Efficient flood mapping methods are needed for large-scale, comprehensive identification of flash flood inundation hazards caused by small upstream rivers. An evaluation of three automated mapping approaches of increasing complexity, i.e., a digital terrain model (DTM) filling and two 1D–2D hydrodynamic approaches, is presented based on three major flash floods in southeastern France. The results illustrate some limits of the DTM filling method and the value of using a 2D hydrodynamic approach.

Model evaluation metrics suggest that RF performs better in snowmelt-driven watersheds. The largest improvements in forecasts compared to benchmark models are found among rainfall-driven watersheds. RF performance deteriorates with increases in catchment slope and soil sandiness. We note disagreement between two popular measures of RF variable importance and recommend jointly considering these measures with the physical processes under study.

This article shows a conversion model of snow depth into snow water equivalent (SWE) using an ensemble of artificial neural networks. The novelty is a direct estimation of SWE and the improvement of the estimation by in-depth analysis of network structures. The usage of an ensemble allows a probabilistic estimation and, therefore, a deeper insight. It is a follow-up study of a similar study over Quebec but extends it to the whole area of Canada and improves it further.

A non-invasive geophysical method (spectral induced polarization, SIP) was used to characterize and predict solute transport patterns in soil columns. Our results show that SIP-based breakthrough curve (BTC) analysis is superior over conventional outflow-based analysis as it can characterize system heterogeneity and is superior over electrical-conductivity-based analysis as it is capable of distinguishing between the adsorption end-members without the need for sampling.

In this study, we address the question of whether groundwater fauna in an urban area is natural or affected in comparison to forested land. We find noticeable differences in the spatial distribution of groundwater species and abiotic parameters. An ecological assessment reveals that conditions in the urban area are mainly not good. Yet, there is no clear spatial pattern in terms of land use and anthropogenic impacts. These are significant findings for conservation and usage of urban groundwater.

Runoff regimes in Switzerland will change significantly under climate change. Projected changes are strongly elevation dependent with earlier time of emergence and stronger changes in high-elevation catchments where snowmelt and glacier melt play an important role. The magnitude of change and the climate model agreement on the sign increase with increasing global mean temperatures and stronger emission scenarios. This amplification highlights the importance of climate change mitigation.

We have collected and synthesized catchment attributes from multiple sources into an extensive dataset, the Catchment Attributes for Brazil (CABra). CABra contains streamflow and climate daily series for 735 catchments in the 1980–2010 period, aside from dozens of attributes of topography, climate, streamflow, groundwater, soil, geology, land cover, and hydrologic disturbance. The CABra intends to pave the way for a better understanding of catchments' behavior in Brazil and the world.

Our original research objective is to investigate the uncertainties of the hydrological responses of nature-based solutions (NBSs) that result from the multiscale space variability in both the rainfall and the NBS distribution. Results show that the intersection effects of spatial variability in rainfall and the spatial arrangement of NBS can generate uncertainties of peak flow and total runoff volume estimations in NBS scenarios.

Lake evaporation from Paiku Co on the TP is low in spring and summer and high in autumn and early winter. There is a ~ 5-month lag between net radiation and evaporation due to large lake heat storage. High evaporation and low inflow cause significant lake-level decrease in autumn and early winter, while low evaporation and high inflow cause considerable lake-level increase in summer. This study implies that evaporation can affect the different amplitudes of lake-level variations on the TP.

Our research assesses the hydrologic vulnerability of the western U.S. to climate by classifying the landscape based on its physical and climatic characteristics and analyzing climate data. We also apply the approach to examine the vulnerabilities of case studies in the ski and wine industries. We show that the west and its ski areas are vulnerable to changes in snow, while vineyard vulnerability varies. This allows us to consider climatic impacts across landscapes, industries, and stakeholders.

In hydrology, it is often necessary to infer from a daily sum of precipitation a possible distribution over the day – for example how much it rained in each hour. In principle, for a given daily sum, there are endless possibilities. However, some are more likely than others. We show that a method from artificial intelligence called generative adversarial networks (GANs) can learn what a typical distribution over the day looks like.

This paper focuses on the groundwater flow aspects of a small hydrological catchment at the northern tip of the Antarctic Peninsula. This region has experienced drastic climatological changes in the recent past. The basin is representative for the rugged coastline of the peninsula. It is discussed as a case study for possible future evolution of similar basins further south. Results include a quantitative analysis of glacial and groundwater contribution to total discharge into coastal waters.

