ABSTRACT Understanding future streamflow and changes to hydrological processes is one of the common uses of hydrological models. But the uncertainty of different warming scenarios, boundary conditions and extent of Earth System Models (ESMs) impacts how future conditions might translate into changes in hydrological processes and streamflow. We hypothesise that the coarse spatial resolution of readily available CORDEX‐CORE simulations (25 km) will either under‐ or overestimate streamflow in small, mesoscale, heterogeneous catchments (< 700 km 2 ), relative to hydrological models driven by local station data, due to the inability of projections to capture steep headwater‐valley climate gradients. Additionally, we test whether the selection of ESMs exerts a stronger influence on the sensitivity of hydrological model parameters than the choice of downscaling method. We focus on the near future (2024–2053) because projections for the far future (e.g., 2100) carry even greater uncertainty. To evaluate these hypotheses, we applied the J2000 rainfall‐runoff model to the Eerste River catchment using the Representative Concentration Pathways (RCPs) 2.6 and 8.5 scenarios for the Coupled Model Intercomparison Project Phase 5 (CMIP5) for 2006–2053. The simulations were driven by both CORDEX‐CORE ESMs as well as local climate station data to allow for performance benchmarking. The results of the application highlight the reduced skill of J2000 when driven by projected input data compared to using local station data, particularly in simulating high flows. The most likely cause of this is the inability of the coarse resolution of CORDEX‐CORE (25 km) to capture the vast differences in climate between the headwater and valley within the Eerste, which is spatially variable. Using the CORDEX‐CORE projections as input into the hydrological model, there were, however, decent representations of simulated low flows. The sensitivity analysis showed that J2000 model parameters were more influenced by the selection of the ESMs than downscaling using the Regional Spectral Models, highlighted by more sensitivity to scaling of the air capacity of the soil module. Exploratory analyses of future hydrological conditions suggest a mean annual flow reduction of 10%–22% (Q1–Q3) under RCP 2.6 compared to 8%–26% (Q1–Q3) under RCP 8.5 for the near future (2024–2053). While most (66%) projections suggest that the high flows will likewise be reduced, there is a low percentage (33%) of projections that suggest an increase in high flows under RCP 8.5 for the near future. Many of the projections suggest a further extension of the dry season (66%) and the wet season could be moved by 1–2 months later, compared to the historical conditions where June typically represents the mid‐winter period. The simulated hydrological flows suggest a reduction in baseflow and interflow, but high‐resolution projections (≈5–10 km) are required to improve the agreement in the historical projections compared to observed data.

ABSTRACT This study examines the sensitivity of mean, high and low streamflows (i.e., Q elasticity) to changes in precipitation (P) and potential evapotranspiration (PET) across South America. The response to P was further assessed by intensifying its seasonal and daily distribution, specifically by increasing (decreasing) P during wet (dry) periods and high (low) events, while maintaining the annual P volume unchanged. Simulations from a continental‐scale hydrological model indicate that Q exhibits a stronger response to increases in P than to decreases. Arid and semi‐arid regions exhibited the highest Q elasticities and amplification of changes in P and PET, whereas in humid regions these effects were lower in magnitude. PET impacts were strongest on low flows ( Q low ) in the Caatinga and on mean/high flows ( Q mean / Q high ) in Pantanal and Pampa biomes. The Q response to P depends not only on the amount of rainfall but also on how and when it occurs. Seasonal intensification reduced Q low (median −6%) and increased Q mean (+4%) and Q high (+12%), whereas daily intensification yielded −6%, +3% and +6% for Q low , Q mean and Q high , respectively, in response to a 20% alteration in P distribution. Sensitivity to seasonal P distribution scaled with baseline seasonality, and unimodal regimes exhibited larger seasonal elasticities than bimodal regimes. Overall, in seasonal regions, the seasonal redistribution of P has stronger effects on extreme flows. Accordingly, streamflow elasticity provides a quantitative framework to assess regional and biome‐specific responses to climate variability and to inform projections of hydrological change across watersheds.

ABSTRACT 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 to −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 and 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.

