{"title":"基于遥感和GIS技术的雨水收集点选择——以埃塞俄比亚南部达瓦盆地为例","authors":"Getachew Haile Wondimu","doi":"10.11648/j.ajme.20200604.12","DOIUrl":null,"url":null,"abstract":"Water is one of the vital requirements for life, economic and social development. Water scarcity affects the environmental, economic and developmental activities of an area. The rainfall in the sub-basins is often very local, erratic, unreliable and unevenly distributed over the whole area of Dawa sub-basin. The pastoral and agro-pastoral communities are usually vulnerable to drought. The present study was an attempt to describe the state of Rain Water Harvesting (RWH) techniques and the contribution of Remote Sensing and GIS technologies for this RWH in the Dawa Sub basin. The study was conducted using physiographic factors of Dawa sub basin. Landsat image with spatial resolution 30m were used to identify LU/LC types. The thematic layers used were land use/land cover, slope, soil, drainage and runoff from derived from Landsat and collateral data. The image processing software Erdas IMAGINE and GIS software were used to process the image and to establish a geo information system by comprising digital data set of satellite image, topography, soil, metrology, drainage density and metrology. This data was used to study RWH was used to study the watershed network in the Dawa sub basin and to identify areas generally suitable for water harvesting in order to determine water harvesting techniques for those sites. Analytical Hierarchy Process (AHP) was used to calculate weighting and the analysis result indicates that the sub-basin supports promising opportunity for the establishment and development of RWH structures. From the total area of 17,402.7 km 2 , The GIS evaluation predicts that 3,092.342 km 2 (22.853%) is extremely suitable, 4,524.221 km 2 (33.435%) is very suitable, 2,968.685 km 2 (21.939%) is suitable, 1,988.986 km 2 (14.7%) is less Suitable and 957.18 km 2 (7.07%) is not suitable for RWH. Keywords: GIS, Rainwater Harvesting (RWH), Remote Sensing (RS), Dawa Sub Basin DOI: 10.7176/JEES/10-9-03 Publication date: September 30 th 2020","PeriodicalId":208155,"journal":{"name":"American Journal of Modern Energy","volume":"88 25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Selection of Rainwater Harvesting Sites by Using Remote Sensing and GIS Techniques: A Case Study of Dawa Sub Basin Southern Ethiopia\",\"authors\":\"Getachew Haile Wondimu\",\"doi\":\"10.11648/j.ajme.20200604.12\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Water is one of the vital requirements for life, economic and social development. Water scarcity affects the environmental, economic and developmental activities of an area. The rainfall in the sub-basins is often very local, erratic, unreliable and unevenly distributed over the whole area of Dawa sub-basin. The pastoral and agro-pastoral communities are usually vulnerable to drought. The present study was an attempt to describe the state of Rain Water Harvesting (RWH) techniques and the contribution of Remote Sensing and GIS technologies for this RWH in the Dawa Sub basin. The study was conducted using physiographic factors of Dawa sub basin. Landsat image with spatial resolution 30m were used to identify LU/LC types. The thematic layers used were land use/land cover, slope, soil, drainage and runoff from derived from Landsat and collateral data. The image processing software Erdas IMAGINE and GIS software were used to process the image and to establish a geo information system by comprising digital data set of satellite image, topography, soil, metrology, drainage density and metrology. This data was used to study RWH was used to study the watershed network in the Dawa sub basin and to identify areas generally suitable for water harvesting in order to determine water harvesting techniques for those sites. Analytical Hierarchy Process (AHP) was used to calculate weighting and the analysis result indicates that the sub-basin supports promising opportunity for the establishment and development of RWH structures. From the total area of 17,402.7 km 2 , The GIS evaluation predicts that 3,092.342 km 2 (22.853%) is extremely suitable, 4,524.221 km 2 (33.435%) is very suitable, 2,968.685 km 2 (21.939%) is suitable, 1,988.986 km 2 (14.7%) is less Suitable and 957.18 km 2 (7.07%) is not suitable for RWH. 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Selection of Rainwater Harvesting Sites by Using Remote Sensing and GIS Techniques: A Case Study of Dawa Sub Basin Southern Ethiopia
Water is one of the vital requirements for life, economic and social development. Water scarcity affects the environmental, economic and developmental activities of an area. The rainfall in the sub-basins is often very local, erratic, unreliable and unevenly distributed over the whole area of Dawa sub-basin. The pastoral and agro-pastoral communities are usually vulnerable to drought. The present study was an attempt to describe the state of Rain Water Harvesting (RWH) techniques and the contribution of Remote Sensing and GIS technologies for this RWH in the Dawa Sub basin. The study was conducted using physiographic factors of Dawa sub basin. Landsat image with spatial resolution 30m were used to identify LU/LC types. The thematic layers used were land use/land cover, slope, soil, drainage and runoff from derived from Landsat and collateral data. The image processing software Erdas IMAGINE and GIS software were used to process the image and to establish a geo information system by comprising digital data set of satellite image, topography, soil, metrology, drainage density and metrology. This data was used to study RWH was used to study the watershed network in the Dawa sub basin and to identify areas generally suitable for water harvesting in order to determine water harvesting techniques for those sites. Analytical Hierarchy Process (AHP) was used to calculate weighting and the analysis result indicates that the sub-basin supports promising opportunity for the establishment and development of RWH structures. From the total area of 17,402.7 km 2 , The GIS evaluation predicts that 3,092.342 km 2 (22.853%) is extremely suitable, 4,524.221 km 2 (33.435%) is very suitable, 2,968.685 km 2 (21.939%) is suitable, 1,988.986 km 2 (14.7%) is less Suitable and 957.18 km 2 (7.07%) is not suitable for RWH. Keywords: GIS, Rainwater Harvesting (RWH), Remote Sensing (RS), Dawa Sub Basin DOI: 10.7176/JEES/10-9-03 Publication date: September 30 th 2020
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