We describe a socio-hydrologic model that couples an agent-based model (ABM) of human decision-making with a hydrologic model. We establish this model for a typical agricultural watershed in Iowa, USA, and simulate the evolution of large discharge events over a 47-year period under changing land use. Using this modeling approach, relationships between seemingly unrelated variables such as crop markets or crop yields and local peak flow trends are quantified.

With the help of a 3-D computer model we examined how long the water of different rain events stays inside small catchments before it is discharged and how the nature of this discharge is controlled by different catchment and climate properties. We found that one can only predict the discharge dynamics when taking into account a combination of catchment and climate properties (i.e., there was not one single most important predictor). Our results can help to manage water pollution events.

Many previous studies using offline drought indices report that future warming will increase worldwide drought. However, this contradicts observations/projections of vegetation greening and increased runoff. We resolved this paradox by re-calculating the same drought indices using direct climate model outputs and find no increase in future drought as the climate warms. We also find that accounting for the impact of CO₂ on plant transpiration avoids the previous overestimation of drought.

Commercial microwave links (CMLs), which form large parts of the backhaul from the ubiquitous cellular communication networks, can be used to estimate path-integrated rainfall rates. This study presents the processing and evaluation of the largest CML data set to date, covering the whole of Germany with almost 4000 CMLs. The CML-derived rainfall information compares well to a standard precipitation data set from the German Meteorological Service, which combines radar and rain gauge data.

BARRA is a high-resolution reanalysis dataset over the Oceania region. This study evaluates the performance of sub-daily BARRA precipitation at point and spatial scales over Australia. We find that the dataset reproduces some of the sub-daily characteristics of precipitation well, although it exhibits some spatial displacement errors, and it performs better in temperate than in tropical regions. The product is well suited to complement other estimates derived from remote sensing and rain gauges.

There is a growing need for information about possible changes to water resource availability in the future due to climate change. Large-scale outputs from global climate models need to be translated to finer-resolution spatial scales before hydrological modelling. Biases in this downscaled data often need to be corrected. We show that usual bias correction methods can retain residual biases in multi-day occurrences of rainfall, which can result in biases in modelled runoff.

This paper assesses the suitability of bias-corrected (BC) WRF daily rainfall across the state of Victoria, Australia, for input to hydrological models to determine plausible climate change impacts on runoff. It compares rainfall and runoff changes using BC WRF with those obtained from empirical scaling (ES) using raw WRF changes. It concludes that BC-derived changes are more plausible than ES-derived changes but that remaining biases in BC WRF daily data add uncertainty to runoff projections.

The hydrologic cycle is one of the greatest natural processes on Earth and strongly influences both regional and global climate as well as ecosystem functioning. Results from this study clearly show the central role trees play in regulating the water cycle of boreal catchments, implying that forest management impacts on stand structure as well as climate change effects on tree growth are likely to have large cascading effects on the way water moves through boreal forested landscapes.

Previous studies on water saving through food trade focussed either on comparing water productivities among countries or on analysing food trade in relation to national water endowments. Here, we consider, for the first time, both differences in water productivities and water endowments to analyse national comparative advantages. Our study reveals that blue water scarcity can be reduced to sustainable levels by changing cropping patterns while maintaining current levels of global production.

The water mass variation at and below the land surface is a major component of the water cycle that was first estimated using GRACE observations (2002–2017). Our analysis shows the advantages of the use of satellite observation for precipitation and evapotranspiration along with river discharge measurement to perform an indirect and coherent reconstruction of this water component estimate over longer time periods.

Isotopic labeling of soil water is a broadly used tool for tracing the origin of water extracted by plants and computing root water uptake (RWU) profiles with multisource mixing models. In this study, we show how a method such as this may misconstrue time series of xylem water isotopic composition as the temporal dynamics of RWU by simulating data collected during a tall fescue rhizotron experiment with an isotope-enabled physical soil–root model accounting for variability in root traits.

Using 50 members of one regional climate model and a processed-based hydrological model applied in four river basins in southern Ontario, this work focused on the winter streamflow projection uncertainties for the first half of 21st century. The results show a January–February increase of streamflow for the 50 projections due to early snowmelt and a rainfall increase. The streamflow projections are also modulated by the change of pressure patterns advecting different air masses over the region.

