Document Type : پژوهشی

Authors

1 Assistant Professor of Water Engineering Department

2 PhD student Water structures

3 Master of Water Engineering

Abstract

1-Introduction
Flood is a natural phenomenon that human societies have accepted as an unavoidable event caused by a number of factors, depending on the climatic and natural conditions of the region. It is believed that the relationship between rainfall and runoff is significantly different from one basin to another. Given that, in order to prevent the occurrence of such harmful phenomena, it is not possible at present to make changes in the factors and elements of the atmosphere. Therefore, any principled and useful solution should be sought on the ground, especially in watersheds. From this point of view, areas with "high potential" for flood production should be identified. Accordingly, the first measure to reduce the risk of floods for the sustainable settlement of the population is to control floods at their source, namely, the watershed sub-basins. Thus, it is essential to identify floodplains within the basin; however, due to the large size and scope of the watersheds, is not possible to carry out modeling, implementation and remediation operations throughout the basin. Thus, it is advised to use various computerized models to prevent floods.
2-Methodology
In this study, it has been attempted to combine GIS and multi-criteria decision-making systems (MCDM) to identify areas with different degrees of flood risk for sustainable settlement of the population in each of the cities of Khorasan Razavi Province, Iran. For this purpose, first the data of 6 effective parameters including Maximum discharge with 2, 3, 5, 10, 25, 50, 100 and 200 year return periods obtained from HEC-HMS software output, drainage density, land use and vegetation, CN, slope and permeability of the

 
study area were prepared in GIS software environment. Then, using ANP method and pairwise comparison, the weight of each criterion and the weight of the classes of each layer were calculated in Super Decision software, respectively. Then, using GIS software analysis functions, the whole range was zoned for each of the specified criteria. Ultimately, through combination of the zoned maps and based on the weights of the ANP, the final map was prepared in five classes of low-risk flooding and high-risk flooding areas.
3-Results and Discussion
The results area of the cities exposed to floods with a very high degree as well as flood risk zoning with a return period of 2 years in the entire Khorasan Razavi province show more than 86% of areas with low and very low flooding, 12.2% of medium areas and 1.8% with high. While the results of flood zoning in the 200-year return period show 41.3% low flooding, 31.4% moderate flooding, 13.3% high flooding and 14.1% very high flooding in the entire province.
4-Conclusions
The results of this study were analyzed using field visits and ground control, which indicates that all selection criteria are met revealing the usefulness of combining MCDM methods with GIS in identifying areas with different degrees of flood risk.
Keywords: Flood risk, Population settlement, Couple comparison, Khorasan Razavi

Keywords

Abedini, M., Fathi Jokadan, R. (2016). Flood Risk Zoning in the Karganroud’s Catchment Basin Using ArcGIS, Hydrogeomorphology, 2(7), 1-17. (In Persian)
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.
Ebadi Aghdam, S., Saqebian, S.M. (2019). Flood risk zoning using GIS and hierarchical analysis process (Case study: Sarandchay watershed), The Second Conference on Architecture, Urban Planning, Civil Engineering and Geography in Sustainable Development, (In Persian).
Ekhtesasi M R. Sepehr A. (2011). Methods and models for assessing and preparing desertification maps. Yazd University (In Persian).
Falah, f., Rahmati, O.,  Rostami, M., Ahmadisharaf, E., Daliakopoulos,  I., Pourghasemi, H.R. (2019).Artificial neural networks for flood susceptibility mapping in data-scarce urban areas, Spatial Modeling in GIS and R forEarth and EnvironmentalSciences, Elsevier, 323–337.
Ghasemiayan, H., Najafi, E. (2019). Flood Hazard Zoning in Kouhdasht City Using Hierarchical and Fuzzy Analysis Model1, Geography and human relationships, 2(3), 403-417. (In Persian)
Gholami, M., Ganavati, E., Ahmadabadi, A. (2019). Simulation of floodplain zones in Tehran's metropolitan watershed (case study: Kaan basin), Journal of Spatial Analysis Environmental hazarts, 6(4), 95-108. (In Persian)
Hajkowicz, S., Collins, K. (2007). A review of multiple criteria analysis for water resource planning and management, Water Resour, Manage, 21 (9), 1553–1566.
Hasanloo, M., Pahlavani, P., Bigdeli, B. (2019). Flood Risk Zonation Using a Multi-Criteria Spatial Group Fuzzy-Ahp Decision Making and Fuzzy Overlay Analysis, The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 42: 455-460.
Kim, V., Tantanee, S., Suparta, W. (2020). Gis-based flood hazard mapping using hec-ras model: a case study of lower mekong river, cambodia, Geographia technica, 15(1), 16-26.
Lyua, H., Long Shena, S., Zhoub, A., Yangc, J. (2019). Perspectives for flood risk assessment and management for mega-city metro system. Tunnelling and Underground Space Technology, 31-44.
Madadi, A., Piroozi, E., Aghayary, L. (2019). Flood Hazard Zonation by Combining SCS-CN and WLC Methods (Case study: Khiyave Chay Meshkinshahr Basin), Hydrogeomorphology, 5(17), 85-102. (In Persian)
Mejía-Navarro, M., Ellen, W., Oaks, E., Sherry D. (1994). Geological hazards, vulnerability, and risk assessment using GIS: model for Glenwood Springs Colorado. Geomorphology, 10 (1), 331–354.
Mokhtari, D., Rezaei Moghaddam, M.H., Rahimpour, T., Moazzez, S. (2020). Preparing the Risk Map of Flood Occurrence in the Ghomnab Chai Basin Using ANP model and GIS Technique, EcoHydrology, 7(2), 497-502. (In Persian)
Nohegar, A., Riahi, F., Kamangar, M. (2016). Determining suitable areas for flood spreading with the approach of sustainable development of groundwater resources Case study: Sarkhon plain, Environmental Science, 42 (1): 33-48. (In Persian)
Nott, J. (2006). Extreme Events: A physical reconstruction and risk assessment. CambridgeUniversity Press.
Rostami, N., Kazemi, Y. (2019). Flood hazard zoning in the Ilam city using AHP and GIS, Journal of Spatial Analysis Environmental Hazarts; 6 (1), 179-192. (In Persian)
Shafiei Motlagh, K., Ebadati, N. (2020). Flood Zoning and Hydraulic Behavior Simulation Using HEC RAS in (GIS) Case Study: Maroon River - Southwestern Iran, journal of Ecohydrology, 7(2), 397-409. (In Persian).
Schumann, Andreas 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.
Saaty, T.L. (1980). The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. McGraw-Hill. Book Co, New York, 287.
Voogd, H., (1983). Multicriteria Evaluation for Urban and Regional Planning, 207 Pion, London
Xiao, Y., Yi, S., Tang, Z. (2017). Integrated flood hazard assessment based on spatial ordered weighted averaging method considering spatial heterogeneity of risk preference.Sci. Total Environ, 599, 10-34.
Yari, A., Ardelan, A., Ostadtaghizadeha, A., Zarezadeh, Y., Soufi Boubakran, M. (2019). Underlying factors affecting death due to flood in Iran: A qualitative content analysis, International Journal of Disaster Risk Reduction, 40, 101258.
Zelenakova, H., Fijko, R., Labant S, Weiss E., Markovic G., Weiss R. (2019). Flood risk modelling of the Slatvinec stream in Kru _ zlov village, Slovakia, Journal of Cleaner Cleaner Production, 21.