Comparison and prioritization of flooding in Nekarood sub-basins using morphometric method in GIS

Subject Areas : Agriculture, rangeland, watershed and forestry

Mehrab Zali ¹ , Karim Solaimani ² , Mahmoud Habibnejad Roshan ³ , Mir Hassan Miryaghoubzadeh ⁴

1 - MSc. Student of Watershed Management, Faculty of Natural Resources, Sari University of Agricultural Sciences and Natural Resources, Iran
2 - Professor, Department of Watershed Management Engineering, Faculty of Natural Resources, Sari University of Agricultural Sciences and Natural Resources, Sari, Iran
3 - Professor, Department of Watershed Management Engineering, Faculty of Natural Resources, Sari University of Agricultural Sciences and Natural Resources, Sari, Iran
4 - Assistant Professor, Department of Watershed Management, Faculty of Natural Resources, Urmia University, West Azerbaijan, Iran

Received: 2021-07-31 Accepted : 2021-08-26 Published : 2022-05-22

Keywords: Nekarood watershed, morphological analysis, prioritization, Flood,

Abstract :

Background and Objective Floods are one of the most catastrophic and dangerous natural hazards because they are sudden and unpredictable and lead to the destruction of infrastructure, and a threat to human life and property. Identifying areas with high flood potential is one of the most important tasks in flood control and reducing the damage caused by it. Floods are one of the most serious natural hazards that pose serious threats to residential areas and also pose financial and human risks. Floods rank first in terms of damage caused by earthquakes, volcanoes, and landslides. Cited. Floods can occur not only in the plains but also in mountainous environments. Flood analysis and its relationship to explanatory variables can help water managers identify the most effective variable in floods. Communities, countries, and pcontinents have suffered severe human losses and economic costs due to the increasing severity and frequency of these natural disasters). In the world due to the increase of these natural disasters, human death in the coming period is probably doubled. Floods are one of the most serious natural hazards that pose a serious threat to residential areas. Climate change and the steady increase in urbanization that occurs with increasing population, followed by an increase in man-made structures, ultimately reduce permeability and possibly further increase the risk of floods and the potential for socio-economic damage. Confirming the growing risks and increasing frequency of flood events, a paradigm shift in flood risk management is observed in many countries, such as Europe. Flood management and mitigation require comprehensive perspectives that take into account a diverse set of flood risk management measures, including active stakeholder engagement, communication, and awareness raising. The present study was conducted in the Neka Rud watershed in Mazandaran province. The use of geographical systems can identify flood-sensitive areas with high accuracy in the shortest time using information layers. This watershed is one of the most important watersheds in the province and its study is of great importance in terms of flood risks due to its high rainfall. Enjoys. The overall purpose of this study is to prioritize sub-basins concerning flooding based on morphological analysis and also to use GIS software as an efficient and cost-effective tool. In this study, the morphometric study of the watershed was investigated and flood sub-basins were identified. The purpose of this study is to identify areas with high flood potential in the Neka River watershed of Mazandaran province to prevent the risks of this natural disaster and prevent financial and human damage.Materials and Methods Seventeen Morphometric parameters were determined to describe the watershed and prioritize the sub-basins of the Neka watershed according to the sensitivity to sudden floods. The basic parameters were measured directly from the DEM using GIS techniques and include basin area, basin length, environment, number of streams, and flow lengths for each flow rating. In this study, very important morphometric parameters were quantitatively selected and used for this analysis. These parameters are directly or inversely related to runoff hazards, peak discharge, and soil erosion. These parameters were divided into three parts: linear, uneven, and surface. Finally, sub-basins were prioritized using this method. To assess the morphology of the watershed, a digital elevation map (DEM) with a resolution of 12.5 m was loaded. Morphological parameters are directly or inversely related to the outbreak. After morphological ranking, the values of each sub-basin were collected to classify and determine their susceptibility to flash floods. The values of the sum of morphometric parameters summarized from 0 for the lowest rank value and 1 for the highest rank value to obtain the flood sensitivity index for each sub-basin were normalized and finally evaluated. Clear changes are observed in the basic parameters of watersheds such as area, environment, and length of the basin. These basin parameters are a very remarkable hydrological feature. The watershed area varies from 484.37 square kilometers under the N1 basin to 48.18 km2 under the N8 basin. The environment can also be used as an indicator of the shape and size of the watershed. According to the obtained results, there is a high correlation between the area and the watershed environment.Results and Discussion The Neka Basin was divided into 12 sub-basins using the Hydrology Toolbox from ArcGIS. According to the obtained results, it was found that sub-basins N8 and N9 have a high priority for flooding. The results show that these two sub-basins are very prone to flooding. Also, sub-basins N11 and N12 have a much lower risk of flooding. The total number of 12 sub-basin flows for the watershed is 366681 and for the first time, it constitutes 52% of the total watershed flows. Geometric values for 12 watersheds are shown in the form of a graph and a straight line, where the log values of the flow number are plotted on a graph.Conclusion Because there are insufficient historical climatic and hydrological records for hydrological modeling, morphometric analysis has been used to assess sub-watershed susceptibility to flooding. The results and analysis obtained in the present study have several fields for practical application and future development. Morphometric analysis of the Neka basin has shown that the watershed is a six-stage drainage system that is very sensitive to flooding. According to the results, sub-basins N8 and N9 have a high risk of flooding. In contrast, the N12 sub-basin has a much lower rate of flooding. The study of the basin showed that the reason for the low flooding below the N12 basin is the shape of the basin and the amount of slope, which has an elongated shape and the area is almost flat in terms of unevenness, which reduces the risk of floods. This study showed that the protection of the region against sudden floods should be the main priority of the competent authorities to protect human lives and agricultural farms and ultimately prevent flood disasters. In this study, it was proved that integration and morphological analysis with GIS can provide a significant tool for understanding the characteristics of watershed sub-basins related to flood management.

