Reverse Flood Routing in Natural Channels using Genetic Algorithm
Establishing a clear overview of data discharge availability for water balance modelling in basins is a priority in Europe, and in the particular in the framework of the system of Economic and Environmental Accounts for Water (SEEAW) developed by the EU Directorate-General for the Environment. Howev...
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          | Published in | Water resources management Vol. 29; no. 12; pp. 4241 - 4267 | 
|---|---|
| Main Authors | , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        Dordrecht
          Springer Netherlands
    
        01.09.2015
     Springer Nature B.V  | 
| Subjects | |
| Online Access | Get full text | 
| ISSN | 0920-4741 1573-1650 1573-1650  | 
| DOI | 10.1007/s11269-015-1058-z | 
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| Abstract | Establishing a clear overview of data discharge availability for water balance modelling in basins is a priority in Europe, and in the particular in the framework of the system of Economic and Environmental Accounts for Water (SEEAW) developed by the EU Directorate-General for the Environment. However, accurate discharge estimation at a river site depends on rating curve reliability usually defined by recording the water level at a gauged section and carrying out streamflow measurements. Local stage monitoring is fairly straightforward and relatively inexpensive compared to the cost to carry out flow velocity measurements which are, in addition, hindered by high flow. Moreover, hydraulic models may not be ideally suitable to serve the purpose of rating curve extension or its development at a river site upstream/downstream where the discharge is known due to their prohibitive requirement of channel cross-section details and roughness information at closer intervals. Likewise, rainfall-runoff transformation might be applied but its accuracy is tightly linked to detailed information in terms of geomorphological characteristics of intermediate basins as well as rainfall pattern data. On this basis, a procedure for reverse flood routing in natural channels is here proposed for three different configurations of hydrometric monitoring of a river reach where lateral flow is significant and no rainfall data are available for the intermediate basin. The first considers only the downstream channel end as a gauged site where discharge and stages are recorded. The second configuration assumes the downstream end as a gauged site but only in terms of stage. The third configuration envisages both channel ends equipped to recording stages. The channel geometry is known only at channel ends. The developed model has basically four components: (1) the inflow hydrograph is expressed by a Pearson Type-III distribution, involving parameters of peak discharge, time to peak, and a shape factor; (2) the basic continuity equation for flow routing written in the characteristic form is employed; (3) the lateral flow is related to stages at channel ends. (4) the relation between local stage and remote discharge as found by Moramarco et al. (2005b) is exploited. The parameters, coefficients and exponents of the model are obtained, for each configuration, using the genetic algorithm method. Three equipped river branches along the Tiber River in central Italy are used to validate the procedure. Analyses are carried out for three significant flood events occurred along the river and where the lateral flow was significant. Results show the good performance of the procedure for all three monitoring configurations. Specifically, the discharge hydrographs assessed at channel ends are found satisfactory both in terms of shape with a Nash-Sutcliffe ranging overall in the interval (0.755–0.972) and in the reproduction of rating curves at channel ends. Finally, by a synthetic test the performance of the developed procedure is compared to that of the hydraulic model coupled with a hydrologic model. Two river reaches are considered, the first along the Tiber River and the second one located in the Rio Grande basin which is a tributary of the Tiber River. Detailed channel geometry data are available for both the river sections. Results showed the effectiveness of the reverse flood routing to reproducing fairly well the hydrographs simulated by the hydraulic model in the three monitoring investigated configurations. | 
    
