Prediction and Analysis of Flood Zones under Climate Change Conditions based on CanESM2 Model’s Scenarios

Document Type : Research Article


1 Ph.D. Student, Department of Watershed Managment Sciences and Engineering , Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Iran

2 Professor, Department of Watershed Management, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Iran

3 Professor, The Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, New South Wales 2007, Australia Professor, Department

4 Assistant Professor, Department of Forestry, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Iran


North of Iran is one of the flood-prone areas as a result of the humid climate and the large amount of maximum daily rainfall. This study aims to predict flood zone in climate change conditions based on the fifth assessment report of the intergovernmental panel on climate change (IPCC) scenarios in the Talar watershed (Zirab city). To investigate the effect of climate change, six synoptic stations were used.  Among the general circulation models (GCM), Canadian Earth System Model (CanESM2) based on Representative Concentration Pathway (RCP) 2.6, RCP4.5, and RCP8.5 scenarios were applied for statistical downscaling of the maximum daily rainfall. To hydrologic and hydraulic simulation of flood were used from Hydrologic Engineering Center-Hydrologic Modeling System (HEC- HMS) and Hydrologic Engineering Center-Hydrologic River System (HEC- RAS) models in the recent decades and the future. The results indicated that maximum daily rainfall will increase in the watershed. The results also showed that the increase in maximum daily rainfall in humid climate (the North) is more than dry climate (the South). In general, maximum daily rainfall will increase the minimum and maximum 8 and 33 mm, respectively in the watershed. The simulation results in terms of flood hydrograph indicate that flood increase in the all periods. The RCP 4.5 scenario will produce at minimum and maximum flood discharge in 2020-2040 (374 m3/s) and 2020-2100 (1209 m3/s), respectively. Flood zoning map showed that floodplain area is the base period in the river basin, but climate change will increase the flood zone in this region.  Besides, the results showed that at least 0.18 percent and at most 8.7 percent of the total Zirab city will effect on flood under climate change conditions.


[1]. Pfahl S, O’Gorman PA, Fischer EM. Understanding the regional pattern of projected future changes in extreme precipitation. Nature Climate Change. 2017; 7(6):423–7.
[2].  Fischer EM, Knutti R. Observed heavy precipitation increase confirms theory and early models. Nat Clim Change. 2016; 6(11):986–91.
[3].  Lenderink G, Fowler HJ. Hydroclimate: Understanding rainfall extremes. Nature Climate Change [Internet]. 2017; 7(6):391–3. Available from:
[4].  Prein AF, Rasmussen RM, Ikeda K, Liu C, Clark MP, Holland GJ. The future intensification of hourly precipitation extremes. Nature Climate Change. 2017; 7(1):48–52.
[5].  Chan SC, Kendon EJ, Roberts NM, Fowler HJ, Blenkinsop S. Downturn in scaling of UK extreme rainfall with temperature for future hottest days. Nature Geoscience. 2016; 9(1):24.
[6].  Kundzewicz ZW, Kanae S, Seneviratne SI, Handmer J, Nicholls N, Peduzzi P, et al. Flood risk and climate change: global and regional perspectives. Hydrological Sciences Journal [Internet]. 2014; 59(1):1–28. Available from:
[7].  II IP on CCWG. Climate change 2014: Impacts, adaptation, and vulnerability. IPCC Working Group II; 2014.
[8].  Linden P Van Der, Parry ML, Parry ML, Canziani O, Palutikof J, Van der Linden P, et al. Climate change 2007-impacts, adaptation and vulnerability: Working group II contribution to the fourth assessment report of the IPCC. Vol. 4. Cambridge University Press; 2007.
[9].  Zainalfikry MK, Ab Ghani A, Zakaria NA, Chan NW. HEC-RAS One-Dimensional Hydrodynamic Modelling for Recent Major Flood Events in Pahang River. In: AWAM International Conference on Civil Engineering. Springer; 2019. p. 1099–115.
