This study uses the concepts of entropy and work to quantify and explain the emergence of preferential flow and transport in heterogeneous saturated porous media. We found that the downstream concentration of solutes in preferential pathways implies a downstream declining entropy in the transverse distribution of solute transport pathways. Preferential flow patterns with lower entropies emerged within media of higher heterogeneity – a stronger self-organization despite a higher randomness.

Groundwater provides flow, known as baseflow, to surface streams and rivers. It is important as it sustains the flow of many rivers at times of water stress. However, it may be affected by water management practices. Statistical models have been used to show that abstraction of groundwater may influence baseflow. Consequently, it is recommended that information on groundwater abstraction is included in future assessments and predictions of baseflow.

Using publications indexed in the Web of Science, we investigated water resources knowledge development at the river basin scale since 1900 and found that legacy-driven knowledge structures, increasingly homogenized management issues, and largely static cross-disciplinary collaborations dominated highly researched river basins. A structural shift of water resources knowledge development to cope with the rapidly changing hydrological systems and associated management issues is urgently needed.

Evaporation led to progressively more heavy-isotope-enriched bulk soil water (BW) following the precipitation/irrigation of heavy-isotope-depleted new water but causes progressively more heavy-isotope-depleted BW following irrigation of heavy-isotope-enriched new water. The results indicated that δ²H and δ¹⁸O in evaporating water (EW) were similar to new water and differed from BW. However, the evaporative water loss calculated from BW did not differ significantly from that of EW.

It is widely assumed that ¹⁴C is in contact with the atmosphere until recharging water reaches the water table. Unsaturated zone (UZ) studies have shown that ¹⁴C decreases with depth below the land surface. We produce a relationship between UZ ¹⁴C and depth to the water table to estimate input ¹⁴C activities for groundwater age estimation. Application of the new relationship shows that it is important for UZ processes to be considered in groundwater mean residence time estimation.

Hydrological models are useful tools that allow us to predict distributions and movement of water. A variety of numerical methods are used by these models. We demonstrate which numerical methods yield large errors when subject to extreme precipitation. As the climate is changing such that extreme precipitation is more common, we find that some numerical methods are better suited for use in hydrological models. Also, we find that many current hydrological models use relatively inaccurate methods.

The hydrological subsurface drainage model SIDRA-RU is assessed at the French national scale, using a unique database representing the large majority of the French drained areas. The model is evaluated following its capacity to simulate the drainage discharge variability and the annual drained water balance. Eventually, the temporal robustness of SIDRA-RU is assessed to demonstrate the utility of this model as a long-term management tool.

Transfer functions with dependence on wind speed and precipitation fall velocity are evaluated alongside transfer functions with wind speed and temperature dependence for unshielded precipitation gauges. The transfer functions with fall velocity dependence reduced the RMSE of unshielded gauge measurements relative to the functions based on wind speed and temperature, demonstrating the importance of fall velocity for precipitation gauge collection efficiency and transfer functions.

A sensitivity analysis based on a simulator of hydrograph parameters (volume, maximum flow) is shown. The method allows us to analyze the impact of calibrated hydrodynamic model parameters, including rainfall distribution and intensity, on the hydrograph. A sensitivity coefficient and the effect of the simulator uncertainty on calculation results are presented. This approach can be used to select hydrographs for calibration and validation of models, which has not been taken into account so far.

We used deep learning (DL) models to simulate the amount of water moving through a river channel (discharge) based on the rainfall, temperature and potential evaporation in the previous days. We tested the DL models on catchments across Great Britain finding that the model can accurately simulate hydrological systems across a variety of catchment conditions. Ultimately, the model struggled most in areas where there is chalky bedrock and where human influence on the catchment is large.

We investigate statistical properties of observed flood series on a European scale. There are pronounced regional patterns, for instance: regions with strong Atlantic influence show less year-to-year variability in the magnitude of observed floods when compared with more arid regions of Europe. The hydrological controls on the patterns are quantified and discussed. On the European scale, climate seems to be the dominant driver for the observed patterns.

We integrate a spatially explicit soil erosion model with plot- and watershed-scale characterization and high-resolution drone imagery to assess the effect of spatial resolution digital terrain models (DTMs) on discharge and soil loss. Results showed reduction in slope due to resampling down of DTM. Higher resolution translates to higher slope, denser fluvial system, and extremer values of soil loss, reducing concentration time and increasing soil loss at the outlet. The best resolution was 4 m.

We evaluate 63 years of changes in annual streamflow volume across Europe, using a data set of more than 3000 stations, with a special focus on the Mediterranean basin. The results show decreasing (increasing) volumes in the southern (northern) regions. These trends are strongly consistent with the changes in temperature and precipitation.

This study assesses methods that estimate flood return periods to identify when we would obtain a large flood return estimate change if the method or input data were changed (sensitivities). We include an examination of multiple flood-generating models, which is a novel addition to the flood estimation literature. We highlight the need to select appropriate flood models for the study watershed. These results will help operational water agencies develop more robust risk assessments.

To quantify how vegetation greening impacts the capacity of water supply, we built a hybrid model and conducted a case study using the upper Han River basin (UHRB) that serves as the water source area to the world’s largest water diversion project. Vegetation greening in the UHRB during 2001–2018 induced annual water yield (WY) greatly decreased. Vegetation greening also increased the possibility of drought and reduced a quarter of WY on average during drought periods.