Examining the maximum discharge values on the occurrence of flooding in the dimensionless gamma structure (Case study: Shiraz geomorphic basin)

Roostaei, Shahram; Eftekhar, Hasan; Karami, Fariba; Negahban, Saeid

doi:10.22111/jneh.2023.43274.1921

Examining the maximum discharge values on the occurrence of flooding in the dimensionless gamma structure (Case study: Shiraz geomorphic basin)

Document Type : Research Article

Authors

¹ Professor of Faculty of Environmental Planning, Department of Geomorphology, University of Tabriz, Tabriz, Iran

² PhD Student of Geomorphology, Faculty of Environmental Planning, Tabriz University, Tabriz, Iran

³ Associate Professor, Department of Geography, Faculty of Economics, Management and Social Sciences, Shiraz University, Shiraz, Iran

10.22111/jneh.2023.43274.1921

Abstract

The present study was conducted with the aim of a comprehensive study on the management of discharges affecting the occurrence of urban floods in the Shiraz Basin. Shiraz catchment area with an area of 1865.10 square kilometers and dry and semi-arid climate with average vegetation is due to droughts and land use changes. which indicates the flood conditions of the basin at the time of sudden showers. The statistical-analytical research method and its type are practical. For this purpose, the long-term statistics of precipitation in the rain gauge station of Shiraz Basin during the 50 years and the maximum daily discharge during the 44 years of the water gauge stations in the region have been used in data collection. Then, to choose the appropriate distribution, the data of each station was entered into the "Excel" environment the maximum discharge was extracted, and the outputs and algebraic criteria were calculated and prepared in the Graphers 16 software. In the next step, based on Pearson's coefficient of goodness of fit, the values of the k² difference of the discharge of each year from the average and dividing it again by the average are calculated during the Pearson-Euler chi-square analysis in an ergodic structure. Dry river, Gamma probability function with 44 years of peak flow degree of freedom, and Riemann integral method for the probability of occurrence of the variance of discharges located in the dry river have been used to predict the confidence interval and the probability of occurrence. Finally, this research showed that the use of the dimensionless gamma grouping structure, which is based on a holomorphism composed of increasing chaos and decreasing fractals, has a very reliable trend with a correlation of 0.8% and a correlation coefficient of 89% for the 44-year river discharge values. Dry with a slope gradient of 30% (16 degrees and 42 minutes), is much more realistic than other groupings, and is more effective for measuring the probability of the occurrence of peak discharges in future years and better management of urban floods.

Keywords

Main Subjects

Environmental Hazards

References

References (in Persian)

Askari, Sh., Ahmadi, M., Hemti, M. (2014). Side erosion of Cherdavel River using HEC-RAS model in GIS environment. Geographical Research Quarterly, 30(1), 80-71. [In Persian].

Damadi, S., Dehwari, A., Dehmarde Ghale, M., Ebrahimian, M. (2019). flood zoning using the HEC-RAS hydraulic model of the Sarbaz River in Sistan and Baluchistan province. Scientific-Research Journal of Watershed Management Engineering, Volume 13, Number 3. pp. 590-610. [In Persian].

Hejazi, A., Khodei Qashlaq, F., Khodayi Qashlaq, L. (2018). flood risk zoning in the Varkash Chai watershed using HEC-RAS software and HEC-GEO-RAS extension. Geographical Sciences Applied Research Quarterly, 19(53), 156-137. [In Persian].

Hosseinzadeh, M., Biranvand, S., Hosseini, A. (2012). Simulation of Kashkan river flood, Iranian Remote Sensing and GIS Quarterly, Volume 5, Number 1. [In Persian].

Portahari, M., Sejasi Khedari, H., Sadeghlou, T. (2017). comparative evaluation of natural hazard rating methods in rural areas, a case study of Zanjan province. Rural Research Quarterly, 2 (3): 31-54. [In Persian].

Rostami Fathabadi, M., Jafar Biglou, M., Moghimi. (2019).Spatial analysis of flood-prone and flood-prone areas of Noorabad city of Lorestan and its hazards. Environmental risk management (former risk knowledge). 7(27), pp: 313-329. [In Persian].

Safari, A., Sasanpour, F., Musa Vand, J. (2018). evaluation of the vulnerability of urban areas against flood risk using geographic information system and fuzzy logic, a case study of the 3rd district of Tehran. Geographical Sciences Applied Research Quarterly, 20: 129-50. [In Persian].

