Modeling rainfall-runoff estimation and assessing water harvesting zone for irrigation practices in Keleta watershed, Awash river basin, Ethiopia

被引:0
|
作者
Debebe, Demelash [1 ]
Seyoum, Teshome [3 ]
Tessema, Negash [2 ]
Ayele, Gebiaw T. [4 ,5 ]
机构
[1] Woldia Univ, Water Resources & Irrigat Engn Dept, Woldia, Ethiopia
[2] Haramaya Univ, Haramaya Inst Technol, Water Resources & Irrigat Engn Dept, Dire Dawa, Ethiopia
[3] Haramaya Univ, Haramaya Inst Technol, Hydraul & Water Resources Engn Dept, Dire Dawa, Ethiopia
[4] Griffith Univ, Australian Rivers Inst, Nathan, Australia
[5] Griffith Univ, Sch Engn & Built Environm, Nathan, Australia
关键词
AHP; fuzzy logic; Keleta watershed; GIS/RS; rainwater harvesting; SWAT model; LAND SUITABILITY; GIS; IDENTIFICATION; PARAMETERS; SITES;
D O I
10.1080/10106049.2023.2236582
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The world's water demand is increasing twice as quickly as the world's population. Contrarily, the greatest problem facing humanity in the twenty-first century is the supply of food. During dry seasons, when water collecting is a crucial survival strategy, the communities in the study area experience water deficit for agricultural production. In this study, socioeconomic and biophysical parameters were considered to evaluate the water harvesting zone for irrigation practices. With the aid of this technology, water harvesting sites can be found in acceptable sites, and water resource management can be improved to address water shortages during the dry season when crops are at key stages of growth and filling. The integrated geographical information system/Remote Sensing (GIS/RS), Soil Water Assessment Tool (SWAT), fuzzy logic, and analytic hierarchy process (AHP) model were used to carry this out. Rainfall, drainage density, surface runoff, percentage of clay content, land use land cover, slope, lithology, lineament, and Euclidian distance to settlement and road were the criteria utilized to choose the Rainwater Harvesting (RWH) sites. The run-off was estimated using the SWAT model, weights for each influential component were determined using AHP, the input factor was standardized using fuzzy membership, and factors were combined using gamma fuzzy (ℽ= 0.9) overlay weighting. The model's statistical performance was demonstrated by R2 values of 0.79 and NSE values of 0.77 for monthly calibration periods and R2 values of 0.81 and NSE values of 0.75 for monthly validation periods. The study area's Rainwater Harvesting potential suitability classes covered very highly suitable (16.91%), extremely suitable (27.6%), moderately suitable (20.23%), low suitable (13.1%), and not suitable (6.43%), and restrictions (15.73%). The study's findings could help decision-makers identify more lucrative and long-lasting irrigation investment options in the Keleta watershed and make better decisions regarding the development of irrigation projects there.
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页数:30
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