Spatio-temporal interpolation of precipitation during monsoon periods in Pakistan |
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| Authors: | Ijaz Hussain Gunter Spöck Jürgen Pilz Hwa-Lung Yu |
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| Institution: | 1. Department of Statistics, University of Klagenfurt, Austria;2. Department of Bioenvironmental Systems Engineering, National Taiwan University, Taiwan |
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| Abstract: | Spatio-temporal estimation of precipitation over a region is essential to the modeling of hydrologic processes for water resources management. The changes of magnitude and space–time heterogeneity of rainfall observations make space–time estimation of precipitation a challenging task. In this paper we propose a Box–Cox transformed hierarchical Bayesian multivariate spatio-temporal interpolation method for the skewed response variable. The proposed method is applied to estimate space–time monthly precipitation in the monsoon periods during 1974–2000, and 27-year monthly average precipitation data are obtained from 51 stations in Pakistan. The results of transformed hierarchical Bayesian multivariate spatio-temporal interpolation are compared to those of non-transformed hierarchical Bayesian interpolation by using cross-validation. The software developed by 11] is used for Bayesian non-stationary multivariate space–time interpolation. It is observed that the transformed hierarchical Bayesian method provides more accuracy than the non-transformed hierarchical Bayesian method. |
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| Keywords: | Bayesian interpolation Hyper-parameters Monsoon precipitation Non-stationary covariance function Pakistan Transformed hierarchical Bayesian interpolation |
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