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Estimating potential direct runoff for ungauged urban watersheds based on RST and GIS

  • Farid RadwanEmail author
  • A. A. Alazba
  • Amr Mossad
Original Paper
  • 235 Downloads

Abstract

Estimating the potential direct runoff for urban watersheds is essential for flood risk mitigation and rainwater harvesting. Thus, this study aims to estimate the potential runoff depth based on the natural resources conservation service (NRCS) method and delineation of the watersheds in Riyadh, Saudi Arabia. To accomplish this objective, the geographic information systems (GIS) and remote sensing technique (RST) data were integrated to save time and improve analysis accuracy. The employed data include the digital elevation model (DEM), soil map, geology map, satellite images, and daily precipitation records. Accordingly, the hydrologic soil groups (HSG), the land use/land cover (LULC), and curve number (CN) were determined for each watershed in the study area. The results of this analysis show that the study area can be delineated into 40 watersheds with a total area of 8500 km2. Furthermore, the dominant HSG is group D, which represents about 71% of the total area. The LULC maps indicate four major land types in the entire study area: urban, barren land, agricultural land, and roads. The CN of the study area ranges from 64 to 98, while the weighted CN is 92 for the city. The rainfall-runoff analysis shows that the area has a high and very high daily runoff (35–50 and > 50 mm, respectively). Therefore, in this case, the runoff leads to flooding, especially in the urban area and agricultural lands.

Keywords

Rainfall-runoff NRCS-CN Urban watershed HSG LULC RST & GIS 

Notes

Funding information

The project was financially supported by King Saud University, Vice Deanship of Research Chairs.

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Copyright information

© Saudi Society for Geosciences 2018

Authors and Affiliations

  1. 1.Alamoudi Water Research ChairKing Saud UniversityRiyadhSaudi Arabia
  2. 2.Agricultural Engineering DepartmentKing Saud UniversityRiyadhSaudi Arabia
  3. 3.Agricultural Engineering DepartmentAin Shams UniversityCairoEgypt

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