Optimizing Rainwater Harvesting Site and Structure Suitability Using Geospatial, Multi-Influencing Factor, and...

Rainwater harvesting (RWH) is an essential practice for water conservation, improved water resource management, and water-related hazards mitigation in mountainous areas. Selection of a suitable site and an appropriate structure of the RWH facility are vital for improving water availability and agricultural productivity under all circumstances, particularly due to climate change-related hydrological uncertainty. It is challenging to evaluate and analyze RWH sites across diverse conditions worldwide, particularly in remote, inaccessible mountainous areas where these sites have significant impacts on the environment, society, and economy of the region and downstream. In this study, the Multi-Influencing Factor (MIF), and the Analytic Hierarchy Process (AHP) were applied in Geographical Information System (GIS) using customary and remote sensing (RS) data for selecting a suitable RWH site and appropriate structures in the Panjkora river basin in the Hindu Kush region in northern Pakistan. According to MIF (and AHP) results, the study region has 80.22 (1572.58) km² less suitable area, 1681.99 (1605.69) km² as moderate suitable, 3116.10 (1768.62) km² as suitable, 844.86 (689.15) km² as high suitable and 35.10 (122.61) km²as very high suitable for RWH structures. The resulting maps were validated using Receiver Operating Characteristic and Area Under the Curve (ROC-AUC) tests (MIF score = 0.724 and AHP score = 0.692) to check the accuracy and robustness of the models. This research, presenting results with promising accuracy, will provide new technical insights on the topic for further improvement, suitability and applicability of the models under different hydro-meteorological and physiographic conditions. Overall, both models successfully identified suitable rainwater harvesting sites; however, the MIF model outperformed the AHP model in terms of predictive accuracy and spatial reliability. The proposed GIS-based framework can support sustainable rainwater harvesting planning and water resource management in mountainous watersheds.