Scientific- Research Quarterly of Geographical Data (SEPEHR)

Scientific- Research Quarterly of Geographical Data (SEPEHR)

Morphometric parameters analysis of watersheds for flood susceptibility zoning (Case study: Kebar-Fordo watershed)

Document Type : Research Paper

Author
Assistant professor, Department of agriculture, Payame Noor University, Tehran, Iran
Abstract
Extended Abstract
Introduction
Flooding as a natural hazard usually takes place in many parts of the world and could be a serious threat to the population and environment of the occurring places. So, analyzing the flooding sensitivity is essential for preventing and reducing future hazardous events in each watershed. Therefore, the following objectives are considered in this study: (a) Determining the sensitivity to flooding of sub-watershed based on some morphometric parameters. (b) Calculating the flood peak discharge in each sub-watershed using Rational method. (c) Investigating the relationship between the flooding sub-watershed rank with respect to morphometric parameters and the estimated rank based on the Rational method.
Materials & Methods
In this study, extracting drainage network and 33 sub-watershed in Kebar-Fordo watershed located in Qom province with an area of ​​128372 hectares were performed by employing Arc Hydro tool in Arc-GIS environment. Then, six different morphometric parameters which affect flood occurrence were calculated. After that, flood sensitivity maps were prepared based on each morphometric parameters while each sub-watershed rank was determined. Finally the total rank of each watershed was estimated by averaging the whole ranks. Due to the lack of adequate observed flood peak discharge values, Rational method was applied to calculate the maximum flood discharge in each sub-watershed. Then Spearman correlation test in SPSS was used to calculate the correlation between the morphometric variable ranks and flood sensitivity of the Rational method.
Results & Discussion
In this study, the main stream length ranking shows that five sub-watersheds 1, 5, 15, 20, and 28 are more susceptible to flooding. The watershed slope ranking indicate that sub-watersheds 20, 22, 25, 27, 28, 30, 31, 32, and 33 are more sensitive to flooding. Based on the roughness number, nine sub-watersheds have a flood sensitivity ranking of more than 3. The total basin relief parameter, which presents the height difference between the highest point and the outlet of the watershed, determines the runoff potential of a basin. The total roughness in sub-watersheds 31, 32, and 33 is higher than 3, which is evidence of flooding in these sub-watersheds. The mean elevation rank also indicates that watersheds 18, 20, 28, 29, 30, 32, and 33 are prone to flooding with a rank greater than 3. The basin perimeter is one of the effective parameters in runoff production. In this study, sub-watersheds 20, 15, 5, 1, and 28 have flood sensitivity ranks greater than 3. The flood susceptibility map of the studied area based on the average rank of the total morphometric parameters shows that the areas with high, medium, low and very low susceptibility classes include 0.49%, 47.79%, 42.87% and 8.85% of the area, respectively. This map shows that sub-watersheds 32, 31 and 33 are the most susceptible areas to flooding. The rank of slope, roughness number, and total basin relief in sub-watershed 32, is higher than 4, which shows that higher elevations and also greater slope lead to less surface infiltration, more overland flow, and therefore higher peak runoff in this sub-watershed. The calculation of the maximum discharge based on Rational method indicates that the flood ranking which is more than 3, could be seen only in sub-watershed 20 whereas, the values less than 3 could be observed in the rest of the sub-watersheds. Also, the Spearman correlation test shows that the relationship between the flood sensitivity rank of Rational method with the parameters of the perimeter and the stream length is significant at the 99% confidence level and the correlation coefficients are 0.898 and 0.784, while its relationship with the parameters of mean elevation, roughness number, total basin relief and slope is not significant. Also, the correlation coefficient between the flood sensitivity ranks of Rational method and the average flood rank of the morphometric parameters is 0.601 which is significant at the confidence level and indicates a positive relationship between these ranks.
Conclusion
This research could be conducted by considering the effect of other parameters, such as land use, flood management practices in each drainage basin, and hydraulic structures along the major streams and rivers. The present study demonstrated that morphometric analysis could be used at different scales to help decision makers for understanding the spatial distribution of flood risk and formulating flood control strategies to minimize its negative impacts on residents and infrastructure, and also, proposed a model for continuously updating the flood mitigation plan for the study area.
Keywords
Subjects