Glaciers can buffer streamflow during dry and warm periods, but under which circumstances can melt compensate precipitation deficits? Streamflow responses to warm and dry events were analyzed using long-term observations of 50 glacierized catchments in Norway, Canada, and the European Alps. Region, timing of the event, relative glacier cover, and antecedent event conditions all affect the level of compensation during these events. This implies that glaciers do not compensate straightforwardly.

Satellite and rain gauge data are tested to predict landslides in India, where the annual toll of human lives and loss of property urgently demands the implementation of strategies to prevent geo-hydrological instability. For this purpose, we calculated empirical rainfall thresholds for landslide initiation. The validation of thresholds showed that satellite-based rainfall data perform better than ground-based data, and the best performance is obtained with an hourly temporal resolution.

The growing water crisis in Central Asia and the complex water politics of the region's transboundary rivers are a hot topic for research, while the dynamic changes of water politics in Central Asia have yet to be studied in depth. Based on the Gini coefficient, water political events and social network analysis, we analyzed the matching degree between water and socio-economic elements and the dynamics of hydropolitics in transboundary river basins of Central Asia.

This study demonstrates how climate warming in peatland-dominated regions of discontinuous permafrost is changing the form and function of the landscape. Key insights into the rates and patterns of such changes in the coming decades are provided through careful identification of land cover transitional stages and characterization of the hydrological and energy balance regimes for each stage.

Data assimilation methods are used throughout the geosciences to combine information from uncertain models and uncertain measurement data. In this study, we distinguish between the characteristics of geophysical systems, i.e., divergent systems (initially nearby states will drift apart) and convergent systems (initially nearby states will coalesce), and demonstrate the implications for sequential ensemble data assimilation methods, which require a sufficient divergent component.

It is not known how much uncertainty the choice of a reference data set may bring to impact studies. This study compares precipitation and temperature data sets to evaluate the uncertainty contribution to the results of climate change studies. Results show that all data sets provide good streamflow simulations over the reference period. The reference data sets also provided uncertainty that was equal to or larger than that related to general circulation models over most of the catchments.

The rapid decline of the Dead Sea level since the 1960s has provoked a dynamic reaction from the coastal groundwater system, with physical and chemical erosion creating subsurface voids and conduits. By combining remote sensing, geophysical methods, and numerical modelling at the Dead Sea’s eastern shore, we link groundwater flow patterns to the formation of surface stream channels, sinkholes and uvalas. Better understanding of this karst system will improve regional hazard assessment.

It is often difficult to determine the sources of solutes in streams and how much each source contributes. We developed a new method of unmixing stream chemistry via machine learning. We found that sulfate in three watersheds is related to groundwater flowpaths. Our results emphasize that acid rain reduces a watershed's capacity to remove CO₂ from the atmosphere, a key geological control on climate. Our method will help scientists unmix stream chemistry in watersheds where sources are unknown.

This study developed an analytical ecohydrological model that considers three aspects of vegetation response to eCO₂ (i.e., stomatal response, LAI response, and rooting depth response) to detect the impact of eCO₂ on continental runoff over the past 3 decades globally. Our findings suggest a minor role of eCO₂ on the global runoff changes, yet highlight the negative runoff–eCO₂ response in semiarid and arid regions which may further threaten the limited water resource there.

This study investigates the effects of climate change on runoff patterns in six Alpine catchments in Austria at the end of the 21st century. Our results indicate a substantial shift to earlier occurrences in annual maximum and minimum flows in high-elevation catchments. Magnitudes of annual extremes are projected to increase under a moderate emission scenario in all catchments. Changes are generally more pronounced for high-elevation catchments.

Previous studies decomposed ET variance in precipitation, potential ET, and total water storage changes based on Budyko equations. However, the effects of snowmelt and vegetation changes have not been incorporated in snow-dependent basins. We thus extended this method in arid alpine basins of northwest China and found that ET variance is primarily controlled by rainfall, followed by coupled rainfall and vegetation. The out-of-phase seasonality between rainfall and snowmelt weaken ET variance.

The simulation of precipitation extreme events is a known problem in modelling. That is why the atmospheric conditions favourable for its development as simulated by two WRF experiments are evaluated in this paper. The experiment including 3DVAR data assimilation outperforms the one without in simulating the TT index, CAPE, and CIN over the Iberian Peninsula. The ingredients for convective precipitation in winter are found at the Atlantic coast, but in summer they are at the Mediterranean coast.

Soil moisture levels have decreased significantly over the past 2 decades. This decrease is not uniformly distributed over the observation period. The largest changes occur at tipping points during years of extreme drought, after which soil moisture levels reach significantly different alternate stable states. Not only the overall trend in soil moisture is affected, but also the seasonal dynamics.

