Spatial Variability and Prediction Modeling of Groundwater Arsenic Distributions 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 µg L-1 of arsenic. Approximately, 43 % area in Bangladesh has arsenic concentrations of 10-50 µg L-1 at shallow depth (< 25 m). More than 17 % area has arsenic concentrations between 50 µg L-1 and 100 µg L-1. High density dataset and small-scale modeling would perform better in prediction of spatial distributions of groundwater arsenic. Sequential simulation and co-kriging methods can be applied to evaluate the spatial distributions of arsenic in groundwater in Bangladesh