Fundamentals of Geostatistics for Assessing Spatial Variation of Groundwater Resources

Abstract

The natural resources on the earth seem to be randomly distributed but their variations over space and time are not all random. They exhibit a spatial correlation. This spatial correlation can be captured by geostatistics. Geostatistics deals with the analysis and modelling of geo-referenced data. The point observations are analyzed and interpolated to create spatial maps. For geostatistical interpolation, first the spatial correlation structures of the parameter of interest are quantified and then spatial interpolation is done using the quantified spatial correlation and optimal predictions at unobserved locations to create a map. In this chapter, the fundamental of randomness and statistical distribution are discussed. The statistical measure of spatial variation is the variogram which characterize the degree of spatial correlation. The quantification of variogram is also discussed in detail. Different interpolation techniques like kriging and its variations are also discussed. The fundamentals of ordinary kriging, indicator kriging and regression kriging are also described and their application aspects are also highlighted. The cross-validation procedure and the errors in geostatistical interpolation have also dealt in detail. The chapter ended with sampling design optimization and stochastic simulation processes, showing their importance and application in groundwater resources. This chapter will help the students, researchers and natural resources managers to understand the fundamentals of geostatistics and their application.