Flash flood forecasting in poorly gauged basins using neural networks: Case study of the Gardon de Mialet basin (southern France)

Natural Hazards and Earth System Science

Volumn 12, Issue 11, 2012, Pages 3307-3324

  Artigue, G ^a   Johannet, A ^a   Borrell, V ^b   Pistre, S ^b  

^a ECOLE DES MINES D ALÈS   (France)

^b UNIV MONTPELLIER   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CLIMATE PREDICTION; FLASH FLOOD; PRECIPITATION INTENSITY; RAINGAUGE; WEATHER FORECASTING;

CEVENNES; FRANCE; GARDON BASIN; LANGUEDOC-ROUSSILLON;

EID: 84869173608     PISSN: 15618633     EISSN: 16849981     Source Type: Journal    
DOI: 10.5194/nhess-12-3307-2012     Document Type: Article

References (46)

1. Alfieri, L., Smith, P. J., Thielen-del Pozo, J., and Beven, K. J.: A staggered approach to flash flood forecasting - case study in the Ćevennes region, Adv. Geosci., 29, 13-20, doi:10.5194/adgeo- 29-13-2011, 2011.
2. Artigue, G., Johannet, A., Borrell, V., and Pistre, S.: Flash floods forecasting without rainfalls forecasts by recurrent neural networks, Case study on the Mialet basin (Southern France), Proceedings of the 3rd world congress on Nature and Biologically Inspired Comuting, 19-21 Oct. 2011 in Salamanca, 303-310, 2011.
3. Ayral, P. A.: Contribution a la spatialisation du modele op'erationnel de pr'evision des crues ́eclair ALHTAIR, approches spatiale et exp'erimentale, application au bassin-versant du Gardon d'Anduze, PhD Thesis, Universit'e de Provence, 311 pp., 2005.
4. Barron, A. R.: universal approximation bounds for superpositions of a sigmoidal function, IEEE Transactions on Information Theory IT-39, 930-945, 1993.
5. Bartholmes, H. and Todini, E.: Coupling meteorological and hydrological models for flood forecasting, Hydrol. Earth Syst. Sci., 9, 333-346, doi:10.5194/hess-9-333-2005, 2005.
6. Beven, K. J. and Kirkby, M. J.: A physically based variable contributing area model of basin hydrology, Hydrol. Sci. Bull., 24, 43-69, 1979.
7. Beven, K. J., Quinn, P., Romanivicz, R., Freer, J., and Lamb, R.: TOPMODEL, in: Computer models of watershed hydrology, edited by: Singh, V.P.,Water Resources Publications, Highlands Ranchs, Colo., 627-668, 1995.
8. Borrell, V., Chorda, J., and Dartus, D.: Pr'evision des crues ́eclair, C. R. Geoscience, 337, 1109-1119, 2005.
9. Ceresetti, D.: Structure spatio-temporelle des fortes pr'ecipitations : application a la r'egion C'evennes-Vivarais, PhD Thesis, Universit ́e de Grenoble, Laboratoire d'́etude des Transferts en Hydrologie et Environnement, 283 pp., 2011.
10. Corzo, G. and Solomatine, D.: Knowledge-based modularization and global optimisation of artificial neural network models in hydrological forecasting, Neural Networks, 20, 528-536, 2007.
11. Coulibaly, P., Anctil, F., and Bobee, B.: Daily reservoir inflow forecasting using artificial neural networks with stopped training approach, J. Hydrol., 230, 244-257, 2000.
12. Coustau, M., Ricci, S., Borrell, V., Piacentini, A., Thual, O., Bouvier, C., and Marchandise, A.: Calibration of rainfall runoff hydrological model for flash flood forecasting using data assimilation, EGU, poster, European Geosciences Union General Assembly 2011 Vienna, Austria 3-8 April 2011, 2011.
13. Dolcin'e, L., Andrieu, H., Sempere-Torres, D., and Creutin, D.: Flash flood forecasting with coupled precipitation model in mountainous Mediterranean basin, J. Hydrol. Eng., 6, 1-10, 2001.
