Regional frequency analysis of annual maximum daily rainfall in Navarra. Quantiles mapping

[EN] The determination of the law of frequency of precipitations is essential for the design of different hydraulic infrastructures as well as for the analysis and determination of flood areas. The objective of this paper is to present the quantiles of the extreme daily rainfall in Navarre, obtained through a regional frequency analysis, and its spatial representation. 142 manual rainfall stations, located in the Autonomous Community of Navarra and in the surrounding area, have been considered for the study. The duration of registration of the series is greater than 20 years. The Regional Frequency Analysis has been carried out according to the Hosking and Wallis methodology obtaining six homogeneous regions and their most appropriate distribution functions. The mapping has been made applying two interpolation methods: the inverse distance weighted; and the ordinary geostatistical Kriging. The selected method has been the Kriging.[ES] La determinación de la ley de frecuencias de precipitaciones resulta imprescindible para el diseño de diferentes infraestructuras hidráulicas así como para el análisis y determinación de zonas inundables. El objetivo de este artículo es presentar los cuantiles de las precipitaciones diarias extremas en el territorio de la Comunidad Foral de Navarra, obtenidos mediante un análisis regional de frecuencia (ARF), y su representación espacial. Se ha partido de las 142 estaciones pluviométricas manuales, localizadas en la Comunidad Foral de Navarra y en el entorno de la misma, con duración de registro superior a 20 años. El Análisis Regional de Frecuencias (ARF) se ha realizado según la metodología de Hosking y Wallis, obteniendo seis regiones homogéneas y sus funciones de distribución más adecuadas. Para la elaboración de los mapas se han aplicado dos métodos de interpolación: el de la distancia inversa ponderada; y el geoestadístico Kriging ordinario. Después del análisis comparativo se ha elegido el Kriging.Este trabajo de investigación se ha financiado y se ha desarrollado gracias al contrato de investigación “OTRI2015021115”, firmado entre la Universidad Pública de Navarra (UPNA) y la empresa pública Navarra de Infraestructuras Locales S.A. (NILSA), titulado “Sistemas de drenaje urbano sostenible. Bioretención. Caracterización de parámetros locales”. Especial agradecimiento a los técnicos de NILSA responsables de la supervisión del trabajo, Ana Marta Las Heras y Gregorio Berrozpe, por su interés, rigor y seguimiento. Expresar nuestro agradecimiento también al Servicio de Meteorología y Climatología de Navarra perteneciente al Gobierno de Navarra por haber facilitado las series de datos de precipitación, especialmente a su responsable D. Joaquín del Valle de Lersundi, que en todo momento ha manifestado su apoyo incondicional, y a Miren Otazu, técnica de Tragsatec.López, J.; Goñi, M.; San Martín, I.; Erro, J. (2019). Análisis regional de frecuencias de las precipitaciones diarias extremas en Navarra. Elaboración de los mapas de cuantiles. Ingeniería del Agua. 23(1):33-51. https://doi.org/10.4995/ia.2019.100583351231Abdi, A., Hassanzadeh, Y., Ouarda, T.B.M.J. 2017. Regional frequency analysis using Growing Neural Gas network. Journal of Hydrology, 550, 92-102. https://doi.org/10.1016/j.jhydrol.2017.04.047Adamowski, K., Alila, Y., Pilon, P.J. 1996. Regional rainfall distribution for Canada. Atmospheric Research, 42, 75-88. https://doi.org/10.1016/0169-8095(95)00054-2Akkala, A., Devabhaktuni, V., Kumar, A. 2010. Interpolation techniques and associated software for environmental data. Environmental Progress and Sustainable Energy, 29(2), 134-141. https://doi.org/10.1002/ep.10455Almasi A., Ahmad J., Toomanian N., 2014. Using OK and IDW methods for prediction the spatial variability of a horizon depth and OM in soils of Shahrekord, Iran. Journal of Environmental Research and Management, 5(8):139-147.