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| AbstractList | Establishing a clear overview of data discharge availability for water balance modelling in basins is a priority in Europe, and in the particular in the framework of the system of Economic and Environmental Accounts for Water (SEEAW) developed by the EU Directorate-General for the Environment. However, accurate discharge estimation at a river site depends on rating curve reliability usually defined by recording the water level at a gauged section and carrying out streamflow measurements. Local stage monitoring is fairly straightforward and relatively inexpensive compared to the cost to carry out flow velocity measurements which are, in addition, hindered by high flow. Moreover, hydraulic models may not be ideally suitable to serve the purpose of rating curve extension or its development at a river site upstream/downstream where the discharge is known due to their prohibitive requirement of channel cross-section details and roughness information at closer intervals. Likewise, rainfall-runoff transformation might be applied but its accuracy is tightly linked to detailed information in terms of geomorphological characteristics of intermediate basins as well as rainfall pattern data. On this basis, a procedure for reverse flood routing in natural channels is here proposed for three different configurations of hydrometric monitoring of a river reach where lateral flow is significant and no rainfall data are available for the intermediate basin. The first considers only the downstream channel end as a gauged site where discharge and stages are recorded. The second configuration assumes the downstream end as a gauged site but only in terms of stage. The third configuration envisages both channel ends equipped to recording stages. The channel geometry is known only at channel ends. The developed model has basically four components: (1) the inflow hydrograph is expressed by a Pearson Type-III distribution, involving parameters of peak discharge, time to peak, and a shape factor; (2) the basic continuity equation for flow routing written in the characteristic form is employed; (3) the lateral flow is related to stages at channel ends. (4) the relation between local stage and remote discharge as found by Moramarco et al. (2005b) is exploited. The parameters, coefficients and exponents of the model are obtained, for each configuration, using the genetic algorithm method. Three equipped river branches along the Tiber River in central Italy are used to validate the procedure. Analyses are carried out for three significant flood events occurred along the river and where the lateral flow was significant. Results show the good performance of the procedure for all three monitoring configurations. Specifically, the discharge hydrographs assessed at channel ends are found satisfactory both in terms of shape with a Nash-Sutcliffe ranging overall in the interval (0.755–0.972) and in the reproduction of rating curves at channel ends. Finally, by a synthetic test the performance of the developed procedure is compared to that of the hydraulic model coupled with a hydrologic model. Two river reaches are considered, the first along the Tiber River and the second one located in the Rio Grande basin which is a tributary of the Tiber River. Detailed channel geometry data are available for both the river sections. Results showed the effectiveness of the reverse flood routing to reproducing fairly well the hydrographs simulated by the hydraulic model in the three monitoring investigated configurations. | 
    
| Author | Tayfur, G. Moramarco, T. Zucco, G.  | 
    
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| Keywords | Hydrograph generation Flood wave Simulation Peak rate Genetic algorithm River reach Time to peak Hydraulic modelling Reverse routing  | 
    
