Document Type

Thesis - University Access Only

Award Date


Degree Name

Doctor of Philosophy (PhD)

Department / School

Civil and Environmental Engineering


Flooding is a natural phenomenon that has increasing impact on man and his environment. Nowhere is that more evident than in the devastation wrought by rising waters inundating the homes and farms of East Africa. Flooding only serves to exacerbate the crisis faced by the people of that region as they struggle against famine and civil war. Crisis fatigue, declining budgets, and competing disasters make it ever more important to utilize the funds available to target relief to the areas of greatest need. The spatial decision support system developed for flood risk monitoring in East Africa, lies at the heart of this effort. Utilizing cutting-edge technology to solve age-old problems may seem incongruous at first glance, but remote sensing offers a new perspective, a "bird's eye view", that simplifies our understanding of the problem. Satellite imagery, historical rainfall-runoff data, digital elevations and hydro logic derivatives, vegetation and land use information, and meteorological and climate data all combine to effectively model the physical processes at work. This decision support system predicts flood risk for a region based on a convergence of evidence from rainfall-runoff models and other data. By integrating the flood risk data into a Geographic Information System (GIS) with population density, economic data, and transportation routes, it provides timely and invaluable information on the location and impact of possible flooding for relief agency planning purposes. The GIS offers another perspective, a worm's eye view, which adds a ground-level sense of collocation and adjacency to the data layers used in the models. And since this spatial decision support system is designed to be Internet-based, the flood risk information and needs analysis could be distributed worldwide simultaneously. Significant advantages over previous flood risk monitoring methods have been incorporated into this spatial decision support system. First, no on-ground monitoring network is required since all of the data is derived from satellite imagery. Second, integration of rainfall-runoff models into the spatial decision support system provides a valuable linkage between risk predictions and subsequent decision analysis. And last, but certainly not least, is the enveloping geographic information system architecture that provides the basis for all of the visualization tools which bring the spatial data to life and greatly enhance the usability of the system for decision makers.

Library of Congress Subject Headings

Flood control -- Africa, East Decision support systems Geographic information systems



Number of Pages



South Dakota State University