Robust Decision-Making Technique for Strategic Environment Assessment with Deficient Information

Abstract

This study developed a framework for an evaluative decision–making system that compensates for information deficiencies by considering the sensitivity of weight factor criteria. The developed decision–making system was applied to the strategic environmental assessment (SEA) for dam planning in South Korea. The SEA investigation included ten potential dam sites (four sites in the Han River, four in the Nakdong River, and two in the Geum River), performing an evaluative comparison of dam construction effects using environmental adequacy criteria and ranking the ten potential sites appropriately. Six different deficient information filling methods were applied: the normal and uniform distribution generations, Maximax, Maximin, Hurwicz, and the equal likelihood criterion. Results indicated sites GM2, HN3, ND4, and GM2 demonstrated the highest environmental adequacies across the combined effected rivers, the Han River, the Nakdong River, and the Geum Rivers, respectively. The probabilistic distribution generations, Hurwicz and the equal likelihood criterion methods produced similar priority scores and rankings based on different river conditions; however, the Maximax and Maximin methods calculated different priority scores and rankings, indicating users should be careful when applying the latter two methods for use in a decision support system (DSS) with deficient information. In future works, it will be necessary to apply other deficient data conditions or SEA examples to perform a more robust verification of the proposed framework.