Abstract
In this paper we tried to fit a predictive model for the average annual rainfall of Bangladesh through a geostatistical approach. From geostatistical point of view, we studied the spatial dependence pattern of average annual rainfall data (measured in mm) collected from 246 stations of Bangladesh. We have employed kriging or spatial interpolation for rainfall data. The data reveals a linear trend when investigated, so by fitting a linear model we tried to remove the trend and, then we used the trend-free data for further calculations. Four theoretical semivariogram models Exponential, Spherical, Gaussian and Matern were used to explain the spatial variation among the average annual rainfall. These models are chosen according to the pattern of empirical semivariogram. The prediction performance of Ordinary kriging with these four fitted models are then compared through ����-fold cross-validation and it is found that Ordinary Kriging performs better when the spatial dependency in average annual rainfall of Bangladesh is modeled through Gaussian semivariogram model.
Highlights
Bangladesh is an agro-economic country, most of the agricultural productions of the country largely depend on the annual amount of precipitation
This stationarity assumption is checked by investigating whether any trend in the log of average annual rainfall exists throughout the study region
A generalized linear model (GLM) technique is used to remove the monotonic trend found in the average annual rainfall of Bangladesh
Summary
Bangladesh is an agro-economic country, most of the agricultural productions of the country largely depend on the annual amount of precipitation. The geographical location along with the low elevation above the sea level made Bangladesh vulnerable for climate change issues. Increasing population density in the country became an alarming issue to deal with given its limited natural resources. Optimal use of its natural resources is not possible by ignoring the natural calamities like flood, drawn etc. To meet the demands it has become very urgent to ensure the maximum production of food. The production of various types of crops, especially rice is extremely dependent on adequate amount of rainfall (Rana et al, 2007), estimation of rainfall is frequently required issue for agricultural planning, water resource management, hydrological and ecological modeling.
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