Abstract
In watersheds that have not sufficient meteorological and hydrometric data for simulating rainfall-runoff events, using geomorphologic and geomorphoclimatic characteristics of watershed is a conventional method for the simulation. A number of rainfall-runoff models utilize these characteristics such as Nash-IUH, Clark-IUH, Geomorphologic Instantaneous Unit Hydrograph (GIUH), Geomorphoclimatic Instantaneous Unit Hydrograph (GcIUH), GIUH-based Nash (GIUH-Nash) and GcIUH-based Clark (GcIUH-Clark). But all these models are not appropriate for mountainous watersheds. Therefore, the objective of this study is to select the best of them for the simulation. The procedure of this study is: a) selecting appropriate rainfall-runoff events for calibration and validation of six hybrid models, b) distinguishing the best model based on different performance criteria (Percentage Error in Volume(PEV); Percentage Error in Peak (PEP); Percentage Error in Time to Peak (PETP); Root Mean Square Error (RMSE) and Nash-Sutcliffe model efficiency coefficient (ENS)), c) Sensitivity analysis for determination of the most effective parameter at each model, d) Uncertainty determination of different parameters in each model and confirmation of the obtained results by application of the performance criteria. For application of this procedure, the Navrood watershed in the north of Iran as a mountainous watershed has been considered. The results showed that the Clark-IUH and GcIUH-Clark are suitable models for simulation of flood hydrographs, while other models cannot simulate flood hydrographs appropriately. The sensitivity analysis shows that the most sensitive parameters are the infiltration constant rate and time of concentration in the Clark-IUH model. Also, the most sensitive parameters include the infiltration constant rate and storage coefficient in the GcIUH-Clark model. The Clark-IUH and GcIUH-Clark models are more sensitive to their parameters. The Latin Hypercube Sampling (LHS) on Monte Carlo (MC) simulation method was used for evaluation of uncertainty of data in rainfall-runoff models. In this method 500 sets of data values are produced and then the peak discharge of flood hydrographs for each produced data set is simulated with rainfall-runoff models. The uncertainty of data changes the value of simulated peak discharge of flood hydrograph. The uncertainty analysis shows that the observed peak discharges of different rainfall-runoff events are within the range of values of simulated by the six hybrid rainfall-runoff models and IUH that inputs of these models were the produced data sets. The range of the produced peak discharge of flood hydrographs by the Clark-IUH and GcIUH-Clark models is wider than those of other models.
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References
Adib A, Salarijazi M, Shooshtari MM, et al. (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-Taiwan 19(2): 201–209.
Bae DH, Trinh HL, Nguyen HM (2018) Uncertainty estimation of the SURR model parameters and input data for the Imjin River basin using the GLUE method. Journal of Hydro-environment Research 20: 52–62. https://doi.org/10.1016/j.jher.2018.05.001
Bellos V, Kourtis IM, Moreno-Rodenas A, et al. (2017) Quantifying roughness coefficient uncertainty in urban flooding simulations through a simplified methodology. Water 9(12): 944. https://doi.org/10.3390/w9120944
Bhadra A, Panigrahy N, Singh R, et al. (2008) Development of a geomorphological instantaneous unit hydrograph model for scantily gauged watersheds. Environmental Modelling & Software 23(8): 1013–1025. https://doi.org/10.1016/j.envsoft.2007.08.008
Bhaskar NR, Parida BP, Nayak AK (1997) Flood estimation for ungaged catchments using the GIUH. Journal of Water Resources Planning and Management-ASCE 123(4): 228–238. https://doi.org/10.1061/(ASCE)0733-9496(1997)123:4(228)
Cao S, Lee KT, Ho J, et al. (2010) Analysis of runoff in ungauged mountain watersheds in Sichuan, China using kinematic-wavebased GIUH model. Journal of Mountain Science 7(2): 157–166. https://doi.org/10.1007/s11629-010-0256-7
Chang TK, Talei A, Alaghmand S, et al. (2017) Choice of rainfall inputs for event-based rainfall-runoff modeling in a catchment with multiple rainfall stations using data-driven techniques. Journal of Hydrology 545: 100–108. https://doi.org/10.1016/j.jhydrol.2016.12.024
Clark CO (1945) Storage and the unit hydrograph. Transactions of the American Society of Civil Engineers 110: 1419–1488.
Del Giudice G, Padulano R (2016) Sensitivity analysis and calibration of a rainfall-runoff model with the combined use of EPA-SWMM and genetic algorithm. Acta Geophysica 64(5): 1755–1778. https://doi.org/10.1515/acgeo-2016-0062
Hall MJ, Zaki AF, Shahin MMA (2001) Regional analysis using the geomorphoclimatic instantaneous unit hydrograph. Hydrology and Earth System Sciences 5(1): 93–102. https://doi.org/10.5194/hess-5-93-2001
Hosseini SM, Mahjouri N, Riahi S (2016) Development of a direct geomorphologic IUH Model for daily runoff estimation in ungauged watersheds. Journal of Hydrologic Engineering–ASCE 21(6). https://doi.org/10.1061/(ASCE)HE.1943-5584.0001333
Hamby DM (1994) A review of techniques for parameter sensitivity analysis of environmental models. Environmental Monitoring and Assessment 32(2): 135–154. https://doi.org/10.1007/BF00547132
Jiang Y, Liu C, Li X, et al. (2015) Rainfall-runoff modeling, parameter estimation and sensitivity analysis in a semiarid catchment. Environmental Modelling & Software 67: 72–88. https://doi.org/10.1016/j.envsoft.2015.01.008
Khaleghi MR, Gholami V, Ghodusi J, et al. (2011) Efficiency of the geomorphologic instantaneous unit hydrograph method in flood hydrograph simulation. Catena 87(2): 163–171. https://doi.org/10.1016/j.catena.2011.04.005
Mayerhofer C, Meißl G, Klebinder K, et al. (2017) Comparison of the results of a small-plot and a large-plot rainfall simulator-Effects of land use and land cover on surface runoff in Alpine catchments. Catena 156: 184–196. https://doi.org/10.1016/j.catena.2017.04.009
Moreno-Rodenas AM, Bellos V, Langeveld JG, et al. (2018) A dynamic emulator for physically based flow simulators under varying rainfall and parametric conditions. Water Research 142: 512–527. https://doi.org/10.1016/j.watres.2018.06.011
Nash JE (1957) The form of the instantaneous unit hydrograph. In: International Association of Hydrological Sciences General Assembly, Toronto, Canada. pp. 114–121.
