Spatial estimation of average daily precipitation using multiple linear regression by using topographic and wind speed variables in tropical climate
Abstract
Complex topography and wind characteristics play important roles in rising air masses and in daily spatial distribution of the precipitations in complex region. As a result, its spatial discontinuity and behaviour in complex areas can affect the spatial distribution of precipitation. In this work, a two-fold concept was used to consider both spatial discontinuity and topographic and wind speed in average daily spatial precipitation estimation using Inverse Distance Weighting (IDW) and Multiple Linear Regression (MLR) in tropical climates. First, wet and dry days were identified by the two methods. Then the two models based on MLR (Model 1 and Model 2) were applied on wet days to estimate the precipitation using selected predictor variables. The models were applied for month wise, season wise and year wise daily averages separately during the study period. The study reveals that, Model 1 has been found to be the best in terms of categorical statistics, R2 values, bias and special distribution patterns. However, it was found that sets of different predictor variables dominates in different months, seasons and years. Furthermore, necessities of other data for further enhancement of the results were suggested.
Keyword : inverse distance weighting, interpolation, multiple linear regression, precipitation occurrence, spatial distribution, wind speed
How to Cite
Anees, M. T., Abdullah, K., Nawawi, M. N. M., Ab Rahman, N. N. N., Mt. Piah, A. R., Syakir, M. I., Ali Khan, M. M., & Mohd. Omar, A. K. (2018). Spatial estimation of average daily precipitation using multiple linear regression by using topographic and wind speed variables in tropical climate. Journal of Environmental Engineering and Landscape Management, 26(4), 299-316. https://doi.org/10.3846/jeelm.2018.6337
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Johansson, B., & Chen, D. (2003). The influence of wind and topography on precipitation distribution in Sweden: Statistical analysis and modelling. International Journal of Climatology, 23(12), 1523-1535. https://doi.org/10.1002/joc.951
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Kurtzman, D., Navon, S., & Morin, E. (2009). Improving interpolation of daily precipitation for hydrologic modelling: spatial patterns of preferred interpolators. Hydrological Processes, 23(23), 3281-3291. https://doi.org/10.1002/hyp.7442
Ly, S., Charles, C., & Degre, A. (2011). Geostatistical interpolation of daily rainfall at catchment scale: the use of several variogram models in the Ourthe and Ambleve catchments, Belgium. Hydrology and Earth System Sciences, 15(7), 2259-2274. https://doi.org/10.5194/hess-15-2259-2011
Mahalanobis, P. (1936). On the generalized distance in statistics. Proceedings of the National Institute of Sciences of India, 2, 49-55.
Mair, A., & Fares, A. (2010). Comparison of rainfall interpolation methods in a mountainous region of a tropical island. Journal of Hydrologic Engineering, 16(4), 371-383. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000330
Masseran, N., & Razali, A. M. (2016). Modeling the wind direction behaviors during the monsoon seasons in Peninsular Malaysia. Renewable and Sustainable Energy Reviews, 56, 1419-1430. https://doi.org/10.1016/j.rser.2015.11.040
McCuen, R. H. (1989). Hydrologic analysis and design. N.J.: Prentice-Hall Englewood Cliffs.
Mikoš, M., Jošt, D., & Petkovšek, G. (2006). Rainfall and runoff erosivity in the alpine climate of north Slovenia: a comparison of different estimation methods. Hydrological Sciences Jour nal, 51(1), 115-126. https://doi.org/10.1623/hysj.51.1.115
Pinho, L. G. B., Nobre, J. S., & Singer, J. M. (2015). Cook’s distance for generalized linear mixed models. Computational Statistics & Data Analysis, 82, 126-136. https://doi.org/10.1016/j.csda.2014.08.008
Qing, Y., Zhu-Guo, M. A., & Liang, C. (2011). A preliminary analysis of the relationship between precipitation variation trends and altitude in China. Atmospheric and Oceanic Science Letters, 4(1), 41-46. https://doi.org/10.1080/16742834.2011.11446899
Rajagopalan, B., & Lall, U. (1998). Locally weighted polynomial estimation of spatial precipitation. Journal of Geographic Information and Decision Analysis, 2(2), 44-51. Retrieved from https://www.researchgate.net/profile/Upmanu_Lall/publication/222797769_Locally_weighted_polynomial_estimation_of_spatial_precipitation/links/0fcfd50943f2a6988c000000.pdf
Seo, D. J. (1998). Real-time estimation of rainfall fields using rain gage data under fractional coverage conditions. Journal of Hydrology, 208(1), 25-36. https://doi.org/10.1016/S0022-1694(98)00140-1
Shepard, D. (1968). A two-dimensional interpolation function for irregularly-spaced data. In Proceedings of the 1968 23rd ACM national conference, ACM (pp. 517-524). New York, NY, USA: ACM. https://doi.org/10.1145/800186.810616
Tabios, G. Q., & Salas, J. D. (1985). A comparative analysis of techniques for spatial interpolation of precipitation. JAWRA, 21(3), 365-380. https://doi.org/10.1111/j.1752-1688.1985.tb00147.x
Tao, T. (2009). Uncertainty analysis of interpolation methods in rainfall spatial distribution–a case of small catchment in Lyon. Journal of Environmental Protection, 1(01), 50-58.
