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dc.contributor.author | Lopez Rodriguez, Jose Javier | es_ES |
dc.contributor.author | Delgado, Oihane | es_ES |
dc.contributor.author | Campo, Miguel Ángel | es_ES |
dc.coverage.spatial | east=-2.019999999999982; north=43.31777779999999; name=Kristobal Balenziaga Kalea, 23, 20008 Donostia, Gipuzkoa, Espanya | es_ES |
dc.date.accessioned | 2018-11-05T12:34:10Z | |
dc.date.available | 2018-11-05T12:34:10Z | |
dc.date.issued | 2018-10-30 | |
dc.identifier.issn | 1134-2196 | |
dc.identifier.uri | http://hdl.handle.net/10251/111877 | |
dc.description.abstract | [EN] Intensity-duration-frequency curves (IDF) are a fundamental tool in hydrological engineering. The work presented in this manuscript was made with the 88-year precipitation series recorded every ten minutes at the Igueldo (San Sebastián) weather station. After verifying the homogeneity and non stationarity of the series, IDF curves were obtained through a frequency analysis (FA) made with the Hydrognomon programme. Those curves were compared with those estimated from the AF of the simulated series with the Modified Bartlett-Lewis (MBL) model and with the Témez equation. The objective of this work is the evaluation of these last two methodologies. Two precipitation characteristic hyetographs were generated with the IDF curves obtained with the three methods. The curves and hyetographs obtained by Témez gave a good fit starting from return periods, T, of over 20 years. The results obtained from the simulated series with MBL were not as satisfactory. | es_ES |
dc.description.abstract | [ES] Las curvas de intensidad-duración-frecuencia (IDF) son una herramienta fundamental en ingeniería hidrológica. Se ha partido de la serie de precipitación de 88 años registrada cada diez minutos en la estación meteorológica de Igueldo (San Sebastián). Después de aplicar varios test para comprobar la homogeneidad y la no estacionariedad de la serie de precipitación, se determinaron las curvas IDF mediante un análisis de frecuencia con el programa Hydrognomon. Dichas curvas se compararon con las obtenidas a partir de la serie simulada con el modelo estocástico de Barlett-Lewis Modificado (MBL) y con las estimadas mediante la ecuación de Témez. El objetivo de este trabajo es la evaluación de estas dos últimas metodologías. Las curvas y los yetogramas generados con la expresión de Témez presentaron un buen ajuste a partir de periodos de retorno, T, mayores a 20 años. No fueron tan buenos los obtenidos a partir de la serie simulada con MBL. | es_ES |
dc.description.sponsorship | Los autores quieren expresar un especial agradecimiento a la Dirección de Obras Hidráulicas de la Diputación de Guipúzcoa y, en particular a Patxi Tamés y Andoni Da Silva, por la disponibilidad a la hora de facilitar los datos y resolver todas las cuestiones planteadas. | es_ES |
dc.language | Español | es_ES |
dc.publisher | Universitat Politècnica de València | |
dc.relation.ispartof | Ingeniería del Agua | |
dc.rights | Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) | es_ES |
dc.subject | Intensidad de precipitación | es_ES |
dc.subject | Curvas IDF | es_ES |
dc.subject | Hydrognomon | es_ES |
dc.subject | Modelo de Barlett-Lewis | es_ES |
dc.subject | Ecuación de Témez | es_ES |
dc.subject | Rainfall intensity | es_ES |
dc.subject | IDF curves | es_ES |
dc.subject | Modified Bartlett-Lewis model | es_ES |
dc.subject | Témez equation | es_ES |
dc.title | Determinación de las curvas IDF en Igueldo-San Sebastián. Comparación de diferentes métodos | es_ES |
dc.title.alternative | Determination of the IDF curves in Igueldo-San Sebastián. Comparison of different methods | es_ES |
dc.type | Artículo | es_ES |
dc.date.updated | 2018-11-05T11:42:21Z | |
dc.identifier.doi | 10.4995/ia.2018.9480 | |
dc.rights.accessRights | Abierto | es_ES |
dc.description.bibliographicCitation | Lopez Rodriguez, JJ.; Delgado, O.; Campo, MÁ. (2018). Determinación de las curvas IDF en Igueldo-San Sebastián. Comparación de diferentes métodos. Ingeniería del Agua. 22(4):209-223. https://doi.org/10.4995/ia.2018.9480 | es_ES |
