Recent  

Using water stable isotopes, we studied from which water source (lake, stream, ground or soil water) two willows were taking their water. We monitored the environmental conditions (e.g., air temperature, soil moisture) and the behavior of the trees (water flow in the stem). We found that the most likely water sources of the willows were the upper soil layers, but that there were seasonal dynamics.

A reasonable assessment of the contribution of the water resources in a river basin to domestic crops supplies will be the first step in balancing the water-food nexus. Our results showed that although the Yellow River Basin had reduced its virtual water outflow, its importance to crop production in China had been increasing when water footprint networks were considered. Our complexity-based approach provides a new perspective for understanding changes in a basin with a severe water shortage.

Sustainability of water-energy-food (WEF) nexus remains challenge, as interactions between WEF and community sensitivity and reservoir operation in water system are often neglected. The paper applies system dynamics model to simulate WEF nexus by incorporating community sensitivity and reservoirs operation. Results indicate environmental awareness keeps WEFS nexus from collapsing by feedback and water resources allocation sustains WEFS nexus by ensuring water supply through reservoir operation.

A study of two glacierised Himalayan catchments reveals that the summer runoff from the glacierised parts of the catchments responds strongly to temperature forcing and is stable to precipitation forcing, while that of the non-glacierised parts has an exactly opposite behaviour. The pattern of changes in mean runoff and its variability under a warming climate is determined by the response of glaciers to temperature forcing, and that of off-glacier areas to precipitation perturbations.

We have analyzed the spatial dependence of rainfall extremes upon elevation and topography in Italy. Regression analyses show that previous rainfall-elevation relations at national scale can be substantially improved with new data, both using topography attributes and constraining the analysis within areas stemming from geomorphological zonation. Short-duration mean rainfall depths can be then estimated, all over Italy, using different parameters in each area of the geomorphological subdivision.

Using an integrated watershed model, we compared simulated watershed hydrologic variables driven by three publicly available gridded meteorological forcings (GMFs) at various spatial and temporal resolutions. Our results demonstrated that spatially distributed variables are sensitive to the spatial resolution of the GMF. The temporal resolution of the GMF impacts the dynamics of watershed responses. The choice of GMF depends on the quantity of interest and its spatial and temporal scale.

Data driven LSTM models constitute a good candidate for prediction of runoff in a catchment. In this work, we used local LSTM models derived from individual catchments and regional models derived from a group of catchments. Our aim was to investigate how regime based information can be used for this class of models. We used a large sample of 740 catchments in the French climatic context. We identified three regime related factors that can make local and regional LSTM-based models more effective.

The quality control and optimization of soil aquifer treatment (SAT) performance is challenging due to the multiple factors and costs involved. We installed in situ subsurface monitoring sensors that provided continuous high-resolution monitoring of the biochemical and physical conditions of an active SAT system. Data analysis facilitated the determination of the optimal drying and wetting stages, which are critical for suitable SAT management.

Millions of West African people encounter serious floods every year. The FANFAR project co-designed a flood forecasting and alert system with 50–60 key West African stakeholders. Multi-Criteria Decision Analysis helped prioritize a system configuration that meets their needs: it should provide accurate, clear flood risk information and work reliably under difficult West African conditions. As theoretical contribution, we propose an assessment framework for transdisciplinary hydrology research.

In this study, daily and hourly rainfall observations were used as inputs to SWAT hydrological model to investigate the impacts of temporal resolution of rainfall on streamflow simulation. Results indicated that groundwater flow parameters were more sensitive for daily time intervals and channel routing parameters were more influential for hourly time intervals. Overall, this study suggests that the SWAT model appears to be a reliable tool to predict discharge over long periods of time.

In this work, we assess the effects of end-of-century extreme dry and wet conditions on the hydrology of California. Our results, derived from cutting-edge and high-resolution climate and hydrologic models, highlight that (1) water storage will be larger and increase earlier in the year, yet the summer streamflow will decrease a result of high evapotranspiration rates (1) groundwater and lower-order streams are very sensitive to the decreases in snowmelt and higher evapotranspiration.

