Multi-Criteria Analysis for Effective Rain Water Harvesting Site Identification in Konso Zone, Ethiopia

IF 4.4 4区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Fitsum Tsehay Bereded, Yohannes Mehari Andiye, Tarun Kumar Lohani
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Abstract

The Konso area of southern Ethiopia has limited resources and is highly vulnerable to climate change. Traditional agriculture practices in this region are adversely affected by water scarcity. The purpose of this study is to determine the most effective site for rainwater harvesting (RWH) through multi-criteria analysis combined with Geographic Information Sysytem. The decision-making criteria used in this study included rainfall, land cover, curve number, topographic wetness index, slope, distance from agriculture, lineament density, geology, and road and city distance. These criteria are categorized into five suitability levels based on their significance for rainwater harvesting using an analytical and hierarchical process (AHP). The study also mapped the restricted area, which includes the built-up area and water accounting for ≈6% of the total area. The area with very high suitability for RWH is ≈658 km2, representing 28.3% of the total area. The suitability model is validated by cross-checking existing RWH ponds with the appropriate map. It is found that most of the existing RWH ponds are located within high to moderately suitable zones, accounting for 92.6% of the total area. This research highlights the effectiveness of integrating MCA with GIS in identifying suitable RWH sites, especially in arid, semi-arid, and data-scarce areas. The weighted overlay process (WOP), available data, and methods are utilized to achieve this goal.

Abstract Image

埃塞俄比亚 Konso 区雨水收集点有效识别的多重标准分析
埃塞俄比亚南部的孔索地区资源有限,极易受到气候变化的影响。该地区的传统农业做法受到缺水的不利影响。本研究的目的是通过多标准分析结合地理信息系统来确定最有效的雨水收集地点。本研究中使用的决策标准包括降雨量、土地覆盖、曲线数、地形湿度指数、坡度、与农业的距离、地形密度、地质以及道路和城市的距离。根据这些标准对雨水收集的重要性,使用分析和层次过程(AHP)将其分为五个适宜性级别。研究还绘制了限定区域,限定区域包括建成区和水体约占总面积的6%。高度适宜水暖区面积约658 km2,占总面积的28.3%。通过与适当的地图交叉检查现有的RWH池塘来验证适用性模型。研究发现,现有的水塘大部分位于高至中等适宜区域内,占总面积的92.6%。该研究强调了将MCA与GIS相结合在确定合适的RWH地点方面的有效性,特别是在干旱、半干旱和数据稀缺的地区。加权叠加过程(WOP)、可用数据和方法被用来实现这一目标。
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来源期刊
Global Challenges
Global Challenges MULTIDISCIPLINARY SCIENCES-
CiteScore
8.70
自引率
0.00%
发文量
79
审稿时长
16 weeks
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