Evaluating the Impact of Environmental Factors on Flood Susceptibility in the Sirwan Watershed Based on Historical Flood Events

Document Type : Research

Authors

1 Assistant Professor, Soil Conservation and Watershed Management Research Department, Kurdistan Agricultural and Natural Resources Research and Education Center, AREEO, Sanandaj, Iran

2 Assistant Professor, Natural Resources Research Department, Golestan Agricultural and Natural Resources Research and Education Center, AREEO, Gorgan, Iran

3 Assistant Professor, Soil Conservation and Watershed Management Research Department, Isfahan Agricultural and Natural Resources Research and Education Center, AREEO, Isfahan, Iran

4 Assistant Professor, Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization AREEO, Tehran, Iran

5 Professor, Soil Conservation and Watershed Management Research Department, Kurdistan Agricultural and Natural Resources Research and Education Center, AREEO, Sanandaj, Iran

Abstract

Introduction and Goal
Floods cause loss of life and financial losses every year, and their management is one of the essential elements of watershed management. In this research, an attempt is made to determine the flood susceptibility of the Sirwan watershed and finally the importance of various environmental factors in flood susceptibility based on historical flood events.
Materials and Methods
In this research, the maximum entropy model along with 13 topographical, hydrological, morpho-hydrological, geological, and environmental flood-affecting factors were used to model the flood susceptibility of the Sirwan watershed and determine the importance and percentage of participation of various factors in the state of flooding potential. A cellular computing unit (pixel) was chosen as the criterion for preparing the predictive factors and flood susceptibility maps. A total of 123 historical flood inundation events detected in the last decade were used as target variables in the model, of which 70% were considered for learning and the remaining 30% for validating the model results. To evaluate the performance of the model, the criterion of the area under the receiver operating characteristic curve was also used.
Results
The results indicate that the accuracy of learning and validation were 98.2% and 97.3%, respectively, indicating the excellent performance of the model. Based on the visual interpretation of the flood susceptibility map, streams with a higher order near the watershed outlet, which are the conduits for the passage of the flow with a larger volume and are located in lower areas, often have a higher proneness to flood inundation. Based on the results of the relative importance test, the four factors of distance from the stream, topographic wetness index, drainage density, and land use were introduced as the most important factors in the modeling flood susceptibility, with of 17, 13, 12 and 10% participation, respectively. These results show that natural hydrological, morpho-hydrological and environmental factors (both natural and man-made) have a mutual effect in increasing flooding susceptibility. Based on the quantitative analysis of modeling, about 0.76% (5600 hectares) of the studied area is in the high and very high flood susceptibility class, which requires planning and flood management.
Conclusion and Suggestions
The high classification of flood susceptibility classes in the Sirwan watershed of Kurdistan province and the determination of the importance of environmental factors in the event of flooding make it possible for managers to take an effective preventive approach by planning relief facilities and infrastructure. To reduce the risk of flooding, flood crisis management in the Sirwan watershed should be defined based on the four main factors identified in this study. Application of the maximum entropy model in flood susceptibility analysis is suggested for flood management of watersheds.

Keywords

Main Subjects

References

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History

  • Receive Date: 17 February 2023
  • Revise Date: 05 June 2023
  • Accept Date: 21 June 2023

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