dc.description.accrualMethod | SWORD | es_ES |
dc.relation.publisherversion | https://doi.org/10.4995/ia.2018.9480 | es_ES |
dc.description.upvformatpinicio | 209 | es_ES |
dc.description.upvformatpfin | 223 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 22 | |
dc.description.issue | 4 | |
dc.identifier.eissn | 1886-4996 | |
dc.description.references | Blanchet, J., Ceresett, D., Molinié, G., Creutin, J. D. 2016. A regional GEV scale-invariant framework for Intensity-Duration-Frequency analysis. Journal of Hydrology, 540, 82-95. https://doi.org/10.1016/j.jhydrol.2016.06.007 | es_ES |
dc.description.references | Bo, Z., Shafiqul, I. 1994. Aggregation-disaggregation properties of a stochastic rainfall model. Water Resources Research, 30(12), 3423-3435. https://doi.org/10.1029/94WR02026 | es_ES |
dc.description.references | Bougadi, J., Adamowski, K., 2006. Scaling model of a rainfall intensity-duration-frequency relationship. Hydrological Processes, 20, 3747-3757. https://doi.org/10.1002/hyp.6386 | es_ES |
dc.description.references | Buishnad. T.A. 1982. Some methods for testing the homogeneity of rainfall records. Juornal of Hydrology, 58, 11-27. https://doi.org/10.1016/0022-1694(82)90066-X | es_ES |
dc.description.references | Cameron, D., Beven, K., Tawn, J. 2000. An evaluation of three stochastic rainfall models. Journal of Hydrology, 228, 130-149. https://doi.org/10.1016/S0022-1694(00)00143-8 | es_ES |
dc.description.references | Campo, M., López, J., Rebolé, J., García, A. 2012. Rainfall stochastic models. European Geophysical Union General Assembly. April 22-27, Viena, Austria. | es_ES |
dc.description.references | Cirauqui, J.C. 2008. Evaluación de modelos estocásticos para la agregación-desagregación de precipitaciones y su aplicación en la Comunidad Foral de Navarra. Trabajo Fin de Carrera. ETSI. Agrónomos. Universidad Pública de Navarra. | es_ES |
dc.description.references | Chow, V.T., Maidment, D.R., Mays, L. 1988. Applied Hydrology. McGraw-Hill Inc. New York. | es_ES |
dc.description.references | Duan, Q., Sorooshian, S., Vijai , K. 1994. Optimal use of the SCE-UA global optimization method for calibrating watershed models. Journal of Hydrology, 158(3-4), 265-284. https://doi.org/10.1016/0022-1694(94)90057-4 | es_ES |
dc.description.references | Georgakakos, K. P., Bras, R. L. 1984. A hydrologically useful station precipitation model. Water Resources Research, 20(11), 1585-1596. https://doi.org/10.1029/WR020i011p01585 | es_ES |
dc.description.references | Gyasi-Agyei, Y. 2005. Stochastic disaggregation of daily rainfall into one-hour time scale. Journal of Hydrology, 309(1-4), 178-190. https://doi.org/10.1016/j.jhydrol.2004.11.018 | es_ES |
dc.description.references | Heyman, D., Sobel, M. 1982. Stochastic Models in Operations Research. Stochastic Processes and Operating Characteristics, 1. McGraw-Hill. | es_ES |
dc.description.references | Hutchinson, M., 1990. A point rainfall model based on a 3-state continuous Markov occurrence process. Journal of Hydrology, 114,(1-2), 125-148. https://doi.org/10.1016/0022-1694(90)90078-C | es_ES |
dc.description.references | Khaliq, M. N., Quarda, T. J., Gachon, P., Susham, L. 2009. Identification of hydrological trends in the presence of serial and cross correlations: A review of selected methods and their application to annual flow regimes of Canadian rivers. Journal of Hydrology, 368(1-4), 117-130. https://doi.org/10.1016/j.jhydrol.2009.01.035 | es_ES |
dc.description.references | D. Koutsoyiannis. 2003. Rainfall disaggregation methods: Theory and applications. Proceedings, Workshop on Statistical and Mathematical Methods for Hydrological Analysis. Edited by D. Piccolo and L. Ubertini, Rome, 1-23. https://doi.org/10.13140/RG.2.1.2840.8564 | es_ES |
dc.description.references | Koutsoyiannis, D. 2004a. Statistics of extremes and estimation of extreme rainfall: I. Theoretical investigation.. Hydrological Sciences Journal, 49(4), 575-590. https://doi.org/10.1623/hysj.49.4.575.54430 | es_ES |