Understanding the natural generation of CO₂ in sedimentary basins is key to optimizing exploitation of natural resources and exploring feasibility of carbon capture and storage. We present a novel modeling approach to estimate the probability of CO₂ generation caused by geochemical reactions at high temperatures and pressure in realistic sedimentary basins. Our model allows estimation of the most probable CO₂ source depth and generation rate as a function of the composition of the source rock.

This study utilized spatiotemporally continuous precipitation anomaly (pr_a) and water table depth anomaly (wtd_a) data from integrated hydrologic simulation results over Europe in combination with Long Short-Term Memory (LSTM) networks to capture the time-varying and time-lagged relationship between pr_a and wtd_a in order to obtain reliable models to estimate wtda at the individual pixel level.

This study analyses changes in magnitude, frequency, and seasonality of moderate low and high flows for 93 catchments in Switzerland. In lower-lying catchments (below 1500 m a.s.l.), moderate low-flow magnitude (frequency) will decrease (increase). In Alpine catchments (above 1500 m a.s.l.), moderate low-flow magnitude (frequency) will increase (decrease). Moderate high flows tend to occur more frequent, and their magnitude increases in most catchments except some Alpine catchments.

We present an application of multivariate statistical models to assess compound flooding events in a managed reservoir. Data (from a previous study) were obtained from a physical-based hydrological model driven by a regional climate model large ensemble, providing a time series expanding up to 800 years in length that ensures stable statistics. The length of the data set allows for a sensitivity assessment of the proposed statistical framework to natural climate variability.

There is a clear trade-off between reservoir hydropower generation and the variability in reservoir water release, which can be used to derive water-sharing policies and provide critical insights during riparian negotiations regarding downstream flows supplementing during drought conditions. This type of water-sharing policy can effectively mitigate the water use conflicts between upstream and downstream countries, especially during drought periods.

We used a tracer-aided ecohydrological model to quantify water flux–storage–age interactions for three urban vegetation types: trees, shrub and grass. The model results showed that evapotranspiration increased in the order shrub < grass < trees during one growing season. Additionally, we could show how infiltration hotspots created by runoff from sealed onto vegetated surfaces can enhance both evapotranspiration and groundwater recharge.

This study integrated a water isotope module into the hydrological model THREW. The isotope-aided model was subsequently applied for process understanding in the glacierized watershed of Karuxung river on the Tibetan Plateau. The model was used to quantify the contribution of runoff component and estimate the water travel time in the catchment. Model uncertainties were significantly constrained by using additional isotopic data, improving the process understanding in the catchment.

To test our hypothesis that the fractal dimensions of streamflow series can be used to improve the calibration of hydrological models, we designed the E–RD efficiency ratio of fractal dimensions strategy and examined its usability in the calibration of lumped models. The results reveal that, in most aspects, introducing RD into model calibration makes the simulation of streamflow components more reasonable. Also, pursuing a better RD during calibration leads to only a minor decrease in E.

We reconstructed historical and present-day tritium, chloride, and nitrate concentrations in stream water of a catchment using land-use-based input curves and calculated travel times of groundwater. Parameters such as the unsaturated zone thickness, mean travel time, and input patterns determine time lags between inputs and in-stream concentrations. The timescale of the breakthrough of pollutants in streams is dependent on the location of pollution in a catchment.

Intensified drying of soil and grassland vegetation is raising the impact of fire severity and extent in Southern California. While browned grassland is a common sight during the dry season, this study has shown that there is a pronounced shift in the timing of senescence, due to changing climate conditions favoring milder winter temperatures and increased precipitation variability. Vegetation may be limited in its ability to adapt to these shifts, as drought periods become more frequent.

A volume-dependent transient isotopic mass balance model was developed for an artificial lake in Canada, in a context where direct measurements of surface water fluxes are difficult. It revealed that floodwater inputs affected the dynamics of the lake in spring but also significantly influenced the long-term water balance due to temporary subsurface storage of floodwater. Such models are paramount for understanding the vulnerability of lakes to changes in groundwater quantity and quality.

This paper is a preliminary study to characterize events of simultaneous heavy rainfall and damaging waves at the regional scale (~600 km of coastline) in the NW Mediterranean. The atmospheric pressure conditions of such events are also classified into three main weather types, which are characterized in terms of severity of the forcing and probability of co-occurrence of simultaneous hazardous waves and rain. The study also presents some historical cases that are compared with obtained results.