Álvarez, A.J., Orduña, L.M. 2014. Caracterización del comportamiento estadístico de los caudales máximos estacionales en la España peninsular: Propuesta metodológica para su cálculo. Ingeniería Civil, 174, 51-69.Álvarez, M., Puertas, J., Soto, B., Díaz-Fierros, F. 1999. Análisis regional de las precipitaciones máximas en Galicia mediante el método del índice de avenida. Ingeniería Del Agua, 6(4), 379-386. https://doi.org/10.4995/ia.1999.2795Ayoade, J.O. 1976. A preliminary study of magnitude of frequency and distribution of intense rainfall in Nigeria. Hydrological Sciences Journal, 21(3), 419-421. https://doi.org/10.1080/02626667609491650Bilham, E.G. 1936. Classification of heavy falls in short periods. British Rainfall, 1935, 262-280.Blanchet, J., Ceresetti, 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.2016.06.007Cannarozzo, M., D'asaro, F., Ferro, V. 1995. Regional rainfall and flood frequency analysis for Sicily using the two component extreme value distribution. Hydrological Sciences Journal, 40(1), 19-41. https://doi.org/10.1080/02626669509491388Caporali, E., Cavigli, E., Petrucci, A. 2006. The index rainfall in the regional frequency analysis of extreme events in Tuscany (Italy). Environmetrics, 19, 714-724. https://doi.org/10.1002/env.949Dalrymple, T. 1960. Flood frequency analyses. U.S. Geol. Surv. Water Supply Pap., no. 1543A, p. 80.Delhomme, J.P. 1978. Kriging in the hydrosciences. Advances in Water Resources, 1(5), 251-266. https://doi.org/10.1016/0309-1708(78)90039-8García-Marín A.P. 2007. Análisis multifractal de series de datos pluviométricos en Andalucía. Universidad de Córdoba, Servicio de Publicaciones.García-Marín, A.P., Estévez, J., Sangüesa-Pool, C., Pizarro-Tapia, R., Ayuso-Muñoz, J.L., Jimenez-Hornero, F.J. 2015. The use of the exponent K(q) function to delimit homogeneous regions in regional frequency analysis of extreme annual daily rainfall. Hydrological Processes, 29, 139-151. https://doi.org/10.1002/hyp.10284G.N. (Gobierno de Navarra). 2001. Estudio Agroclimático de Navarra. Gobierno de Navarra. http://meteo.navarra.es/Gong ,G., Mattevada, S., O'Bryant, S. 2014. Comparison of the accuracy of kriging and IDW interpolations in estimating groundwater arsenic concentrations in Texas. Environmental Research, 130, 59-69. https://doi.org/10.1016/j.envres.2013.12.005Gotway, C., Ferguson, R., Hergert, G., Peterson, T. 1996. Comparison of kriging and inverse-distance methods for mapping soil parameters. Soil Science Society of American Journal, 60, 1237-1247. https://doi.org/10.1016/j.envres.2013.12.005Guodong, J., Yancong, L., Wenjie, N. 2003. Comparison between inverse distance weighting method and Kriging. Journal of Changchun University of Technology, 24(3), 53-57.Hailegeorgis, T.T., Alfredsen, K. 2017. Regional flood frequency analysis and prediction in ungauged basins including estimation of major uncertainties for mid-Norway. Journal of Hydrology, Regional Studies: 9, 104-126.Halbert, K., Nguyen, C.C., Payrastre, O., Gaume, E. 2016. Reducing uncertainty in flood frequency analyses: A comparison of local and regional approaches involving information on extreme historical flood. Journal of Hydrology, 541, 