Remote Sensing and GIS Applications in Environmental Sciences

Investigating the potential of flood risk in the Kerman watershed

Document Type : Original Article

Authors

1 Associat Professor, Department of Geography, Faculty of Literature, Shahid Bahonar University of Kerman, Kerman, Iran

2 Associat Professor, Department of Geography, Faculty of Literature, Shahid Bahonar University of Kerman, Kerman, Iran.

3 MSc Student of Natural Hazard. Department of Geography, Faculty of Literature, Shahid Bahonar University of Kerman. Kerman, Iran.

10.22034/rsgi.2025.65134.1117

Abstract

Objective: Nowadays, due to climate change, the flood problem is one of the most important problems in arid and semi-arid regions. Kerman Plain is one of these regions that has suffered extensive damage in infrastructure and agriculture. The purpose of this research is to analyze the flooding of the Kerman watershed and to zone the flood risk using radar data processing and fuzzy techniques.
Methods: In this regard, eight factors were used: cumulative flow, discharge capacity, distance from the watercourse, runoff rate, land cover, land elevation, slope and geology. Pairwise comparison matrices for the aforementioned factors were prepared using the fuzzy-hierarchical method, weighted and integrated in GIS. Then, a flood risk map was drawn using the flood risk index.
Results: The results showed that about 16 percent of the study area is at very high risk (81,184 hectares), 22 percent at high risk (111,628 hectares), 35 percent at medium risk (177,590 hectares), 18 percent at low risk (91,332 hectares) and 9 percent at very low risk (45,666 hectares). The results showed that in addition to agricultural gardens, many residential areas are at risk of flooding. In addition, By processing radar images, the flood that occurred on August 8, 1401 in the study area was mapped and used to validate the flood hazard map.
Conclusions: the present study shows that many areas of the Kerman Plain are at high flood risk and should be specifically considered..

Keywords

Main Subjects

امروزه به سبب تغییرات آب و هوایی مسئله سیلاب یکی از مهمترین معظلات مناطق خشک و نیمه­خشک است. دشت کرمان از جمله این مناطق است که تا کنون دچار خسارت­های زیادی در حوزه­های زیربنایی و کشاورزی شده است. هدف از این پژوهش تحلیل سیل­خیزی حوضه آبریز کرمان و پهنه­بندی خطر سیلاب، با استفاده از پردازش داده­های راداری و تکنیک فازی است. در این جهت از هشت عامل جریان تجمعی، قابلیت تخلیه، فاصله از آبراهه، میزان رواناب، پوشش زمین، ارتفاع سطح زمین، شیب و لیتولوژی استفاده شد. ماتریس مقایسات زوجی برای عوامل مذکور با استفاده از روش فازی- سلسله مراتبی، تهیه و در GIS وزن­دهی و مورد تلفیق قرار گرفتند ؟؟؟؟. سپس با استفاده از شاخص خطر سیلاب، نقشه خطر سیلاب ترسیم شد. نتایج حاصله نشان داد که در حدود 16 درصد از منطقه مورد مطالعه در خطر بسیار بالا (81184 هکتار)، 22 درصد در خطر بالا (111628 هکتار)،  35 درصد در خطر متوسط (177590 هکتار)، 18 درصد در خطر کم (91332 هکتار) و 9 درصد در خطر بسیار کم (45666 هکتار)، قرار دارد. نتایج حاصله نشان داد که علاوه بر باغات کشاورزی بسیاری از مناطق مسکونی در معرض خطر سیلاب هستند. با پردازش تصاویر راداری، سیلاب 8 مرداد ماه 1401 رخ­ داده در محدوده مورد مطالعه، نقشه­برداری و از آن در راستای اعتبارسنجی نقشه خطر سیلاب، استفاده شد. بنابراین پژوهش حاضر نشان می­دهد که بسیاری از مناطق دشت کرمان در معرض خطر سیلاب بالا قرار دارند و بایستی به طور ویژه مورد نظر باشند.