ABSTRACT In arid regions with limited water supplies like the Colorado River basin of the southwestern United States, flow regimes and water availability are major controls on native riparian ecosystems' resilience, persistence and function. In this paper, we share a case study that uses a long‐term dataset of topographic, vegetation and groundwater data collected over water years 2011–2021 to demonstrate how secondary channels formed during high flow events enhance groundwater‐dependent riparian ecosystem resilience, favouring native over non‐native vegetation. In the Cliff‐Gila Valley of southwestern New Mexico, channelization and levee construction between 1940 and 1980 profoundly altered the floodplain and channel of the Gila River, a Colorado River tributary. During subsequent large floods, river anastomosis (branching) left a network of secondary channels across the floodplain. Long‐term data show that these channels improve vegetation access to groundwater, facilitating regeneration and expansion of diverse native groundwater‐dependent vegetation. Data also show that even the lowest perennial flows (0.4–0.6 m 3 s −1 ) sustain rates of groundwater recession favourable to successful native riparian seedling recruitment in the topographic lows created by secondary channels. Alluvial groundwater recedes more sharply in a reach seasonally dewatered by irrigation diversions, but seepage through diversion structures and unlined ditches maintains shallow groundwater levels. This case study demonstrates that even in arid regions, robust native groundwater‐dependent riparian areas can co‐exist with human water demands when large floods can move across broad floodplains and create topographic complexity. The study also highlights the importance of long‐term datasets for documenting ecosystem resilience to floods, drought and ongoing climate change.

ABSTRACT Linear models in recession analysis have been widely used, particularly at larger scales and longer times, to make accurate predictions of streamflow recession. However, their derivation has been somewhat impenetrable until now, since water flowing out of the soil of a catchment and into streams flows out of an area, but water stored in the soil is stored in a volume. This mismatch in units, as given in Euclidean geometry, requires a relationship that has a length scale included and which makes the flow a non‐linear function of the volume. However, in percolation theory, the surface area has two terms: one that is proportional to the volume V as well as the customary Euclidean term proportional to V 1−1/ d . Here, d = 2 or 3 is used as a generalisation of 3, in case the vertical dimension of the flow in the catchment can be considered negligibly thin in comparison with the scale of the catchment heterogeneity. Then, the Euclidean term is proportional to V 1−1/2 = V 1/2 . The term linear in V must dominate at large volumes or areas in either case, since its dependence on length is to a larger power than the Euclidean surface area. Thus, identification of the principal flow paths as near the percolation threshold automatically concentrates flow across a boundary as having the same units as the interior, making Q proportional to S and d Q /d t proportional to d S /d t . The mass conservation constraint then makes d S /d t proportional to − Q in low flow regimes without P or ET, generating the ‘linear’ model, d Q /d t proportional to − Q . Results are tested against known recession constants for Iowa streams.

ABSTRACT Dynamic surface water wetting and drying are characteristic of most headwater stream networks, influencing ecological function and downstream water quality. While topography and subsurface properties have been shown to influence spatial surface water persistence, it is unclear how sensitive non‐perennial stream network flow regimes are to persistent drought conditions. To address this unknown, we monitored surface water presence and absence for three consecutive drought years at 31 locations across a 0.25 km 2 non‐perennial headwater stream network in central coastal California. We coupled these observations with landscape characteristics and climatic conditions to examine both physical and climatic drivers of spatiotemporal flow activation and persistence. We observed non‐stationarity in flow regimes throughout the stream network; reaches that were characterised by seasonal flow in 1 year became ephemeral as the drought conditions progressed. We observed declining spatial variability in surface water persistence and declining correlations between persistence and landscape attributes with ongoing drought. From year one to year three, as drought conditions intensified, correlation coefficients between surface water persistence and topographic wetness index declined from r = 0.60 to r = 0.17, stream channel slope declined from r = 0.47 to r = 0.21, profile curvature declined from r = −0.51 to r = −0.21, and elevation declined from r = −0.33 to r = −0.06. A principal component analysis suggests that, unlike prior years, flow activation events after several years of drought were more closely associated with precipitation event characteristics than antecedent storage states. This work suggests semi‐arid landscapes such as central coastal California may see shifts in the flow regimes of aquatic systems as landscape aridity intensifies with climate change. As predictive indicators of flow may shift from physical to climatic factors, the timing, intensity and frequency of individual storm events may play increasingly larger roles in driving annual‐scale flow conditions.