14. Dreyfus, G.: Neural networks, methodology and applications, Springer, Berlin, 2005.
15. Gaume, E.: El'ements d'analyse sur les crues ́eclair, PhD Thesis, Ecole Nationale du G'enie Rural, des Eaux et For○ets and Institut National de la Recherche Scientifique, 359 pp., 2002.
16. Gaume, E., Bain, V., Bernardara, P., Newinger, O., Barbuc, M., Bateman, A., Blaskoviov'a, L., Bloschl, G., Borga, M., Dumitrescu, A., Daliakopoulos, I., Garcia, J., Irimescu, A., Kohnova, S., Koutroulis, A., Marchi, L., Matreata, S., Medina, V., Preciso, E., Sempere-Torres, D., Stancalie, G., Szolgay, J., Tsanis, I., Velasco, D., and Viglione, A.: A compilation of data on European flash floods, J. Hydrol., 367, 70-78, 2009.
17. Geman, S., Bienenstock, E., and Doursat, R.: Neural networks and the bias/variance dilemma, Neural Comput., 4, 1-58, 1992.
18. Hornik, K., Stinchcombe, M., and White, H.: Multilayer Feedforward Networks Are Universal Approximators, Neural Networks, 2, 359-366, 1989.
19. Johannet, A.: Artificial Neural Networks, Environmental hydraulics 2, Mathematical Models, 419-443, 2010.
20. Kessler, J. and Chambraud, A.: Ḿet́eo de la France, tous les climates localit́e par localit́e, J.C. Lattes, 391 pp., 1990.
21. Kitadinis, P. K. and Bras, R.: Real time forecasting with a conceptual hydrologic model, applications and results, Water Resour. Re., 16, 1034-1044, 1980.
22. Kong A Siou, L., Johannet, A., Borrell, V., and Pistre, S.: Complexity selection of a neural network model for karst flood forecasting: The case of the Lez Basin (southern France), J. Hydrol., 403, 367-380, 2011.
23. Kong A Siou, L., Johannet, A., Borrell, V., and Pistre, S.: Optimization of the generalisation capability for rainfall-runoff modeling by neural networks: the case of the Lez aquifer (southern France), Environ. Earth Sci., 65, 2365-2375, 2012.
24. Le-Lay, M. and Saulnier, G. M.: Exploring the signature of climate and landscape spatial variabilities in flash flood events: case of the 8-9 September 2002 C'evennes-Vivarais catastrophic event, Geophys. Res. Lett., 34, L13401, doi:10.1029/2007GL029746, 2007.
25. Maier, H. R. and Dandy, G. C.: Neural networks for the forecasting and forecasting of water resources variables: a review of modeling issues and applications, Environ. Model. Softw., 15, 101- 124, 2000.
26. Marchandise, A.: Mod'elisation hydrologique distribu'ee sur le Gardon d'Anduze: ́etude comparative de diff'erents modeles pluie-d'ebit, extrapolation de la normale a l'extr○eme et tests d'hypotheses sur le processus hydrologiques, PhD Thesis, Universit ́e des Sciences et Techniques du Languedoc (Montpellier), 2007.
27. M'et'eo France, Jacq, F.: Pluies Extr○emes en France M'etropolitaine, availanle at: http://pluiesextremes.meteo.fr/index.php, last access: 28 July 2011.
28. MEDDTL, Ministere de l'Ecologie, du D'eveloppement Durable, des Transports et du Logement, available at: http://www.vigicrues.gouv.fr (last access: October 2012), 2011.
29. Moussa, R., Chahinian, N., and Bocquillon, C.: Distributed hydrological modelling of a Mediterranean mountainous catchment - model construction and multi-site validation, J. Hydrol., 337, 35-51, 2007.
30. Nash, J. E. and Sutcliffe, J. V.: River flow forecasting through concepteual models part I - A discussion of principles, J. Hydrol., 10, 282-290, 1970.
31. Pereira Filho, A. J. and Dos Santos, C. C.: Modeling a densely urbanized watershed with an artificial neural network, weather radar and telemetric data, J. Hydrol., 317, 31-48, 2006.