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Hørsholm, Denmark SahooBPerumalMMoramarcoTBarbettaSRating Curve Development at Ungauged River Sites using Variable Parameter Muskingum Discharge Routing Method”Water Resour Manag20142820143783380010.1007/s11269-014-0709-9 DasAReverse stream flow routing by using Muskingum models”Sadhana200934348349910.1007/s12046-009-0019-8 MoramarcoTMeloneFSinghVPAssessment of flooding in urbanized ungauged basins: a case study in the Upper Tiber area, Italy”Hydrol Process200519101909192410.1002/hyp.5634 LiongSYChanWTShreeRamJPeak flow forecasting with genetic algorithm and SWMM”J Hydraul Eng ASCE1995121861361710.1061/(ASCE)0733-9429(1995)121:8(613) BarbettaSFranchiniMMeloneFMoramarcoTEnhancement and comprehensive evaluation of the Rating Curve Model for different river sites”J Hydrol2012464–46537638710.1016/j.jhydrol.2012.07.027 ChengCTWuXYChauKWMultiple criteria rainfall-runoff model calibration using a parallel genetic algorithm in a cluster of computer”Hydrol Sci J200550610691088 TayfurGSoft Computing in Water Resources Engineering”2012SouthamptonWIT Press TayfurGSinghVPPredicting Mean and Bankfull Discharge from Channel Cross-Sectional Area by Expert and Regression Methods”Water Resour Manag20112551253126710.1007/s11269-010-9741-6 GoldbergDEGenetic algorithms for search, optimization, and machine learning”1989USAAddison-Wesley JainABhattacharjyaRKSanagaSOptimal design of composite channels using genetic algorithm”J Irrig Drain Eng2004130428629510.1061/(ASCE)0733-9437(2004)130:4(286) SzymkiewiczRNumerical stability of implicit four-point scheme applied to inverse linear flow routing”J Hydrol1996176132310.1016/0022-1694(95)02785-8 SahooBField application of the multilinear Muskingum discharge routing method”Water Resour Manag20132720131193120510.1007/s11269-012-0228-5 TayfurGMoramarcoTSinghVPPredicting and forecasting flow discharge at sites receiving significant lateral inflow”Hydrol Process2007211848185910.1002/hyp.6320 BruenMDoogeJCIHarmonic analysis of the stability of reverse routing in channels”Hydrol Earth Syst Sci200711155956810.5194/hess-11-559-2007 Palisade Corporation“Evolver, the genetic algorithm solver for Microsoft Excel 2012”2013New YorkNewfield SenZOztopalAGenetic algorithms for the classification and prediction of precipitation occurrence”Hydrol Sci J200146225526710.1080/02626660109492820 TayfurGGA-optimized method predicts dispersion coefficient in natural channels”Hydrol Res2009401657810.2166/nh.2009.010 TayfurGMoramarcoT“Predicting hourly-based flow discharge hydrographs from level data using genetic algorithms”J Hydrol20083521–2779310.1016/j.jhydrol.2007.12.029 AytekAKisiOA genetic programming approach to suspended sediment modelling”J Hydrol20083513–428829810.1016/j.jhydrol.2007.12.005 DoogeJCIBruenMProblems in reverse routing”Acta Geol Pol2005534357371 WuCLChauKWA flood forecasting neural network model with genetic algorithm”Int J Environ Pollut2006283–426127310.1504/IJEP.2006.011211 D’OriaMTandaMGReverse flow routing in open channels: A Bayesian geostatistical approach”J Hydrol2012460–46113013510.1016/j.jhydrol.2012.06.055 MoramarcoTBarbettaSMeloneFSinghVPRelating local stage and remote discharge with significant lateral inflow”J Hydrol Eng2005101586910.1061/(ASCE)1084-0699(2005)10:1(58) B Sahoo (1058_CR28) 2014; 28 SY Liong (1058_CR19) 1995; 121 JCI Dooge (1058_CR12) 2005; 53 RM Singh (1058_CR30) 2006; 11 M Bruen (1058_CR5) 2007; 11 MI Hejazi (1058_CR17) 2008; 10 T Moramarco (1058_CR23) 2008; 13 K Taji (1058_CR32) 1999; 5 G Tayfur (1058_CR33) 2009; 40 L Brocca (1058_CR4) 2011; 25 G Tayfur (1058_CR37) 2007; 21 J Guan (1058_CR16) 2005; 10 1058_CR10 Palisade Corporation (1058_CR24) 2013 T Moramarco (1058_CR22) 2005; 10 B Sahoo (1058_CR27) 2013; 27 CL Wu (1058_CR39) 2006; 28 1058_CR1 T Moramarco (1058_CR20) 2004; 9 RN Eli (1058_CR13) 1974; 10 DE Goldberg (1058_CR14) 1989 R Szymkiewicz (1058_CR31) 1996; 176 A Aytek (1058_CR2) 2008; 351 CT Cheng (1058_CR8) 2006; 316 Z Sen (1058_CR29) 2001; 46 G Tayfur (1058_CR34) 2012 CT Cheng (1058_CR7) 2005; 50 S Barbetta (1058_CR3) 2012; 464–465 DE Goldberg (1058_CR15) 1999 1058_CR25 G Tayfur (1058_CR38) 2009; 14 A Jain (1058_CR18) 2004; 130 CT Cheng (1058_CR6) 2002; 268 1058_CR26 A Das (1058_CR11) 2009; 34 G Tayfur (1058_CR35) 2008; 352 G Tayfur (1058_CR36) 2011; 25 M D’Oria (1058_CR9) 2012; 460–461 T Moramarco (1058_CR21) 2005; 19  | 
    
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| SubjectTerms | Algorithms Atmospheric Sciences Basins Channels Civil Engineering Discharge Discharge hydrographs Downstream Earth and Environmental Science Earth Sciences Environment Environmental monitoring equations European Union Flood peak Flood routing Floods Flow measurement Flow velocity Genetic algorithms Geometry Geotechnical Engineering & Applied Earth Sciences High flow Hydraulic models Hydraulics Hydrogeology hydrograph Hydrologic data Hydrologic models Hydrology Hydrology models Hydrology/Water Resources Italy Mathematical models meteorological data monitoring Parameter estimation rain Rainfall-runoff relationships Ratings reproduction Rivers roughness Stream discharge Stream flow Water balance Water inflow Water levels Water resources  | 
    
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| Title | Reverse Flood Routing in Natural Channels using Genetic Algorithm | 
    
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