Rainwater harvesting (RWH) is one of the essential alternative sources of water that may be used. However, finding potential RWH locations on a broad scale has always been challenging, requiring further research. The effectiveness of RWH structures depends on their design and the selection of suitable sites. This study aimed to select potential sites for rainwater harvesting in the Garmian region of Kurdistan-Iraq, using GIS and Remote Sensing (RS) techniques. Two multicriteria analysis (MCA) techniques: the analytical hierarchal process (AHP) and Fuzzy analytical hierarchal process (FAHP) were used for comparison purposes to identify potential RWH sites. A suitability map of potential RWH systems was then generated following the weighted linear combination (WLC) and the Fuzzy Gamma methods. The outcomes showed that, unlike most recent studies, which relied on the minimum and maximum local rainfall values, a minimum agreed-upon rainfall depth should be used as a benchmark when classifying rainfall to obtain realistic results. The findings also showed that 9.7%, 43.4%, 33.6%, and 13.3% of the sites have very high, high, moderate, and low suitability for rainwater harvesting, respectively, depending on the suitability map produced by the WLC method. However, the outcome of the Fuzzy Gamma technique appeared more realistic and revealed that 10.6%, 15.6%, 26.6%, 21.9%, and 25.3% of the sites have very high, high, moderate, low, and very low appropriateness for rainwater harvesting, respectively. The methods adopted in this study can be helpful for researchers in the field of RWH to achieve reliable results. Also, this study’s findings can assist in well-organized water resource management planning to ensure sustainable water development in the Garmian region.

Increasing water demand driven by population growth and climate change strains water resources, especially in arid regions. The effectiveness of rainwater harvesting (RWH) as a viable solution is contingent upon the meticulous selection of appropriate sites. Contemporary efforts have increasingly utilized Geographic Information Systems (GIS) and remote sensing technologies to optimize the identification of ideal locations for implementing RWH infrastructure. However, inconsistencies in rainfall classification methodologies can compromise the accuracy of the resulted suitability maps. Consequently, a standardized approach to grading rainfall depth for mapping RWH sites becomes imperative. This study presents an innovative rainfall classification method tailored for both micro and macro catchment areas, offering a reliable and adaptable approach to rainfall analysis. By refining classification criteria, this method aims to improve the consistency and precision of RWH mapping, addressing a gap in existing methodologies and providing a more standardized approach. Through the application of FAHP and Fuzzy overlay techniques in ArcGIS 10.4, the study compares traditional rainfall classification with the proposed new classification method to assess RWH suitability in Kalar. The comparison highlights that the new rainfall classification-based map yielded higher accuracy and realism compared to traditional methods.