Thiessen, A. H. (1911). Precipitation averages for large areas. Monthly Weather Review, 39(7), 1082-1089. https://doi.org/10.1175/1520-0493(1911)39<1082b:PAFLA>2.0.CO;2
Xie, P., Chen, M., Yang, S., Yatagai, A., Hayasaka, T., Fukushima, Y., & Liu, C. (2007). A gauge-based analysis of daily precipitation over East Asia. Journal of Hydrometeorology, 8(3), 607-626. https://doi.org/10.1175/JHM583.1
Anees, M. T., Abdullah, K., Nawawi, M. N. M., Rahman, N. N. N. A., Piah, A. R. M., Omar, F. M., Syakir, M. I., Zakaria, N. A., & Abdul Kadir, M. O. (2017). Development of daily rainfall erosivity model for Kelantan state, Peninsular Malaysia. Hydrology Research, 49(5), 1434-1451. https://doi.org/10.2166/nh.2017.020
Bennett, N. D., Croke, B. F., Guariso, G., Guillaume, J. H., Hamilton, S. H., Jakeman, A. J., Marsili-Libelli, S., Newham, L. T., Norton, J. P., Perrin, C., & Pierce, S. A. (2013). Characterising performance of environmental models. Environmental Modelling & Software, 40, 1-20. https://doi.org/10.1016/j.envsoft.2012.09.011
Buytaert, W., Celleri, R., Willems, P., De Bievre, B., & Wyseure, G. (2006). Spatial and temporal rainfall variability in mountainous areas: A case study from the south Ecuadorian Andes. Journal of Hydrology, 329(3), 413-421. https://doi.org/10.1016/j.jhydrol.2006.02.031
Carpenter, T. M., & Georgakakos, K. P. (2004). Impacts of parametric and radar rainfall uncertainty on the ensemble streamflow simulations of a distributed hydrologic model. Journal of Hydrology, 298(1), 202-221. https://doi.org/10.1016/j.jhydrol.2004.03.036
Castro, L. M., Gironás, J., & Fernández, B. (2014). Spatial estimation of daily precipitation in regions with complex relief and scarce data using terrain orientation. Journal of Hydrology, 517, 481-492. https://doi.org/10.1016/j.jhydrol.2014.05.064
Cook, R. D. (1977). Detection of influential observation in linear regression. Technometrics, 19(1), 15-18. https://doi.org/10.1080/00401706.1977.10489493
Daly, C., Neilson, R. P., & Phillips, D. L. (1994). A statisticaltopographic model for mapping climatological precipitation over mountainous terrain. Journal of applied meteorology, 33(2), 140-158. https://doi.org/10.1175/1520-0450(1994)033<0140:ASTMFM>2.0.CO;2
Diodato, N. (2005). The influence of topographic co‐variables on the spatial variability of precipitation over small regions of complex terrain. International Journal of Climatology, 25(3), 351-363. https://doi.org/10.1002/joc.1131
Drogue, G., Humbert, J., Deraisme, J., Mahr, N., & Freslon, N. (2002). A statistical–topographic model using an omnidirectional parameterization of the relief for mapping orographic rainfall. International Journal of Climatology, 22(5), 599-613. https://doi.org/10.1002/joc.671
Gonga-Saholiariliva, N., Neppel, L., Chevallier, P., Delclaux, F., & Savéan, M. (2016). Geostatistical estimation of daily monsoon precipitation at fine spatial scale: Koshi river basin. Journal of Hydrologic Engineering, 21(9), 1-15. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001388
Goovaerts, P. (2000). Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. Journal of Hydrology, 228(1), 113-129. https://doi.org/10.1016/S0022-1694(00)00144-X
Guan, H., Wilson, J. L., & Makhnin, O. (2005). Geostatistical mapping of mountain precipitation incorporating autosearched effects of terrain and climatic characteristics. Journal of Hydrometeorology, 6(6), 1018-1031. https://doi.org/10.1175/JHM448.1
Hamill, P., Giordano, M., Ward, C., Giles, D., & Holben, B. (2016). An AERONET-based aerosol classification using the Mahalanobis distance. Atmospheric Environment, 140, 213-233. https://doi.org/10.1016/j.atmosenv.2016.06.002
Hewitson, B. C., & Crane, R. G. (2005). Gridded area-averaged daily precipitation via conditional interpolation. Journal of Climate, 18(1), 41-57. https://doi.org/10.1175/JCLI3246.1
Hwang, Y., Clark, M., Rajagopalan, B., & Leavesley, G. (2012). Spatial interpolation schemes of daily precipitation for hydrologic modeling. Stochastic Environmental Research and Risk Assessment, 26(2), 295-320. https://doi.org/10.1007/s00477-011-0509-1
