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یوسفی, الهام, کفاش, مهدی, شریعتی, محسن. (1403). Spatial analysis of flood risk in Tabas watershed using satellite images and geographic information system (GIS). , 2(2), 105-118. doi: 10.22077/jdcr.2024.7489.1066
الهام یوسفی; مهدی کفاش; محسن شریعتی. "Spatial analysis of flood risk in Tabas watershed using satellite images and geographic information system (GIS)". , 2, 2, 1403, 105-118. doi: 10.22077/jdcr.2024.7489.1066
یوسفی, الهام, کفاش, مهدی, شریعتی, محسن. (1403). 'Spatial analysis of flood risk in Tabas watershed using satellite images and geographic information system (GIS)', , 2(2), pp. 105-118. doi: 10.22077/jdcr.2024.7489.1066
یوسفی, الهام, کفاش, مهدی, شریعتی, محسن. Spatial analysis of flood risk in Tabas watershed using satellite images and geographic information system (GIS). , 1403; 2(2): 105-118. doi: 10.22077/jdcr.2024.7489.1066

Spatial analysis of flood risk in Tabas watershed using satellite images and geographic information system (GIS)

مجله پژوهش های خشکسالی و تغییراقلیم
دوره 2، شماره 2 - شماره پیاپی 6، شهریور 1403، صفحه 105-118    اصل مقاله (1.17 M)
نوع مقاله: مقاله پژوهشی
شناسه دیجیتال (DOI): 10.22077/jdcr.2024.7489.1066
نویسندگان
الهام یوسفی* 1؛ مهدی کفاش2؛ محسن شریعتی3
1استادیار، گروه محیط زیست، دانشکده منابع طبیعی و محیط زیست، دانشگاه بیرجند، ایران.
2کارشناسی ارشد برنامه‌ریزی کاربری اراضی، دانشکده محیط زیست، دانشگاه بیرجند.بیرجند، ایران.
3کارشناسی ارشد برنامه‌ریزی محیط زیست، دانشگاه تهران، تهران، ایران.
چکیده
Among the natural phenomena, flood can be the biggest cause of damage, which always endangers the lives and properties of people. One of the management measures which can play a significant role in reducing the damages is flood risk zoning. In this research, flood risk zoning has been done in the Tabas watershed. In general, the steps and this research were done in four steps the effective criteria in creating the risk of flooding were identified, and the relevant layers were prepared. In the next step, rasterization and standardization were done using fuzzy membership functions, then weighting of parameters was done using the ahp, and finally overlapping of the layers was done using fuzzy operators. The criteria of distance from river, slope, land use, rainfall, soil, dem and ndvi were respectively assigned the highest weight. Also, all fuzzy superposition operators have been used for flood risk zoning.
Among these operators, the 0.9 gamma operator shows the best and most reasonable result, so this map was chosen as the final flood risk zoning. In the final map, the total area of high-risk areas is 15432.13 ha. According to the final map obtained, areas with very high flood risk are located in the eastern part of the studied area. Areas with low risk are mostly located in the plains, valleys and depressions with less slope. The method used in this study can be used in other studies such as zoning of earthquake risk potential, development zoning and spatial analysis of disease distribution.
کلیدواژه‌ها
Zoning؛ hierarchical method؛ Tabas؛ Fuzzy
مراجع

Bagheri, M. H., Farzaneh, M., & Rayegani, B. (2022). Development of Remote SensingBased Flood Estimation Methodology in Google Earth Engine. Environment and Interdisciplinary Development, 7(76), 12-26. https://doi.org/10.22034/envj.2022.154826

Beheshti Rad, M., Faiznia, S., Selajqa, A., & Ahmadi, H. (2009). Investigating the efciency of landslide risk zoning model, confdence factor (CF) A case study of Moalem Kalaye watershed. Natural Geography, 2(5), 19-28. [In Persian].

Chezgi, J., & Hamedi, E. (2023). Flood Prioritization of Sarbaz River Sub-Basins Using SWAT Model. Journal of Drought and Climate change Research, 1(3), 73-86. doi: 10.22077/jdcr.2023.6478.1026.

Eslaminezhad, S.A., Eftekhari, M., Akbari, M., Haji Elyasi, A., & Farhadian, H. (2022). Predicting flood prone areas using advanced machine learning models (Birjand plain), Journal of Water and Irrigation Management, 11(4), 885-904. [In Persian]. 10.22059/jwim.2022.332875.934 .