Permeability of natural systems exhibits heterogeneous spatial variations linked with the size of the measurement support scale. As the latter becomes coarser, the system appearance is less heterogeneous. As such, sets of permeability data associated with differing support scales provide diverse amounts of information. In this contribution, we leverage information theory to quantify the information content of gas permeability datasets collected with four diverse measurement support scales.

Floods and severe rainfall are among the major natural hazards in the Mediterranean basin. Though precipitation weather forecasts have improved considerably, precipitation estimation is still affected by errors that can deteriorate the hydrological forecast. To improve hydrological forecasting, a regional-scale meteorological–hydrological ensemble is presented. This allows for predicting potential severe events days in advance and for characterizing the uncertainty of the hydrological forecast.

A multinational assessment of radar's ability to capture heavy rain events is conducted. In total, six different radar products in Denmark, the Netherlands, Finland and Sweden were considered. Results show a fair agreement, with radar underestimating by 17 %-44 % on average compared with gauges. Despite being adjusted for bias, five of six radar products still exhibited strong conditional biases with intensities of 1–2% per mm/h. Median peak intensity bias was significantly higher, reaching 44 %–67%.

Environmental modelling is complex, and models often require the calibration of several parameters that are not able to be directly evaluated from a physical quantity or a field measurement. Based on our experience in hydrological modelling, we propose combining two algorithms to obtain a fast and accurate way of calibrating complex models (many parameters and many objectives). We built an R package, caRamel, so that this multi-objective calibration algorithm can be easily implemented.

Rainfall seasonal anomalies in a Mediterranean climate are assessed by using two distinct approaches: a static approach based on the standardized precipitation index and a dynamic approach that identifies the rainy season by considering rainfall magnitude, timing, and duration. The impact of rainfall seasonality on catchment-scale water balance components is evaluated through scenario-based simulations of the Soil Water Assessment Tool in the upper Alento River catchment in southern Italy.

Although geomorphic recovery is a key issue in many rivers worldwide, controlled floods have been rarely designed using geomorphological criteria. An integrated approach is used to assess the effects of different controlled-flood scenarios in a strongly regulated river. None of the controlled-flood strategies provide significant morphological benefits. Nevertheless, this study represents a significant contribution for the management and restoration of highly disturbed rivers.

This paper studies the impact of climate change on high and low flows and quantifies the contribution of uncertainty sources from representative concentration pathways (RCPs), global climate models (GCMs) and internal climate variability in extreme flows. Internal climate variability was reflected in a stochastic rainfall model. The results show the importance of internal climate variability and GCM uncertainty in high flows and GCM and RCP uncertainty in low flows especially for the far future.

Our field observation-based examination of flow path evolution, soil formation, and vegetation succession across 10 millennia shows how water flow paths and subsurface water storage are linked to the organization of evolving landscapes. The increase found in water storage and preferential flow paths with increasing soil age shows the effect of the complex interaction of vegetation and soil development on flow paths, water balance, and runoff formation during landscape evolution.

Quantifying the seasonal contributions of the runoff components, including groundwater, snowmelt, glacier melt, and rainfall, to streamflow is highly necessary for understanding the dynamics of water resources in glacierized basins given the vulnerability of snow- and glacier-dominated environments to the current climate warming. Our study provides the first comparison of two end-member mixing approaches for hydrograph separation in glacierized basins.

The impacts of different levels of global warming on the thermal structure of Lake Erken are assessed. We used the General Ocean Turbulence Model (GOTM) to simulate water temperature driven by meteorological scenarios supplied by the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) and tested its ability at different frequencies. Then, daily ISIMIP meteorological scenarios were disaggregated and assessed for the effects of climate change on lake thermal structure.

In the absence of discharge data in ungauged basins, remotely sensed river water level data, i.e. altimetry, may provide valuable information to calibrate hydrological models. This study illustrated that for large rivers in data-scarce regions, river altimetry data from multiple locations combined with GRACE data have the potential to fill this gap when combined with estimates of the river geometry, thereby allowing a step towards more reliable hydrological modelling in data-scarce regions.

Speleothems are powerful archives of past climate for understanding modern local hydrology and its relation to regional circulation patterns. We use a 3-year monitoring dataset to test the sensitivity of Waipuna Cave to seasonal changes and El Niño–Southern Oscillation (ENSO) dynamics. Drip water data suggest a fast response to rainfall events; its elemental composition reflects a seasonal cycle and ENSO variability. Waipuna Cave speleothems have a high potential for past ENSO reconstructions.