The distributed lag model (DLM), used most prominently in air pollution studies, finds application wherever the effect of a covariate is delayed and distributed through time. We specify modified formulations of DLMs to provide computationally attractive, flexible varying-coefficient models that are applicable in any setting in which lagged covariates are regressed on a time-dependent response. ...

Topography is an important land-surface characteristic that affects most aspects of the water balance in a catchment, including the generation of surface and sub-surface runoff; the flow paths followed by water as it moves down and through hillslopes and the rate of water movement. All of the spatially explicit fully distributed hydraulic and hydrological models use topography (represented by t...

The coupling of hydrological distributed models to numerical weather prediction outputs is an important issue for hydrological applications such as forecasting of flood events. Downscaling meteorological predictions to the hydrological scales requires the resolution of two fundamental issues regarding precipitation, namely, (1) understanding the statistical properties and scaling laws of rainfa...

Spatial data infrastructures support the most common requirements of spatial information users –discovery, access, and visual overlay of datasets– however specialized users such as hydrological scientists require more advanced services for capturing, analyzing and processing huge volumes of data. To shift from locally-processed complex tasks to on-line, distributed service-data offers, we prese...

In recent years, forest fires frequency and intensity has increased, causing a new awareness about their impact not only on vegetation, but also on hydrological regime. Changes in vegetation influence the processes of interception and evapotranspiration, seriously affecting the hydrological cycle. Forest fires can also affect hydrological processes indirectly, altering the hydraulic properties ...

An operational hydrological ensemble forecasting system based on a meteorological ensemble prediction system (M-EPS) coupled with a hydrological model searches to capture the uncertainties associated with the meteorological prediction to better predict river flows. However, the structure of the hydrological model is also an important source of uncertainty that has to be taken into account. This...