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Monitoring flash flood hazard using modeling-based techniques and multi-source remotely sensed data: the case study of Ras Ghareb City, Egypt

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Abstract

Flash floods are among the most common natural hazards in Egypt. Wadi El-Darb, one of the vastest drainage catchment in the Eastern Desert of Egypt, is considerably subjected to severe flash flood events. The coastal city of Ras Gharib is located at the outlet of this Wadi, which consequently makes it susceptible to the flash flood hazard. Ras Gharib has a strategic importance to Egypt that it produces 65% of the petroleum requirement; therefore, the government seeks hard to protect the city. Using hydrological modeling approach was necessary, especially in case of the lack of hydrological and meteorological data in the region, to simulate the spatial extent, depth, and speed of the floodwater and then identify the sites at risk of flooding. The elevation data were extracted from digital elevation models (SRTM and ALOS PALSAR). The soil texture properties can be derived from Sentinel-1 radar images fused with geological data to produce the hybrid land cover map containing the rock types and their texture information. Sentinel-2 imagery was used to map the land use/land cover (LULC) in the downstream area of the basin. The results showed that the rainstorm with 51 mm of precipitation intensity would cause, at the outlet of the Wadi El-Darb basin, peak discharge rate of 852.73 m3/s, and the flash flood water can reach Ras Gharib city within 4 h, with an average flood depth of 1.69 m. Also, the flash flood impacts concentrated in the midtown covering about 2.93 km2, about 342 houses, 33.35 km of Ras Ghareb-Minya highway, and 55.9-km long of the internal road network were inundated. The hydrologic modeling results were validated using Jaccard coefficient (= 0.72), based on the integration of Sentinel-2 images along with aerial photos (captured post the flood), Google Earth images, and Open Street Map (OSM). Accordingly, this work provides the developing countries with a practical and quick technique to predict flash flood hazards in arid regions where data are scarce.

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Acknowledgements

The authors would like to thank European Commission’s Copernicus program to support free data Sentinel-1 and 2 and the Egyptian Water Resource Institute for providing the essential information about flash flood in Ras Ghareb city.

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Authors and Affiliations

  1. Department of Earth & Environmental Science, Institute of Global Environmental Change, School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an, 710049, China

    Mohammed Sadek, Xuxiang Li, Eman Mostafa & Jacqueline Fifame Dossou

  2. Surveying Engineering Department, Shoubra Faculty of Engineering, Benha University, Benha, Egypt

    Mohammed Sadek & Eman Mostafa

Authors
  1. Mohammed Sadek
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  2. Xuxiang Li
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  3. Eman Mostafa
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  4. Jacqueline Fifame Dossou
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Contributions

M.S, X.L, and E.M have contributed in conceptualization, methodology, validation, investigation, and writing-original draft preparation. Furthermore, J.D has contributed in review project administration, writing-original draft preparation, and writing-review and editing.

Corresponding author

Correspondence to Mohammed Sadek.

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The authors declare no competing interests.

Additional information

Responsible Editor: Amjad Kallel

Supplementary Information

ESM 1

(1) band combinations, (2) data availability, (3) videos and links, (4) outputs of HEC-RAS 2D software, (5) outputs of WMS software, and (6) photos after flood (DOCX 8614 kb)

Appendix

Appendix

The used equations for computing the hydrological parameters

Equation

Parameters

Sr = 25.4((1000/CN) − 10)

Sr = maximum potential retention (mm)

CN= curve number

Q = depth of direct runoff (mm)

P = depth of precipitation (mm)

Tc = time of concentration (min)

L = maximum flow distance (m)

S = maximum flow distance slope (%)

TLAG = lag time (hour)

qp = peak discharge (m3/s)

A = drainage area (km2)

Tp = time until the peak (hour)

Δt = duration of designed stormwater

\( \mathbf{Q}=\frac{{\left(\mathbf{P}-\mathbf{0.2}\mathbf{Sr}\right)}^{\mathbf{2}}}{\left(\mathbf{P}+\mathbf{0.8}\mathbf{Sr}\right)} \)

\( {\mathbf{T}}_{\boldsymbol{c}}=\mathbf{0.0195}\ \left(\ \frac{{\boldsymbol{L}}^{\mathbf{0.77}}}{{\boldsymbol{S}}^{\mathbf{0.385}}}\right) \)

 TLAG = 0.6 × Tc

\( \mathbf{qp}=\frac{\mathbf{0.208}\ \mathbf{AQ}}{\kern1em {\mathbf{T}}_{\mathbf{P}}} \)

 TP = ∆t/2 + TLAG

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Sadek, M., Li, X., Mostafa, E. et al. Monitoring flash flood hazard using modeling-based techniques and multi-source remotely sensed data: the case study of Ras Ghareb City, Egypt. Arab J Geosci 14, 2030 (2021). https://doi.org/10.1007/s12517-021-08341-3

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