significant progress in recent decades, largely through the sustained support of the International Atomic Energy Agency (IAEA). Current practices show water stable isotope applications and precipitation-groundwater monitoring at the core of most networks, providing valuable insights into recharge mechanisms, groundwater to surface water connectivity, pollution tracking, and climate variability. Despite these advances, critical challenges persist, including short and fragmented monitoring records, limited capture of extreme events, restricted data accessibility, and persistent barriers related to funding, analytical capacity, and weak policy integration. Improving science communication emerges as an urgent need to transform technical findings into actionable knowledge that informs decision-makers and empowers communities. Opportunities exist to build on IAEA’s legacy by sustaining long-term networks, diversifying tracer applications, mobilizing citizen science in monitoring efforts, expanding modeling and laboratory capacity, and advocating for FAIR data sharing across end-users. Strengthened collaboration across the region, improved communication, and deeper policy engagement can elevate tracer hydrology into a pillar of regional water governance and hydro-climate resilience.

Since the 1960s, continental serpentinization environments have served as natural laboratories for investigating low-temperature aqueous geochemistry involving dissolved H 2 and CH 4, with broad implications for deep Earth elemental cycles, energy resources, and astrobiology. Despite extensive site-specific research, global comparisons of serpentinization geochemistry remain limited, largely due to the heterogeneity in sampling snapshots across serpentinizing sites. To address this gap, we compiled, homogenized, and analyzed geochemical data (aqueous and dissolved gas) from 32 studies focused exclusively on hyperalkaline spring seepage manifestations. The resulting database includes 1,866 individual measurements spanning 15 physical and chemical variables. pH is the most consistently reported parameter (90.3%), followed by water temperature and major cations (57.5%), whereas dissolved H 2 (38.1%) and CH 4 (44.4%) are less frequently documented, and Ni shows the lowest coverage (8.2%), highlighting a strong bias toward bulk chemistry over trace metals and volatiles. Because reported degrees of rock serpentinization are highly variable and inconsistently described, we normalized all variables by mean annual precipitation (mm yr -1) and grouped them by precipitation regime (tropical, temperate, arid, cold continental) to separate geochemical effects from water availability and evapoconcentration. Prior to normalization, several statistically significant differences were found in pH, oxidation-reduction potential (ORP), electrical conductivity (EC), major ions, and gas concentrations among the precipitation regimes. Tropical environments exhibited higher median values in Fe 2+/3+, Ni 2+, OH -, CO 3 2-, and dissolved CH 4. Dissolved H 2 presented the highest median values in arid and cold continental settings. The arid environment also showed the highest median values in EC and major ions (Na +, K +, Ca 2+, Cl -). Following normalization by precipitation, the differences in geochemical load per unit of water were reduced in factors such as water temperature, pH, ORP, EC, major ions, and gas concentrations, primarily across tropical, temperate, and cold continental precipitation regimes. Differences persisted in dissolved carbonate (tropical and temperate) and Fe and Ni (tropical). The arid precipitation regime resulted in notable differences across several parameters, likely due to strong surface evapoconcentration conditions under a low relative humidity environment. However, the H 2 median value remained the highest in the arid group after normalization, which highlights a potentially favorable H 2 production setting under deeper groundwater flow systems and longer residence times. In contrast, wetter serpentinizing environments with greater groundwater recharge and increase dissolved inorganic carbon, favored the occurrence of CH 4-dominated systems, most likely driven by Fischer-Tropsch type reactions, elevated dissolved carbonate, and microbial methanogenesis. Our global comparison provides a systematic synthesis and framework for identifying both common patterns and site-specific differences in low-temperature continental serpentinization, underscoring the critical influence of regional hydrology, particularly groundwater residence times and water availability, in regulating H 2 and CH 4 production. Plain Language Abstract Since the 1960s, serpentinizing environments have been investigated as natural laboratories where the interaction of groundwater with ultramafic rocks generates H 2 and CH 4. These sites are also important because they provide clues about Earth’s deep chemical cycles, possible new energy sources, and even the origins of life. Although many individual sites have been studied, global comparisons remain limited. To address this, we combined data from 32 studies of hyperalkaline springs, creating a database of 1,866 measurements that track 15 chemical and physical variables. We found that most studies consistently report water pH, temperature, and major dissolved ions, while H 2 and CH 4, and trace metals like Ni, are measured less often. When grouped by rainfall regimes (tropical, temperate, arid, and cold continental), clear differences emerged. Tropical sites showed higher CH 4 and carbonate contents, while arid sites showed greater H 2 and solute concentrations. After accounting for rainfall, many of these differences were reduced, but H 2 remained highest in arid systems. Overall, our global analysis shows that water availability strongly influences serpentinization chemistry and the balance between H 2- and CH 4-rich system