References:

Abuzied S, Yuan M, Ibrahim S, Kaiser M, Saleem T. 2016. Geospatial risk assessment of flash floods in Nuweiba area, Egypt. Journal of Arid Environments, 133: 54-72. doi:https://doi.org/10.1016/j.jaridenv.2016.06.004.

Akay H, Baduna Koçyiğit M. 2020. Flash flood potential prioritization of sub-basins in an ungauged basin in Turkey using traditional multi-criteria decision-making methods. Soft Computing, 24(18): 14251-14263. doi:10.1007/s00500-020-04792-0.

Alam A, Ahmed B, Sammonds P. 2021. Flash flood susceptibility assessment using the parameters of drainage basin morphometry in SE Bangladesh. Quaternary International, 575-576: 295-307. doi:https://doi.org/10.1016/j.quaint.2020.04.047.

Altın TB, Altın BN. 2011. Development and morphometry of drainage network in volcanic terrain, Central Anatolia, Turkey. Geomorphology, 125(4): 485-503. doi:https://doi.org/10.1016/j.geomorph.2010.09.023.

Asfaw D, Workineh G. 2019. Quantitative analysis of morphometry on Ribb and Gumara watersheds: Implications for soil and water conservation. International Soil and Water Conservation Research, 7(2): 150-157. doi:https://doi.org/10.1016/j.iswcr.2019.02.003.

Barman BK, Rao CUB, Rao KS, Patel A, Kushwaha K, Singh SK. 2021. Geomorphic Analysis, Morphometric-based Prioritization and Tectonic Implications in Chite Lui River, Northeast India. Journal of the Geological Society of India, 97(4): 385-395. doi:10.1007/s12594-021-1696-0.

Bhat MS, 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. doi:https://doi.org/10.1007/s12665-019-8046-1.

Borga M, Gaume E, Creutin JD, Marchi L. 2008. Surveying flash floods: gauging the ungauged extremes. Hydrological Processes, 22(18): 3883. doi:https://doi.org/10.1002/hyp.7111.

Bui DT, Hoang N-D, Martínez-Álvarez F, Ngo P-TT, Hoa PV, Pham TD, Samui P, Costache R. 2020. A novel deep learning neural network approach for predicting flash flood susceptibility: A case study at a high frequency tropical storm area. Science of The Total Environment, 701: 134413. doi:https://doi.org/10.1016/j.scitotenv.2019.134413.

Charizopoulos N, Mourtzios P, Psilovikos T, Psilovikos A, Karamoutsou L. 2019. Morphometric analysis of the drainage network of Samos Island (northern Aegean Sea): Insights into tectonic control and flood hazards. Comptes Rendus Geoscience, 351(5): 375-383. doi:https://doi.org/10.1016/j.crte.2019.03.001.

Faniran A. 1968. The index of drainage intensity: a provisional new drainage factor. Australian Journal of Science, 31(9): 326-330. doi:https://doi.org/10.1007/s13201-017-0534-4.

Hajam RA, Hamid A, Bhat S. 2013. Application of morphometric analysis for geo-hydrological studies using geo-spatial technology–a case study of Vishav Drainage Basin. Hydrology Current Research, 4(3): 1-12. doi:https://doi.org/10.4172/2157-7587.1000157.

