Recent  

With intensified extremes under climate change, water demand increases. Every drop of water is more valuable than before when drought is experienced particularly. We developed drought intensity–duration–frequency curves using physical indicators, the deficit in precipitation and streamflow, for a more straightforward interpretation. Tests with the observed major droughts in two climatologically different catchments confirmed the practical applicability of the curves under drought conditions.

We proposed an iteration method in combination with the MixSIAR model and water isotopes to quantify the river water contribution (RWC) to riparian deep-rooted trees nearby a losing river. River water can indirectly contribute by 20.3 % to water uptake of riparian trees. River recharged riparian groundwater rapidly with a short groundwater residence time (no more than 0.28 d). The RWC to riparian trees was negatively correlated with the water table depth and leaf δ¹³C in linear functions.

This study proposes a low-budget method to quantify the radial distribution of water transport velocities within trees at a high spatial resolution. We observed a wide spread of water transport velocities within a tree stem section, which were on average 3 times faster than the flux velocity. The distribution of transport velocities has implications for studies that use water isotopic signatures to study root water uptake and usually assume uniform or even implicitly infinite velocities.

We present the results of a large visual inspection campaign of 674 streamflow time series in France. The objective was to detect non-natural records resulting from instrument failure or anthropogenic influences, such as hydroelectric power generation or reservoir management. We conclude that the identification of flaws in flow time series is highly dependent on the objectives and skills of individual evaluators, and we raise the need for better practices for data cleaning.

Flood forecasts are only useful if they are understood correctly. They are also uncertain, and it is difficult to present all of the information about the forecast and its uncertainty on a map, as it is three dimensional (water depth and extent, in all directions). To overcome this, we interviewed 139 people to understand their preferences in terms of forecast visualization. We propose simple and effective ways of presenting flood forecast maps so that they can be understood and useful.

A novel methodology for the development of a stormwater network performance simulator including advanced risk assessment was proposed. The applied tool enables the analysis of the influence of spatial variability in catchment and stormwater network characteristics on the relation between (SWMM) model parameters and specific flood volume, as an alternative approach to mechanistic models. The proposed method can be used at the stage of catchment model development and spatial planning management.

Teaching hydrological modeling is an important, but difficult, matter. It requires appropriate tools and teaching material. In this article, we present the airGRteaching package, which is an open-source software tool relying on widely used hydrological models. This tool proposes an interface and numerous hydrological modeling exercises representing a wide range of hydrological applications. We show how this tool can be applied to simple but real-life cases.

We compared hourly data from precipitation gauges with lysimeter reference data at three sites under different climatic conditions. Our results show that precipitation gauges recorded 33–96 % of the reference precipitation data for the period under consideration (2015–2018). Correction algorithms increased the registered precipitation by 9–14 %. It follows that when using point precipitation data, regardless of the precipitation measurement method used, relevant uncertainties must be considered.

We propose a model calibration method constraining groundwater seepage in the hydrographic network. The method assesses the hydraulic properties of aquifers in regions where perennial streams are directly fed by groundwater. The estimated hydraulic conductivity appear to be highly sensitive to the spatial extent and density of streams. Such an approach improving subsurface characterization from surface information is particularly interesting for ungauged basins.

The Priestley–Taylor equation is widely used in hydrologic, climate, and meteorological models to estimate evaporation. α represents the impact of dry air that is carried into the region; this occurs even in extensive saturated regions. Four hypotheses regarding the nature of α are evaluated. Data from 171 FLUXNET stations were used to test the hypotheses. The best-supported hypothesis sees α as a constant fraction of the distance between theoretical minimum and maximum values.

The computational cost of sensitivity analysis (SA) becomes prohibitive for large hydrologic modeling domains. Here, using a large-scale Variable Infiltration Capacity (VIC) deployment, we show that watershed classification helps identify the spatial pattern of parameter sensitivity within the domain at a reduced cost. Findings reveal the opportunity to leverage climate and land cover attributes to reduce the cost of SA and facilitate more rapid deployment of large-scale land surface models.

The current research investigated, as a representative study case, the sediment accumulated in the Poechos Reservoir (located on the west coast of northern Peru) for retrospectively reconstructing the impact on sediment dynamics (1978–2019) of extreme phases of the El Niño–Southern Oscillation, land cover changes after humid periods and agricultural expansion along the riverine system.

The exceptional flood of July 2021 in central Europe impacted Belgium severely. This study aims to characterize rainfall amounts in Belgium from 13 to 16 July 2021 based on observational data (i.e., rain gauge data and a radar-based rainfall product). The spatial and temporal distributions of rainfall during the event aredescribed. In order to document such a record-breaking event as much as possible, the rainfall data are shared with the scientific community on Zenodo for further studies.

This study proposes a model to predict soil hydraulic properties (SHPs) of constructed Technosols for urban greening. The SHPs are determined by the Technosol composition and describe their capacity to store and supply water to plants. The model predicts SHPs of any binary mixture based on the SHPs of its two pure components, facilitating simulations of flow and transport processes before production. This can help create Technosols designed for efficient urban greening and water management.

In our study, we tested the utility and skill of a state-of-the-art forecasting product for the prediction of regional crop productivity using a land surface model. Our results illustrate the potential value and skill of combining seasonal forecasts with modelling applications to generate variables of interest for stakeholders, such as annual crop yield for specific cash crops and regions. In addition, this study provides useful insights for future technical model evaluations and improvements.

In this paper, we use a novel surface nuclear magnetic resonance (SNMR) method for rapid high-quality data acquisition. The SNMR results from more than 100 soundings in three different case studies were used to map groundwater. The soundings successfully track the water table through the three areas and are compared to boreholes and other geophysical measurements. The study highlights the use of SNMR in hydrological surveys and as a tool for regional mapping of the water table.