Urban expansion significantly alters the hydrological response of cities, particularly in steep-slope regions where the increase in impervious surfaces intensifies surface runoff and contributes to drainage system overload. This study evaluates the combined impacts of land cover change and rainfall spatial distribution on four urban subcatchments in Medellín, Colombia, using the EPA-SWMM model. Seven synthetic and real rainfall scenarios were developed by combining two spatial patterns, typical uniform rainfall (SP1) and rainfall concentrated in the lower subcatchment (SP2), with three levels of accumulated rainfall (R1, R2, and R3), along with a real event (SP3) derived from radar and gauge observations. Land use scenarios for the years 2012, 2018, and 2024 were derived from satellite imagery and reflect distinct urbanization trajectories in each subcatchment. Model simulations were evaluated using four key performance metrics: peak flow, runoff volume, runoff coefficient, and the percentage of overloaded nodes in the urban drainage network. Results show that SP2 scenarios produce significantly higher impacts for the same rainfall accumulation, particularly in subcatchments with greater imperviousness in the lower and flatter areas. Furthermore, increases in the metrics were more pronounced for moderate-magnitude events (R1 and R2) compared to extreme events (R3 and SP3), which showed relatively stable behavior across the years studied. A ternary diagram was used to classify total runoff into three components: infiltration, runoff from permeable areas, and runoff from impervious areas, highlighting the influence of land cover on runoff generation and the differential behavior among subcatchments. Overall, the study demonstrates the importance of accounting for both rainfall spatiality and urban expansion in hydrological impact assessments and supports the use of scenario-based modeling as a decision-making tool in urban water management, particularly in small, steep tropical urban catchments where intense rainfall and rapid runoff generation significantly increase the risk of flash flooding and infrastructure vulnerability.

\received DD MMMM YYYY \acceptedDD MMMM YYYY Groundwater supplies over 90% of Costa Rica’s drinking water and supports vital ecosystem services, yet many aquifers, especially in high-altitude headwater catchments, remain understudied. This study aimed to (i) characterize the hydrogeochemistry and isotopic composition of the Poás volcanic aquifer system (PVAS), ii) identify the key drivers controlling the chemical and isotopic evolution, and (iii) understand recharge governing processes, including mean potential recharge elevations (MREs). We hypothesize that the groundwater in the PVAS exhibits distinct geochemical and isotopic patterns (from high to low altitudes) that reflect a combination of altitude-dependent recharge and anthropogenic pollution influence. Despite the complex geological setting, the predominant facies across the PVAS were of the bicarbonate-calcic-magnesic type. Moderately high levels of nitrate and E. coli in more than 56% of the samples indicate anthropogenic pollution legacy. Isotope-inferred MREs ranged from 768 to 2,407 m a.s.l with a mean of 1,549±227 m a.s.l, overlapping a diverse land use mosaic. These findings show the high vulnerability of the PVAS to anthropogenic contamination and the strong dependency on high-elevation recharge. This information provides a valuable tool for prioritizing conservation efforts in key recharge areas and may be translated to other similar settings across the Central America Cordillera.

Climate change has increased the stress on water resources, making reliable predictions, particularly of low flows vital for sustainable management, challenging. This study evaluates 47 hydrological models in 125 catchments in the Republic of Ireland with the MARRMoT framework and uses two low-flow objective functions (inverse Kling–Gupta Efficiency and log-transformed Nash–Sutcliffe Efficiency). The results show that the moderate complexity models (e.g., GR4J, HYMOD, Collie3) performed best in both the calibration and validation periods. By comparing objective functions, the log-transformed Nash-Sutcliffe Efficiency demonstrated greater stability between the validation and calibration periods (mean difference = 0.007, SD = 0.093) compared to the inverse Kling-Gupta efficiency (mean difference = -0.204, SD = 0.233). The performance of the models was also evaluated against several catchment attributes that represent the climate, topography, land use, and hydrogeology of the catchment using the Spearman correlation coefficient. Higher model performance was generally associated with lower mean annual precipitation and higher potential evapotranspiration. Statistically significant positive correlations were also observed between model performance and catchment steepness, whereas negative correlations were found with base-flow index and reservoir storage. In general, our findings advocate for multi-objective calibration, ensemble modelling, and improved representations of the groundwater, wetlands, and urban hydrology process to improve the prediction of low flows.

