Analysis of Hydrogeomorphic Properties of Aland Chai Basin to Prioritize Sub-Basins in terms of Flood Sensitivity

Document Type : Research Article

Authors

• Mohammad Hossein Rezaei Moghaddam
• Seid Asadollah Hejazi
• Khalil Vlaizadeh Kamran
• Tohid Rahimpoor

University of Tabriz

10.22067/geo.v9i1.84675

Abstract

Introduction

Flood is a disaster which causes a lot of economic damages to farmlands, forests, gas and power transmission lines, roads, engineering structures, and buildings. There are numerous floods in the northwest of the country at the beginning of spring and the start of spring rains, which in most cases results in heavy damage. The purpose of this study is Geographic Information System (GIS)-based analysis of hydrogeomorphic properties of Aland Chai Basin for preparing flood sensitivity map. To this aim, hydrogeomorphic parameters of sub-basins have been studied from three aspects of drainage network characteristics (e.g., stream order, streams number, streams length, stream frequency, bifurcation ratio, length of overland flow, drainage density, drainage texture, texture ratio, infiltration number, constant of channel maintenance, and rho coefficient), basin geometry (e.g., basin area, compactness coefficient, circulatory ratio, elongation ratio, form factor, and shape factor) and relief properties (relief, relief ratio, ruggedness number, and gradient).

Study area

Aland Chai basin is located between 38, 30´ and 38, 48´ N and between 44, 15´ and 45, 01´ E in the West Azerbaijan province. It covers an area of 1147.30 km2 and it is situated in the north-western part of Iran. This basin is one of the sub-basins of the Aras River basin to which surface water flows after joining the grand Qotour River. Basin elevation variations are from 1093m in the Aland Chai River bed to 3638m above sea level in the Avrin Mountain.
Figure 1. The study area location in the West Azerbaijan province

Materials and Methods

The Step-Wise Weight Assessment Ratio Analysis (SWARA) model was introduced to the provided relational database in weighting of data layers. SWARA technique is one of the multi-criteria decision methods which was developed by Keršuliene et al. (2010). In this method, an expert has an important role in evaluating and calculating weights. Based on this method, the most signifcant criterion is ranked as the first, while the least signifcant one is ranked as the last.

Results and Discussion

Hydrogeomorphic analysis plays an important role in the analysis of hydrological behavior of the basins. In the present study, 22 hydrogeomorphic parameters were analyzed from three aspects of drainage network characteristics, shape parameters, and relief properties in order to investigate the role of these parameters in flood sensitivity of Aland Chai basin. Digital Elevation Model (DEM) with 12.5m spatial resolution and ArcGIS software were used to generate the data layers maps. In the next step, all necessary weights were calculated for factors and Sub-basins using SWARA model. According to a comparison between factors for each sub-basin, it was specified that sub-basins 3, 1, 4, and 2 (weighted as 0.142, 0.122, 0.091, and 0.087) have the highest impacts on Flood occurrence in study area. On the contrary, sub-basins 13 and 6 (weighted as 0.018 and 0.020) show the lowest weight.

Conclusion

In this study, an attempt was investigated to identify sub-basins with high potential for flood occurrence in Aland Chai basin. Based on the effective parameters, flood occurrence inside of Aland Chai basin could be separated into 5 distinguished classes from very high to very low flood susceptibility. According to the SWARA-based flood susceptibility map, sub-basins 3, 1, 4, and 2 of the study area have very high potential, sub-basin 7, 15 and 11 have high susceptibility, sub-basin 12, 5, and 9 have moderate susceptibility, sub-basins 8, 10, and 14 have low susceptibility, and sub-basins 6 and 13 have very low susceptibility toward flood occurrence. The total area of sub-basins in the high and very high class of flood is 656.72 km2, which comprises 57.24% of the total Aland Chai basin. Therefore, according to the results of the study, it is necessary to take protective measures such as watershed planning and dam construction in the sub-basins that are highly sensitive to prevent flood or reduce potential damages in case of flooding.
 

Keywords

• Flood
• Hydrogeomorphic analysis
• Prioritization
• GIS
• SWARA
• Aland Chai Basin

20.1001.1.23221682.1399.9.1.4.2

---

References

بدری، بهرام؛ زارع بیدکی، رفعت؛ هنربخش، افشین؛ آتشخوار، فاطمه؛ 1395. اولویت‌بندی زیر حوضه‌های آبخیز بهشت‌آباد از نظر پتانسیل سیل‌خیزی. پژوهش‌های جغرافیای طبیعی. دوره 48. شماره 1. ص 158-143.