dc.description.references | Koutsoyiannis, D. 2004b. Statistics of extremes and estimation of extreme rainfall: II. Empirical investigation of long rainfall records. Hydrological Sciences Journal, 49(4), 591-609. https://doi.org/10.1623/hysj.49.4.591.54424 | es_ES |
dc.description.references | Kozanis, S. C. 2010. Hydrognomon - open source software for the analysis of hydrological data. European Geophysical Union General Assembly 2010. Viena, Austria. | es_ES |
dc.description.references | Lozano, P. 2016. Regimen precipitacional en el norte de Navarra y Guipúzcoa ¿Record peninsular y europeo? Nimbus: revista de climatología, meteorología y paisaje (17-18), 125-144. | es_ES |
dc.description.references | Nguyen, V. T. V., Nguyen T. D., Wang, H. 1998. Regional estimation of short duration rainfall extremes. Water & Science Technology, 37(11), 15-19. https://doi.org/10.2166/wst.1998.0425 | es_ES |
dc.description.references | Onof, C., Chandler, R., Kakou, A., Northrop, P., Wheater, H.S., V. Isham. 2000. Rainfall modelling using Poissoncluster processes: a review of developments. Stochastic Enviromental Research and Risk Assessment 14(6), 384-411. https://doi.org/10.1007/s004770000043 | es_ES |
dc.description.references | Onof, C., Arnbjerg-Nielsen, K. 2009. Quantification of anticipated future changes in high resolution design rainfall for urban areas. Atmospheric Research, 92(3), 350-363. https://doi.org/10.1016/j.atmosres.2009.01.014 | es_ES |
dc.description.references | Partal, T., Kahya, E. 2011. Trend analysis in Turkish precipitation data. Hydrological Processes, 20(9), 2011-2026. https://doi.org/10.1002/hyp.5993 | es_ES |
dc.description.references | Rao, A. R., Hamed, K. H. 2000. Flood frequency analysis. CRC Press, Londres, Reino Unido. | es_ES |
dc.description.references | Ritschel, C., Ulbrich, U., Névir, P., Rust, H.W. 2017. Precipitation extremes on multiple time scales - Bartlett-Lewis Rectangular Pulse Model and Intensity-Duration-Frequency curves. Hydrology and Earth System Sciences, 21, 6501-6517. https://doi.org/10.5194/hess-21-6501-2017 | es_ES |
dc.description.references | Rodriguez-Iturbe, I., Cox, D., Isham, V. 1988. A Point Process Model for Rainfall: Further Developments. Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 417(1853), 283-298. https://doi.org/10.1098/rspa.1988.0061 | es_ES |
dc.description.references | Saez, J. A., Gómez Piñeiro, J. 1999. Geografía e Historia de Donostia - San Sebastian. Instituto Geográfico Vasco "Andrés de Urdaneta". | es_ES |
dc.description.references | Salsón, S., García, R. 1998. Desagregación de lluvias para aplicaciones en simulaciones de sistemas de recursos hidráulicos. Ciencia y técnica de la ingeniería civil, 145, 25-35. https://doi.org/10.1029/2000WR900196 | es_ES |
dc.description.references | Sivakumar, B., Sorooshian, S., Gupta, H.V., Gao, H. 2001. A chaotic approach to rainfall disaggregation. Water Resources Research 37(1), 61-72. https://doi.org/10.1029/2000WR900196 | es_ES |
dc.description.references | Tayanc, M., Dalfes, M. Karaka y O. Yenigün. 1998. A comparative assessment of different methods for detecting inhomogeneities in Turkish temperature data set. International Journal of Climatology, 18(5), 561-578. https://doi.org/10.1002/(SICI)1097-0088(199804)18:5%3C561::AID-JOC249%3E3.0.CO;2-Y | es_ES |
dc.description.references | Témez, J. 1978. Cálculo Hidrometeorológico de caudales máximos en pequeñas cuencas naturales. Alanmer S.A., Madrid, España. | es_ES |
dc.description.references | Verhoest, N. E., Vandenberghe, S., Cabus, P., Onof, C. 2010. Are stochastic point rainfall models able to preserve extreme. Hydrological Processes, 24, 3439-3445. https://doi.org/10.1002/hyp.7867 | es_ES |
dc.description.references | Winjgaard, J. R., Kisin Tank, A. M., Konnen, G. P. 2003. Homogeneityof 20th century European daily temperature and precipitation series. International Journal of Climatology, 23, 679-692. https://doi.org/10.1002/joc.906 | es_ES |