Hydrologic variability is predicted to increase across much of the world in response to a changing climate and increased groundwater extraction. Because flow regime is a primary control on habitat viability for aquatic species, including non-native, native, threatened, and endangered species, our ability to understand and quantify flow regime is important for managing these changes in the future. However, predicting flow regime is difficult at ungauged sites and models that can predict flow parameters (e.g., mean annual flow, flow predictability, annual coefficient of flow) are needed. In this study, we used USGS streamflow data to calculate 10 hydrological indices at gaged sites in central Texas, USA using the Indicators of Hydrological Alteration software. Values at gauged sites were then used in conjunction with environmental parameters (climate, geology, land use, etc.) to model the same hydrological indices at ungauged sites. Models were validated using bootstrap resampling (final average R 2 of 0.76, range of 0.69 – 0.94). Cluster analysis was used to group gauged and ungauged sites into two clusters of ‘wet’ and ‘dry’ sites. ‘Dry’ sites experience systematic declines or complete cessation in discharge because of anthropogenic effects such as river water withdrawal and groundwater extraction. Regression-based regionalization for flow regime prediction improves our ability to model hydrological regimes in rivers and, specifically, in river segments lacking continuous gauge data, and to derive model variables that are key predictors required for many ecological models.

Adequate quantification of precipitation and its spatio-temporal variability is crucial for understanding the physical and biological processes within a watershed. Mountain watersheds pose particular challenges due to strong spatial heterogeneity in precipitation and typically sparse in-situ monitoring networks. The increasing availability of gridded precipitation products can help address these limitations, but their reliability at local or sub-regional scales remains difficult to assess. This study proposes a novel, process-based approach that incorporates daily streamflow data to evaluate the performance of four widely used gridded precipitation datasets (CHIRPS-v2, MSWEP-v2.8, GPCC-v2022, and TerraClimate). Five key watersheds in central-western Argentina (ca. 30–37°S) serve as case studies. The evaluation framework is based on five process-informed expectations derived from the region’s climate and topography: (a) most annual precipitation should fall as snow during winter (April–September); (b) a strong positive relationship should exist between winter precipitation and summer streamflow; (c) interannual variability of precipitation should exceed that of streamflow due to basin-scale damping effects; (d) runoff coefficients should be statistically lower than unity, reflecting mass conservation; and (e) winter precipitation should be concentrated at higher elevations. We apply simple non-parametric statistical tests to evaluate how well each dataset meets these expectations. A comparative assessment identifies the most reliable product for each watershed. Our findings show that MSWEP and TerraClimate perform best overall, particularly in capturing total precipitation and its seasonality. Other datasets fail to reproduce key hydrological signals, likely due to a lack of physically based inputs (e.g., reanalysis). Overall, this process-based, catchment-integrative evaluation offers a promising framework for assessing precipitation products in other snow-dominated mountain regions with limited ground observations, provided that the dominant hydroclimatic processes are well understood.

Riverine dissolved organic carbon (DOC) is a critical biogeochemical component that transmits information from Arctic soils to the Arctic Ocean, significantly influencing carbon dynamics in this unique ecosystem. As DOC travels downstream, it undergoes transformations that alter its composition and fate. The Yukon River serves as an effective testbed for modeling these dynamics, offering sufficient scale to capture key biogeochemical processes, simpler hydrology than other major Arctic rivers, and access to long-term DOC data for model validation. To investigate DOC transformations during transit, we adapted our Arctic Riverine Organic Macromolecular Model by applying regional-specific parameterizations. Our model simulates the transport and transformation of 15 organic macromolecules, including CDOM (Coloured Dissolved Organic Matter), proteins, polysaccharides, lipids, lignin phenols, and humic substances. Initial DOC concentrations were derived from surrounding observed soil organic carbon stocks, while chemical transformations and hydrological dynamics were modeled along the river’s course. Sensitivity and uncertainty analyses were conducted using a Monte Carlo approach under two experimental setups. Results revealed that variability in DOC and CDOM concentrations at the river mouth were predominantly driven by initial DOC concentration (~70% of variability explained) and dilution at confluence points (~10%). The refractory fraction of DOC explained 21-88% of the variability in 14 macromolecular concentrations. River velocity, which determines residence time, explained 8-47% of the variability in protein, polysaccharide, lipid, pigments, and lignin phenols at the river mouth. In contrast, chemical turnover times contributed only 1–5% to output variability. Our findings underscore the need for improved land-specific headwater observations, including seasonal soil moisture and lateral transport dynamics that control the initial tributary-specific DOC inputs. With accelerated permafrost thaw and increasing river discharge, extending our model to other Arctic River systems and seasons will enhance understanding of Arctic riverine carbon fluxes and their contributions to the Arctic Ocean.