90-98. https://doi.org/10.1016/j.jhydrol.2016.01.017Hengl, T. 2009. A Practical guide to Geostatistical Mapping. http://spatial-analyst.net/book/system/files/Hengl_2009_GEOSTATe2c1w.pdfHosking, J., Wallis J. 1997. Regional frequency analysis: An approach based on L-moments. Cambridge University Press.Hosking, J. 2015a. Regional Frequency Analysis using L-Moments, Lmom R Package, Version 2.5.Hosking, J. 2015b. Regional Frequency Analysis using L-Moments, LmomRFA R Package, Version 3.0-1.Kjeldsen, T.R., Smithers, J., Schulze, R. 2002. Regional flood frequency analysis in the KwaZulu-Natal province, South Africa, using the index-flood method. Journal of Hydrology, 255(1), 194-211. https://doi.org/10.1016/S0022-1694(01)00520-0Kumari, M., Basistha, A., Bakimchandra, O., Singh, C.K. 2016. Comparison of Spatial Interpolation Methods for Mapping Rainfall in Indian Himalayas of Uttarakhand Region. In: Raju JN (ed) Geostatistical and Geospatial Approaches for the Characterization of Natural Resources in the Environment. pp. 159-168. Springer International Publishing. https://doi.org/10.1007/978-3-319-18663-4_27Kysely, J., Picek, J. 2007. Regional growth curve and improved design values of extreme precipitation events in the Czech Republic. Climate Research, 33(3), 243- 255. https://doi.org/10.3354/cr033243Kysely, J., Picek, J., Huth, R. 2007. Formation of homogeneous regions for regional frequency analysis of extreme precipitation events in the Czech Republic, Studia Geophysica et Geodeatica, 51(2), 327-344. https://doi.org/10.1007/s11200-007-0018-3Lee, S.H., Maeng, S.J. 2003. Frequency analysis of extreme rainfall using Lmoments. Irrigation and Drainage, 52(3), 219-230. https://doi.org/10.1002/ird.90Lin G.-F., Chen Lu-H. 2006. Identification of homogeneous regions for regional frequency analysis using the self-organizing maps. Journal of Hydrology, 324(1-4), 1-9. https://doi.org/10.1016/j.jhydrol.2005.09.009Li, J., Heap, A. 2011. Review of comparative studies of spatial interpolation methods in environmental sciences: performance and impact factors. Ecological Informatics, 6(3-4), 228-241. https://doi.org/10.1016/j.ecoinf.2010.12.003Liu, G., Yang, X. 2008. Spatial variability analysis of soil properties within a field. International Conference on Computer and Computing Technologies in Agriculture. Wuyishan, China (08-18-2007). 1341-1344 pp. Springer. US. https://doi.org/10.1007/978-0-387-77253-0_75Liu, J., Doan, C.D., Liong, S.-Y., Sanders, R., Dao, A.T., Fewtrell, T. 2015. Regional frequency analysis of extreme rainfall events in Jakarta. Natural Hazards, 75(2), 1075-1104. https://doi.org/10.1007/s11069-014-1363-5Liu, W., Du, P., Zhao, Z., Zhang, L. 2016. An Adaptive Weighting Algorithm for Interpolating the Soil Potassium Content. Scientific Reports, 6, 1-12. https://doi.org/10.1038/srep23889Malekinezhad, H., Zare-Garizi, A. 2014. Regional frequency analysis of daily rainfall extremes using L-moments approach. Atmósfera, 27(4), 411-427. https://doi.org/10.1016/S0187-6236(14)70039-6Montes, J., Álvarez, M., Pertierra, L., Moralo, J., Baztán, J. 2018. Regional Frequency Analysis of extremes flows in Northern of Spain. Ingeniería del agua, 22(2), 93-107. https://doi.org/10.4995/Ia.2018.8782Ngongondo, C.S., Xu, C.