 1- Abdel-Fattah, M., Saber, M., Kantoush, S. A., Khalil, M. F., Sumi, T., & Sefelnasr, A. M. (2017). A hydrological and geomorphometric approach to understanding the generation of wadi flash floods. Water, 9(7), 553.
2- Adnan, M. S. G., Dewan, A., Zannat, K. E., & Abdullah, A. Y. M. (2019). The use of watershed geomorphic data in flash flood susceptibility zoning: a case study of the Karnaphuli and Sangu river basins of Bangladesh. Natural Hazards, 99(1), 425-448.
3- Ahmed, A., Alrajhi, A., Alquwaizany, A., Al Maliki, A., & Hewa, G. (2022). Flood susceptibility mapping using watershed geomorphic data in the Onkaparinga Basin, South Australia. Sustainability, 14(23), 16270.
4- Alam, A., Ahmed, B., & Sammonds, P. (2021). Flash flood susceptibility assessment using the parameters of drainage basin morphometry in SE Bangladesh. Quaternary International, 575, 295-307.
5- Amir Ahmadi, A., Mohammadnia, M., & Golshani, N. (2015). Analysis of Geomorphological Factors Influencing the Flood Using the HEC-HMS Model (Case Study: Zrchshmh Hunjan-Isfahan Province). Journal of Hydrogeomorphology, 2(3), 21-42. (In Persian)
6- Asgari, Sh., Safari, A., Fathi, H. (2018). Investigating the potential of flooding in the Jafarabad watershed. Applied Research in Geographical Sciences, 50(17), 77-90. (In Persian)
7- Azizi, E., Mostafazadeh, R., Hazbavi, Z., Esmali Ouri, A., & Mirzaie, S. (2022). Screening watersheds of Ardabil province concerning flood vulnerability. Iranian Journal of Rainwater Catchment Systems, 10(2), 11-26. (In Persian)
8- Bajabaa, S., Masoud, M., & Al-Amri, N. (2014). Flash flood hazard mapping based on quantitative hydrology, geomorphology and GIS techniques (case study of Wadi Al Lith, Saudi Arabia). Arabian Journal of Geosciences, 7(6), 2469-2481.
9- Behzad, A., Sarvati, M., & Moghimi, E. (2010). Estimating Flood Potential of Goharrud Basin by Emphasize on Geomorphologic Characters by Using SCS Method. Geographic Thought, 4(7), 88-105. (In Persian)
10- Bhat, M. S., Alam, A., Ahmad, S., Farooq, H., & Ahmad, B. (2019). Flood hazard assessment of upper Jhelum basin using morphometric parameters. Environmental Earth Sciences, 78(2), 54.
11- Chamani, R., Mostafazadeh, R., Kalehhouei, M., & Haji, K. (2023). Determining the spatial correlation and pattern of changes in the height and volume of runoff in the sub-watersheds of Sharganj Birjand region. Quantitative Geomorphological Research, 12(3), 201-219. (In Persian)
12- Costa, J. E. (1987). Hydraulics and basin morphometry of the largest flash floods in the conterminous United States. Journal of hydrology, 93(3-4), 313-338.
13- Dutal H (2023). Using morphometric analysis for assessment of flash flood susceptibility in the Mediterranean region of Turkey. Environmental Monitoring and Assessment, 195(5), 582.
14- Elnazer, A. A., Salman, S. A., & Asmoay, A. S. (2017). Flash flood hazard affected Ras Gharib city, Red Sea, Egypt: a proposed flash flood channel. Natural hazards, 89(3), 1389-1400.
15- Fakhrabadi, S. M. T., & Chezgi, J. (2023). Effect of morphometric factors in prioritizing flooding of sub-watersheds in the north of Birjand Plain.Soil and Soil Management and Modeling, 3(3), 240-255. (In Persian)
16- Farhan, Y., Anaba, O., & Salim, A. (2017). Morphometric analysis and flash floods assessment for drainage basins of the Ras En Naqb Area, South Jordan Using GIS. Applied Morphometry and Watershed Management Using RS, GIS and Multivariate Statistics (Case Studies), Scientific research publishing, Inc. USA.  p 413.
17- Ghodrati, M., (1401). A training book on the use of ARC GIS in water and environmental engineering, Simaye Danesh, Iran. p 285. (In Persian)
18- Hettiarachchi, S., Wasko, C., & Sharma, A. (2018). Increase in flood risk resulting from climate change in a developed urban watershedthe role of storm temporal patterns. Hydrology and Earth System Sciences, 22(3), 2041-2056.
19- Javan, P., Tabari, M. M. R., & Mirzaei, M. (2013). Flood Risk Mapping Using Flow Energy Equation and Geographic Information System. Journal of Water and Wastewater; 24(3), 101-111. (In Persian)