ABSTRACT Measurement of sediment concentrations in runoff plots has previously lacked refined quantitative operational standards specifically targeting the stirring and sampling procedures within the collection tank, often leading to substantial representativeness issues in unevenly stirred samples. Consequently, sediment concentration measurements have frequently underestimated true values, incurring significant errors. In this study, we investigated how sampling parameters (stirring time, sampling interval and sample volume) affect the accuracy of sediment concentration measurements. For the experiment, we utilised topsoil from a quaternary red soil with sediment concentrations set at 5.07, 50.72 and 101.45 g/L, at a water depth of 60 cm. Relative measurement errors were compared for different stirring times, sampling intervals and sample volumes. Additionally, three sampling methods—manual, mechanical and mechanical plus depth profile—were evaluated for sediment concentrations of 1.05, 5.07, 10.49, 50.72, 101.45 and 439.1 g/L under identical water depth conditions (60 cm). In each method, water samples were collected from the surface, middle and bottom layers of the collection tanks, then thoroughly mixed and weighed in aluminium boxes to measure the sediment concentration. The findings indicate that the impacts of the assessed sampling parameters on measurement errors stabilise at a stirring time of 180 s, a sampling interval of 0 s, and a sample volume of 800 mL. Under these conditions, the average relative errors obtained using the manual, mechanical and mechanical plus depth profile methods were 37%, 24% and 14%, respectively, with the mechanical plus depth profile method thus demonstrating the highest measurement accuracy. Notably, this study was conducted using a single soil type (quaternary red soil), which may limit the generalizability of the findings to soils with different textures (e.g., sandy or clayey soils) or physicochemical properties. On the basis of these findings, we recommend the adoption of the mechanical plus depth profile method, coupled with a precise control of stirring time, sampling interval and sample volume, to enhance the accuracy of sediment concentration measurements in collection tanks. This approach promises to provide significant improvements in the reliability and precision of sediment concentration assessments, while future research could expand to investigate multiple soil types to further validate the conclusions.

ABSTRACT Quantifying weathering‐driven carbon sinks in human‐impacted subtropical basins remains a critical gap. In the carbonate‐dominated, densely populated Xiangjiang River Basin, this study tracked hydrochemistry through two hydrological years to partition solute sources and constrain CO 2 consumption at high resolution. Findings revealed precipitation total dissolved solids (TDSs) spanning 1.7–201.4 mg/L, where Ca 2+ , K + , SO 4 2− and NO 3 − constituted the principal ionic constituents and the values for Xiangjiang River water were 25.8–183.1 mg/L, with Ca 2+ and HCO 3 − as the dominant ions. The chemical weathering contributions from carbonate rock (62.2%) and silicate rock (14.5%) were estimated using a forward model, indicating that carbonate rock weathering is the primary source of the Xiangjiang River solutes. The average annual weathering fluxes of carbonate and silicate rocks in the Xiangjiang River were 21.6 and 3.4 t/km 2 /year, respectively, with corresponding CO 2 consumption rates of 293.1 × 10 3 and 81.0 × 10 3 mol/km 2 /year. This study provides the first high‐resolution quantification confirming that the subtropical monsoon climate of the Xiangjiang River Basin generates intermediate weathering‐driven CO 2 consumption rates, positioning its carbon sink capacity between that of arid/plateau regions and tropical zones. The findings establish hydrochemical baselines for the Xiangjiang and offer quantitative benchmarks for regional water‐resource management and carbon‐cycle modelling under intensifying anthropogenic pressures.

ABSTRACT Considering the intensified floods in the tropical river basins, this study assesses the climate change‐induced flood risk accounting for the reservoir releases associated with crop damage and the monetary benefits from paddy cultivation. Using the three best‐performing Global Climate Models (GCMs) out of nine, it analyzes the flood risk for agricultural production associated with a design flood in the typical Mahanadi River delta under a retrospective and six (2010s, 2040s and 2070s; and Representative Concentration Pathways (RCP): RCP4.5 and RCP8.5) projected scenarios. Subsequently, a probable flood adaptation strategy employing alternate rice planning in the near‐future period and a selected GCM is proposed. It reveals an increased flood hazard in the mid‐century followed by a decline towards the end of the century. Prolonged duration of low flood depth leads to very high crop vulnerability to floods in the projected periods under both RCP4.5 and RCP8.5 scenarios. While a little to moderate increase in overall flood risk is depicted by the MIROC‐ESM‐CHEM model‐based predictions, the HadGEM2‐AO and IPSL‐CM5A‐MR models indicate high flood risk in the future projected periods as compared to the historical episode. An alternate agricultural planning considering the net return from crop production can serve as a potential adaptation strategy dealing with the harsh effects of extreme floods in the river delta. The advocated methodology of flood risk assessment and adaptation using hydrodynamic flood modelling with consideration of reservoir releases is one of its kind and can be implemented in any world river basin.