-Yu, Tallaksen, L.M., Alemaw, B., Chirwa, T. 2011. Regional frequency analysis of rainfall extremes in Southern malwai using index rainfall and L-moments approaches. Stochastic Environmental Research and Risk Assesment, 25(7), 939-955. https://doi.org/10.1007/s00477-011-0480-xNorbiato, D., Borga, M., Sangat,i M., Zanon, F. 2007. Regional frequency analysis of extreme precipitation in the eastern Italian Alps and the August 29, 2003 flash flood. Journal of Hydrology, 345(3), 149-166. https://doi.org/10.1016/j.jhydrol.2007.07.009Oliver, M.A., Webster, R. 1990. Kriging: a method of interpolation for geographical information systems. International Journal of Geographical Information Systems, 4(3), 313-332. https://doi.org/10.1080/02693799008941549Parida, B.P., Kachroo, R.K., Shrestha, D.B. 1998. Regional Flood Frequency Analysis of Mahi-Sabarmati Basin (subzone 3-a) using Index-Flood Procedure with L-moments. Water Resources Management, 12(1-2), 1-12.Park, J.S., Jung, H.S., Kim, R.S., Oh, J.H. 2001. Modelling summer extreme rainfall over the Korean peninsula using Wakeby distribution. International. Journal of Climatology, 21(11), 1371-1384. https://doi.org/10.1002/joc.701Pearson, C., McKerchar, A., Woods, R. 1991. Regional flood frequency analysis of western Australian data using L-moments. National Conference Publication-Institute of Engineers. Australia. 631-632.Schaefer, M.G. 1990. Regional analyses of mean annual precipitation in Washington State. Water Resources Research, 26(1), 119-131. https://doi.org/10.1029/89WR01513Shahzadi, A., Akhter, A.S., Saf, B. 2013. Regional Frequency Analysis of Annual Maximum Rainfall in Monsoon Region of Pakistan using L-moments. Pakistan Journal of Statistics and Operation Research, 9(1), 111-136. https://doi.org/10.18187/pjsor.v9i1.461Smithers, J.C., Schulze, R.E. 2001. A methodology for the estimation of short duration design storms in South Africa using a regional approach based on L-moments. Journal of Hydrology, 24(1-2), 42-52. https://doi.org/10.1016/S0022-1694(00)00374-7Sveinsson, O.G.B., Salas, J.D., Boes, D.C. 2002. Regional frequency analysis of extreme precipitation in northeastern Colorado and Fort Collins flood of 1997. Journal of Hydrologic Engineering, 7(1), 49-63. https://doi.org/10.1061/(ASCE)1084-0699(2002)7:1(49)Trefry, C.M., Watkins, Jr., Johnson, D. 2005. Regional rainfall frequency analysis for the State of Michigan. Journal of Hydrological Engineering, 10(6), 437-449. https://doi.org/10.1061/(ASCE)1084-0699(2005)10:6(437)Vogel, R.M., Thomas, Jr. W.O., McMahon, T.A. 1993. Flood-flow frequency model selection in southwestern United States. Journal of Water Resources Planning and Management, 119(3), 353-366. https://doi.org/10.1061/(ASCE)0733-9496(1993)119:3(353)Weaver, J.C. 2006. Frequency of annual maximum precipitation in the city of Charlotte and Mecklenburg country, North Carolina, through 2004. Scientific Investigation Report 2006-5017. U.S. Department of Interior, U.S.Weber, D., Englund, E. 1992. Evaluation and comparison of spatial interpolators. Mathematical Geology, 24, 381-391. https://doi.org/10.1007/BF00891270Yang, T., Shao, Q., Hao, Z., Chen, X., Zhang, Z., Xu, C., Sun, L. 2010. Regional frequency analysis and spatio-temporal pattern characterization of rainfall extremes in the pearl river basin, China. Journal of Hydrology, 380(3), 386-405. https://doi.org/10.1016/j.jhydrol.2009.11.013Yao, X., Fu, B., Lu, Y., Sun, F., Wang S., Liu, M. 2013. Comparison of Four Spatial Interpolation Methods for Estimating Soil Moisture in a Complex Terrain Catchment. Plos One, 8(1), 1-13. https://doi.org/10.1371/journal.pone.0054660Yasrebi, J., Saffari, M., Fathi, H., Karimian, N., Moazallahi, M., Gazni, R. 2009. Evaluation and comparison of ordinary kriging and inverse distance weighting methods for prediction of spatial variability of some soil chemical parameters. Research Journal of Biological Sciences, 4(1), 93-102