Ahmed, I.,  Das, N., Debnath, J.,  Bhowmik, M., & Bhattacharjee, S. (2024).   Flood hazard zonation using GIS-based multi-parametric Analytical Hierarchy Process. Geosystems and Geoenvironment, 3(2): 100250. https://doi.org/10.1016/j.geogeo.2023.100250
Andualem, T.G., & Demeke, G.G. (2019). Groundwater potential assessment using GIS and remote sensing: A case study of Guna tana landscape, upper blue Nile Basin, Ethiopia. Journal of Hydrology: Regional Studies, 24, 100610. https://doi.org/10.1016/j.ejrh.2019.100610.
Ashtari, N., Goorabi, A., Rahmati, M., & Darban Astaneh, A. (2022). Evaluation of Flood Hazard Potential and Investigation of Damage Caused by it in Talar Drainage Watershed. E.E.R. 12 (4) :1-25. (In Persian). URL: http://magazine.hormozgan.ac.ir/article-1-708-fa.html
Azadikhah, A., Bouzari, S., Yassaghi, A., & Emami, M.H. (2015). Formation of Extensional Basin in Internal Part of the Zag-Ros Orogeny in West of Sirjan, Iran. Open Journal of Geology, 5, 821-827. https://doi.org/10.4236/ojg.2015.511070
Baharvand, S., Rahnamarad, J., & Soori, S. (2016). Delineation of groundwater recharge potential zones using weighted linear combination method (case study: Kuhdasht plain, Iran). Journal of Geotechnical Geology, 12(2): 119-125.  https://www.sid.ir/paper/691618/en
Bates, P.D., Anderson, M.G., Baird, L., Walling, D.E, & Simm, D. (2009). Modelling floodplain flow with a two dimensional finite element scheme. Earth Surface Processes and Landforms, 17, 575-588. https://doi.org/10.1002/esp.3290170604
Chang, D.Y. (1996). Applications of the extent analysis method on fuzzy AHP. Eur J Oper Res., 95, 649–655. https://doi.org/10.1016/0377-2217(95)00300-2
Das, S. (2019). Geospatial mapping of flood susceptibility and hydro-geomorphic response to the floods in Ulhas basin, India. Remote Sensing Applications: Society and Environment, 14, 60-74. https://doi.org/10.1016/j.rsase.2019.02.006
Dash, P., & Sar, J. (2020). Identification and validation of potential flood hazard area using GIS-based multi-criteria analysis and satellite data-derived water index. J Flood Hazard Management. 13, 12620. https://doi.org/10.1111/jfr3.12620.
Deshmukh, K.S., & Shinde, G., (2005). An adaptive color image segmentation electron. Electron Lett Computer Vis Image Anal, 5(4):12–23. https://doi.org/10.5565/rev/elcvi a.115.
Esfandyari, F., Abedini, M., fakheripour, N., & Nezafat takle, B. (2023). Flood Risk Zoning Using Hec_Ras Hydrodynamic Model (Case Study: Qarahsou Basin, Kermanshah Province). Journal of Environmental Science Studies, 8(3), 6952-6961. (In Persian).   https://doi.org/10.22034/jess.2022.344023.1795
Jenifer, M.A., & Jha, M.K., (2017). Comparison of Analytic Hierarchy process, Catastrophe and Entropy techniques for evaluating groundwater prospect of hard-rock aquifer systems. J. Hydrol. (Amst), 548, 605–624. https://doi.org/10.1016/j.jhydrol.2017.03.023
Kazakis, N., Kougias, I., & Patsialis, T. (2015). Assessment of flood hazard areas at a regional scale using an index-based approach and analytical hierarchy process: Application in Rhodope-Evros region, Greece. Science of the Total Environment, 538, 555–563. https://doi.org/10.1016/j.scitotenv.2015.08.055.
Khedmatzadeh, A., & Najafzadeh, A. (2020). Flood Susceptibility Mapping and Risk Area Using GIS-Based Analytic Network Process (Case Study: Ghasemlou Hydrometric Station Basin). Journal of Science and Engineering Elites, 5(1): 6-12. (In Persian). https://www.sid.ir/paper/363369/en.
Mind'je, R., Li, L., Amanambu, A. C., Nahayo, L., Nsengiyumva, J. B., Gasirabo, A.,  & Mindje, M. (2019). Flood susceptibility modeling and hazard perception in Rwanda. International Journal of Disaster Hazard Reduction, 10, 1211. https://doi.org/10.1016/j.ijdrr.2019.101211
