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Implementation of Distributed Hydrological Modeling in a Semi-Arid Mediterranean Catchment Azzaba, Morocco

Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The typical Mediterranean climate is marked at certain times of the year by sudden torrential rains causing high water flows, which leads to heavy flooding and hydroclimatic fluctuations due to a semi-arid climate. This explains the need for hydrological modeling for water resource management in these contexts. This work concerns the hydrological modeling of the Azzaba catchment area in Haut-Sebou “Morocco”. In the first part of this work, a bibliographic synthesis was carried out to characterize certain factors (physical, geological and climatic), and a hydrological study was carried out by processing rainfall and hydrometric data from the considered time periods. Ultimately, the use of the “ATHYS” platform is beginning to reproduce the flows at the Azzaba outlet. This model is really applicable in the semi-arid context based on several studies carried out on these contexts, since it has to consider the chronological sequence of phenomena on one hand and the influence of the climatic and physicalhydrogeological parameters of the basin (humidity and soil exchange) on the other. Several criteria were used in this study to estimate the model performance; the most common is Nash-Sutcliffe. After observation and analysis of the overall results, it can be concluded that the model reproduces flows in the Azzaba River watershed well, especially in event mode (mean Nash-Sutcliffe value of 0.71). The use of a historical meteorological time series to simulate flow using a daily time step gives average results with a Nash of 0.50, which strengthens the reliability of the ATHYS platform in the Mediterranean climate area.
Rocznik
Strony
236--254
Opis fizyczny
Bibliogr. 26 poz., rys., tab.
Twórcy
  • Laboratory of Georesources and Environment, Faculty of Sciences and Technology, USMBA, PO Box 2202, Route d’ Imouzzer, 30000 Fez, Morocco
  • Laboratory of Georesources and Environment, Faculty of Sciences and Technology, USMBA, PO Box 2202, Route d’ Imouzzer, 30000 Fez, Morocco
  • Laboratory of Georesources and Environment, Faculty of Sciences and Technology, USMBA, PO Box 2202, Route d’ Imouzzer, 30000 Fez, Morocco
  • Laboratory of Geology and Oceanology, Faculty of sciences Tétouan, Abdelmalek Essaadi University, Mhannech II. B.P. 2121, 93002 Tétouan, Morocco
Bibliografia
  • 1. Andréassian, V., Perrin, C., & Michel, C. 2004. Impact of imperfect potential evapotranspiration knowledge on the efficiency and parameters of watershed models. Journal of Hydrology, 286(1–4), 19–35. doi:10.1016/j.jhydrol.2003.09.030
  • 2. Andreassian, V., Perrin, C., Michel, C., Sanchez, I.U., & Lavabre, J. 2001. Impact of imperfect rainfall knowledge on the ef®ciency and the parameters of watershed models. Journal of Hydrology, 250, 206–223.
  • 3. Archer, D. 1992. Walls of water. Circulation-British Hydrological Society Newsletter Society 44, 1–3.
  • 4. Bentura, P.L.F., & Michel, C. 1997. Flood routing in a wide channel with a quadratic lag-and-route method. Hydrological Sciences Journal, 42(2), 169–189. doi: 10.1080/02626669709492018
  • 5. Berthet, L., Andreassean, V., Perrin, C., & Javelle, P. 2009. How crucial is it to account for the Antecedent Moisture Conditions in flood forecasting? Comparison of event-based and continuous approaches on 178 catchments. Hydrol. Earth Syst. Sci., 13, 819-831.
  • 6. Bouvier, C., & Delclaux, F. 1996. ATHYS: a hydrological environment for spatial modelling and coupling with a GIS, in: Proceedings HydroGIS’96, Vienna, Austria, 19–28. IAHS Publication No. 235.
  • 7. Bouvier, C., Fuentes Mariles, G., & Dominguez Mora, R. 1994. MERCEDES, un modèle hydrologique d’analyse et de prévision de crues en milieu hétérogène. 4p., 23è Journées de l’Hydraulique-Congrès de la SHF, Nîmes (France), Septembre, 257–260.
  • 8. Ciarapica, L., & Todini, E. 2002. TOPKAPI: A model for the representation of the rainfall-runoff process at different scales. Hydrological Processes, 16(2), 207–229. doi:10.1002/hyp.342
  • 9. Clarke, R.T. 1973. A review of some mathematical models used in hydrology, with observations on their calibration and use. Journal of Hydrology, 19(1), 1–20. doi:10.1016/0022-1694(73)90089-9
  • 10. Endreny, T.A., Wood, E.F., & Lettenmaier, D.P. 2000. Satellite-derived digital elevation model accuracy: hydrological modelling requirements, 194(April 1999), 177–194.