[10].             asquier U, He Y, Hooton S, Goulden M, Hiscock KM. An integrated 1D–2D hydraulic modelling approach to assess the sensitivity of a coastal region to compound flooding hazard under climate change. Natural Hazards. 2019; 98(3):915–37.
[11].             löschl G, Hall J, Parajka J, Perdigão RAP, Merz B, Arheimer B, et al. Changing climate shifts timing of European floods. Science. 2017; 357(6351):588–90.
[12].            Ashok V, Sridhar R V, Ajey NVU, Patel K, Rangari VA, Sridhar V, et al. Floodplain mapping and management of urban catchment using HEC-RAS: a case study of Hyderabad City. Journal of the Institution of Engineers (India): Series A [Internet]. 2019; 100(1):49–63. Available from:
[13].            Kunkel KE, Karl TR, Easterling DR, Redmond K, Young J, Yin X, et al. Probable maximum precipitation and climate change. Geophysical Research Letters. 2013; 40(7):1402–8.
[14].            Universiteit V, Bouwer LM. Have disaster losses increased due to anthropogenic climate change? Bulletin of the American Meteorological Society. 2011; 92(1):39–46.
[15].            Shahzad M, Faizan K, Tariq A, Saeed U, Sharif M, Sheraz K, et al. Floodplain mapping using HEC-RAS and ArcGIS: a case study of Kabul River. Arabian Journal for Science and Engineering. 2016; 41(4):1375–90.
[16].            16.          Ward PJ, Jongman B, Aerts JCJH, Bates PD, Botzen WJW, Loaiza AD, et al. A global framework for future costs and benefits of river-flood protection in urban areas. Nature Climate Change. 2017; (July):1–7.
[17].            Posthumus H, Hewett CJM, Morris J, Quinn PF. Agricultural land use and flood risk management : Engaging with stakeholders in North Yorkshire. Agricultural Water Management [Internet]. 2008; 95(7):787–98. Available from:
[18].            Muis S, Güneralp B, Jongman B, Aerts JCJH, Ward PJ. Flood risk and adaptation strategies under climate change and urban expansion: A probabilistic analysis using global data. Science of the Total Environment [Internet]. 2015; 538:445–57. Available from:
[19].            Kourgialas NN, Dokou Z, Karatzas GP. Statistical analysis and ANN modeling for predicting hydrological extremes under climate change scenarios: The example of a small Mediterranean agro-watershed. Journal of environmental management [Internet]. 2015; 154:86–101. Available from:
[20].            Khan B, Iqbal MJ, Yosufzai MAK. Flood risk assessment of river Indus of Pakistan. Arabian Journal of Geosciences. 2011; 4(1–2):115–22.
[21].            Huang S, Chang J, Huang Q, Chen Y, Leng G. Quantifying the relative contribution of climate and human impacts on runoff change based on the Budyko hypothesis and SVM model. Water resources management. 2016; 30(7):2377–90.
[22].            Issn J, Online FA, Ologunorisa TE, Abawua MJ. Flood risk assessment: a review. Journal of Applied Sciences and Environmental Management. 2005; 9(1):57–63.
[23].            Re M. Innovative new ways of analysing historical loss events. 2016.
[24].            Georgakakos KP. Analytical results for operational flash flood guidance. Journal of Hydrology. 2006; 317(1–2):81–103.
[25].            Ac- G, Witt L, Oceanic N, Downton MW, Pielke Jr RA. Discretion without accountability: Politics, flood damage, and climate. Natural Hazards Review. 2001; 2(4):157–66.
[26].            Golian S, Saghafian B, Maknoon R. Derivation of Probabilistic Thresholds of Spatially Distributed Rainfall for Flood Forecasting. Water Resources Management [Internet]. 2010; 24(13):3547–59. Available from:
[27].            Hirabayashi Y, Mahendran R, Koirala S, Konoshima L, Yamazaki D, Watanabe S, et al. Global flood risk under climate change. Nature Climate Change [Internet]. 2013 Jun 9; 3(9):816–21. Available from:
[28].            Winsemius HC, Aerts J, van Beek LPH, Bierkens MFP, Bouwman A, Jongman B, et al. Global drivers of future river flood risk. Nature Climate Change. 2015; 6(4):381–5.