20- Jodi, R., Esmali Ouri, A., Mostafazadeh, R., & Golshan, M. (2023). Flood susceptibility mapping using the frequency ratio method in Khiav Chai Watershed, Ardabil. Journal of Watershed Management Research, 14(27), 1-14. (In Persian)
21- Kabenge, M., Elaru, J., Wang, H., & Li, F. (2017). Characterizing flood hazard risk in data-scarce areas, using a remote sensing and GIS-based flood hazard index. Natural hazards, 89(3), 1369-1387.
22- Kamal, A. M., Shamsudduha, M., Ahmed, B., Hassan, S. K., Islam, M. S., Kelman, I., & Fordham, M. (2018). Resilience to flash floods in wetland communities of northeastern Bangladesh. International journal of disaster risk reduction, 31, 478-488.
23- Kazemi, M., & Jafarpoor, A. (2024). Identifying the threshold of variables affecting flood zones using machinelearning technique (Case study: the downstream region of the Karun River). Water and Soil Management and Modeling, 4(1), 214-232. (In Persian)
24- Lin, L., Di, L., Tang, J., Yu, E., Zhang, C., Rahman, M. S., & Kang, L. (2019). Improvement and validation of NASA/MODIS NRT global flood mapping. Remote Sensing, 11(2), 205.
25- Melton, M. (1957). An Analysis of the Relations Among Elements of Climate, Surface Properties and Geomorphology. Department of Geology, Columbia University, Technical Report, 11, Project NR 389-042. Office of Navy Research, New York.
26- Menbari, F., Maleki, A., & Nayyeri, H. (2023). Factor Analysis of the morphometric indices and Flood modeling: A Case Study of Watersheds in Kurdistan Province. Quantitative Geomorphological Research, 12(1), 224-240. (In Persian)
27- Mostafazadeh, R., Haji, K., Esmali-Ouri, A., & Nazarnejad, H. (2017). Prioritization the critical subwatersheds based on soil erosion and sediment using watershed erosion response model (WERM) and morphometric analysis (case study: Rozechai watershed, West Azerbaijan Province). Journal of Watershed Management Research, 8(16), 142-156. (In Persian)
28- Pangali Sharma, T. P., Zhang, J., Khanal, N. R., Prodhan, F. A., Nanzad, L., Zhang, D., & Nepal, P. (2021). A geomorphic approach for identifying flash flood potential areas in the East Rapti River Basin of Nepal. ISPRS International Journal of Geo-Information, 10(4), 247.
29- Rahman, M. S., & Di, L. (2017). The state of the art of spaceborne remote sensing in flood management. Natural Hazards, 85(2), 1223-1248.
30- Rajabi, M., Roostaei, S., & Barzkar, M. (2022). Evaluation of flood potential under basins based on morphometric parameters and correlation test (Case: Zab catchment to Mirabad). Journal of Geography and Planning, 26(79), 139-127. (In Persian)
31- Sarkar, D., & Mondal, P. (2020). Flood vulnerability mapping using frequency ratio (FR) model: a case study on Kulik river basin, Indo-Bangladesh Barind region. Applied Water Science, 10(1), 1-13.
32- Schumm, S. A. (1956). Evolution of drainage systems and slopes in badlands at Perth Amboy, New Jersey. Geological society of America bulletin, 67(5), 597-646.
33- Sharma, A., Wasko, C., & Lettenmaier, D. P. (2018). If precipitation extremes are increasing, why aren’t floods?. Water resources research, 54(11), 8545-8551.
34- Shehata, M., & Mizunaga, H. (2018). Flash flood risk assessment for Kyushu Island, Japan. Environmental earth sciences, 77(3), 76.
35- Singh, S., Dhote, P. R., Thakur, P. K., Chouksey, A., & Aggarwal, S. P. (2021). Identification of flash-floods-prone river reaches in Beas river basin using GIS-based multi-criteria technique: validation using field and satellite observations. Natural Hazards, 105(3), 2431-2453.
36- Taheri Behbahani, M.T., Bozorgzadeh, M. (1996). Urban floods, Iranian Urban Planning and Architecture Studies and Research Center, Iran. p 536. (In Persian)
37- Youssef, A. M., Pradhan, B., & Hassan, A. M. (2011). Flash flood risk estimation along the St. Katherine road, southern Sinai, Egypt using GIS based morphometry and satellite imagery. Environmental Earth Sciences, 62(3), 611-623.