Evaluation of Integrating SWAT Model into a Multi-Criteria Decision Analysis towards Reliable Rainwater Harvesting Systems

• Main Authors: Shahab Doulabian, Erfan Ghasemi Tousi, Reza Aghlmand, Babak Alizadeh, Alireza Ghaderi Bafti, Ali Abbasi
• Format: Article
• Language: English
• Published: MDPI AG 2021-07-01
• Series: Water
• Subjects: rainwater harvesting; multi-criteria decision analysis; geospatial techniques; SWAT model; arid and semi-arid regions
• Online Access: https://www.mdpi.com/2073-4441/13/14/1935

Rainwater harvesting (RWH) has been recognized as one of the most reliable and efficient methods for water supply, especially in arid and semi-arid regions (ASARs) facing freshwater scarcity. Nevertheless, due to the inherent uncertainty of input data and subjectivity involved in the selection of influential parameters, the identification of RWH potential areas is a challenging procedure. In this study, two approaches for locating potential RWH sites were implemented. In the first approach, a frequently-used method of the multi-criteria decision analysis and geographic information system (MCDA-GIS) was utilized, while, in the second approach, a novel strategy of integrating the soil and water assessment tool (SWAT) model as a hydrology model into an MCDA-GIS method was proposed to evaluate its performance in locating potential RWH sites. The Mashhad Plain Basin (MPB) was selected as a case study area. The developed potential RWH maps of the two approaches indicated similar patterns for potential RWH areas; in addition, the correlation coefficient (CC) between the two obtained maps were relatively high (i.e., CC = 0.914) revealing that integration of SWAT as a comprehensive hydrologic model does not necessarily result in very different outputs from the conventional method of MCDA-GIS for RWH evaluation. The overlap of developed maps of the two approaches indicated that 3394 km² of the study area, mainly located in the northern parts, was identified as high-potential RWH areas. The performed sensitivity analysis indicated that rainfall and slope criteria, with weights of 0.329 and 0.243, respectively, had the greatest sensitivity on the model in the first approach while in the second approach, the criterion of runoff coefficient (with weights of 0.358) had the highest impact. Based on results from the identification of the potential locations for conventional RWH techniques, pond and pan techniques are the most proper options, covering high-potential areas of RWH more effectively than other techniques over MPB.