Thesis (Ph. D.)--University of Hawaii at Manoa, 1995.Includes bibliographical references (leaves 132-137).Microfiche.xviii, 137 leaves, bound maps (some col.) 29 cmIn one out of every two years, 20 percent of Bangladesh is inundated. Floods that occur at frequencies of one in 5, 10, 20 and 50 years inundate 30, 37, 43, and 52 percent of the country, respectively. The nation pays a heavy price in human sufferings and property from these floods. The purpose of this research is to assemble a prototype decision support system that could enable extension agents to search for alternative ways to minimize flood damage to agricultural crops and policy makers to assess yield losses and prepare for food shortages. The prototype system consists of a crop simulation model for rice, a rule-based system for assessing rice yield loss from flooding and a geographic information system for aggregating site-specific flood damage into yield loss for the entire nation. The system is designed to accommodate more than one crop, but this study was restricted to the rice crop. It is able to simulate the growth, development and grain yield of rice varieties cultivated by Bangladeshi farmers in any location and season under a wide range of management options. Simulated rice yields for a flood-free crop is used as a basis for computing yield loss from floods of varying severity. A rule-based system called FLOODEX was developed to compute yield loss from flooding which is expressed as a percent of the simulated non-flooded grain yield and computed on the bases of yield loss from depth of submergence, duration of submergence, growth stage and clarity of water. The expected yield is a fraction of the simulated yield, and production for a homogeneous area is the product of yield and area. The geographic information system enables yield loss and production levels to be displayed spatially. A major constraint to early application of the system was the lack of site-specific input data to operate the crop simulation models. These data include a minimum set of crop, soil, and weather data for benchmark locations in the country. The immediate value of this system may lie in its capacity to serve as a framework for organizing interdisciplinary research and prioritizing resource allocation