Understanding how rainfall and snowmelt influence baseflow, the groundwater-fed component of streamflow, is essential for sound water resources management. Current approaches that aim to uncover the spatial couplings between these processes and baseflow are limited. The most commonly used methods include geochemical tracers and hydrologic models. A key limitation of the first is cost, while the second is limited by the need for simplifying assumptions. This study developed a data-driven approach which leverages satellite Earth observation data and ground-based data to assess the degree to which baseflow is influenced by upstream rainfall and snowmelt in California’s Sierra Nevada. The procedure involved: (1) separation of baseflow from streamflow time series using a low-pass filtering technique, (2) application of time series and information theory methods to identify the areas which have the greatest impacts on baseflow through both rainfall and snowmelt, and (3) characterization of the elevation zones which have a prevailing influence on baseflow. Results suggest that areas which have the strongest impact on baseflow through rainfall and snowmelt are not necessarily the areas which experience the highest annual rates of snowmelt or rainfall; snowmelt occurring in the 3000 – 3700 m elevation range was found to be the most important driver of baseflow.

Sand dams are small, reinforced barriers constructed across seasonal and ephemeral streams which trap water in sediments deposited s. For these reservoirs to provide sustainable and dependable water supplies or valuable sand for other purposes, they should primarily fill with coarse sand rather than fine sediments. Excessive accumulation of fine sediments in sand dam reservoirs limits recharge and recoverable water. We describe a novel approach to preventing the accumulation of fine sediments in sand dam reservoirs by geomorphic management of reservoir sedimentation. We propose building sand dams with outlets at the foot of the dam to selectively trap coarse sediments (>0.125 mm; Rouse number = 2.5) across a range of flows and sediment transport rates. An optimal outlet had an “Eiffel Tower” shape which maintains the desired Rouse number, ensuring finer particles will pass out of the reservoir remaining suspended, while coarser particles settle. HEC-RAS simulations confirm that these designs promote uniform coarse sediment deposition within the reservoir and perform effectively, with minimal deviation (with an MSE value of less than 1%) from the target Rouse number. Alternative circular and rectangular base cutouts were also found to provide good performance across a wide range of flows and would be easier to construct and have less impact of the strength of the dam.

Understanding rainfall partitioning and streamflow generation processes have become indispensable due to the increasing frequency of hydrological extremes globally. River catchments in the tropics are particularly vulnerable to changing characteristics of rainfall and decoding the rainfall partitioning into pre-event and event water becomes more critical in tropical catchments where runoff generation processes, are often poorly understood. In this context, the present study is aimed at understanding the runoff generation processes in Vamanapuram river – a humid tropical forested experimental catchment in the Southern Western Ghats, India utilizing high-resolution (30 min) hydrological measurements. Data from 78 and 76 storm events (during 2022 and 2023) were used for storm hydrograph separation using the conductivity mass balance method at Kallar River Gauging Station (KRGS) and Chettachal River Gauging Station (CRGS), respectively. Both KRGS and CRGS are found to be sub-surface dominated catchments irrespective of season. In 98% and 96% of the storm events respectively at KRGS and CRGS, pre-event water dominated the hydrograph.. The seasonality in the PEWF(avg) and Pre-Event Water Fraction at peak (PEWF(at peak)) has higher values in the dry period and lower values in the wet period. PEWF(avg) decreases from 0.82 to 0.80, and PEWF(at peak) from 0.76 to 0.73 from upstream to downstream reaches respectively. The beta distribution fits well the temporal variability in the PEWF(avg) and PEWF(at peak) at both river gauging stations. The effect of differential precipitation forcing in the subsequent year’s storm PEWFs has been studied, and it was observed that higher precipitation forcing results in higher PEWF at CRGS. However, the effect of precipitation forcing is not seen at KGRS, possibly due to significantly different geomorphic characteristics and higher forest cover. A more extended period of hydrological data in catchments with diverse climatic and geological settings will provide a better understanding on the effect of precipitation forcing on catchment rainfall partitioning and thus improve conceptualization of rainfall-runoff models.