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

Abstract

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.

Proposing Optimal Locations for Runoff Harvesting and Water Management Structures in the Hami Qeshan Watershed, Iraq

“…Year Applied Techniques Country [47] 2022 WLC, RS, and GIS Australia [48] 2021 AHP and GIS Morocco [49] 2021 BO, WLC, and GIS Iraq [50] 2017 AHP, Fuzzy-AHP, ROM, VI, BO, RS, SWAT, and GIS Iraq [51] 2021 WLC, BO, RS, and GIS Iraq [30] 2017 FL, AHP, WLC, and GIS Iraq [4] 2020 AHP, WSM, RS, and GIS Iraq [2] 2019 WLC, AHP, RS, and GIS Iraq [31] 2019 AHP, FL, RS, and GIS Iraq [52] 2017 WLC, BO, and GIS Jordan [53] 2016 AHP, WLC, BO, and GIS Jordan [54] 2022 AHP, WLC, BO, RS, and GIS Yemen [55] 2014 AHP, FIM, BO, WLC, and GIS Pakistan [33] 2020 AHP, RS, and GIS Pakistan [29] 2019 AHP, ML, GIS, and RS UAE [56] 2019 AHP, SSS, and GIS Iran [57] 2021 AHP, WLC, and GIS Iran [23] 2018 AHP, TOPSIS, and GIS Iran [44] 2021 AHP, WLC, SWAT, RS, and GIS Iran [20] 2020 BWM, FL, AHP, WOP, BO, and GIS Iran [8] 2022 AHP, RS, SWAT, RUSLE, and GIS Rwanda [58] 2021 AHP, RS, and GIS MOZ The torrential rainfall and subsequent floods of spring 2019 that hit Iraq and neighboring countries [56,59] raised water levels in the Tigris River and its tributaries (Figure 1a). Consequently, water management features such as Dukan Reservoir (DR) reached its maximum safe storage capacity.…”

“…Many insightful studies have revealed that integrating the WLC and AHP approaches with GIS is an effective and competent RH suitability technique [2,44,54]. The WLC and AHP models have been utilized to determine suitable RH locations by identifying the weights of various criteria and their sub-criteria [4,47,48,53].…”

“…One of the essential procedures in evaluating the accuracy of any model is the validation of results, where models might not be advantageous from a scientific perspective without verification [112]. In reviewing the literature, different methodologies are utilized to validate the RH maps, such as correlation analysis, segmentation accuracy assessment, receiver operating characteristic curve, and sensitivity analysis [4,20,31,44,56]. To examine the robustness and viability of the implemented models, WLC and AHP, the SAA method was performed by correlating the resulting suitability maps with the locations of 16 dams suggested by MAWR (Table A3 and Figure A1 in Appendix A).…”

“…A topical literature review reveals that numerous regional and worldwide studies have developed and employed various MCDA approaches, combined with in situ measurements, RS data, hydrologic models, and GIS techniques, to identify optimal sites for runoff harvesting and dam construction (Table 1). In addition, determining suitable criteria is another significant element in effectively implementing MCDA and geospatial techniques for mapping potential RH zones [44]. According to the Food and Agriculture Organization (FAO), six influential factors were identified to categorize RH areas: topography, climate, hydrology, soil, agronomy, and socioeconomic criteria [45,46].…”

Water resource management for improved crop cultivation and productivity with hydraulic engineering solution in arid northern Afghanistan

“…Another study evaluates the rainwater harvesting system using the SWAT model and MCDA in Iran (Doulabian et al 2021).…”