Geostatistical approach for identification of transmissivity structure at Dulliu area in Taiwan

A thorough understanding of the characteristics of transmissivity makes gro undwater deterministic models more accurate. These transmissivity data char acteristics occasionally possess a complicated spatial variation over an in vestigated site. This study presents both geostatistical estimation and con ditional simulation methods to generate spatial transmissivity maps. The me asured transmissivity data from the Dulliu area in Yun-Lin county, Taiwan, is used as the case study. The spatial transmissivity maps are simulated by using sequential Gaussian simulation (SGS), and estimated by using natural log ordinary kriging and ordinary kringing. Estimation and simulation resu lts indicate that SGS can reproduce the spatial structure of the investigat ed data. Furthermore, displaying a low spatial variability does not allow t he ordinary kriging and natural log kriging estimates to fit the spatial st ructure and small-scale variation for the investigated data. The maps of kr iging estimates are smoother than those of other simulations. A SGS multipl e realizations has significant advantages over ordinary kriging and even na tural log kriging techniques at a site with a high variation in investigate d data. These results are displayed in geographic information systems (GIS) as basic information for further groundwater study.