رضایی مقدم، محمدحسین؛ یاسی، مهدی؛ نیکجو، محمدرضا؛ رحیمی، مسعود؛ 1397. پهنه‌بندی و تحلیل مورفولوژیکی سیلاب‌های رودخانه قره‌سو با استفاده از مدل هیدرودینامیکی HEC-RAS (از روستای پیرازمیان تا تلاقی رودخانه اهر چای). جغرافیا و مخاطرات محیطی. شماره 25. ص 15-1.

عرب عامری، علیرضا؛ پورقاسمی، حمیدرضا؛ شیرانی، کورش؛ 1396. پهنه‌بندی حساسیت سیل گیری با استفاده از روش ترکیبی نوین تئوری بیزین – فرایند تحلیل سلسله مراتبی (مطالعه موردی: حوضه آبخیز نکا – استان مازندران). اکوهیدرولوژی. دوره 4. شماره 2. ص 462-447.

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. http://dx.doi.org/10.1016/j.jaridenv.2016.06.004.

Ahmadisharaf, E., Tajrishy, M., Alamdari, N., 2016. Integrating flood hazard into site selection of detention basins using spatial multi-criteria decision-making, Journal of Environmental Planning and Management 59: 1397–1417. https://doi.org/10.1080/09640568.2015.1077104.

Bisht, S., Chaudhry, S., Sharma, S., Soni, S., 2018. Assessment of flash flood vulnerability zonation through Geospatial technique in high altitude Himalayan watershed, Himachal Pradesh India, Remote Sensing Applications: Society and Environmen 12: 35-47. https://doi.org/10.1016/j.rsase.2018.09.001.

Borga, M., Gaume, E., Creutin, J.D., Marchi, L., 2008. Surveying flash floods: gauging the ungauged extremes. Hydrological Processes 22: 3883–3885. https:// doi. org/ 10. 1002/ hyp. 7111.

Chandrashekara, H., Lokesh, K.V., Sameena, M., Roopa, J., Ranganna, G., 2015. GIS –Based Morphometric Analysis of Two Reservoir Catchments of Arkavati River, Ramanagaram District, Karnataka, INTERNATIONAL CONFERENCE ON WATER RESOURCES, COASTAL AND OCEAN ENGINEERING (ICWRCOE 2015), doi: 10.1016/ j. aqpro. 2015.02.175.

Christopher, O., Idowu, A., Olugbenga, A., 2010. Hydrological analysis of Onitsha North

East drainage Basin using Geoinformatic techniques, World Appl. Sci. J 11 (10):

1297–1302.

Cloke, H.L., Pappenberger, F., 2009. Ensemble flood forecasting: a review, Journal of Hydrology 375(3): 613–626. https://doi.org/10.1016/j.jhydrol.2009.06.005.

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.

Degiorgis, M., Gnecco, G., Gorni, S., Roth, G., Sanguineti, M., Celeste Taramasso, A., 2012. Classifiers for the detection of flood prone areas using remote sensed elevation data, Journal of Hydrology 470–471: 302–315. http://dx.doi.org/ 10.1016/j.jhydrol.2012.09.006.

Faniran, A., 1968. The index of drainage intensity – a provisional new drainage factor, Australian Journal of Science 31: 328–330.

Furl, C., Sharif, H., Zeitler, J.W., El Hassan, A., Joseph, J., 2018. Hydrometeorology of the catastrophic Blanco River flood in South Texas, May 2015, Journal of Hydrology: Regional Studies 15: 90–104. https://doi.org/10.1016/j.ejrh.2017.12.001.

Horton, R. E., 1945. Erosional development of streams and their drainage basins; hydrophysical approach to quantitative morphology, Bulletin of the Geological Society of America 56(3): 275–370.

Kale, V.S., Gupta, A., 2001. Introduction to Geomorphology. Academic (India). Publishers New Delhi.

Kendall, M. G., 1970. Rank correlation methods, 4th edn. Griffin, London

Keršuliene, V., Zavadskas, E. K., Turskis, Z., 2010. Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA), Journal of Business Economics and Management 11(2): 243–258. https:// doi. org/ 10. 3846/ jbem. 2010.12.

Kourgialas, N.N., Karatzas, G.P., 2011. Flood management and a GIS modelling method to assess flood-hazard areas—a case study, Hydrological Sciences Journal 56(2): 212–225. https://doi.org/10.1080/02626667.2011.555836.

Kumar Rai, P., Narayan Mishra, V., Mohan, K., 2017. A study of morphometric evaluation of the Son basin, India using geospatial approach, Remote Sensing Applications: Society and Environment 7: 9-20. http://dx.doi.org/10.1016/j.rsase.2017.05.001.

Mahmood, Sh., Rahman, A., 2019. Flash flood susceptibility modeling using geo- morphometric and hydrological approaches in Panjkora Basin, Eastern Hindu Kush, Pakistan, Environmental Earth Sciences 78(43): 1-16. https://doi.org/10.1007/s12665-018-8041-y.

