Hydrological Processes最新文献

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.

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.

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 m³ 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.

Assessing riparian ecosystem water use, particularly transpiration from vegetation and evaporation from soils (‘plant water use’, hereafter), is key to developing sound water management approaches. In western North America, a multidecadal drought is reducing water availability and increasing the use of detailed water budgets. Questions related to both removal of vegetation for water salvage and budgeting water to maintain valuable riparian areas have led to a wealth of studies on riparian plant water use across dryland river systems in North America. Towards evaluating broad patterns in riparian plant water use, we synthesise results from over two decades of research, with the goal of informing water management policies and planning. This study asks: (1) Do some riparian plant communities exhibit lower plant water use than others? (2) Do riparian plant communities have higher water use under hotter climates? (3) Can statistical models based on existing data, plant communities and climate data be used to predict water use for unmeasured locations? Using hierarchical Bayesian models to synthesise data on annual and daily-scale plant water use, we show that marshes, cottonwood-willow stands and tamarisk not impacted by biocontrol use larger amounts of water at the annual scale than other vegetation communities. All plant communities have higher annual water use in hotter climates, which is likely related to a longer growing season and higher evaporative demand. Statistical models based on existing water-use data, plant communities and climate provide bounds on plant water use that can be applied to unmeasured locations and used to evaluate the effects of plant community change on water use. This synthesis produces the most complete summary of riparian plant water use in North American drylands to date and provides water use predictions across different climate and community scenarios that can be used for current and future conditions.

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.