Mir Mosavi, S., & Esmaeili, H. (2021). Zoning of Flood-prone Areas Using Geographic Information System (GIS) and Remote Sensing (RS), (Case Study: Darab City). Journal of Natural Environmental Hazards, 10(27): 21-46. doi: https://doi.org/10.22111/jneh.2020.32986.1613. (In Persian).
Mitra, R., Saha, P., & Das, J. (2022). Assessment of the performance of GIS-based analytical hierarchical process (AHP) approach for flood modelling in Uttar Dinajpur district of West Bengal, India. Geomatics. Nat Hazards Risk, 13(1): 2183–2226 https://doi.org/10.1080/19475705.2022.2112094
Mohammad Doust, A., & Shamsnia, S.A. (2023). Identification and Zoning of Flood-Prone Areas Using AHP - GIS (Case Study: Dayyer County, Bushehr Province). Journal of Geography and Environmental  Studies, 47,152-167. (In Persian). Dor: 20.1001.1.20087845.1402.12.47.9.5
Osman, S.A., & Das, J. (2023). GIS-based flood risk assessment using multi-criteria decision analysis of Shebelle River Basin in southern Somalia. SN Appl. Sci., 5, 134. https://doi.org/10.1007/s42452-023-05360-5
Ouma, Y. O., & Tateishi, R. (2014). Urban flood vulnerability and hazard 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
Pappenberger, F., Frodsham, K., Beven, K., Romanowicz, R., & Matgen, P. (2007). Fuzzy set approach to calibrating distributed flood inundation models using remote sensing observations. Hydrol. Earth Syst. Sci., 11, 739–752, https://doi.org/10.5194/hess-11-739-2007, 2007.
Poddar, I,. Alam, J., Basak, A., Mitra, R., & Das, J. (2023). Application of a geospatial-based subjective MCDM Method for Flood susceptibility modeling in Teesta River Basin, West Bengal, India. Monitoring and managing multi-hazards. Springer, Cham, pp 135–152. https://doi.org/10.1007/978-3-031-15377-8_10
Rajasekhar, M., Raju, G.S., Sreenivasulu, Y., & Raju, R.S. (2019). Delineation of groundwater potential zones in semi-arid region of Jilledubanderu river basin, Anantapur District, Andhra Pradesh, India using fuzzy logic, AHP and integrated fuzzy-AHP approaches. HydroResearch, 2, 97–108. https://doi.org/10.1016/j.hydres.2019.11.006.
Samela, C., Albano, R., Sole, A., & Manfreda, S., (2018). A GIS tool for cost-effective delineation of flood-prone areas, Computers. Environment and Urban Systems, 70, 43-52. https://doi.org/10.1016/j.compenvurbsys.2018.01.013
Soleimani Sardoo, F., Rafiei Sarooi, 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, jwmseir. 15(53): 23-32. (In Persian). http://jwmsei.ir/article-1-976-fa.html
Tseng, M.L., Lin, Y.H., Chiu, A.S.F., & Chen, C.Y. (2008). Fuzzy AHP approach to TQM strategy evaluation. IEMS 7(1): 34–43. http://www.iemsjl.org/journal/article.php
Valizadeh, K., Delire R., & Azari, K. (2019). Flood zoning and its impact on land use in the surrounding area using unmanned aerial vehicles (UAV) images and GIS. Journal of RS and GIS for Natural Resources, 10(3): 59-75. (In Persian). https://www.sid.ir/paper/189492/fa
Viglione, A., Merz, R., & Blöschl, G. (2009). On the role of the runoff coefficient in the mapping of rainfall to flood return periods, Hydrology and Earth System Sciences. 13(5): 577–593. http://hdl.handle.net/20.500.12708/166187
Wu, Y., Zhong, P. A., Zhang, Y., Xu, B., Ma, B., & Yan, K. (2015). Integrated flood hazard assessment and zonation method: A case study in Huaihe River basin, China. Natural Hazards, 78(1): 635–651. https://doi.org/10.1007/s11069-015-1737-3
Xiao, JF., Li, J., & Moody, A. (2003). A detail-preserving and flexible adaptive filter for speckle suppression in SAR imagery. Int J Remote Sens., 24(12): 2451–2465. https://doi.org/10.1080/01431 16021 01548 85.
 
Remote Sensing and GIS Applications in Environmental Sciences
Volume 5, Issue 17
February 2026
Pages 33-17
  • Receive Date: 23 December 2024
  • Revise Date: 08 February 2025
  • Accept Date: 12 December 2025