Determining the Most Susceptible Areas of Flood Occurrence Using MaxEnt Model in Marzdaran Watershed, Tehran Province
The objective of the current study was to zone flood probability in the Marzdaran watershed. Since the allocated budget for management work is limited and it is not possible to carry out operations in the whole area, having a map that has prioritized different areas in terms of the probability of fl...
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| Format: | Article |
| Language: | fas |
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Isfahan University of Technology
2023-09-01
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| Series: | علوم آب و خاک |
| Subjects: | |
| Online Access: | http://jstnar.iut.ac.ir/article-1-4245-en.pdf |
| _version_ | 1797653630995660800 |
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| author | Y. Esmaeli F. Yosefvand S. Shabanlou M.A. Izadbakhsh |
| author_facet | Y. Esmaeli F. Yosefvand S. Shabanlou M.A. Izadbakhsh |
| author_sort | Y. Esmaeli |
| collection | DOAJ |
| description | The objective of the current study was to zone flood probability in the Marzdaran watershed. Since the allocated budget for management work is limited and it is not possible to carry out operations in the whole area, having a map that has prioritized different areas in terms of the probability of flood occurrence will be very useful and necessary. A well-known data mining model namely MaxEnt (ME) is applied due to its robust computational algorithm. Flood inventories are gathered through several field surveys using local information and available organizational resources, and the corresponding map is created in the geographic information system. The twelve predisposing variables are selected and the corresponding maps are generated in the geographic information system by reviewing several studies. The area under the curve (ROC) is used to evaluate the modeling results. Then, the most prone areas of flood occurrence which are prioritized for management operations are identified based on the prepared map. Based on the results, about 100 km2 of the study area is identified as the most prone area for management operations. The results showed that the accuracy of the maximum entropy model is 98% in the training phase and 95% in the validation phase. The distance from the river, drainage density, and topographic wetness index are identified as the most effective factors in the occurrence of floods, respectively. |
| first_indexed | 2024-03-11T16:46:25Z |
| format | Article |
| id | doaj.art-915e0a623fc248c48c5cb838a03ebdfe |
| institution | Directory Open Access Journal |
| issn | 2476-3594 2476-5554 |
| language | fas |
| last_indexed | 2024-03-11T16:46:25Z |
| publishDate | 2023-09-01 |
| publisher | Isfahan University of Technology |
| record_format | Article |
| series | علوم آب و خاک |
| spelling | doaj.art-915e0a623fc248c48c5cb838a03ebdfe2023-10-22T09:49:48ZfasIsfahan University of Technologyعلوم آب و خاک2476-35942476-55542023-09-012723351Determining the Most Susceptible Areas of Flood Occurrence Using MaxEnt Model in Marzdaran Watershed, Tehran ProvinceY. Esmaeli0F. Yosefvand1S. Shabanlou2M.A. Izadbakhsh3 Islamic Azad University, Kermanshah Branch Islamic Azad University, Kermanshah Branch Islamic Azad University, Kermanshah Branch Islamic Azad University, Kermanshah Branch The objective of the current study was to zone flood probability in the Marzdaran watershed. Since the allocated budget for management work is limited and it is not possible to carry out operations in the whole area, having a map that has prioritized different areas in terms of the probability of flood occurrence will be very useful and necessary. A well-known data mining model namely MaxEnt (ME) is applied due to its robust computational algorithm. Flood inventories are gathered through several field surveys using local information and available organizational resources, and the corresponding map is created in the geographic information system. The twelve predisposing variables are selected and the corresponding maps are generated in the geographic information system by reviewing several studies. The area under the curve (ROC) is used to evaluate the modeling results. Then, the most prone areas of flood occurrence which are prioritized for management operations are identified based on the prepared map. Based on the results, about 100 km2 of the study area is identified as the most prone area for management operations. The results showed that the accuracy of the maximum entropy model is 98% in the training phase and 95% in the validation phase. The distance from the river, drainage density, and topographic wetness index are identified as the most effective factors in the occurrence of floods, respectively.http://jstnar.iut.ac.ir/article-1-4245-en.pdfzoninggismaxentdrainage densityland useflood |
| spellingShingle | Y. Esmaeli F. Yosefvand S. Shabanlou M.A. Izadbakhsh Determining the Most Susceptible Areas of Flood Occurrence Using MaxEnt Model in Marzdaran Watershed, Tehran Province علوم آب و خاک zoning gis maxent drainage density land use flood |
| title | Determining the Most Susceptible Areas of Flood Occurrence Using MaxEnt Model in Marzdaran Watershed, Tehran Province |
| title_full | Determining the Most Susceptible Areas of Flood Occurrence Using MaxEnt Model in Marzdaran Watershed, Tehran Province |
| title_fullStr | Determining the Most Susceptible Areas of Flood Occurrence Using MaxEnt Model in Marzdaran Watershed, Tehran Province |
| title_full_unstemmed | Determining the Most Susceptible Areas of Flood Occurrence Using MaxEnt Model in Marzdaran Watershed, Tehran Province |
| title_short | Determining the Most Susceptible Areas of Flood Occurrence Using MaxEnt Model in Marzdaran Watershed, Tehran Province |
| title_sort | determining the most susceptible areas of flood occurrence using maxent model in marzdaran watershed tehran province |
| topic | zoning gis maxent drainage density land use flood |
| url | http://jstnar.iut.ac.ir/article-1-4245-en.pdf |
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