Flood Peak Flow Simulation and Determination of Flood Source Area in the QARANQU Watershed Using Hydrological Mod-Clark Model and GIS

Authors

Abstract

Flood management needs to identify and prioritize of watershed flood source area. The most studies in the field of flood management are based on the application of the integrated-conceptual models. These models have not appropriate precision to identify watershed-wide flood source area and moreover they have restriction to investigate the spatial distribution of effective components in runoff generation. The main aim of this study is to determine the severity of flooding and priority determination of flood generation potential area based on unit response approach using Mod-Clark distributed (spatial) hydrological model for Qaranqu watershed. In this study, digital elevation model (DEM) with a cell size of 30 m was prepared in the GIS using the topographic maps. Furthermore the watershed gridded file, based on the Standard Hydrologic Grid (SHG), was created using HEC-GeoHMS as input data for the HEC-HMS model. In order to choose the suitable grid scale, two different resolutions of 1*1 and 2*2 kilometers were utilized.  Although the results revealed that the 1*1 km grid scale could more accurately specifies the boundaries of flood area source, there is no significant difference between results in comparison to 2*2 km grid. Outcomes of the current study suggest 1*1 km resolution for priority determination of the flood source area. By iterative execution of Mod-Clark model for different scenarios, flooding severity index of the basin was spatially determined. Based on the flooding severity index the Almalochai sub-watershed was recognized as the most flood source areas from point of flood peak flow generation view.

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الوان کار، ر. 1382. مدل توزیعی شبیه سازی سیل بر اساس GIS . رسالهء دکتری گروه هیدرولوژی و منابع آب، دانشگاه علوم و تحقیقات ، 125 ص.
یمانی م.، م. تورانی و س. چزغه. 1391. تعیین پهنه­های سیلگیر با استفاه از مدل HEC-RAS (مطالعه موردی: بالادست سد طالقـان از پـل گلینک تا پل وشته)، مجله جغرافیا و مخاطرات محیطی، شماره اول، ص 16 –1.
محمدی مطلق، ر. ن. جلال کمالی، جلال ا. کمالی. 1392. بررسی نقش مشارکت زیرحوضه­های آبریز در شدت سیل‌خیزی، مطالعه موردی: حوضه آبریز دالکی. فصلنامه علمی پژوهشی آبیاری و آب. سال چهارم، شماره 13، ص 44-31.
وزیری ، ف. 1370 . تجزیه وتحلیل رگبارها و تعیین منحنی های شدت -   مدت در نقاط مختلف ایران. انتشارات دانشگاه صنعتی خواجه نصیرالدین طوسی.
مهندسین مشاور بوم آباد 1378.  مطالعات توجیهی حوضه آبخیز قرنقوچای. جلد ششم ،گزارش هیدرولوژی (سیل خیزی و آب های سطحی).
 