32. Piotrowski, A., Napi'orkowski, J. J., and Rowi'nski, P. M.: Flashflood forecasting by means of neural networks and nearest neighbour approach - a comparative study, Nonlin. Processes Geophys., 13, 443-448, doi:10.5194/npg-13- 443-2006, 2006.
33. Pr'efecture du Gard: Direction D'epartementale de l'Equipement, Reglement de surveillance, de pr'evision et de transmission de l'information sur les crues, available at: http://www.gard.equipement.gouv.fr/IMG/pdf/ RIC SPCGD version 2011 cle7bd5c2.pdf (last access: October 2012), 2006.
34. Rouzeau, M., Martin, X., and Pauc, J. C.: Retour d'exp'erience des inondations survenues dans le d'epartement du Var les 15 et 16 Juin 2010, Rapport du Ministere de l'Ecologie, de l'Energie, du D'eveloppement Durable et de la Mer, en Charge des Technologies Vertes et des N'egociations sur le Climat, Ministere de l'Int'erieur, de l'Outre-Mer et des Collectivit'es Territoriales, Secr'etariat d'Etat Charg'e de l'Ecologie, Inspection g'en'erale de l'Administration, Conseil G'en'eral de l'Environnement et du D'eveloppement Durable, 87 pp., 2010.
35. Sahoo, G. B., Ray, C., and De Carlo, E. H.: Use of neural network to predict flash flood and attendant water qualities of a mountainous stream on Oahu, Hawaii, J. Hydrol., 317, 63-80, 2006.
36. Schmitz, G. H. and Cullmann, J.: PAI-OFF: A new proposal for online flood forecasting in flash flood prone catchments, J. Hydrol., 360, 1-14, 2008.
37. Sjoberg, J. and Ljung, L.: Overtraining, regularisation and searching for minimum in neural networks, Preprint IFAC Symposium on Adaptive Systems in Control and Signal Processing, 1992.
38. Stone, M.: Cross-validatory choice and assessment of statistical forecasting, J. Roy. Stat. Soc., B36, 111-147, 1974.
39. Sudheer, K. P., Gosain, A. K., Rangan, D. M., and Saheb, S. M.: Modelling evaporation using an artificial neural network algorithm, Hydrol. Process., 16, 3189-3202, 2002.
40. Sun, X., Mein, R. G., Keenan, T. D., and Elliott, J. F.: Flood estimation using radar and raingauge data, J. Hydrol., 239, 4-18, 2000.
41. Tabary, P., Dupuy, P., L'Henaff, G., Laurantin, O., Merlier, C., and Soubeyroux, J. M.: A 10-year (1997-2006) reanalysis of quantitative precipitation estimation over France: methodology and first results, Hydrol. Sci. J., in press, 2012.
42. Toukourou, M. S., Johannet, A., and Dreyfus, G.: Flash flood forecasting by statistical larning in the absence of rainfall forecast: a case study, Engineering Applications of Neural Networks Proceedings, 98-107, 2009.
43. Toukourou, M., Johannet, A., Dreyfus, G., and Ayral, P.-A.: Rainfall-runoff modelling of flash floods in the absence of rainfall forecasts: the case of "C'evenol flash floods", J. Appl. Intell., 35, 1078-189, 2011.
44. Tramblay, Y., Bouvier, C., Martin,C., Didon-Lescot, J. F., Todorovik, D., and Domergue, J. M.: Assessment of initial soil moisture conditions for event-based rainfall-runoff modelling, J. Hydrol., 387, 176-187, 2010.
45. Vinet, F.: Geographical analysis of damage due to flash floods in southern France: The cases of 12-13 November 1999 and 8-9 September 2002, Appl. Geogr., 28, 323-336, 2008.
46. Younis, J., Anquetin, S., and Thielen, J.: The benefit of highresolution operational weather forecasts for flash flood warning, Hydrol. Earth Syst. Sci., 12, 1039-1051, doi:10.5194/hess-12- 1039-2008, 2008.