%0 Journal Article %T Zoning and Monitoring of Spring 2019 Flood Hazard in Khuzestan Using Landsat-8 Data %J Iranian journal of Ecohydrology %I Faculty of New Sciences and Technologies, University of Tehran %Z 2423-6098 %A Solaimani, Karim %A Darvishi, Shadman %D 2020 %\ 09/22/2020 %V 7 %N 3 %P 647-662 %! Zoning and Monitoring of Spring 2019 Flood Hazard in Khuzestan Using Landsat-8 Data %K flood zoning %K MNDWI %K NDWI %K Landsat 8 and Khuzestan %R 10.22059/ije.2020.302703.1333 %X Flood monitoring and zoning play an important role in reducing the damage caused by this natural crisis. The purpose of this paper is to investigate the risk of flooding of April 2019 in Khuzestan using Landsat-8 data. First, image processing was performed in ENVI 5.3 software and then MNDWI and NDWI indices were used to monitor the floods. Then, the flood hazard map was prepared in ArcGIS10.4 software. The results show that the southern and southwestern parts of the province are in a very severe situation and the central and southeastern parts are in a very hazardous condition, which is one of the most prone flood areas in the province. Also, monitoring of flood maps in Khuzestan province shows that there is a complete similarity between the recent flood and flood zoning map. Examination of the maps showing that the recent floods occurred mostly in the western, southern and southwestern parts. Spatial survey of floodplain areas shows that the cities of Hoveyzeh, Azadegan Plain, Ahvaz, Khorramshahr, Bandar Mahshahr, Abadan and especially Shadegan have been flooded more than other cities. Meanwhile, Shadegan city has been affected by floods based on MNDWI and NDWI indices of 191349 and 174813 hectares, respectively, which shows the highest rate compared to other cities in the province. In general, according to the results, the use of remote sensing data and MNDWI and NDWI indices for flood monitoring, as well as the use of geographic information system for flood risk zoning in related studies are recommended. %U https://ije.ut.ac.ir/article_77571_504179d0f2f05323ed7973bc0e36ff07.pdf