In the present study the flood trends have been assessed for a large sample of 171 basins located in southern France, which has a Mediterranean climate. Results show that, despite the increase in rainfall intensity previously observed in this area, there is no general increase in flood magnitude. Instead, a reduction in the annual number of floods is found, linked to a decrease in soil moisture caused by the increase in temperature observed in recent decades.

Variation in stemflow (rain water running down the stem) enhances the formation of flow hot spots at the forest floor. Investigating drivers based on detailed measurements, we find that forest structure affects stemflow, both for individual trees and small communities. Densely packed forest patches received more stemflow, due to a higher proportion of woody structure and canopy morphology adjustments, which increase the potential for flow path generation connecting crowns and soil.

We develop a new indicator of reservoir effects, called the rainfall–reservoir composite index (RRCI). RRCI, coupled with the effects of static reservoir capacity and scheduling-related multivariate rainfall, has a better performance than the previous indicator in terms of explaining the variation in the downstream floods affected by reservoir operation. A covariate-based flood frequency analysis using RRCI can provide more reliable downstream flood risk estimation.

River flow regimes are expected to change and so are extreme flow regimes. We propose two methods for estimating extreme flow regimes and show on a data set from Switzerland how these extreme regimes are expected to change. Our results show that changes in low- and high-flow regimes are distinct for rainfall- and melt-dominated regions. Our findings provide guidance in water resource planning and management.

This study investigates the impact of dam-induced hydrologic alterations and modification of riparian buffers on stream temperatures and thermal habitat for aquatic species. We enhanced and applied a model system (DHSVM-RBM) that couples a distributed hydrologic model, DHSVM, with the distributed stream temperature model, RBM, in the Farmington River basin in the Connecticut River system, which includes varying types of watershed development (e.g., deforestation and reservoirs).

We found that small dams in rivers alter the thermal regimes of downstream waters in two distinct ways: either only the downstream daily minimum temperatures increase, or both the downstream daily minimum and maximum temperatures increase. We further show that only two physical dam characteristics can explain this difference in temperature response: (1) residence time, and (2) surface area. These results may help managers prioritize efforts to restore the fragmented thermalscapes of rivers.

We provide evidence of high groundwater storage and flow in catchments with active glaciers. Groundwater is found within gravels at the front of glaciers and replenished by both ice melt and precipitation. We studied a glacier in Iceland for 3 years, characterising the aquifer properties and measuring groundwater, river flow and precipitation. The results are important for accurately measuring meltwater and show that groundwater can provide strategic water supplies in de-glaciating catchments.

This paper presents the application of a new approach for calculating the path of a pressure transient in a heterogeneous porous medium containing a slightly compressible fluid. Unlike previous asymptotic approaches, the expressions for the path and travel time are valid in the presence of rapid variations in material properties. The technique is applied to both synthetic transient pressure variations from a test example and actual field data from a field experiment in Widen, Switzerland.

Recently, the first global groundwater models were developed to better understand surface-water–groundwater interactions and human water use impacts. However, the reliability of model outputs is limited by a lack of data as well as model assumptions required due to the necessarily coarse spatial resolution. In this study we present the first global maps of model sensitivity according to their parameterization and build a foundation to improve datasets, model design, and model understanding.

It is important to understand historic droughts in order to plan and prepare for possible future events. In this study we use the standardised streamflow index for 1891–2015 to systematically identify, characterise and rank hydrological drought events for 108 near-natural UK catchments. Results show when and where the most severe events occurred and describe events of the early 20th century, providing catchment-scale detail important for both science and planning applications of the future.

This study explores novel modelling avenues using machine learning in combination with process-based models to predict the shallow water table at high spatial resolution. Due to climate change and anthropogenic impacts, the shallow groundwater is rising in many parts of the world. In order to adapt to risks induced by groundwater flooding, new modelling tools need to emerge. In this study, we found that machine learning is capable of reaching the required accuracy and resolution.

This work demonstrates a new approach to obtain flood level trend information from surveillance footage with minimal prior information. A neural network trained to detect flood water is applied to video frames to create a qualitative flooding metric (namely, SOFI). The correlation between the real water trend and SOFI was found to be 75 % on average (based on six videos of flooding under various circumstances). SOFI could be used for flood model calibration, to increase model reliability.

