Advances in computational tools and modelling techniques combined with enhanced process knowledge have, in recent decades, facilitated a rapid progress in hydrologic modelling. From the use of traditional lumped models, the hydrologic science has moved to the much more complex, fully distributed models that exude an enhanced knowledge of hydrologic processes. Despite this progress, uncertaintie...

[1] The primary advantage of radar observations of precipitation compared with traditional rain gauge measurements is their high spatial and temporal resolution and large areal coverage. Unfortunately, radar data require vigorous quality control before being converted into precipitation products that can be used as input to hydrologic models. In this study we coupled a physically based atmosphe...

Highly resolved precipitation forecasts are necessary in many applications, especially in mountain meteorology and flash flood forecasts for smallto medium-sized alpine watersheds. Here we present precipitation forecasts simulated by the limited area model ALADIN applying different grid resolutions (1x = 10 km and 4 km). Target area of the investigations is the Alpine Ticino-Verzasca-Maggia wat...

In this paper, the issue of nonlinear sensitivity analysis for dimensionality reduction in hydrologic model calibration is discussed, and a novel method to quantify the sensitivity of each parameter that considers the nonlinear relationship in the model is presented. The method is based on computing the absolute variation of the nonlinear function represented by the model in its parameter space...

Models are widely used to assess hydrologic impacts of land-management, land-use change and climate change. Two hydrologic models with different spatial scales, MIKE SHE (spatially distributed, watershed-scale) and DRAINMOD (lumped, fieldscale), were compared in terms of their performance in predicting stream flow and water table depth in a first-order forested watershed in coastal South Caroli...

Study of hydro-climatology at a range of temporal scales is important in understanding and ultimately mitigating the potential severe impacts of hydrological extreme events such as floods and droughts. Using daily in-situ data over the last two decades combined with the recently available multiple-years satellite remote sensing data, we analyzed and simulated, with a distributed hydrologic mode...

Distributed physical models for the space-time distribution of water, energy, vegetation, and mass flow require new strategies for data representation, model domain decomposition, a-priori parameterization, and visualization. The Geographic Information System (GIS) has been traditionally used to accomplish these data management functionalities in hydrologic applications. However, the interactio...