Physically-based, distributed hydrologic model for Makkah watershed using GPM satellite rainfall and ground rainfall stations

The purpose of this study is to understand flooding in a 1,725-km(2) arid catchment in Makkah Province, Saudi Arabia, with very limited ground observations. This mountainous catchment includes densely urbanized areas built on lowlands and in the ephemeral streams of flood zones, which makes them vulnerable to flooding. A physically based, fully distributed hydrologic model was produced by three Integrated Multi-satellite Retrievals for Global Precipitation Measurement Mission (IMERG) high-resolution satellite rainfall products, together with a limited number of ground observations to simulate recent flood events. The hydrologic model was calibrated and validated using two events that occurred in 2010 and 2018, respectively. Details of the flooding in the urbanized areas were examined through simulation of a third event. Significant differences were noticed when the three IMERG rainfall products (Early, Late, and Final) were compared in terms of the spatial patterns and total half-hour accumulation for the three events. Accordingly, a method was developed to remove the biases of IMERG rainfall estimates using ground observations. The Early product was the closest to ground observations, producing peak discharges of 428 m(3)/s and 663.6 m(3)/s for calibration and validation storm events, respectively, and resulted in better estimates of the observed peak discharge even before adjustment. The Final run product significantly underestimated rainfall, as peak discharges of 204 m(3)/s and 123 m(3)/s for calibration and validation storm events, respectively, resulted in an amplified underestimation of the runoff.

Automated summary

This study aims to understand flooding in a 1,725-km(2) arid catchment in Makkah Province, Saudi Arabia, using a physically based hydrologic model calibrated and validated with limited ground observations and high-resolution satellite rainfall products. Significant differences were found in rainfall estimates from different IMERG products, leading to the development of a method to adjust biases using ground observations. The study highlights the vulnerability of densely urbanized areas in flood zones and the importance of accurate rainfall data for flood prediction and management.