Background

Integrating modelling has been shown as the best available technique to provide data for catchments where there are no biophysical data and, thus, a valuable procedure to provide data as a management resource within Integrated Catchment Management (ICM) practices. The main hypothesis behind our work is that theoretical river networks and the Network Dynamic Hypothesis will provide a better physical basis for the prediction of ecological consequences to environmental changes and/or restoration and engineering works in rivers. The high complexity of fluvial systems will be better represented by river networks, which have been shown as capturing successfully the hierarchical and spatial organisation of fluvial systems, and, thus, by coupling modelled data from different components of the fluvial system with river networks, we expect to elucidate which are the biophysical relationships that account for the largest variability in fluvial systems. Moreover, given that different climates originate different hydrological patterns we also expect that the interaction between watershed dynamics and the spatial structure of river networks will generate different biophysical patterns in Atlantic and Mediterranean catchments. The implementation of Spatial Decision Support Systems has also been shown as the most efficient tool for ICM, and we expect to improve the methodology by coupling river networks and integrated modelling. Finally, few studies have deal with multiple or cumulative effects of restoration and/or engineering works, but probability network models have been shown as been able to capture the high complexity of relationships and feedback effects of the different components of the fluvial systems and, thus, we expect that the integration of river networks with probability network models will constitute the best available structural basis to predict the ecological consequences of environmental change.