Navas R, Delrieu G (2018) Distributed hydrological modeling of floods in the Cévennes-Vivarais region, France: Impact of uncertainties related to precipitation estimation and model parameterization. Journal of Hydrology 565: 276–288. https://doi.org/10.1016/j.jhydrol.2018.08.032
Nourali M, Ghahraman B, Pourreza-Bilondi M, et al. (2016) Effect of formal and informal likelihood functions on uncertainty assessment in a single event rainfall-runoff model. Journal of Hydrology 540: 549–564. https://doi.org/10.1016/j.jhydrol.2016.06.022
Pianosi F, Wagener T (2016) Understanding the time varying importance of different uncertainty sources in hydrological modelling using global sensitivity analysis. Hydrological Processes 30(22): 3991–4003. https://doi.org/10.1002/hyp.10968
Razmkhah H (2018) Parameter Uncertainty Propagation in a Rainfall-Runoff Model; Case Study: Karoon-III River Basin. Water Resources 45(1): 34–49. https://doi.org/10.1134/S0097807817050074
Rigon R, Bancheri M, Formetta G, et al. (2016) The geomorphological unit hydrograph from a historical-critical perspective. Earth Surface Processes and Landforms 41(1): 27–37. https://doi.org/10.1002/esp.3855
Rodriguez-Iturbe I, Valdes JB (1979) The geomorphic structure of hydrologic response. Water Resources Research 15(6): 1409–1420. https://doi.org/10.1029/WR015i006p01409
Rodriguez-Iturbe I, Devoto G, Valdes JB (1979) Discharge response analysis and hydrologic similarity: The interrelation between the geomorphologic IUH and the storm characteristics. Water Resources Research 15(6): 1435–1444. https://doi.org/10.1029/WR015i006p01435
Rodriguez-Iturbe I, Gonzalez-Sanabria M, Bras RI (1982a) A geomorphoclimatic theory of instantaneous unit hydrograph. Water Resources Research 18(4): 877–886. https://doi.org/10.1029/WR018i004p00877
Rodriguez-Iturbe I, Gonzalez-Sanabria M, Camano G (1982b) On the climatic dependence of the IUH: A rainfall-runoff theory of the Nash model and the geomorphoclimatic theory. Water Resources Research 18(4): 887–903. https://doi.org/10.1029/WR018i004p00887
Sadeghi SHR, Mostafazadeh R, Sadoddin A (2015) Changeability of simulated hydrograph from a steep watershed resulted from applying Clark’s IUH and different time-area histograms. Environmental Earth Sciences 74(4): 3629–3643. https://doi.org/10.1007/s12665-015-4426-3
Sahoo R, Jain V (2018) Sensitivity of drainage morphometry based hydrological response(GIUH) of a river basin to the spatial resolution of DEM data. Computers & Geosciences 111: 78–86. https://doi.org/10.1016/j.cageo.2017.10.001
Samadi A, Sadrolashrafi SS, Kholghi MK (2019) Development and testing of a rainfall-runoff model for flood simulation in dry mountain catchments: A case study for the Dez River Basin. Physics and Chemistry of the Earth, Parts A/B/C, In Press. https://doi.org/10.1016/j.pce.2018.07.003
Strahler AN (1956) Quantitative slope analysis. Bulletin Geological Society of America 67(5): 571–596. https://doi.org/10.1130/0016-7606(1956)67[571:QSA]2.0.CO;2
Yating T, Marshall L, Sharma A, et al. (2019) Modelling precipitation uncertainties in a multi-objective Bayesian ecohydrological setting. Advances in Water Resources 123: 12–22. https://doi.org/10.1016/j.advwatres.2018.10.015
Zakizadeh F, Malekinezhad H (2015) Comparison of methods for estimation of flood hydrograph characteristics. Russian Meteorology and Hydrology 40(12): 828–837. https://doi.org/10.3103/S1068373915120080
Zhang J, Li Y, Huang G, et al. (2016) Assessment of parameter uncertainty in hydrological model using a Markov-Chain-Monte-Carlo-based multilevel-factorial-analysis method. Journal of Hydrology 538: 471–486. https://doi.org/10.1016/j.jhydrol.2016.04.044
Zhu G, Li X, Ma J, et al. (2018) A new moving strategy for the sequential Monte Carlo approach in optimizing the hydrological model parameters. Advances in Water Resources 114: 164–179. https://doi.org/10.1016/j.advwatres.2018.02.007
Acknowledgement
The authors of this manuscript would like to thank the managers and staffs of civil engineering department and engineering faculty of Shahid Chamran University of Ahvaz for providing the facilities of this study.
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Adib, A., Lotfirad, M. & Haghighi, A. Using uncertainty and sensitivity analysis for finding the best rainfall-runoff model in mountainous watersheds (Case study: the Navrood watershed in Iran). J. Mt. Sci. 16, 529–541 (2019). https://doi.org/10.1007/s11629-018-5010-6
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DOI: https://doi.org/10.1007/s11629-018-5010-6