Hamdi SA, Ali SA, Ghareb JISA. 2019. Analysis of Basin Geometry in Ataq Region, Part of Shabwah Yemen: Using Remote Sensing and Geographic Information System Techniques. Bulletin of Pure & Applied Sciences-Geology, 38-F (Geology)(1): 1-15. doi:https://doi.org/10.5958/23203234.2019.00001.5.

Horton RE. 1945. Erosional development of streams and their drainage basins; hydrophysical approach to quantitative morphology. Geological society of America bulletin, 56(3): 275-370. doi:https://doi.org/10.1177/030913339501900406.

Jodar-Abellan A, Valdes-Abellan J, Pla C, Gomariz-Castillo F. 2019. Impact of land use changes on flash flood prediction using a sub-daily SWAT model in five Mediterranean ungauged watersheds (SE Spain). Science of The Total Environment, 657: 1578-1591. doi:https://doi.org/10.1016/j.scitotenv.2018.12.034.

Magesh NS, Chandrasekar N, Soundranayagam JP. 2011. Morphometric evaluation of Papanasam and Manimuthar watersheds, parts of Western Ghats, Tirunelveli district, Tamil Nadu, India: a GIS approach. Environmental Earth Sciences, 64(2): 373-381. doi:https://doi.org/10.1007/s12665-010-0860-4.

Mansor P. 2020. Investigating the relationship between basin morphometric conditions and groundwater resources: Case study of Kamyaran Basin. Quantitative Geomorphological Research, 8(4): 18-33. doi:https://doi.org/10.22034/GMPJ.2020.106408.

Melton MA. 1958. Correlation structure of morphometric properties of drainage systems and their controlling agents. The Journal of Geology, 66(4): 442-460. doi:https://doi.org/10.1086/626527.

Miller VC. 1953. A quantitative geomorphic study of drainage basin characteristics on the Clinch Mountain area, Virgina and Tennessee. Columbia Univ New York, Proj. NR 389–402, Tech Rep 3. New York: Columbia University, Department of Geology, ONR. https://doi.org/10.1086/626413.

Patel DP, Dholakia MB, Naresh N, Srivastava PK. 2012. Water Harvesting Structure Positioning by Using Geo-Visualization Concept and Prioritization of Mini-Watersheds Through Morphometric Analysis in the Lower Tapi Basin. Journal of the Indian Society of Remote Sensing, 40(2): 299-312. doi:https://doi.org/10.1007/s12524-011-0147-6.

Ratna Reddy V, Saharawat YS, George B. 2017. Watershed management in South Asia: A synoptic review. Journal of Hydrology, 551: 4-13. doi:https://doi.org/10.1016/j.jhydrol.2017.05.043.

Ratnam KN, Srivastava YK, Venkateswara Rao V, Amminedu E, Murthy KSR. 2005. Check dam positioning by prioritization of micro-watersheds using SYI model and morphometric analysis-Remote sensing and GIS perspective. Journal of the Indian Society of Remote Sensing, 33(1): 25. doi:https://doi.org/10.1007/BF02989988.

Schumm SA. 1956. Evolution of drainage systems and slopes in badlands at Perth Amboy, New Jersey. Geological Society of America Bulletin, 67(5): 597-646. doi:https://doi.org/10.1130/0016-7606(1956)67[597.

Siahkamari S, Zeinivand H. 2017. Flood prone areas mapping by using statistical index and weights of evidence models (Case study: Madar Soo watershed, Golestan). Journal of RS and GIS for Natural Resources, 7(4): 116-133. ( In Persion).

Strahler AN. 1952. Hypsometric (area-altitude) analysis of erosional topography. Geological society of America bulletin, 63(11): 1117-1142. doi:https://doi.org/doi.org/10.1130/0016-7606(1952)631117.

Strahler AN. 1964. Quantitative geomorphology of drainage basin and channel networks. Handbook of Applied Hydrology In V Chow (Ed), Handbook of applied hydrology (pp 439– 476) New York: McGraw Hill https://doiorg/101130/0016-7606(1952)631117.

Taha MMN, Elbarbary SM, Naguib DM, El-Shamy IZ. 2017. Flash flood hazard zonation based on basin morphometry using remote sensing and GIS techniques: A case study of Wadi Qena basin, Eastern Desert, Egypt. Remote Sensing Applications: Society and Environment, 8: 157-167. doi:https://doi.org/10.1016/j.rsase.2017.08.007.

Valizadeh Kamran K, Delire Hasannia R, Azari Amghani 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 Persion).