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Hydrological modelling of wadi Ressoul watershed, Algeria, by HEC-HMS model

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Warianty tytułu
PL
Hydrologiczne modelowanie zlewni rzeki Ressoul w Algierii za pomocą modelu HEC-HMS
Języki publikacji
EN
Abstrakty
EN
This study presents a flood estimation model for wadi Ressoul in El Berda watershed, north east of Algeria. To ensure the overall consistency of simulated results, it is necessary to develop a validation process, particularly in regions where data are scarce or limited and unreliable. To this we must calibrate and validate the model over the hydrograph as measured at the output. Calibration and validation processes were carried out using different sets of data (CN, SCS Lag and Muskingum K). Evaluation on the performance of the developed flood model derived using HEC-HMS (hydrologic modelling system) yield a correlation coefficient R2 close to 1 and the Nash–Sutcliffe efficiency. We limit ourselves to modelling flood of short duration for which the process of evapotranspiration is negligible. Several events have been tested, including two to calibrate and one to validate the model. So it can be said that using the HEC-HMS model had the highest efficiency in with the values of these parameters calibrated, based on objective functions (percent error in peaks), with 8.8 percent difference between of observed and simulated discharges with R2 value is 0.87 and the Nash-Sutcliffe efficiency value is 0.99.
PL
W publikacji przedstawiono model oceny powodzi opracowany dla rzeki Rassoul w zlewni El Berda w północno-wschodniej Algierii. Aby zapewnić spójność wyników symulacji, należy przeprowadzić proces sprawdzenia modelu, szczególnie w odniesieniu do regionów, w których dane są skąpe lub ograniczone i mało wiarygodne. W tym celu należało kalibrować model i dokonać jego potwierdzenia na podstawie danych hydrograficznych. Procesy kalibracji i testowania przeprowadzono z użyciem różnych zestawów danych (CN, SCS Lag i Muskingum K). W wyniku oceny zachowania skonstruowanego modelu HEC-HMS uzyskano współczynnik determinacji R2 bliski 1 i dobry współczynnik efektywności Nasha–Sutcliffa. Autorzy ograniczyli się do modelowania powodzi o krótkim czasie trwania, gdy można pominąć ewapotranspirację. Testowano kilka zdarzeń, w tym dwa w celu kalibracji i jedno w celu potwierdzenia modelu. Można stwierdzić, że model HEC-HMS ma najwyższą wydajność opartą na obiektywnych funkcjach (procent błędu w szczytach fali) wyrażoną 8,8-procentową różnicą między obserwowanym i symulowanym odpływem, gdy R2 = 0,87 i wartość współczynnika efektywności Nasha–Sutcliffa wynosi 0,99.
Wydawca
Rocznik
Tom
Strony
139--147
Opis fizyczny
Bibliogr. 31 poz., fot., rys., tab.
Twórcy
  • Laboratory of Hydraulics and Hydraulic Constructions, Badji Mokhtar-Annaba University, P.O. BOX 12, 23000 Annaba, Algeria
autor
  • Laboratory of Hydraulics and Hydraulic Constructions, Badji Mokhtar-Annaba University, P.O. BOX 12, 23000 Annaba, Algeria
Bibliografia
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  • CHU H.J., CHANG L.C. 2009. Applying Particle Swarm Optimization to Parameter Estimation of the Nonlinear Muskingum Model. Journal of Hydrologic Engineering. Vol. 14. Iss. 9 p. 1024–1027.
  • CUNGE J.A. 1969. On the subject of a flood propagation computation method (Muskingum Method). Journal of Hydraulic Research. Vol. 7. Iss. 2 p. 205–230.
  • IBRAHIM-BATHIS K., AHMED S.A. 2016. Rainfall-runoff modelling of Doddahalla watershed – an application of HEC-HMS and SCN-CN in ungauged agricultural watershed. Arabian Journal of Geosciences. Vol. 9 p. 1–16. DOI: 10.1007/s12517-015-2228-2.
  • JAYAKRISHNAN R., SRINIVASAN R., SANTHI C., ARNOLD J.G. 2005. Advances in the application of the SWAT model for water resources management. Hydrological Processes. Vol. 19. Iss. 3 p. 749–762.
  • KASHID S.S., GHOSH S., MAITY R. 2010. Streamflow prediction using multi-site rainfall obtained from hydroclimatic teleconnection. Journal of Hydrology. Vol. 395. Iss. 3 p. 23–38.
  • KEBLOUTI M., OUERDACHI L., BERHAIL S. 2015. The use of weather radar for rainfall runoff modeling, case of Seybouse watershed (Algeria). Arabian Journal of Geosciences. Vol. 8 p. 1–11. DOI: 10.1007/s12517-013-1224-7.
  • LEGATES D.R., MCCABE G.J. 1999. Evaluating the use of “goodness-of-fit” measures in hydrologic and hydroclimatic model validation. Water Resources Research. Vol. 35. Iss. 1 p. 233–241.
  • MAJIDI A., SHAHEDI K. 2012. Simulation of rainfall-runoff process using Green-Ampt method and HEC-HMS model (Case study: Abnama Watershed, Iran). International Journal of Hydraulic Engineering. Vol. 1. Iss. 1 p. 5–9.
  • MANOHARAN A., MURUGAPPAN A. 2012. Estimation of runoff in an ungauged rural watershed, Tamil Nadu State, India. International Journal of Engineering Science and Technology. Vol. 4. Iss. 2 p. 449–456.
