Spatial Analysis of Environmental Hazards

Spatial Analysis of Environmental Hazards

Analysis of the june(2024) flood in Ardabil Province with an emphasis on synoptic patterns

Authors
nafiseh rahimi
abdo faraj
zanjan uni
10.66224/jsaeh.12.4.2
Abstract
Objective: in recent decades, population growth, urbanization development, and change in land use have led flooding as one of the most destructive natural disasters in the world. Therefore, our goal is to identify flood areas and the synoptic patterns that lead to it, which are among the most important issues in preventing and reducing the effects of flooding and dealing with it.

Methods: In this study, in order to prepare a map of flooded areas, the extent of the floodwater that occurred in June (2024) in Ardabil province, were processed SAR radar images before and after the flood. Then, to identify synoptic patterns, daily maps of geopotential height at 500 hectopascals, sea level pressure at 1000 hectopascals, omega pressure at 500 hectopascals, and relative humidity at 700 hectopascals with a spatial resolution of 2.5 degrees in 2.5 degrees latitude were received and analyzed from the National Center for Environmental Prediction and the National Center for Atmospheric Research (NCEP/NCAR) of the United States.

Results: The flood area study indicated that in the studied province, Bilehsavar city with an area of 593 hectares, Parsabad city with 505 hectares, Meshkin-shahr with 245 hectares, and Germi city with 192 hectares were flooded due to the waterlog. The analysis of the flood zones also showed that the largest volume of flood entering Ardabil Province during the studied period was related to the northern cities of the province, where the provision of all moisture conditions and instability at the full depth of the troposphere layer led to the occurrence of heavy flood-causing rainfall in these areas.

Conclusions: The results of this study indicate that the use of radar data, due to its outstanding capabilities, is a useful tool in detecting and continuously monitoring of floods. Therefore, by detecting flood-prone areas and synoptic conditions that produce floods, executive managers can make the best decisions to deal with possible future floods.
Keywords
Ardabil province
Flood
June 2024
Radar images
synoptic patterns
- SOLAIMANI, KARIM, Sharifipour, Mahdi, & Abdoli Bojani, Sepideh. (2020). Flood Damage Detection Algorithm Using Sentinel-2 Images (Case study; Golestan Province, March 2019). IRANIAN JOURNAL OF ECOHYDROLOGY, 7(2 ), 303-312. SID. https://sid.ir/paper/360777/en.
- Soleimani Sardoo, F., Rafiei Sardooi, E., MESBAHZADEH, T., & Azareh, A.. (2021). Utilizing Sentinel 1 Images for Monitoring Damage of Flood Event in March 2020, the South of Kerman Province Based on Random Forest Algorithm. IRANIAN JOURNAL OF WATERSHED MANAGEMENT SCIENCE AND ENGINEERING, 15(53 ), 23-32. SID. https://sid.ir/paper/393773/en.
- Zambon, M. Lawrence, R. Bunn, A. and Powell, S. 2006. Effect of Alternative Splitting Rules on Image Processing Using Classification Tree Analysis. Photogrammetric Engineering and Remote Sensing, vol. 72(1):25-30.
- Zambon, M. Lawrence, R. Bunn, A. and Powell, S. 2006. Effect of Alternative Splitting Rules on Image Processing Using Classification Tree Analysis. Photogrammetric Engineering and Remote Sensing, vol. 72(1):25-30.
- 16. Jahanbakhshi, F. and Ekhtesasi, M. R. 2019. Evaluation of Three Image Classification Methods (Random Forest, Support Vector Machine and the Maximum Likelihood) in Land Use Mapping. Journal of Water and Soil Science (Science and Technology of Agriculture and Natural Resources). 22(4): 235-247.
- Vatanfada, J. (2009), "Flood management of Iran (country report)", Flood Prevention Committee.