Assessment of the performance of satellite rainfall products over Makkah watershed using a physically based hydrologic model

Abstract

Makkah region is one of the most flash flood-prone areas of Saudi Arabia due to terrain characteristics and the synoptic-scale weather conditions that intensify through interaction with the local topography causing high convective short-lived rainfall events, although these conditions are quite infrequent. Most of these events last for less than two hours. This study aims to assess the performance of five satellite precipitation products over a 1725 km2 sparsely gauged, arid basin. A fully distributed, physically based hydrologic model was forced by the five satellite precipitation products, and the evaluation included the hydrographs and runoff maps predicted by the model. Moreover, the propagation of the satellite rainfall errors into runoff predictions was quantified. Large variations and significant biases were found in satellites precipitation estimates compared to the available ground rainfall measurements. The Early IMERG product showed the best agreement with the reported total rainfall accumulations followed by Late IMERG while the other products significantly underestimated precipitation accumulations. Comparison with estimated runoff peaks showed that the Early IMERG product has the lowest errors in runoff peaks. Therefore, the hydrographs produced by the Early IMERG product were used as a reference to quantify the propagation of satellite precipitation errors into runoff predictions over the Makkah watershed. The results clearly indicated that both systematic and random rainfall errors were significantly amplified in runoff predictions.

Flash Flood Risk Assessment in the Asir Region, Southwestern Saudi Arabia, Using a Physically-Based Distributed Hydrological Model and GPM IMERG Satellite Rainfall Data

“…To further test the feasibility and applicability of the conceptual semi-distributed (HEC-HMS) model, this model was compared with the GSSHA model [7]. They found that the HEC-HMS model significantly overestimated the peak discharge before calibration, while providing satisfactory results after calibration, and this can confirm the validity of our results.…”

“…Here, a fully physical-based, distributed hydrological model run with HEC-HMS, one of the well-known systems used for simulating flood and surface runoff based on precipitation event, was used to generate flood hydrographs for the main outlet and the wadi sub-basins [9]. For more details about the HEC-HMS model, readers are referred to Al-Areeq et al [7].…”

“…The HEC-HMS model was used here simulate the flow and predict the flash flood hazard of the Wadi Hail catchment and its associated sub-basins. It is a semi-distributed model [7] characterized by many advantages, including flexibility and ease of use, simulation with high efficiency, requiring fewer environmental factors, and fast computation [7]. According to Lautenbach et al [38] it has some drawbacks.…”

Utilizing Satellite Data to Establish Rainfall Intensity-Duration-Frequency Curves for Major Cities in Iraq

“…Jaber et al [59] also showed the efficacy of remote sensing precipitation in rainfall-runoff modelling in Iraq. Studies in the nearby region also showed the applicability of satellite rainfall in hydrological applications in Jordan [60], Iran [61], Saudi Arabia [62,63], and Turkey [64].…”

Comparing Remote Sensing and Geostatistical Techniques in Filling Gaps in Rain Gauge Records and Generating Multi-Return Period Isohyetal Maps in Arid Regions—Case Study: Kingdom of Saudi Arabia

“…Additionally, historical rainfall data frequently contains gaps that require filling before the data can be utilized [8][9][10][11]. Several techniques detailed in the literature aim to address these gaps, including the utilization of satellite data and geospatial interpolation techniques [12][13][14][15]. Terrestrial gauged data is the most reliable precipitation data source and is used as a benchmark for checking the accuracy of any proposed data processing technique [16][17][18].…”