  • 11. Gaume, E., Livet, M., Desbordes, M., & Villeneuve, J.P. 2004. Hydrological analysis of the river Aude, France, flash flood on 12 and 13 November 1999. Journal of Hydrology, 286(1–4), 135–154. doi:10.1016/j.jhydrol.2003.09.015
  • 12. Janssen, P.H.M., & Heuberger, P.S.C. 1995. Calibration of process-oriented models. Ecological Modelling, 83(1–2), 55–66. doi:10.1016/03043800(95) 00084-9
  • 13. Kampf, S.K., & Burges, S.J. 2007. A framework for classifying and comparing distributed hillslope and catchment hydrologic models. Water Resources Research, 43(5). doi: 10.1029/2006WR005370
  • 14. Kouassi, A.M., Koffi, Y.B., Kouamé, K.F., & Lasm, T. 2013. Application d’un modèle conceptuel et d’un modèle de réseaux de neurones artificiels à la simulation des débits annuels dans le bassin versant du N’zi-Bandama (Côte d’Ivoire ) Résumé, 9(1), 64–76.
  • 15. Lhomme, J., Bouvier, C., & Perrin, J.L. 2004. Applying a GIS-based geomorphological routing model in urban catchments. Journal of Hydrology, 299(3–4), 203–216. doi:10.1016/S00221694(04)00367-1
  • 16. Mishra, S.K., & Singh, V.P. 2003. Soil Conservation Service Curve Number (SCS-CN) Methodology. Kluwer Academic Publishers, Dordrecht, The Netherlands, ISBN 1-4020-1132-6.
  • 17. Moriasi, D.N., Arnold, J. G., Liew, M. W. Van, Bingner, R.L., Harmel, R.D., & Veith, T. L. 2007. Megsqaws, 50(3), 885–900.
  • 18. Nash, J.E., & Sutcliffe, J.V. 1970. River flow forecasting through conceptual models Part I A discussion of principles. J. Hydrol. 10: 282–290.
  • 19. Orlandini, S., & Rosso, R. 1996. Diffusion wave modeling of distributed catchment dynamics. Journal of Hydrological Engineering 1(3): 101–113.
  • 20. Saulnier, G.M., & Le Lay, M. 2009. Sensitivity of flash-flood simulations on the volume, the intensity, and the localization of rainfall in the CévennesVivarais region (France). Water Resources Research, 45(10), 1–9. doi:10.1029/2008WR006906
  • 21. SCS, 1956. National Engineering Handbook, Hydrology, Section 4, Soil Conservation Service, US Department of Agriculture, Washington DC.
  • 22. Singh, V.P., & Woolhiser, D.A. 2002. Mathematical Modeling of Watershed Hydrology. Journal of Hydrologic Engineering, 7(4), 270–292. doi: 10.1061/(ASCE)1084-0699(2002)7:4(270)
  • 23. Tramblay, Y., Bouvier, C., Ayral, P.A., & Marchandise, A. 2011. Impact of rainfall spatial distribution on rainfall-runoff modelling efficiency and initial soil moisture conditions estimation. Natural Hazards and Earth System Science, 11(1), 157–170. doi: 10.5194/nhess-11-157-2011
  • 24. Vannier, O., Braud, I., & Anquetin, S. 2014. Regional estimation of catchment-scale soil properties by means of streamflow recession analysis for use in distributed hydrological models. Hydrological Processes, 28(26), 6276–6291. doi: 10.1002/hyp.10101.
  • 25. Wagener, T., Gupta, H., Yatheendradas, S., Goodrich, D., Unkrich, C., & Schaffner, M. 2007. Understanding sources of uncertainty in flash-flood forecasting for semi-arid regions. IAHS Publication 313, (July), 204–212.
  • 26. White, K.L., & Chaubey, I. 2006. Sensitivity Analysis, Calibration, and Validation for a Multisite and Multivariable SWAT Model1. Journal of The American Water Resources Association, 41(5), 1077–1089. https://engineering.purdue. edu/~ichaubey/Pubs/White_Chaubey_JAWRA_ Oct05.pdf.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-4af2aed4-4abc-4793-957e-2aac5c948378
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