[29].            Arnell NW, Gosling SN. The impacts of climate change on river flood risk at the global scale. Climatic Change. 2016; 134(3):387–401.
[30].            Re M. Munich reinsurance company geo risks research. NatCatSERVICE Database. 2013;
[31].            Shahiriparsa AA, Noori M, Heydari M, Rashidi M. Floodplain Zoning Simulation by Using HEC-RAS and CCHE2D Models in the Sungai Maka River. Air, Soil and Water Research. 2020; 9(1).
[32].            Pappenberger F, Stephens E, Thielen J, Salamon P, Demeritt D, Jan S, et al. Visualizing probabilistic flood forecast information: expert preferences and perceptions of best practice in uncertainty communication. Hydrological Processes. 2013; 27(1):132–46.
[33].            Sampson CC, Smith AM, Bates PD, Neal JC, Alfieri L, Freer JE. A high‐resolution global flood hazard model. Water resources research. 2015; 51(9):7358–81.
[34].            Golshan M, Jahanshahi A, Afzali A. Flood hazard zoning using HEC-RAS in GIS environment and impact of manning roughness coefficient changes on flood zones in Semi-arid climate. Desert. 2016; 21(1):24–34.
[35].            Khan MS, Coulibaly P, Dibike Y. Uncertainty analysis of statistical downscaling methods. Journal of Hydrology. 2006; 319(1–4):357–82.
[36].            Shrestha S, Anal AK, Salam PA, Valk M Van Der, America L. Managing Water Resources under Climate Uncertainty.
[37].            Sayari N, Bannayan M, Alizadeh A, Farid A. Using drought indices to assess climate change impacts on drought conditions in the northeast of Iran ( case study : Kashafrood basin ). 2013; 127(August 2012):115–27.
[38].            Zhang Y, You Q, Chen C, Ge J. Impacts of climate change on streamflows under RCP scenarios: A case study in Xin River Basin, China. Atmospheric Research. 2016; 178:521–34.
[39].            Pervez MS, Henebry GM. Projections of the Ganges–Brahmaputra precipitation—Downscaled from GCM predictors. Journal of Hydrology. 2014; 517:120–34.
[40].            Zhou J, He D, Xie Y, Liu Y, Yang Y, Sheng H, et al. Integrated SWAT model and statistical downscaling for estimating streamflow response to climate change in the Lake Dianchi watershed, China. Stochastic Environmental Research and Risk Assessment [Internet]. 2015; 29(4):1193–210. Available from:
[41].            Feyissa G, Zeleke G, Bewket W, Gebremariam E. Downscaling of future temperature and precipitation extremes in Addis Ababa under climate change. Climate. 2018; 6(3):58.
[42].            Wilby RL, Dawson CW, Barrow EM. SDSM - A decision support tool for the assessment of regional climate change impacts. Environmental Modelling and Software. 2002; 17(2):145–57.
[43].            Wilby RL, Dawson CW, Barrow EM. SDSM—a decision support tool for the assessment of regional climate change impacts. Environmental Modelling & Software. 2002; 17(2):145–57.
[44].            Eguibar M, Bodoque JM, Stoffel M. Estimating flash flood discharge in an ungauged mountain catchment with 2D hydraulic models and dendrogeomorphic palaeostage indicators. 2011; 979(November 2010):970–9.
[45].            Chatterjee C, Saskia F, Bronstert A, Förster S, Bronstert A. Comparison of hydrodynamic models of different complexities to model floods with emergency storage areas. Hydrological Processes: An International Journal. 2008; 22(24):4695–709.
[46].            Brocca L, Melone F, Moramarco T. Distributed rainfall‐runoff modelling for flood frequency estimation and flood forecasting. Hydrological processes. 2011; 25(18):2801–13.
