Estimating of runoff height and flood maximum discharge using Cellular Automata and SCS models, (Case Study: Lavijrood watershed)

Document Type : Research Article

Authors

1 Department of Geography, Islamic Azad University of Nour

2 Shahid Beheshti University

Abstract

The Lavijrood watershed can produce seasonal floods; this is due to its topographical and physiological situation, climate system, non-compliance with technical construction standards, riverside violation, geology, and the other factors that affect the runoff production. In this research, we investigated the performance of the cellular automata (CA) and SCS model as a suitable estimation method and examined the possibility of integrating the method with the ArcGIS application to simulate the flood hazards and the hydrograph flow for the Lavijrood. The runoff height and the flood hazard were obtained through the SCS method. The flood simulation using the SCS method requires the data of land use, hydrologic groups of soils, Digital Elevation Map (DEM), rainfall, and the roughness coefficient of the basin. The raster format of all these layers was prepared with cell sizes of 30×30 m. A large part of the Lavijrood watershed belongs to the hydrological groups C and D, which have very low permeability. This means that a large volume of rainfalls converts into runoffs. Due to the low permeability and the vicinity to the watershed outlet, the northern half, especially in the northwest of the watershed, has a very high runoff depth and height. Also, the flood risk is high in the Lavijrood River route and its surrounding area especially at the downstream. The runoff simulation in this watershed showed that land use, soil, permeability, slope, and the geographical distribution of rainfalls are the most important factors that control runoffs and their movement to downstream locations to produce floods.

Keywords


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  • Receive Date: 22 April 2019
  • Revise Date: 28 November 2019
  • Accept Date: 12 February 2020
  • First Publish Date: 21 May 2020
  • Publish Date: 21 May 2020