The international research project QBic 3 (Quebec-Bavarian Collaboration on Climate Change) aims at investigating the potential impacts of climate change on the hydrology of regional scale catchments in Southern Quebec (Canada) and Bavaria (Germany). Yet, the actual change in river runoff characteristics during the next 70 years is highly uncertain due to a multitude of uncertainty sources. The...

[1] We determine a regional spatiotemporal gravity field over northern South America including the Amazon region using GRACE inter-satellite range-rate measurements by application of a wavelet-based multiresolution technique. A major advantage of this method is that we are able to represent the Amazon hydrological signals in form of time series of detail signals with level-dependent temporal re...

Abstract. Distributed hydrological models rely on hydrography data such as flow direction, river length, slope and width. For large-scale applications, many of these still a few direction datasets, which are often manually derived. We propose the Iterative Hydrography Upscaling (IHU) method to upscale high-resolution typically coarser resolutions distributed models. The IHU aims preserve upstre...

This study is a part of an on-going Danish research project HYACINTS. A key outcome of the project is a fully coupled model setup using the HIRHAM regional climate model and the MIKE SHE hydrological model with the intent of improving hydrological predictions. We here present results from the initial studies prior to the coupling performed to aid in the decision of optimal climate model domain ...

A watershed simulation and forecasting system is widely used in Finland for simulation of hydrological cycle and for making real-time forecasts. The system is based on a watershed model. This was based originally on the HBV-model and simulates the hydrological cycle using standard meteorological data. The model simulates the whole land area of Finland, including cross-border watersheds. This is...

Two recent studies have suggested that neural network modelling offers no worthwhile improvements in comparison to the application of weighted linear transfer functions for capturing the non-linear nature of hydrological relationships. The potential of an artificial neural network to perform simple non-linear hydrological transformations under controlled conditions is examined in this paper. Ei...