Assessment of Surface Water Availability in the Riyadh Region Using Integrated Satellite Data and Field Measurements (2001 to 2024)

Abstract

Surface water availability in arid regions like the Riyadh region of Saudi Arabia is a significant concern due to its low and highly variable rainfall. This study represents the first comprehensive attempt to estimate surface runoff in the Riyadh region by integrating satellite data with field measurements, including dam observations, for enhanced accuracy. Utilizing the advanced Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Dynamic Infrared Rain Rate near-real-time (PDIR-Now) dataset, the study covers a 23-year period from 2001 to 2023. The research aimed to determine runoff coefficients, which are critical for predicting how much rainfall contributes to surface runoff. Analysis of annual runoff volumes and rainfall data from 39 dams, divided into calibration and validation sets, led to a runoff coefficient of 0.059, indicating that 5.9% of rainfall contributes to runoff. The calibration process, validated by statistical measures such as mean bias (0.23 mm) and RMSE (0.94 mm), showed reasonable model accuracy but also highlighted areas for refinement. With an average annual rainfall of 89.6 mm, resulting in 1733.1 million cubic meters (mil. m3) of runoff, the study underscores the importance of localized calibration and ongoing model refinement to ensure sustainable water management in the face of environmental and climatic challenges.