Application of spatial analysis in prediction water quality

Hydrologic and environmental variables change from location to location in complex and inadequately understood ways. Consider a spatially variable quantity, such as chemical concentration or precipitation; this quantity is a function of the spatial coordinates and may be represented as depending on whether it varies is one, two, or three dimensions. For brevity the notation will be used to include all three cases, where is the location index (a vector with one, two, or three components). The function, known as a regionalized or field variable, is not known everywhere but needs to be estimated from available observations and, perhaps, additional information. We limit our attention to estimators that are linear combinations of the measurements, i.e., ؟؟؟ Thus, the problem is reduced to selecting a set of coefficients . The expected value of at location is a probability-weighted average over the ensemble. Mathematically, we write E [Z(t)] Si pi z(t) , where pi = Pr[Z(ti) = z(ti) ] Kriging involves applying the general methodology known as best linear unbiased estimation( BLUE) to intrinsic functions. In this paper, we want to study component of water quality in the Birjand region, with use spatial data analysis.

کلیدواژه ها:

Spatial Analysis ، Kriging ، Variogram ، Isotropic ، Cross Validation