High-resolution regional climate modeling that resolves convection was conducted over western Canada for the current climate and a high-end greenhouse gas emission scenario by 2100. The simulation demonstrates its good quality in capturing the temporal and spatial variation in the major hydrometeorological variables. The warming is stronger in the northeastern domain in the cold seasons. It also shows a larger increase in high-intensity precipitation events than moderate and light ones by 2100.

This paper examines the influence of the subsurface structure on water routing, water residence times, and the hydrologic response of distinct groundwater stores and further investigates their contribution to streamflow. We conclude that deep groundwater from the fractured aquifer system, rather than shallow groundwater, is the dominant source of streamflow, which highlights the need to better characterize the deep subsurface of mountain systems using interdisciplinary studies such as this one.

A database of soil moisture measurements from the middle Heihe River basin of China was used to test the potential of a soil moisture database in estimating the soil water balance components (SWBCs). We determined SWBCs using a method that combined the soil water balance method and the inverse Richards equation. This work confirmed that relatively reasonable estimations of the SWBCs in coarse-textured sandy soils can be derived using soil moisture measurements.

Dissolved methane in Lake Kivu (East Africa) represents a precious energy deposit, but the high gas loads have also been perceived as a threat by the local population. Our measurements confirm the huge amount of methane and carbon dioxide present, but do not support the current theory of a significant recharge. Direct measurements of gas pressure indicate no imminent danger due to limnic eruptions. A continuous survey is mandatory to support responsible action during industrial exploitation.

In this paper we address one of the big challenges in snow hydrology, namely the accurate simulation of the seasonal snowpack in ungauged regions. We do this by assimilating satellite observations of snow cover into a modelling framework. Importantly (and a novelty of the paper), we include a clustering approach that permits highly efficient ensemble simulations. Efficiency gains and dependency on purely global datasets, means that this method can be applied over large areas anywhere on Earth.

We characterised for the first time the rainfall microphysics for Southern Hemisphere temperate latitudes. Co-located instruments were deployed to provide information on the sampling effect and spatio-temporal variabilities at micro scales. Substantial differences were found across the instruments, increasing with increasing values of the rain rate. Specific relations for reflectivity–rainfall are presented together with related uncertainties for drizzle and stratiform and convective rainfall.

Water management in mountains is challenging when there are no climate data of good quality. This can be addressed by using statistical methods or by including alternative sources of information. This project tests a relatively complex statistical method and compares it with simpler alternatives while including satellite data. It was found that the simple alternative may behave as well as the complex one, and how good the alternative sources of information are could also be established.

A new stochastic rainfall model evaluation framework is introduced, with three key features: (1) streamflow-based, to directly evaluate modelled streamflow performance, (2) virtual, to avoid confounding errors in hydrological models or data, and (3) targeted, to isolate errors according to specific sites/months. The framework identified the importance of rainfall in the wetting-up months for providing reliable predictions of streamflow over the entire year despite their low flow volumes.

This study evaluated the performance of 36 CMIP5 GCMs in simulating seasonal precipitation and maximum and minimum temperature over Pakistan using spatial metrics (SPAtial EFficiency, fractions skill score, Goodman–Kruskal's lambda, Cramer's V, Mapcurves, and Kling–Gupta efficiency) for the period 1961–2005. NorESM1-M, MIROC5, BCC-CSM1-1, and ACCESS1-3 were identified as the most suitable GCMs for simulating all three climate variables over Pakistan.

Flowing stream networks extend and retract seasonally and in response to precipitation. This affects the distances and thus the time that it takes a water molecule to reach the flowing stream and the stream outlet. When the network is fully extended, the travel times are short, but when the network retracts, the travel times become longer and more uniform. These dynamics should be included when modeling solute or pollutant transport.

While conventional approaches focus on flood designs at individual locations, there are many situations requiring an understanding of spatial dependence of floods at multiple locations. This research describes a new framework for analyzing flood characteristics across civil infrastructure systems, including conditional and joint probabilities of floods. This work leads to a new flood estimation paradigm, which focuses on the risk of the entire system rather than each system element in isolation.

This study presents an analysis of 135 soil moisture profiles for identification of the spatial and temporal preferential flow occurrence in a complex landscape. Especially dry conditions and high rainfall intensities were found to increase preferential flow occurrence in soils. This results in a seasonal pattern of preferential flow with a higher occurrence in summer. During this time grasslands showed increased flow velocities, whereas forest sites exhibited a higher amount of bypass flow.