Spatio-temporal interpolation of precipitation during monsoon periods in Pakistan
Journal
Advances in Water Resources
Journal Volume
33
Journal Issue
8
Pages
880-886
Date Issued
2010
Author(s)
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.
Subjects
Bayesian interpolation; Hyper-parameters; Monsoon precipitation; Non-stationary covariance function; Pakistan; Transformed hierarchical Bayesian interpolation
SDGs
Type
journal article