[1] A novel method is presented for model uncertainty estimation using machine learning techniques and its application in rainfall runoff modeling. In this method, first, the probability distribution of the model error is estimated separately for different hydrological situations and second, the parameters characterizing this distribution are aggregated and used as output target values for buil...

Spatially distributed modelling is an important instrument for studying the hydrological cycle, both concerning its present state as well as possible future changes in climate and land use. Results of such simulations are particularly relevant for the fields of water resources, natural hazards and hydropower. The semi-distributed hydrological modelling system PREVAH (PREecipitation-Runoff-EVApo...

The MINERVE project was initiated for flood management in the Upper Rhone river basin. Its first goal is the prediction of floods. The second one is the optimum management of the complex system of hydropower plants located in the basin in order to diminish the peak discharge in the Rhone River and its tributaries. The MINERVE Interactive Decision Support (MINDS) proposes turbine and bottom outl...

Land use change and climate variability are two key factors impacting watershed hydrology, which is strongly related to the availability of water resources and the sustainability of local ecosystems. This study assessed separate and combined hydrological impacts of land use change and climate variability in the headwater region of a typical arid inland river basin, known as the Heihe River Basi...

Assessing the impact of climate change on streamflow is critical to understanding the changes to water resources and to improve water resource management. The use of hydrological models is a common practice to quantify and assess water resources in such situations. In this study, two hydrological models with different structures, e.g., a physically-based distributed model Liuxihe (LXH) and a lu...

The prototype discussed in this article retrieves Essential Terrestrial Variable (ETV) web services and uses data-model workflows to transform ETV data for hydrological models in a distributed computing environment. The ETV workflow is a service layer to 100's of terabytes of national datasets bundled for fast data access in support of watershed modeling using the United States Geological Surve...

Low-flow is the flow of water in a river during prolonged dry weather. This paper investigated the uncertainty originating from hydrological model calibration and structure in low-flow simulations under climate change conditions. Two hydrological models of contrasting complexity, GR4J and SWAT, were applied to four sub-watersheds of the Yamaska River, Canada. The two models were calibrated usin...

Achieving a successful long-term strategy for sustainable water resource management of the Murray-Darling Basin (MDB) involves improving our understanding of the integrated hydrological system and assessing the impacts of land use and climate change upon this system. A methodology is currently being developed with the potential for addressing these issues by way of a new satellite technology sy...

The Indus basin heavily depends on its upstream mountainous part for the downstream supply of water while downstream demands are high. Since downstream demands will likely continue to increase, accurate hydrological projections for the future supply are important. We use an ensemble of statistically downscaled CMIP5 General Circulation Model outputs for RCP4.5 and RCP8.5 to force a cryospheric-...