Simulating Spatial Distributions, Variability and Uncertainty of Soil Arsenic by Geostatistical Simulations in Geographic Information Systems

摘要

This study quantifies and delineates the spatial distributions, variability and uncertainties of soil arsenic (As) inthe northern part of Changhua County in central Taiwan by using kriging, sequential Gaussian simulation (SGS) andsimulated annealing simulation (SAS) in geographic information systems. Thousand realizations of soil As are simulatedby using SGS and SAS. The impacts of the number of generated realizations on the standard deviation of the soil arsenicdistributions simulated by SGS and SAS were performed for assessing and mapping spatial variability and distributions ofsoil arsenic. The semivariogram results show that As data exhibited small scale variation in the study area. Kriging capturesspatial distribution of soil As, but underestimate high As concentration area. However, both SGS and SAS well capturespatial distributions and variability of soil arsenic in the study area, but SGS results in higher average standard deviationthan SAS with the same number of realizations. 40 realizations of SAS are reliable to simulate and map the distributions,variability and uncertainty of soil arsenic, but 100 realizations are needed by using SGS. Both estimates and simulatesdemonstrated that the high As concentration area distributed around the irrigation ditch systems and industrial plantsin the study site. Finally, the cumulative distribution of soil As of 100 SGS realizations is obtained and can be used forfurther risk assessment.