Mahmood, Sh., Rahman, A., 2019. Flash flood susceptibility modelling using geomorphometric approach in the Ushairy Basin, eastern Hindu Kush, J. Earth Syst. Sci 128(97): 1-14. https://doi.org/10.1007/s12040-019-1111-z.

Mesa, L.M., 2006. Morphometric analysis of a subtropical Andean basin (Tucuman,

Argentina), Environ. Geol 50 (8): 1235–1242.

Miller, V.C., 1953. A Quantitative Geomorphic Study of Drainage Basin Characteristics in the Clinch Mountain Area, Virgina and Tennessee, Technical Report (3), Dept. of

Geol. New York: Columbia University: 389–402.

Nookaratnam, K., Srivastava, Y.K., Venkateswarao, V., Amminedu, E., Murthy, K.S.R.,

2005. Check dam positioning by prioritization of micro-watersheds using SYI model

and morphometric analysis - remote sensing and GIS perspective, Jour. Indian Soc.

Remote Sens 33 (1): 25–38.

Ozdemir, H., Bird, D., 2009. Evaluation of morphometric parameters of drainage networks derived from topographic maps and DEM in point of floods, Environmental Geology 56(7): 1405–1415. https://doi.org/10.1007/s00254-008-1235-y.

Prasad, R. N., Pani, P., 2017. Geo-hydrological analysis and sub watershed prioritization for flash flood risk using weighted sum model and Snyder’s synthetic unit hydrograph, Modeling Earth Systems and Environment 3(4): 1491–1502. https://doi.org/10.1007/s40808-017-0354-4.

Ramani Sujatha, E., Selvakumar, R., Rajasimman, U.A.B., Victor, R.G., 2015. Morphometric analysis of sub-watershed in parts of Western Ghats, South India using ASTER DEM, Geomatics, Natural Hazards and Risk 6: 326-341. http:// dx. doi. org/1 0.1080/ 19475705.2013.845114.

Reddy, O.G.P., Maji, A.K., Gajbhiye, S.K., 2004. Drainage morphometry and its influence on landform characteristics in a basaltic terrain, Central India—a remote sensing and GIS approach, Int J Appl Earth Observation Geoinf 6(1): 1–16.

Schanze, J., Zeman, E., Marsalek, J., 2006. Flood risk management: hazards, vulnerability and mitigation measures. Springer, Dordrecht, http://dx.doi.org/10.1007/978-1-4020-4598-1.

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. http:// dx. doi. / 10.1130/0016-7606(1956)67[597:EODSAS]2.0.CO;2.

Shulits, S., 1968. Quantitative formulation of stream and watershed morphology, Bulletin of the International Association of Scientifc Hydrology 3: 201–207.

Singh, N., Singh, K. K., 2017. Geomorphological analysis and prioritization of sub- watersheds using Snyder’s synthetic unit hydrograph method, Applied Water Science 7(1): 275–283. https://doi.org/10.1007/s13201-014-0243-1.

Singh, S., Singh, M.C., 1997. Morphometric analysis of Kanhar river basin, Natl. Geogr. J. lndia 43(1): 31–43.

Smith, K.G., 1950. Standards for grading texture of erosional topography, Am. J. Sci 248:

655–668.

Strahler, A.N., 1964. Quantitative geomorphology of drainage basin and channel networks, Handbook of applied hydrology.

Taha, M. M. N., Elbarbary, S. M., Naguib, D. M., El-Shamy, I. Z., 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. https://doi.org/10.1016/j.rsase.2017.08.007.

Tang, Z., Zhang, H., Yi, Sh., Xiao, Y., 2018. Assessment of flood susceptible areas using spatially explicit, probabilistic multi-criteria decision analysis, Journal of Hydrology 558: 144-158. https://doi.org/10.1016/j.jhydrol.2018.01.033.

Van Tu, T., Duc, D.M., Tung, N.M., 2016. Preliminary assessments of debris flow hazard in relation to geological environment changes in mountainous regions, North Vietnam. Vietnam Journal of Earth Sciences 38 (3): 277–286.

Yousefi, S., Mirzaee, S., Keesstra, S., Surian, N., Pourghasemi, H.R., Zakizadeh, H.R., Tabibian, S., 2018. Effects of an extreme flood on river morphology (case study: Karoon River, Iran), Geomorphology 304: 30–39. https://doi.org/10.1016/j.geomorph.2017.12.034.

Zavadskas, E. K., Turskis, Z., Ustinovichius, L., Shevchenko, G., 2010. Attributes weights determining peculiarities in multiple attribute decision making methods, Economics of Engineering Decisions 21(1): 32–43.

Zavadskas, E. K., Vilutiene, T., 2006. A multiple criteria evaluation of multi-family apartment block’s maintenance contractors: I-model for maintenance contractor evaluation and the determination of its selection criteria, Building and Environment 41(5): 621–632.