Adib, A., M., Salarijazi, and K. Najafpour. 2010. Evaluation of synthetic outlet runoff assessment models. Journal of Applied Sciences and Environmental Management, 14(3): 13-18.
Adib, A., M., Salarijazi, M. M., Shooshtari, and A. M. Akhondal. 2011. Comparison between characteristics of geomorphoclimatic instantaneous unit hydrograph be produced by GcIUH based Clark Model and Clark IUH model.Journal of Marine Science and Technology, 19(2): 201-209.
Adib, A., M., Salarijazi, M., Vaghefi, M. M., Shooshtari, and A. M. Akhonali. 2010. Comparison between GcIUH-Clark, GIUH-Nash, Clark-IUH, and Nash-IUH models. Turkish Journal of Engineering and Environmental Sciences, 34(2): 91-104.
Aksoy, H., V. S. O., Kirca, H. I., Burgan, and D. Kellecioglu. 2016. Hydrological and hydraulic models for determination of flood-prone and flood inundation areas. Proc. IAHS, 373: 137-141.
Arnaud, P., C., Bouvier, L., Cisneros, & R. Dominguez. 2002. Influence of rainfall spatial variability on flood prediction. Journal of Hydrology, 260(1): 216-230.
Bae, D. H., and Y. J. Kim. 2015. Development of Concentration Time and Storage Coefficient Considering Regional Trend in Urban Stream Watershed.Journal of Korea Water Resources Association, 48(6): 479-489.
Baldassarre, G. D., A., Viglione, G., Carr, L., Kuil, J. L., Salinas, & G. Blöschl. 2013. Socio-hydrology: conceptualising human-flood interactions.Hydrology and Earth System Sciences, 17(8): 3295-3303.
Bhatt, G. D., K., Sinha, P. K., Deka, and A. Kumar. 2014. Flood hazard and risk assessment in Chamoli district, Uttarakhand using satellite remote sensing and GIS techniques. International Journal of Innovative Research in Science, Engineering and Technology, 3(8): 9-18.
Degiorgis, M., G., Gnecco, S., Gorni, G., Roth, M., Sanguineti, and A. C. Taramasso, 2012. Classifiers for the detection of flood-prone areas using remote sensed elevation data. Journal of hydrology, 470: 302-315.
Divín, J., and T. Mikita. 2016. Effects of Land Use Changes on the Runoff in the Landscape Based on Hydrological Simulation in HEC-HMS and HEC-RAS Using Different Elevation Data. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 64(3): 759-768.
Eidipour, A., A. M., Akhondali, H., Zarei, and M. Salarijazi. 2016. Flood Hydrograph Estimation Using GIUH Model in Ungauged Karst Basins (Case Study: Abolabbas Basin). TUEXENIA, 36 (36): 26-33
Fan, F. M., W., Collischonn, K. J., Quiroz, M. V., Sorribas, D. C., Buarque, and V. A. Siqueira. 2015. Flood forecasting on the Tocantins River using ensemble rainfall forecasts and real‐time satellite rainfall estimates. Journal of Flood Risk Management.
Foody, G. M., E. M., Ghoneim, and N. W. Arnell. 2004. Predicting locations sensitive to flash flooding in an arid environment. Journal of Hydrology, 292(1): 48-58.
 Knebl, M. R., Z. L., Yang, K., Hutchison, and D. R. Maidment, 2005. Regional scale flood modeling using NEXRAD rainfall, GIS, and HEC-HMS/RAS: a case study for the San Antonio River Basin Summer 2002 storm event.Journal of Environmental Management, 75(4): 325-336.
Lee, J. H., S. K., Yang, and W. Y. Jung. 2015. A Proposal of Unit Hydrograph Using Statistical Analysis in Oedo Stream, Jeju. Journal of Environmental Science International, 24(4): 393-401.
Mandal, S. P., and A. Chakrabarty, 2016. Flash flood risk assessment for upper Teesta river basin: using the hydrological modeling system (HEC-HMS) software. Modeling Earth Systems and Environment, 2(2): 1-10.
Manfreda, S., M., Di Leo, and A. Sole. 2011. Detection of flood-prone areas using digital elevation models. Journal of Hydrologic Engineering, 16(10): 781-790.
Manfreda, S., F., Nardi, C., Samela, S., Grimaldi, A. C., Taramasso, G., Roth and A. Sole. 2014. Investigation on the use of geomorphic approaches for the delineation of flood prone areas. Journal of Hydrology, 517: 863-876.
Napradean, I., and R. Chira. 2006. The hydrological modeling of the Usturoi valley-using two modeling programs-WetSpa and HecRas. Carpathian Journal of Earth and Environmental Sciences, 1(1): 53-62.
Naulin, J. P., O., Payrastre, and E. Gaume. 2013. Spatially distributed flood forecasting in flash flood prone areas: Application to road network supervision in Southern France. Journal of hydrology, 486: 88-99.
Nikolova, M., S., Nedkov, V., Nikolov, I., Zuzdrov, M., Genev, T., Kotsev,... and Y. Krumova, 2009. Implementation of the" KINEROS" model for estimation of the flood prone territories in the Malki Iskar River basin. Information & Security, 24, 76.
Papaioannou, G., L., Vasiliades, and A. Loukas, 2015. Multi-criteria analysis framework for potential flood prone areas mapping. Water Resources Management, 29(2): 399-418.
Sikder, S., X., Chen, F., Hossain, J. B., Roberts, F., Robertson, C. K., Shum, and F. J. Turk. 2016. Are General Circulation Models Ready for Operational Streamflow Forecasting for Water Management in the Ganges and Brahmaputra River Basins?. Journal of Hydrometeorology, 17(1): 195-210.
Tehrany, M. S., B., Pradhan, and M. N. Jebur, 2013. Spatial prediction of flood susceptible areas using rule based decision tree (DT) and a novel ensemble bivariate and multivariate statistical models in GIS. Journal of Hydrology, 504: 69-79.
Wang, Y., Z., Li, Z., Tang, and G. Zeng. 2011. A GIS-based spatial multi-criteria approach for flood risk assessment in the Dongting Lake Region, Hunan, Central China. Water resources management, 25(13): 3465-3484.