Integrating streamflow and evaporation data can help improve the physical realism of hydrologic models. We investigate the capabilities of the Variable Infiltration Capacity (VIC) to reproduce both hydrologic variables for 189 headwater located in Spain. Results from sensitivity analyses indicate that adding two vegetation parameters is enough to improve the representation of evaporation and that the performance of VIC exceeded that of the largest modelling effort currently available in Spain.

Hydrological modelling is a powerful tool to support decision-making. We assessed spatio-temporal patterns and trends of streamflow for 2001–2022 with a hydrological model, integrating stakeholder expert knowledge on management operations. The results provide insight into how climate change and anthropogenic pressures affect water resources availability in regions vulnerable to water scarcity, thus raising the need for sustainable management practices and integrated hydrological modelling.

We provide a set of benchmarking scenarios for geostatistical inversion, and we encourage the scientific community to use these to compare their newly developed methods. To facilitate transparent, appropriate, and uncertainty-aware comparison of novel methods, we provide some accurate reference solutions, a high-end reference algorithm, and a diverse set of benchmarking metrics, all of which are publicly available. With this, we seek to foster more targeted and transparent progress in the field.

It is crucial to improve global precipitation estimates to understand water-related disasters and water resources. This study proposes a new methodology to interpolate global precipitation fields from ground rain gauge observations using ensemble data assimilation and the precipitation of a numerical weather prediction model. Our estimates agree better with independent rain gauge observations than existing precipitation estimates, especially in mountainous or rain-gauge-sparse regions.

This study establishes a framework to incorporate cosmic-ray neutron measurements into the mesoscale Hydrological Model (mHM). We evaluate different approaches to estimate neutron counts within the mHM using the Desilets equation, with uniformly and non-uniformly weighted average soil moisture, and the physically based code COSMIC. The data improved not only soil moisture simulations but also the parameterisation of evapotranspiration in the model.

We introduce a new deep-learning model that addresses the limitations of existing urban flood models in handling varied terrains and rainfall events. Our model subdivides a city into small patches and presents a novel approach to incorporate broader terrain information. It accurately predicts high-resolution flood maps across diverse rainfall events and cities (on minute and meter scales) that haven’t been seen by the model, which offers valuable insights for urban flood mitigation strategies.

In 2019, Hurricane Dorian led to salinization of groundwater resources on the island of Grand Bahama. We assessed the feasibility of managed aquifer recharge (MAR) for restoring fresh groundwater. Furthermore, we applied a financial and an extended cost–benefit analysis for assessing ecosystem services supported by MAR and reforestation. As a first estimate, MAR could only provide a small contribution to the water demand. Reforestation measures were assessed to be financially profitable.

Hydrological modeling is valuable for estimating the potential impact of climate change on hydropower generation. This study presents a comprehensive approach to modeling the management of hydroelectric reservoirs in hydrological models. The total power grid demand for hydropower is distributed to the various power plants to compute their release. The method is tested on the French national power grid, and it is demonstrated that it successfully reproduces the observed behavior of reservoirs.

Evapotranspiration (ET) is computed from the vegetation (plant transpiration) and soil (soil evaporation). In western Africa, plant transpiration correlates with vegetation growth. Vegetation is often represented using the leaf area index (LAI). In this study, we evaluate the importance of the LAI for ET calculation. We take a close look at this interaction and highlight its relevance. Our work contributes to the understanding of terrestrial water cycle processes .

In coastal cities, rainfall and tides contribute to compound flooding. This study quantifies the impacts of rainfall and tides on compound flooding and analyzes interactions between different flood types. Findings show that rainfall generally has a greater effect on flooding than tide levels. The interaction between fluvial and pluvial flooding amplifies the flood disaster, with tide levels having the most significant impact during the interaction phase.