In East Africa are conflict over water and vegetation prominent. On top of that, water abstraction of commercial farms are increasing the competition of water. Therefore, this study has developed a model which can investigate what the influence is of these farming activities on the water balance of the region and people's livelihood activities in times of dry periods. We do that by ‘replacing’ the farms in the model, and see what the effect would be if there were communities or forests instead.

Understanding how reactive solutes move through nearly saturated soil is important for many environmental processes. However, this movement is influenced by both soil deformation and chemical reactions, which are often treated separately. This paper proposes a flexible framework that links these coupled effects. The results show that changes in loading, moisture, and mineral reactions can shift both the rate and pattern of solute movement, improving long-term predictive capability.

The Explore2 project has provided an unprecedented set of hydrological projections in terms of the number of hydrological models used and the spatial and temporal resolution. The results have been made available through various media. Under the high-emission scenario, the hydrological models mostly agree on the decrease in seasonal flows in the south of France, confirming its hotspot status, and on the decrease in summer flows throughout France, with the exception of the northern part of France.

As natural hazards evolve, understanding how extreme events interact over time is crucial. While single extremes have been widely studied, joint extremes remain challenging to analyze. We present a framework that combines advanced statistical modeling with copula theory to capture changing dependencies. Applying it to historical data reveals dynamic patterns in extreme events. To support broader use, we provide an open-source tool for improved hazard assessment.

Pumping wells may not be officially registered or documented. We develop a new framework to jointly estimate spatially variable conductivity and identify unknown pumping well locations and rates. Our results support the ability of the new approach to accurately estimate conductivity and identify well location and rates under diverse configurations, attaining a quality of performance similar to its traditional counterpart while computational time is reduced by nearly an order of magnitude.

Common metrics used to evaluate hydrologic models make it relatively easy to achieve high performance scores in highly seasonal catchments. However, we analysed 18 hydrologic models and found that almost all were worse at simulating interannual variability and change in seasonal streamflow regimes. This suggests that climate change impacts on streamflow may not be accurately predicted in highly seasonal tropical, alpine, and polar regions, which are highly vulnerable to climate change.

This study investigated groundwater-driven nutrient fluxes in a Yangtze Basin oxbow lake using a year of high-frequency monitoring. Water level and ²²²Rn tracing revealed a seasonal groundwater discharge pattern. This dynamic was regulated by net precipitation, which controlled lake level fluctuations and subsequent groundwater discharge rates. Associated N and P loads varied synchronously with discharge. The N/P closely matched that of lake water and correlated with chlorophyll-a dynamics.