Análisis de métodos de interpolación geoestadísticos para la estimación espacial de la precipitación en la cuenca del Río Paute

Jheimy Pacheco; Alex Avilés; Omar Delgado

Autores/as

Jheimy Pacheco
Alex Avilés
Omar Delgado

Palabras clave:

cokriging, interpolación, kriging, precipitación

Resumen

El conocimiento de la variabilidad espacial y temporal de la precipitación constituye un importante insumo para el estudio de las ciencias del ambiente. Contar con datos continuos en una superficie resulta costoso, en especial en zonas de montaña debido a lo agreste del terreno. Esta investigación empleó dos métodos de interpolación geoestadísticos: Kriging y Cokriging, para estimar la precipitación promedio en lugares desprovistos de información a partir de datos históricos (1980 - 2010) de 19 estaciones meteorológicas en la cuenca del Paute incorporando la altura en el método Cokriging. Mediante el ajuste del semivariograma, se determinó los parámetros de interpolación para obtener los mapas de predicción y medidas de error óptimos. Los resultados no mostraron mayor variación entre los dos métodos, lo que indica que posiblemente el método Cokriging requiera tomar en cuenta otras variables adicionales para la predicción espacial de la precipitación.

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Bilewu, S. O., & Sule, B. F. (2015). Selection of an Appropriate Interpolation Method for Rainfall Data in Central Nigeria. Ethiopian Journal of Environmental Studies & Management, 8(4), 423–432. http://doi.org/10.4314/ejesm.v8i4.7

Borges, P. de A., Franke, J., Anunciação, Y. M. T., Weiss, H., & Bernhofer, C. (2015). Comparison of spatial interpolation methods for the estimation of precipitation distribution in Distrito Federal, Brazil. Theoretical and Applied Climatology, 123(1), 335–348. http://doi.org/10.1007/s00704-014-1359-9

Buytaert, W., Celleri, R., Willems, P., Bièvre, B. De, & Wyseure, G. (2006). Spatial and temporal rainfall variability in mountainous areas: A case study from the south Ecuadorian Andes. Journal of Hydrology, 329(3-4), 413–421. http://doi.org/10.1016/j.jhydrol.2006.02.031

Campozano, L., Sánchez, E., Aviles, a, & Samaniego, E. (2014). Evaluation of infilling methods for time series of daily precipitation and temperature: The case of the Ecuadorian Andes. Maskana, 5(1), 99–115. Retrieved from http://dspace.ucuenca.edu.ec:8080/handle/123456789/5586

Castro, L. M., Girona´s, J., & Ferna´ndez, B. (2014). Spatial estimation of daily precipitation in regions with complex relief and scarce data using terrain orientation. Journal of Hydrology, 517, 481–492. http://doi.org/10.1016/j.jhydrol.2014.05.064

Celleri, R., Willems, P., Buytaert, W., & Feyen, J. (2007). Space – time rainfall variability in the Paute Basin , Ecuadorian Andes. Wiley InterScience, 3327(August), 3316–3327. http://doi.org/10.1002/hyp

Chahouki, M. A. Z., Chahouki, A. Z., Malekian, A., Bagheri, R., & Vesali, S. A. (2014). Evaluation of Different Cokriging Methods for Rainfall Estimation in Arid Regions ( Central Kavir Basin in Iran ). Desert, 1, 1–9.

Climate, W. (2007). THE ROLE OF CLIMATOLOGICAL NORMALS IN A CHANGING CLIMATE Edited by : Omar Baddour and Hama Kontongomde. Organization, (61). Retrieved from https://www.wmo.int/datastat/documents/WCDMPNo61_1.pdf

Coulibaly, M., & Becker, S. (2009). Spatial Interpolation of Annual Precipitation in South Africa-Comparison and Evaluation of Methods Spatial Interpolation of Annual Precipitation in South Africa - Comparison and Evaluation of Methods. Water International, (May 2012), 37–41.

