Spatial variability & prediction modeling of groundwater arsenic distribution in the shallowest alluvial aquifers in Bangladesh
Elevated arsenic in groundwater is the greatest environmental problem in Bangladesh. Spatial variability of arsenic in groundwater has been examined by semivariogram analysis that revealed high degree of small-scale spatial variability in alluvial aquifers. Small-scale variability of arsenic concentrations, indicated by high "nugget' values in semivariograms, is associated with heterogeneity in local-scale geology and geochemical processes. In unsampled locations, arsenic concentrations have been predicted using both deterministic and stochastic prediction methods. Natural neighbor (NN) method predicted better than inverse distance to power (IDP) method, and small-scale variations of arsenic concentrations are preserved. Ordinary kriging (OK) method on the untransformed arsenic data and their residual values performed considerably in predicting spatial arsenic distributions on regional-scale. Predicted results are evaluated by cross-validation, mean prediction error, and root mean square methods. Results show that approximately 25% area of Bangladesh, excluding Chittagong Hill Tracts and southern coastal parts, is below the concentration of 10