Eastman, J. R. (2012). IDRISI Selva manual. Clark University. Sitio web: www. Clarklabs. org.

Khorshidi , Sh., Rostami, N., & Salehpourjam, A. (2021). Prioritizing flood producing potential in ungauged watersheds using the AHP-VIKOR method (Case study: HajiBakhtiar Watershed, Ilam), Environmental Erosion Researches, 11(2), 66-92. 20.1001.1.22517812.1400.11.2.4.4 [In Persian].

Kubal, C., Haase, D., Meyer, V., & Scheuer, S. (2009). Integrated urban flood risk assessment–adapting a multicriteria approach to a city. Natural hazards and Earth System Sciences, 9(6), 1881-1895. https://doi.org/10.5194/nhess-9-1881-2009.

Mishra, K., & Sinha, R. (2020). Flood risk assessment in the Kosi megafan using multi-criteria decision analysis: A hydrogeomorphic approach. Geomorphology, 350, 106861. https://doi.org/10.1016/j. geomorph.2019.106861

Ogato, G. S., Bantider, A., Abebe, K., & Geneletti, D. (2020). Geographic information system (GIS)-Based multicriteria analysis of flooding hazard and risk in Ambo Town and its watershed, West shoa zone, oromia regional State, Ethiopia. Journal of Hydrology: Regional Studies, 27, 100659. https://doi. org/10.1016/j.ejrh.2019.100659

Qanavati, E., Karam, A., & Agha Alikhani, M. (2012). Flood risk zonation in the Farahzad basin (Tehran) using Fuzzy model. Journal of Geography and Environmental Planning Consecutive, 48(4). 20.1001.1.20085362.1391.23.4.8.2

Ouma, Y. O., & Tateishi, R. (2014). Urban flood vulnerability and risk mapping using integrated multi-parametric AHP and GIS: methodological overview and case study assessment. Water, 6(6), 1515-1545. https://doi.org/10.3390/w6061515.

Patil, J. P., Sarangi, A., Singh, O. P., Singh, A.K., & Ahmad, T. (2008). Development of a GIS interface for estimation of runoff from watersheds. Water ResourcesManagement, 22(9), 1221-1239. https://doi.org/10.1007/s11269-007-9222-8

Rezaei, A. R., & Roshani, A. (2024). Prioritization of Factors Affecting Drought using the Fuzzy Analytic Hierarchy Process Method (Study Case: Torbat Heydarieh City). Journal of Drought and Climate change Research, 2(1), 77-92. doi: 10.22077/jdcr.2024.7255.1057

Rashetnia, S., & Jahanbani, H. (2021). Flood vulnerability assessment using a fuzzy rule-based index in Melbourne, Australia. Sustainable Water Resources Management, 7(2), 1-13. https://doi. org/10.1007/s40899-021-00489-w.

Saaty, T. L. (1990). How to make a decision: the analytic hierarchy process. European Journal of Operational Research, 48(1), 9-26. https://doi.org/10.1016/0377-2217(90)90057-I.

Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1), 83-98. https://doi.org/10.1504/IJSSCI.2008.017590.

Saeedi, S., & Asiaei, M. (2021). Flood risk zoning in Sabzevar city using fuzzy logic, Journal of Urban and Regional Development Planning, 5(15), 27-49 [In Persian]. https://doi. org/10.30473/grup.2024.55316.2554.

Schumann, G. J. (2021). Earth Observation for Flood Applications: Progress and Perspectives. Earth Observation for Flood Applications, 3-6. https://doi.org/10.1016/B978-0-12-819412-6.00001-8.

Solaimani, K., & Darvishi, Sh. (2020). Zoning and monitoring of spring 2019 Flood hazard in Khuzestan using Landsat-8 data, Iranian Journal of Eco Hydrology, 7(3), 647-662. 10.22059/ije.2020.302703.1333 [In Persian].

Zadeh, L. A. (1965). Fuzzy sets. Information and control, 8(3), 338-353. https://doi. org/10.1016/S0019-9958(65)90241-X.

Zadeh, L. A. (1988). Fuzzy logic. Computer, 21(4), 83-93. https://doi.org/10.1109/2.53

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