[47].            Kourgialas NN, Karatzas GP. A hydro-sedimentary modeling system for flash flood propagation and hazard estimation under different agricultural practices. Natural Hazards and Earth System Sciences. 2014; 14(3):625.
[48].            Papaioannou G, Loukas A, Vasiliades L, Aronica GT. Flood inundation mapping sensitivity to riverine spatial resolution and modelling approach. Natural Hazards. 2016; 83(1):117–32.
[49].            Fijko R, Labant S, Weiss E, Zele M, Markovi G, Zeleňáková M, et al. Flood risk modelling of the Slatvinec stream in Kružlov village, Slovakia. Journal of cleaner production. 2019; 212:109–18.
[50].            Hafnaoui MA, Madi M, Hachemi A, Farhi Y, Amin M, Madi M, et al. El Bayadh city against flash floods: case study. Urban Water Journal [Internet]. 2020; 00(00):1–6. Available from:
[51].            Papagiannaki K, Lagouvardos K, Kotroni V, Bezes A. Flash flood occurrence and relation to the rainfall hazard in a highly urbanized area. Natural Hazards & Earth System Sciences. 2015; 15(8):1859–71.
[52].            Moramarco T, Melone F, Singh VP. Assessment of flooding in urbanized ungauged basins: a case study in the Upper Tiber area, Italy. Hydrological Processes: An International Journal. 2005; 19(10):1909–24.
[53].            Molinari D, Menoni S, Aronica GT, Ballio F, Berni N, Pandolfo C, et al. Ex post damage assessment: an Italian experience. 2014; 4(c):901–16.
[54].            Shustikova I, Domeneghetti A, Neal JC, Bates P, Castellarin A. Comparing 2D capabilities of HEC-RAS and LISFLOOD-FP on complex topography. Hydrological Sciences Journal [Internet]. 2019; 64(14):1769–82. Available from:
[55].            Llasat MC, Petrucci O, Pasqua AA, Rossell J, Llasat-Botija M, Petrucci O, et al. Towards a database on societal impact of Mediterranean floods within the framework of the HYMEX project. Natural Hazards and Earth System Sciences. 2013; 13(5):1337.
[56].            Gaume E, Livet M, Desbordes M, Villeneuve J-P. Hydrological analysis of the river Aude, France, flash flood on 12 and 13 November 1999. Journal of Hydrology. 2004; 286(1–4):135–54.
[57].            Eau D, Lyon G De, Delrieu G, Nicol J, Yates E, Kirstetter P-E, et al. The catastrophic flash-flood event of 8–9 September 2002 in the Gard Region, France: a first case study for the Cévennes–Vivarais Mediterranean Hydrometeorological Observatory. Journal of Hydrometeorology. 2005; 6(1):34–52.
[58].            Hong Quang N, Tuan VA, Le Hang TT, Manh Hung N, Thi Dieu D, Duc Anh N, et al. Hydrological/Hydraulic Modeling-Based Thresholding of Multi SAR Remote Sensing Data for Flood Monitoring in Regions of the Vietnamese Lower Mekong River Basin. Water. 2020; 12(1):71.
[59].            Stoleriu CC, Urzica A, Mihu‐Pintilie A. Improving flood risk map accuracy using high‐density LiDAR data and the HEC‐RAS river analysis system: A case study from north‐eastern Romania. Journal of Flood Risk Management. 2020; 13:e12572.
[60].            Vojtek M, Petroselli A, Vojteková J, Asgharinia S, Publishing IWA. Flood inundation mapping in small and ungauged basins: sensitivity analysis using the EBA4SUB and HEC-RAS modeling approach. Hydrology Research. 2019; 50(4):1002–19.
[61].            Martins M, Gonçalves P, Gomes A, Teixeira J. Definition of Flood-Prone Areas: A Comparison between HEC-RAS and Iber Software Results. In: Advances in Natural Hazards and Hydrological Risks: Meeting the Challenge. Springer; 2020. p. 127–31.
