Using multiple-criteria decision-making techniques for eco-environmental vulnerability assessment: a case study on the Chi-Jia-Wan Stream watershed, Taiwan View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2009-07-24

AUTHORS

Pi-Hui Huang, Jing-Shyan Tsai, Wen-Tzu Lin

ABSTRACT

The Chi-Jia-Wan Stream watershed, located in the area of the upstream Da-Chia River in central Taiwan, is famous for slopeland agriculture and the land-locked salmon. Improper agricultural activities have caused apparent ecosystem vulnerability and sensitivity. In this study, a system that combined three watershed-based environmental indicators with multiple-criteria decision-making techniques, the Analytical Hierarchy Process, and the Preference Ranking Organization METHod for Enrichment Evaluations was developed to assess eco-environmental vulnerability. The composite evaluation index system was set up including sediment, runoff, and nutrient factors. Supported by geographic information system and K-means clustering and taking the subwatershed as the evaluation unit, the vulnerability is classified into four levels: potential, low, moderate, and high. The evaluated results show that 8.82% of subwatersheds (six subwatersheds) are in the moderately and highly vulnerable zones. These subwatersheds represent vertical-belt distribution, mainly concentrated in the right side of the studied area and near the riparian zone along the Chi-Jia-Wan Stream. The exploited farmland in the moderately and highly vulnerable zones is about 142.21 ha, occupying 75.38% of the total farmland in the studied watershed. These seriously vulnerable zones that have caused degradation in the quality of the eco-environment should be treated with more best management practices for eco-environmental rehabilitation. Additionally, the proposed model can effectively evaluate the eco-environmental vulnerability grade for reference in policy planning and ecological restoration in this area. More... »

PAGES

141-158

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10661-009-1098-z

DOI

http://dx.doi.org/10.1007/s10661-009-1098-z

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1017213977

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/19629735


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