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Conventional MCDA techniques have been used in the field of water resources in the past. A GIS can offer an effective spatial data-handling tool that can enhance water resources modeling through interfaces with sophisticated models. However, GIS systems have a limited capability as far as the analysis of the value structure is concerned. The MCDA techniques provide the tools for aggregating the geographical data and the decision maker`s preferences into a one-dimensional value for analyzing alternative decisions. In other words, the MCDA allows multiple criteria to be used in deciding upon the best alternatives. The combination of GIS and MCDA capabilities is of critical importance in spatial multi-criteria analysis. The advantage of having spatial data is that it allows the consideration of the unique characteristics at every point. The purpose of this study is to identify, review, and evaluate the performance of a number of conventional MCDA techniques for integration with GIS. Even though there are a number of techniques which have been applied in many fields, this study will only consider the techniques that have been applied in floodplain decision-making problems. Two different methods for multi-criteria evaluation were selected to be integrated with GIS. These two algorithms are Compromise Programming (CP), Spatial Compromise Programming (SCP). The target region for a demonstration application of the methodology was the Suyoung River Basin in Korea.

A Study on the GIS-based Deterministic MCDA Techniques for Evaluating the Flood Damage Reduction Alternatives