[62].            Ramachandran A, Palanivelu K, Mudgal B V, Jeganathan A, Guganesh S, Abinaya B, et al. Climate change impact on fluvial flooding in the Indian sub-basin: A case study on the Adyar sub-basin. PloS one. 2019; 14(5):1–24.
[63].            Rangari VA, Sridhar V, Umamahesh N V, Patel AK. Floodplain mapping and management of urban catchment using HEC-RAS: a case study of Hyderabad City. Journal of the Institution of Engineers (India): Series A. 2019; 100(1):49–63.
[64].            Rangari VA, Umamahesh N V, Bhatt CM. Assessment of inundation risk in urban floods using HEC RAS 2D. Modeling Earth Systems and Environment. 2019; 5(4):1839–51.
[65].            Murray V, Ebi KL. IPCC special report on managing the risks of extreme events and disasters to advance climate change adaptation (SREX) [Internet]. BMJ Publishing Group Ltd; 2012. Available from:
[66].            Beven KJ. Rainfall-runoff modelling: the primer. John Wiley & Sons; 2011.
[67].            Maghsood FF, Moradi H, Bavani ARM, Panahi M, Berndtsson R, Hashemi H, et al. Climate Change Impact on Flood Frequency and Source Area in Northern Iran under CMIP5 Scenarios. Water. 2019; 11(2):273.
[68].            Runhaar HAC, Uittenbroek CJ, van Rijswick HFMW, Mees HLP, Driessen PPJ, Gilissen HK. Prepared for climate change? A method for the ex-ante assessment of formal responsibilities for climate adaptation in specific sectors. Regional Environmental Change. 2016; 16(5):1389–400.
[69].            Baldassarre G Di, Montanari A, Lins H, Koutsoyiannis D, Brandimarte L, Blöschl G, et al. Flood fatalities in Africa: from diagnosis to mitigation. Geophysical Research Letters. 2010; 37(22):2–6.
[70].            Motevalli A, Vafakhah M. Flood hazard mapping using synthesis hydraulic and geomorphic properties at watershed scale. Stochastic Environmental Research and Risk Assessment. 2016; 30(7):1889–900.
[71].            Kundzewicz ZW, Krysanova V, Dankers R, Hirabayashi Y, Kanae S, Huang S, et al.
Differences in flood hazard projections in Europe – their causes and consequences for decision making. Hydrological Sciences Journal [Internet]. 2017; 62(1):1–14. Available from:
[72].            Dankers R, Arnell NW, Clark DB, Falloon PD, Fekete BM, Gosling SN, et al. First look at changes in flood hazard in the Inter-Sectoral Impact Model Intercomparison Project ensemble. Proceedings of the National Academy of Sciences. 2014; 111(9):3257–61.
[73].            Roudier P, Andersson JCM, Donnelly C, Feyen L, Greuell W, Ludwig F. Projections of future floods and hydrological droughts in Europe under a+ 2 C global warming. Climatic Change. 2016; 135(2):341–55.
[74].            Cloke HL, Pappenberger F. Ensemble flood forecasting : A review. Journal of Hydrology [Internet]. 2009; 375(3–4):613–26. Available from:
[75].            Kavian A, Mohammadi M, Gholami L, Rodrigo-Comino J. Assessment of the spatiotemporal effects of land use changes on runoff and nitrate loads in the Talar River. Water (Switzerland). 2018; 10(4).
[76].            Jahanshahi A, Golshan M, Afzali A. Simulation of the catchments hydrological processes in arid, semi-arid and semi-humid areas. Desert. 2017; 22(1):1–10.
[77].            Maghsood FF, Moradi H, Bavani M, Reza A, Panahi M, Berndtsson R, et al. Climate Change Impact on Flood Frequency and Source Area in Northern Iran under CMIP5 Scenarios. Water. 2019; 11(2):273.
Volume 7, Issue 2
July 2020
Pages 551-562
  • Receive Date: 05 March 2020
  • Revise Date: 19 April 2020
  • Accept Date: 19 April 2020
  • First Publish Date: 21 June 2020
  • Publish Date: 21 June 2020