4.0 Article

Flood Risk Analysis in Lower Part of Markham River Based on Multi-Criteria Decision Approach (MCDA)

期刊

HYDROLOGY
卷 3, 期 3, 页码 -

出版社

MDPI
DOI: 10.3390/hydrology3030029

关键词

GIS; rating; weight; multi-criteria decision approach; flood risk mapping

向作者/读者索取更多资源

Papua New Guinea is blessed with a plethora of enviable natural resources, but at the same time it is also cursed by quite a few natural disasters like volcanic eruptions, earthquakes, landslide, floods, droughts etc. Floods happen to be a natural process of maintaining the health of the rivers and depth of its thalweg; it saves the river from becoming morbid while toning up the fertility of the riverine landscape. At the same time, from human perspective, all these ecological goodies are nullified when flood is construed overwhelmingly as one of the most devastating events in respect to social and economic consequences. The present investigation was tailored to assess the use of multi-criteria decision approach (MCDA) in inland flood risk analysis. Categorization of possible flood risk zones was accomplished using geospatial data sets, like elevation, slope, distance to river, and land use/land cover, which were derived from digital elevation model (DEM) and satellite image, respectively. A pilot study area was selected in the lower part of Markham River in Morobe Province, Papua New Guinea. The study area is bounded by 146 degrees 31' to 146 degrees 58' east and 6 degrees 33' to 6 degrees 46' south; covers an area of 758.30 km(2). The validation of a flood hazard risk map was carried out using past flood records in the study area. This result suggests that MCDA within GIS techniques is very useful in accurate and reliable flood risk analysis and mapping. This approach is convenient for the assessment of flood in any region, specifically in no-data regions, and can be useful for researchers and planners in flood mitigation strategies.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.0
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据