The capacity to discern surface water improved as satellites became more available. Because remote sensing data is discontinuous, integrating models with satellite observations will improve knowledge of water resources. However, given the current limitations (e.g., parameter errors) of water resource modeling, merging satellite data with simulations is problematic. Integrating observations and models with the unique approaches given here can lead to a better estimation of surface water dynamics.

Reservoir regulation affects various streamflow characteristics. Still, information on when water is stored in and released from reservoirs is hardly available. We develop a statistical model to reconstruct reservoir operation signals from observed streamflow time series. By applying this approach to 74 catchments in the Alps, we find that reservoir management varies by catchment elevation and that seasonal redistribution from summer to winter is strongest in high-elevation catchments.

Knowing the severity of an extreme event is of particular importance to hydrology and water policies. In this paper we propose a mixed distribution approach for low flows. It provides one consistent approach to quantify the severity of summer, winter, and annual low flows based on their respective annualities (or return periods). We show that the new method is much more accurate than existing methods and should therefore be used by engineers and water agencies.

We present a novel framework to estimate how much water is lost by ephemeral rivers using satellite imagery and machine learning. This framework proved to be an efficient approach, requiring less fieldwork and generating more data than traditional methods, at a similar accuracy. Furthermore, applying this framework improved our understanding of the water transfer at our study site. Our framework is easily transferable to other ephemeral rivers and could be applied to long time series.

This paper presents a new analytical concept to answer long-lasting questions of the cosmic-ray neutron sensing community, such as what is the influence of a distant area or patches of different land use on the measurement signal? or is the detector sensitive enough to detect a change of soil moisture (e.g. due to irrigation) in a remote field at a certain distance? The concept may support signal interpretation and sensor calibration, particularly in heterogeneous terrain.

Riparian vegetation has been identified as a strategy to control rising stream temperatures by shading streams. Riparian vegetation is included within a sub-basin-scale hydrological model and evaluated for full and efficient restoration scenarios. Results showed average temperature reductions of 0.91 and 0.86 °C for full and efficient riparian restoration, respectively. Notwithstanding the similar benefits, efficient restoration was 14.4 % cheaper than full riparian vegetation restoration.

Water can move between river catchments via the subsurface, termed intercatchment groundwater flow (IGF). We show how a perceptual model of IGF can be developed with relatively simple geological interpretation and data requirements. We find that IGF dynamics vary in space, correlated to the dominant underlying geology. We recommend that IGF loss functions may be used in conceptual rainfall–runoff models but should be supported by perceptualisation of IGF processes and connectivities.

This paper describes an experiment and modeling of the hydrological response of desiccation cracks under long-term wetting–drying cycles. We developed a new dynamic dual-permeability model to quantify the dynamic evolution of desiccation cracks and associated preferential flow and moisture distribution. Compared to other models, the dynamic dual-permeability model could describe the experimental data much better, but it also provided an improved description of the underlying physics.

Here we present a hydrological framework for understanding the mechanisms supporting the persistence of water in pools along non-perennial rivers. Pools may collect water after rainfall events, be supported by water stored within the river channel sediments, or receive inflows from regional groundwater. These hydraulic mechanisms can be identified using a range of diagnostic tools (critiqued herein). We then apply this framework in north-west Australia to demonstrate its value.

The long-term effects of climate change will include an increase in lake surface and deep water temperatures. Incorporating up to 6 decades of limnological monitoring into an improved 1D lake model approach allows us to predict the thermal regime and oxygen solubility in four peri-alpine lakes over the period 1850–2100. Our modeling approach includes a revised selection of forcing variables and provides a way to investigate the impacts of climate variations on lakes for centennial timescales.