Recent  

Accurate estimation of terrestrial water storage (TWS) is essential for reliable water resource assessments. TWS can be estimated from the Community Atmosphere–Biosphere Land Exchange model (CABLE), but the resolution is limited to 0.5°. We reconfigure CABLE to improve TWS spatial details from 0.5° to 0.05°. GRACE satellite data are assimilated into CABLE to improve TWS accuracy. Our workflow relies only on publicly accessible data, allowing reproduction of 0.05° TWS in any region.

We benchmarked the skill of ensemble streamflow prediction (ESP) for a diverse sample of 46 Irish catchments. We found that ESP is skilful in the majority of catchments up to several months ahead. However, the level of skill was strongly dependent on lead time, initialisation month, and individual catchment location and storage properties. We also conditioned ESP with the winter North Atlantic Oscillation and show that improvements in forecast skill, reliability, and discrimination are possible.

Pore pressure is important for the trigger of debris slides and flows. But how, exactly, does the pore pressure vary just before a slide happens? We drilled and installed a piezometer 1.6 m below the ground in a hillslope susceptible to debris flows in western Norway and measured pore pressure and water temperature through the years 2010–2013. We found the largest anomaly in our groundwater data during the storm named Hilde in November in 2013, when a debris flow happened in this slope.

We developed a stochastic framework with indicator random variables to characterize the spatiotemporal distribution of environmental hot spots and hot moments (HSHMs) that represent rare locations and events exerting a disproportionate influence over the environment. HSHMs are characterized by static and dynamic indicators. This framework is advantageous as it allows us to calculate the uncertainty associated with HSHMs based on uncertainty associated with its contributors.

This study evaluates how the sequential assimilation of flood extent derived from synthetic aperture radar data can help improve flood forecasting. In particular, we carried out twin experiments based on a synthetically generated dataset with controlled uncertainty. Our empirical results demonstrate the efficiency of the proposed data assimilation framework, as forecasting errors are substantially reduced as a result of the assimilation.

In this study, we simulated the water balance over the South American Dry Chaco and assessed the impact of land cover changes thereon using three different land surface models. Our simulations indicated that different models result in a different partitioning of the total water budget, but all showed an increase in soil moisture and percolation over the deforested areas. We also found that, relative to independent data, no specific land surface model is significantly better than another.

Significant biases in real-time radar rainfall products limit the use for hydrometeorological forecasting. We introduce CARROTS (Climatology-based Adjustments for Radar Rainfall in an OperaTional Setting), a set of fixed bias reduction factors to correct radar rainfall products and to benchmark other correction algorithms. When tested for 12 Dutch basins, estimated rainfall and simulated discharges with CARROTS generally outperform those using the operational mean field bias adjustments.

Typhoon (TY) and non-typhoon (NTY) rainy days in northern Taiwan summer seasons showed more large drops on NTY than TY rainy days. Relatively higher convective activity and drier conditions in NTY than TY lead to variations in microphysical characteristics between TY and NTY rainy days. The raindrop size distribution and kinetic energy relations assessed for TY and NTY rainfall can be useful for evaluating the radar rainfall estimation algorithms, cloud modeling, and rainfall erosivity studies.

We compare two approaches for coupling a 2D groundwater model with multiple 1D models for the unsaturated zone. One is non-iterative and very fast. The other one is iterative and involves a new way of treating the specific yield, which is crucial for obtaining a consistent solution in both model compartments. Tested on different scenarios, this new method turns out to be slower than the non-iterative approach but more accurate and still very efficient compared to fully integrated 3D model runs.

This paper provides a comprehensive overview of the differences within streamflow droughts derived using different identification approaches, namely the variable threshold, fixed threshold, and the Standardized Streamflow Index, including an analysis of both historical drought and implications for forecasting. Our results clearly show that streamflow droughts derived from different approaches deviate from each other in terms of drought occurrence, timing, duration, and deficit volume.

The R programming language has become an important tool for many applications in hydrology. In this study, we provide an analysis of some of the R tools providing hydrological models. In total, two aspects are uniformly investigated, namely the conceptualisation of the models and the practicality of their implementation for end-users. These comparisons aim at easing the choice of R tools for users and at improving their usability for hydrology modelling to support more transferable research.

At our study site during the experimental period, trunk water was only isotopically similar to root water at 100–160 cm depths. The isotopic composition of root water deviated from that of bulk soil water but overlapped with the composition derived for less mobile water. These findings suggest that the isotopic offset between bulk soil water and trunk water was due to the isotopic mismatch between root water and bulk soil water associated with soil water heterogeneity.

Weather and water extremes have devastating effects each year. One of the principal challenges for society is understanding how extremes are likely to evolve under the influence of changes in climate, land cover, and other human impacts. This paper provides a review of the methods and challenges associated with the detection, attribution, management, and projection of nonstationary weather and water extremes.

We examine whether several climate indices alter the magnitude, timing and duration of floods in the Amazon. We find significant changes in both flood magnitude and duration, particularly in the north-eastern Amazon for negative SST years in the central Pacific Ocean. This response is not repeated when the negative anomaly is positioned further east. These results have important implications for both social and physical sectors working towards the improvement of flood early warning systems.

Evapotranspiration (ET) links the water, energy and carbon cycle on land. Reliable ET estimates are key to understand droughts and flooding. We develop a new ET dataset, DOLCE V3, by merging multiple global ET datasets, and we show that it matches ET observations better and hence is more reliable than its parent datasets. Next, we use DOLCE V3 to examine recent changes in ET and find that ET has increased over most of the land, decreased in some regions, and has not changed in some other regions

We measured the silicon isotopic composition of groundwater from Rottnest Island, Western Australia, to investigate water–rock interactions in a coastal aquifer. Silicon isotopic ratios varied spatially across the island and were related to secondary mineral formation and vertical mixing within the aquifer. We find that silicate dissolution occurs in the freshwater–seawater transition zone, supporting the recent recognition of submarine groundwater discharge in the oceanic silicon isotope cycle.

Assessment of changes in the global water cycle has been a challenge. This study estimated long-term global latent heat and sensible heat fluxes for recent decades using machine learning and ground observations. The results found that the decline in evaporative fraction was typically accompanied by an increase in long-term runoff in over 27.06 % of the global land areas. The observation-driven findings emphasized that surface vegetation has great impacts in regulating water and energy cycles.

Accurate spatial precipitation estimates are important in various fields. An approach to simulate spatial rainfall fields conditioned on radar and rain gauge data is proposed. Unlike the commonly used Kriging methods, which provide a Kriged mean field, the output of the proposed approach is an ensemble of estimates that represents the estimation uncertainty. The approach is robust to nonlinear error in radar estimates and is shown to have some advantages, especially when estimating the extremes.

Ground information on the occurrence of blowing snow has been sorely lacking because direct observations of blowing snow are sparse in time and space. In this paper, we investigated the potential capability of the decision tree model to detect blowing snow events in the European Alps. Trained with routine meteorological observations, the decision tree model can be used as an efficient tool to detect blowing snow occurrences across different regions requiring limited meteorological variables.

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.

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.

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.

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.

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.

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.

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.