Johansson, B., & Chen, D. (2003). The influence of wind and topography on precipitation distribution in Sweden: Statistical analysis and modelling. International Journal of Climatology, 23(12), 1523-1535. https://doi.org/10.1002/joc.951
Johnson, F., Hutchinson, M. F., The, C., Beesley, C., & Green, J. (2016). Topographic relationships for design rainfalls over Australia. Journal of Hydrology, 533, 439-451. https://doi.org/10.1016/j.jhydrol.2015.12.035
Kurtzman, D., Navon, S., & Morin, E. (2009). Improving interpolation of daily precipitation for hydrologic modelling: spatial patterns of preferred interpolators. Hydrological Processes, 23(23), 3281-3291. https://doi.org/10.1002/hyp.7442
Ly, S., Charles, C., & Degre, A. (2011). Geostatistical interpolation of daily rainfall at catchment scale: the use of several variogram models in the Ourthe and Ambleve catchments, Belgium. Hydrology and Earth System Sciences, 15(7), 2259-2274. https://doi.org/10.5194/hess-15-2259-2011
Mahalanobis, P. (1936). On the generalized distance in statistics. Proceedings of the National Institute of Sciences of India, 2, 49-55.
Mair, A., & Fares, A. (2010). Comparison of rainfall interpolation methods in a mountainous region of a tropical island. Journal of Hydrologic Engineering, 16(4), 371-383. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000330
Masseran, N., & Razali, A. M. (2016). Modeling the wind direction behaviors during the monsoon seasons in Peninsular Malaysia. Renewable and Sustainable Energy Reviews, 56, 1419-1430. https://doi.org/10.1016/j.rser.2015.11.040
McCuen, R. H. (1989). Hydrologic analysis and design. N.J.: Prentice-Hall Englewood Cliffs.
Mikoš, M., Jošt, D., & Petkovšek, G. (2006). Rainfall and runoff erosivity in the alpine climate of north Slovenia: a comparison of different estimation methods. Hydrological Sciences Jour nal, 51(1), 115-126. https://doi.org/10.1623/hysj.51.1.115
Pinho, L. G. B., Nobre, J. S., & Singer, J. M. (2015). Cook’s distance for generalized linear mixed models. Computational Statistics & Data Analysis, 82, 126-136. https://doi.org/10.1016/j.csda.2014.08.008
Qing, Y., Zhu-Guo, M. A., & Liang, C. (2011). A preliminary analysis of the relationship between precipitation variation trends and altitude in China. Atmospheric and Oceanic Science Letters, 4(1), 41-46. https://doi.org/10.1080/16742834.2011.11446899
Rajagopalan, B., & Lall, U. (1998). Locally weighted polynomial estimation of spatial precipitation. Journal of Geographic Information and Decision Analysis, 2(2), 44-51. Retrieved from https://www.researchgate.net/profile/Upmanu_Lall/publication/222797769_Locally_weighted_polynomial_estimation_of_spatial_precipitation/links/0fcfd50943f2a6988c000000.pdf
Seo, D. J. (1998). Real-time estimation of rainfall fields using rain gage data under fractional coverage conditions. Journal of Hydrology, 208(1), 25-36. https://doi.org/10.1016/S0022-1694(98)00140-1
Shepard, D. (1968). A two-dimensional interpolation function for irregularly-spaced data. In Proceedings of the 1968 23rd ACM national conference, ACM (pp. 517-524). New York, NY, USA: ACM. https://doi.org/10.1145/800186.810616
Tabios, G. Q., & Salas, J. D. (1985). A comparative analysis of techniques for spatial interpolation of precipitation. JAWRA, 21(3), 365-380. https://doi.org/10.1111/j.1752-1688.1985.tb00147.x
Tao, T. (2009). Uncertainty analysis of interpolation methods in rainfall spatial distribution–a case of small catchment in Lyon. Journal of Environmental Protection, 1(01), 50-58.
Thiessen, A. H. (1911). Precipitation averages for large areas. Monthly Weather Review, 39(7), 1082-1089. https://doi.org/10.1175/1520-0493(1911)39<1082b:PAFLA>2.0.CO;2
Xie, P., Chen, M., Yang, S., Yatagai, A., Hayasaka, T., Fukushima, Y., & Liu, C. (2007). A gauge-based analysis of daily precipitation over East Asia. Journal of Hydrometeorology, 8(3), 607-626. https://doi.org/10.1175/JHM583.1