References (in English)

Avand, M.T., Moradi, H.R., and M, Ramazanzadeh., (2021). Spatial modeling of flood probability using geo-environmental variables and machine learning models, case study: Tajan watershed, Iran. Advances in Space Research, 67: 3169-3186 .https://doi.org/10.1016/j.asr.2021.02.011

Bates, P.D., De Roo, A.P.J. (2000). A simple raster-based model for flood inundation simulation. Journal of Hydrology, 236, 54 – 77.

Black, A.R., Burns, J.C. (2002). Re-assessing the flood risk in Scotland. Science of The Total Environment, 294 (1), 169–184.

Brierley, G., L., and Fryirs, K., 2005. geomorphology and river management application of the river style framework. Blackwell Publishing, Malden. MA. pp 398. DOI:10.1002/9780470751367

Chang, H.S., Chen, T.L., (2016). Spatial heterogeneity of local flood vulnerability indicators within flood-prone areas in Taiwan. Environmental Earth Sciences, 75(23): 1-14. https://doi.org/10.1007/s12665-016-6294-x

Dass 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.

Ezzine, A., Saidi, S., Hermassi, T., Kammessi, I., Darragi, F., Rajhi, H., (2020). Flood mapping using hydraulic modeling and Sentinel-1 image: Case study of Medjerda Basin, northern Tunisia: The Egyptian. Journal of Remote Sensing and Space Sciences, 23: 303-310. https://doi.org/10.1016/j.ejrs.2020.03.001

Fernandez, Diego., Lutz, M. A. (2010). Urban flood hazard zoning in Tucuman Province, Argentina, using GIS and multicriteria decision analysis. Engineering Geology, 111, 90–98.

Green, C., Diepernk, G., EK, K., Hegger, D., Pettersson, M., Priest, S., Tapsell, S. (2014). Flood risk management in Europe: the flood problem and interventions, Star flood.

Hajkowicz, S., Collins, K. (2007). A review of multiple criteria analysis for water resource planning and management. Water Resour Manage, 21 (9), 1553–1566.

Khattak, M.S., Anwar, F., Saeed, T., Sharif, M., Sheraz, K., Ahmed, A. (2016). Floodplain Mapping Using HEC-RAS And ArcGIS: A Case Study of Kabul River.Arab J SciEng. 41:1375–1390.

Khosravi, K.h., Panahi, M., Golkarian, A., Keesstra, S.D., Saco, P.M., Tien, B.D., Lee, S., (2021). Convolutional neural network approach for spatial prediction of flood hazard at national scale of Iran. Journal of Hydrology, 591: 2-35. https://doi.org/10.1016/j.jhydrol.2020.125552

Khosravi, K.h., Pham, B.T., Chapi, K., Shirzadi, A., Shahabi, H., Revhaug, I., Prakash, I., Tien Bui, D., (2018). A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran. Science of The Total Environment,627: 744-755. https://doi.org/10.1016/j.scitotenv.2018.01.266

Lyu, H.M., Shen, S.L. Zhou, A.Y. (2019). Perspectives for flood risk assessment and management for mega-city metro system. Tunnelling and Underground Space Technology, 76, 31-46.

Mejía-Navarro, M., Wohl, E.E., Oaks, S.D. (1994). Geological hazards, vulnerability, and risk assessment using GIS: a model for Glenwood Springs Colorado. Geomorphology, 10 (1), 331–354.

Parhi, P.K. (2018). Flood Management in Mahanadi Basin using HEC-RAS and Gumbel’s Extreme Value Distribution. Journal of the Institution of Engineers (India): Series A, 99(4):751–755.

Schumann, A. H., Funke, R., Schultz, G. A. (2000). Application of a geographic information system for conceptual rainfall-runoff modeling. Journal of Hydrology, 240 (1), 45–61.

Voogd, j.H. (1983). Multicriteria Evaluation for Urban and Regional Planning: Pion, London. 388 p.

Xiao, Y., Yi, S., Tang, Z. (2017). Integrated flood hazard assessment based on spatial ordered weighted averaging method considering spatial heterogeneity of risk preference. Science of The Total Environment, 599-600, 1034-1046.

Zelenakova, F.R., Labant, S., Weiss, E., Markovic, G., Weiss, R. (2019). Flood risk modeling of the Slatvinec stream in Kru_zlov village, Slovakia. Journal of Cleaner Production, 212, 109-118.

Zhu, S., Li, D., Huang, G., Chhipi-Shrestha, G., Nahiduzzaman, K.M., Hewage, K., Sadiq, R. (2020); Enhancing urban flood resilience: a holistic framework incorporating historic worst flood to Yangtze River Delta, China, International Journal of Disaster Risk Reduction, Vol 61: 1-52.