We assimilated three satellite soil moisture retrievals based on different microwave frequencies into a hydrological model. Two sets of experiments were performed, first assimilating the retrievals individually and then assimilating each set of two retrievals jointly. Overall, assimilation improved agreement between model and field-measured soil moisture. Joint assimilation resulted in model performance similar to or better than assimilating either retrieval individually.

The soil water retention curve (SWRC) is fundamental to researching water flow and chemical transport in unsaturated media. However, the traditional prediction models underestimate the water content in the dry range of the SWRC. A method was therefore proposed to improve the estimation of the SWRC using a pore model containing slit-shaped spaces. The results show that the predicted SWRCs using the improved method reasonably approximated the measured SWRCs.

This research work focuses on the development of an innovative method for enhancing the predictive capability of macro-scale rainfall–runoff models by means of a geostatistical apporach. In our method, one can get enhanced streamflow simulations without any further model calibration. Indeed, this method is neither computational nor data-intensive and is implemented only using observed streamflow data and a GIS vector layer with catchment boundaries. Assessments are performed in the Tyrol region.

Drought is a natural hazard that has severe environmental and socioeconomic impacts around the globe. Here, we quantified the time taken for drought to propagate from precipitation droughts to soil moisture and streamflow droughts. Results show that propagation timescales are strongly related to climate type, with fast responses in tropical regions and slow responses in arid regions. Insight into the timescales of drought propagation globally may help improve seasonal drought forecasting.

Flooding in vulnerable and data-sparse regions such as the Limpopo basin in Southern Africa is a key concern. Data available to local flood managers are often limited, inconsistent or asymmetrically distributed. We demonstrate that freely available global datasets are well suited to provide essential information. Despite the poor performance of simulated discharges, these datasets hold potential in identifying damaging flood events, particularly for higher-resolution datasets and larger basins.

In high-latitude (> 60° N) watersheds, measuring the snowpack and predicting of snowmelt runoff are uncertain due to the lack of data and complex physical processes. This provides challenges for hydrological assessment and operational water management. Global re-analysis datasets have great potential to aid in snowpack representation and snowmelt prediction when combined with a distributed hydrological model, though they still have clear limitations in remote boreal forest and tundra environments.

This paper aims to compare freshwater quality scenarios under different land uses, related to ecosystem-based adaptation in subtropical headwaters. Using a spatially semi-distributed model, nitrate, total phosphorous loads and sediments yield were modeled in Brazilian catchments ranging from 7 to 1037 km². In short, we proposed the new hydrologic services index as a composite metric comparing water pollution levels for reference catchments related to the grey water footprint and water yield.

The curve number (CN) method is the most widely used approach for estimating runoff from rainfall. Despite its popularity, there is a conceptual flaw where CN varies with rainfall although it is assumed to be constant. In this paper, we describe theoretical analyses that show how this behavior is due to watershed heterogeneity, and we then provide simple modifications to the method to improve its runoff predictions. The findings will benefit hydrologists and watershed models that use CN method.

Geospatial technologies and OIP are promising tools to study the effect of demographic changes and LULC transformations on the spatiotemporal variations in the water quality (WQ) across a large river basin. Therefore, this study could help to assess and solve local and regional WQ-related problems over a river basin. It may help the policy makers and planners to understand the status of water pollution so that suitable strategies could be planned for sustainable development in a river basin.

It is important to understand potential impacts of climate change and human water use on streamflow and groundwater levels. This study used climate models with an integrated hydrologic model to project future streamflow and groundwater level in Tampa Bay for a variety of future water use scenarios. Impacts of different climate projections on streamflow were found to be much stronger than the impacts of different human water use scenarios, but both were significant for groundwater projection.

Providing reliable estimates of water fluxes at the continental scale is challenging. We extended a regional hydrological model to the entirety of South America and assessed its performance using multiple observations. After a comparison with global models, we show the extent to which estimates of daily river discharge can be improved, even by using global forcing data. Issues of global-/continental-scale modeling and future directions for simulating discharge in this continent are discussed.

Cross-validation of free-running bias-corrected climate change simulations against observations is misleading, because it is typically dominated by internal variability. In particular, a sensible bias correction may be rejected and a non-sensible bias correction may be accepted. We therefore propose to avoid cross-validation when evaluating bias correction of free-running bias-corrected climate change simulations. Instead, one should evaluate temporal, spatial and process-based aspects.

Groundwater is a significant water resource for humans and for groundwater-dependent vegetation. Several challenges to managing both groundwater resources and dependent vegetation include defining the location of dependent vegetation, the rate of groundwater use, and the depth of roots accessing groundwater. In this study we demonstrate a novel application of measurements of stable isotopes of carbon that can be used to identify the location, the rooting depth, and the rate of groundwater use.

Ephemeral snowpacks are snowpacks that persist for less than 2 months. We show that ephemeral snowpacks melt earlier and provide less soil water input in the spring. Elevation is strongly correlated with whether snowpacks are ephemeral or seasonal. Snowpacks were also more likely to be ephemeral on south-facing slopes than north-facing slopes at high elevations. In warm years, the Great Basin shifts to ephemerally dominant as rain becomes more prevalent at increasing elevations.

Peatlands are a major stock of carbon that can be released as dissolved organic carbon (DOC), affecting carbon balance and downstream water quality. This study investigates the impact of peatland restoration on water balance and DOC exports using a simple modelling approach. The results suggest that the restoration can affect the water balance and the dynamics of DOC in the peatland. However, there is no major impact in the quantity of DOC released in a short-term period (3 years).

Data assimilation methods like the ensemble Kalman filter (EnKF) can combine models and measurements to estimate states and parameters, but require a proper representation of uncertainties. In soil hydrology, model errors typically vary rapidly in space and time, which is difficult to represent. Inflation methods can account for unrepresented model errors. To improve estimations in soil hydrology, we designed a method that can adjust the inflation of states and parameters to fast varying errors.

Multiple satellite observations can be used for surface and subsurface soil moisture estimations. In this study, satellite observations along with a mathematical model were used to distribute and develop multiyear soil moisture profiles over the southeastern US. Such remotely sensed profiles become particularly useful at large spatiotemporal scales, can be a significant tool in data-scarce regions of the world, can complement various land and crop models, and can act as drought indicators etc.

Evaporation from wetlands, lakes and irrigation areas needs to be measured to understand water scarcity. So far, this has only been possible for small regions. Here, we develop a solution that can be applied at a very high resolution globally by making use of satellite observations. Our results show that 16% of global water resources evaporate before reaching the ocean, mostly from surface water. Irrigation water use is less than 1% globally but is a very large water user in several dry basins.

This study investigated how land use affects stream water sources and flow paths in an East African tropical montane area. Rainfall was identified as an important stream water source in the forest and smallholder agriculture sub-catchments, while springs were more important in the commercial tea plantation sub-catchment. However, 15 % or less of the stream water consisted of water with an age of less than 3 months, indicating that groundwater plays an important role in all land use types.

The feasibility of drought prediction is assessed in the Brazilian northeast. The models were provided by a regional agency and a European meteorological agency and downscaling was done using three empirical models. This work showed that the combination of different forecast and downscaling models can provide skillful predictions of drought events on timescales relevant to water managers. But the models also showed little to no skill for quantitative predictions of monthly precipitation.