Fallah Ghalhari, G. A., Dadashi Roudbari, A. A., & Asadi, M. (2016). Identifying the spatial and temporal distribution characteristics of precipitation in Iran. Arabian Journal of Geosciences, 9(12), 595. http://doi.org/10.1007/s12517-016-2606-4

Fleming, M., Stuart Champin III, F., Cramer, W., Hufford, G., & Serreze, M. (2000). Geographic patterns and dynamics of alaskan climate interpolated from a sparse station record. Global Change Biology.

Goovaerts, P. (2000). Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. Journal of Hydrology, 228(1-2), 113–129. http://doi.org/10.1016/S0022-1694(00)00144-X

Hay, L., Viger, R., & McCabe, G. (1998). Precipitation interpolation in mountainous regions using multiple linear regression. In In Proceedings of the HeadWater’98 conference, Italy.

Hevesi, J., Istok, J., & Flint, A. (1992). Precipitation Estimation in mountainous Terrain Using Multivariate Geostatistics Part I.pdf, 661–676.

Johnston, K., Ver Hoef, J. M. ., Krivoruchko, K., & Lucas, N. E. (2003). Using ArcGIS Geostatistical Analyst.

Karani, H. P., Eslami, H., & Vafakhah, M. (2014). Application of Geostatistics for Evaluation of Spatial variability of Precipitation concentration Index ( PCI ) in Ghazvin Province , Iran, 3(March), 60–64.

Keblouti, M., Ouerdachi, L., & Boutaghane, H. (2012). Spatial interpolation of annual precipitation in Annaba-Algeria - Comparison and evaluation of methods. Energy Procedia, 18, 468–475. http://doi.org/10.1016/j.egypro.2012.05.058

Montgomery, D. C., & Runger, G. C. (2011). bibliografia. John

Wiley & Sons, Ltd.

Moreno Jiménez, A., & Cañada Torrecilla, R. (2006). Sistemas y Análisis de la Información Geográfica.

Tao, T. (2009). Uncertainty Analysis of Interpolation Methods in Rainfall Spatial Distribution–A Case of Small Catchment in Lyon. Journal of Water Resource and Protection, 01(02), 136–144. http://doi.org/10.4236/jwarp.2009.12018

Thiessen, A. H. (1911). Precipitation averages for large areas, (7), 1082–1084.

Univesidad del Azuay, U., & Consejo de Gestión de aguas de la cuenca del Paute, C. (2008). Proyecto : Caracterización territorial de la cuenca hidrográfica del río Paute, Fase I y II.

Vicente-Serrano, S., Saz-Sánchez, M., & Cuadrat, J. (2003). Comparative analysis of interpolation methods in the middle Ebro Valley ( Spain ): application to annual precipitation and temperature. Climate Research, 24, 161–180.

Vuille, M., Bradley, R. ., & Keimig, F. (2000). Climate variability in the andes of Ecuador and its relation to tropical Pacific and Atlantic sea surface temperature anomalies. Journal of Climate, 13, 2520–2535.

Wang, S., Huang, G. H., Lin, Q. G., Li, Z., Zhang, H., & Fan, Y. R. (2014). Comparison of interpolation methods for estimating spatial distribution of precipitation in Ontario, Canada. International Journal of Climatology, 34(14), 3745–3751. http://doi.org/10.1002/joc.3941

Webster, R., & Oliver, M. (2007). Geostatistics for Environmental Scientists (Second Edi). John Wiley & Sons, Ltd.

Zhang, X., Lu, X., & Wang, X. (2016). Comparison of Spatial Interpolation Methods Based on Rain Gauges for Annual Precipitation on the Tibetan Plateau. Polish Journal of Environmental Studies, 25(3), 1339–1345. http://doi.org/10.15244/pjoes/61814

Zhang, X., & Srinivasan, R. (2009). GIS-Based Spatial Precipitation Estimation: A comparison of Geostatical approaches, 45(4), 894–906.