Unbeknownst to most hydrologists, many methods used in groundwater hydrology today go back to work by Adolf and Günther Thiem. Their work goes much beyond the Dupuit-Thiem analytical model for pump tests mentioned in many textbooks. It includes e.g. the development and improvement of isopotential maps, tracer tests and vertical well constructions. An extensive literature and archive research has been conducted to identify how and where the Thiems developed their methods and how they spread.

We introduce a new multi-process river sediment module for the Earth System models. Application and validation over the contiguous U.S. indicate a satisfactory model performance over large river systems, including those heavily regulated by reservoirs. This new sediment module enables future modeling of the transportation and transformation of carbon and nutrients carried by the fine sediment along the river-ocean continuum to close the global carbon and nutrients cycles.

Forecasts of evaporative water loss in the future are highly valuable for water resource management. These forecasts are often produced using outputs of climate models. We developed an innovative method to correct errors in these forecasts, particularly the errors caused by deficiencies of climate models in modeling the changing climate. We apply this method to seasonal forecasts of evaporative water loss across Australia and achieve significant improvements in forecast quality.

An improved Gis-derived distributed unit hydrograph routing method considering time-varying soil moisture content was proposed for flood routing. The proposed method considered the changes of time-varying soil moisture content and rainfall intensity. The response of underlying surface to the soil moisture content was considered as an important factor in this study. The DUH, TDUH and proposed routing methods were used for flood forecasts, and the simulated results were compared and discussed.

Pesticides continue to pose a threat to surface water quality worldwide. Here, we present a spatial Bayesian Belief Network (BBN) for assessing inherent pesticide risk to water quality. The BBN was applied in a small catchment with limited data to simulate the risk of five pesticides and evaluate the likely effectiveness of mitigation measures. The probabilistic graphical model combines diverse data and explicitly accounts for uncertainties, which are often ignored in pesticide risk assessments.

Global hydrological models (GHMs) are usually applied with a spatial resolution of about 50 km, but this time we applied the H08 model, one of the most advanced GHMs, with a high resolution of 2 km to Kyushu Island, Japan. Since the model was not accurate as it was, we incorporated local information and improved the model, which revealed detailed water stress in subregions that was not visible with the previous resolution.

Here we present the first hydrological framework for understanding the mechanisms supporting the persistence of water in pools along non-perennial rivers. Pools may collect water after rainfall events, be supported by water stored within the river channel sediments, or receive inflows from regional groundwater. These hydraulic mechanisms can be identified using a range of diagnostic tools (critiqued herein). We then apply this framework in north-west Australia to demonstrate it's value.

Using specific conductivity (SC) to estimate groundwater inflow to rivers is complicated by bank return waters, interflow, and flows off floodplains contributing to baseflow in all but the driest years. Using the maximum SC of the river in dry years to estimate the SC of groundwater produces the best baseflow vs streamflow trends. The variable composition of baseflow hinders calibration of hydrograph-based techniques to estimate groundwater inflows.

Regional climate models not only provide projections on temperature and precipitation, but also on snow. Here, we employed statistical post-processing using satellite observations to reduce bias and uncertainty from model projections of future snow covered area and duration under different greenhouse gas concentration scenarios for the European Alps.

At present, there is a lack of time series of runoff generated by glacial regions in the world. In this paper, we quantified glacial runoff (including meltwater runoff and delayed runoff) in arid regions of China from 1961 to 2015 by using remote sensing datasets of glacier mass balance with high resolution. Glacier runoff is the water resource used by oases in arid regions of China. The long-term glacial runoff data can indicate the climate risk faced by different basins in arid regions.

The aim of this study is to predict long term averages of low flow on a hydrological diverse dataset in Austria. We compared seven statistical learning methods and included a backward variable selection approach. We found that separating the low flow processes in winter and summer low flow leads to good performance for all models. Variable selection results in parsimonious and more interpretable models. Linear approaches for prediction and variable selection are sufficient for our dataset.