Computational Modeling of River Flow, Sediment Transport, and Bed Evolution Using Remotely Sensed Data

Abstract

Abstract : This project is focused on combining remotely sensed data for river bathymetry with computational flow models in order to make detailed predictions of flow, sediment transport and bed morphologic change in rivers. The long-term goals include developing a better characterization of the accuracy and range of applicability of remote sensing techniques for collection of river bathymetry data, assessment of errors associated with computational river model applications using remotely sensed information relative to similar applications using conventional surveying techniques, and development and distribution of public domain software for applying river models using remotely sensed data. These goals are driven by the increasing demand for river modeling applications for assessment of flow pattern, navigation, habitat, flood inundation and morphologic variation in river systems where conventional bathymetric surveys are not available and access is limited. Furthermore, even in certain situations where conventional surveys can be carried out, the use of remotely sensed data is an attractive alternative due to its relative speed and safety. The key to developing this methodology is the collection of appropriate field data in concert with modeling applications to better characterize the range of applicability and potential error; this is the central focus of the work described here.