Flow depth and velocity determine various river functions, but their high-resolution simulations are expensive. Here, we developed a downscaling approach that can provide fast and accurate estimation of high-resolution river hydrodynamics. The 84-fold acceleration achieved by the method makes reliable flood risk analysis that needs hundreds or thousands of model runs feasible. More importantly, it provides an opportunity to couple large-scale hydrodynamics with local processes in river models.

We produced a new interpolated map of stable isotopes in groundwater in southern Germany and compared it to local precipitation. Interestingly, discrepancies were found between two components of the hydrological cycle, highlighting different recharge patterns and evaporation processes in the northern and southern part of the study area. This research provides insights into understanding different groundwater recharge patterns on a large scale and eventually for groundwater management.

Soil moisture is crucial for the water cycle since it is at the front line of drought. Satellite, model and in situ data help identify soil moisture stress but are challenged by data uncertainties. This study evaluates trends and data coherence of common active/passive microwave sensors and model-based soil moisture data against in situ stations across Europe from 2007 to 2022. Data reliability is increasing, but combining data types improves soil moisture monitoring capabilities.

This study explored the occurrence of flow on and just below the soil surface for 14 small vegetated plots across a pre-Alpine catchment. Overland flow and lateral flow through the topsoil occurred frequently. The spatial variation in the occurrence and amount of flow depended on site characteristics, particularly the topographic wetness index. The amount of flow also depended on the antecedent-wetness conditions and total precipitation.

Instruments that use absorption of laser light to measure isotopic concentrations in water are advancing our understanding of the water cycle, but for some sample types these instruments suffer from major biases caused by organic compounds. A new dataset of water from >1800 plant and soil samples shows that these effects are common and severe for many plant species but can be mathematically corrected to obtain high-quality research data.

A method for estimating extreme rainfall from radar observations is provided. Extreme value statistics are applied on merged radar rainfall product covering different area sizes from a single point up to about 1000 km². The rainfall extremes are supposed to decrease as the area increases. This behavior could not be confirmed by the radar observations. The reason is the limited single-point sampling approach for extreme value analysis. New multiple-point sampling strategies are proposed to mitigate this problem.

Using advances in transit time estimation and tracer data, we tested if fast-flow transit times are controlled solely by soil moisture or if they are also controlled by precipitation intensity. We used soil-moisture-dependent and precipitation-intensity-conditional transfer functions. We showed that a significant portion of event water bypasses the soil matrix through fast flow paths (overland flow, tile drains, preferential-flow paths) in dry soil conditions for both low- and high-intensity precipitation.

Mining activities threaten aquatic ecosystems, soil ecosystems, and human health worldwide. This study establishes a high-quality database and a national 0.5° gridded dataset to reveal the status and spatial pattern of mining-affected water pollution, human health risks, and potential multifaceted challenges in China. It provides in-depth insights to guide policymakers in designing differentiated management strategies for the sustainable development of mines.

We developed a new method using sap-flow and water-potential data to estimate key plant water-use properties without destructive sampling. Testing on drooping sheoak showed that our approach captures seasonal changes in plant water transport and that these hydraulic properties have seasonal variation. This method could improve models predicting how vegetation responds to drought and climate change.

Understanding water balance in lakes is complex. We studied Lake Groβ Glienicke in Germany, using an innovative method that combines isotope measurements and a hydrological model to improve estimates of water inflow and evaporation. Our findings show a high correlation between the two approaches, leading to better predictions of lake water dynamics. This research offers a reliable way of evaluating the model outputs.