  • MARTIN P.H., LEBOEUF E.J., DOBBINS J.P., DANIEL E.B., ABKOWITZ M.D. 2005. Interfacing GIS with water resource models: a state-of-the-art review. Journal of the American Water Resources Association. Vol. 41. Iss. 6 p. 1471–1487.
  • MASOUD M. 2015. Rainfall-runoff modeling of ungauged wadis in arid environments (case study wadi Rabigh Saudi Arabia). Arabian Journal of Geosciences. Vol. 8 p. 2587–2606. DOI: 10.1007/s12517-014-1404-0.
  • MCCUEN R.H., KNIGHT Z., CUTTER A.G. 2006. Evaluation of the Nash–Sutcliffe efficiency index. Journal of Hydrologic Engineering. Vol. 11. Iss. 6 p. 597–602.
  • MIAO C.Y., DUAN Q.Y., SUN Q.H., LI J.D. 2013. Evaluation and application of Bayesian multi-model estimation in temperature simulations. Progress in Physical Geography. Vol. 37 p. 727–744. DOI: 10.1177/0309133313494961.
  • MORIASI D.N., ARNOLD J.G., VAN LIEW M.W., BINGNER R.L., HARMEL R.D., VEITH T.L. 2007. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE. Vol. 50. Iss. 3 p. 885−900.
  • NASH J.E., SUTCLIFFE J.V. 1970. River flow forecasting through conceptual models: Part 1. A discussion of principles. Journal of Hydrology. Vol. 10. Iss. 3 p. 282–290.
  • PEDRAM E., RASHIDI M. 2014. Studying the efficiency of HEC-HMS models in simulating the flood of the Kordan stream. Advances in Natural and Applied Sciences. Vol. 8. Iss. 5 p. 463–468.
  • RAZI M.A.M. ARIFFIN J., TAHIR W., ARISH N.A.M. 2010. Flood estimation studies using Hydrologic Modelling System (HEC-HMS) for Johor River, Malaysia. Journal of Applied Sciences. Vol. 10. No. 11 p. 930–939.
  • REINELT L.E., VELIKANJE J., BELL E.J. 1991. Development and application of a geographic information-system for wetland watershed analysis. Computers, Environment and Urban Systems. Vol. 15. Iss. 4 p. 239–251.
  • RUELLAND D., ARDOIN-BARDIN S., BILLEN G., SERVAT E. 2008. Sensitivity of a lumped and semi-distributed hydrological model to several methods of rainfall interpolation on a large basin in West Africa. Journal of Hydrology. Vol. 361. Iss. 1–2 p. 96–117.
  • SANTHI C., ARNOLD J.G., WILLIAMS J.R., DUGAS W.A., SRINIVASAN R., HAUCK L.M. 2001. Validation of the SWAT model on a large river basin with point and nonpoint sources. Journal of the American Water Resources Association. Vol. 37. Iss. 5 p. 1169–1188.
  • SCHARFFENBER W., ELY P., DALY S., FLEMING M., PAK J. 2010. Hydrologic modeling system (HEC-HMS): Physically-based simulation components [online]. 2nd Joint Federal Interagency Conference, Las Vegas, NV, June 27–July 1, 2010. [Access 20.02.2016]. Available at: http://acwi.gov/sos/pubs/2ndJFIC/Contents/4F_Scharffenberg_02_24_10.pdf
  • SCHAEFLI B., GUPTA H.V. 2007. Do Nash values have value? Hydrological Processes. Vol. 21. Iss. 15 p. 2075–2080. DOI:10.1002/hyp.6825
  • USACE 2000. Hydrologic Modeling System HEC-HMS. Technical Reference Manual. Davis CA pp. 149.
  • VAN LIEW M.W., ARNOLD J.G., GARBRECHT J.D. 2003. Hydrologic simulation on agricultural watersheds: Choosing between two models. Transactions of ASAE. Vol. 46. Iss. 6 p. 1539–1551.
  • VERMA A.K., JHA M.K., MAHANA R.K. 2010. Evaluation of HEC-HMS and WEPP for simulating watershed runoff using remote sensing and geographical information system. Paddy Water Environ. Vol. 8. Iss. 2 p. 131–144. DOI: 10.1007/s10333-009-0192-8.
  • WAŁĘGA A. 2013. Application of HEC-HMS programme for the reconstruction of a flood event in an uncontrolled basin. Journal of Water and Land Development. No. 18 p. 13–20.
  • WHEATER H.S., JOLLEY T.J., ONOF C., MACKAY N., CHANDLER R.E. 1999. Analysis of aggregation and disaggregation effects for grid-based hydrological models and the development of improved precipitation disaggregation procedures for GCMs. Hydrology and Earth System Sciences. Vol. 3. Iss. 1 p. 95–108. DOI: 10.5194/hess-3-95-1999.
  • ZHANG H.L., WANG Y.J., WANG Y.Q., LI D.X., WANG X.K. 2013. The effect of watershed scale on HEC-HMS calibrated parameters: A case study in the Clear Creek watershed in Iowa, US. Hydrology and Earth System Sciences. Vol. 17. Iss. 7 p. 2735–2745.
  • ZHANG X.S., SRINIVASAN R., DEBELE B., HAO F.H. 2008. Runoff simulation of the headwaters of the Yellow River using the SWAT model with three snowmelt algorithms. Journal of the American Water Resources Association. Vol. 44. Iss. 1 p. 48–61. DOI: 10.1111/j.1752-1688.2007.00137.x.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-c8d2e792-ca14-409e-9a47-fed42b151d8f
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