| Summary: | 碩士 === 國立交通大學 === 土木工程系所 === 101 === Hydraulic conductivity (K) is an important parameter of an aquifer and is usually obtained using conventionally pumping test method. However, the pumping test method is time consuming and expensive so that only limited data can be collected. In recent years, some studies estimated hydraulic conductivity using surface electrical resistivity survey along with pumping test data. These studies demonstrate its efficiency with low requirement of pumping test data and low cost. However, majority of these studies apply simple linear regression to modeling the relationship between pumping test data (K) and formation factor derived from electric resistivity data without consideration of clay layers. Thus, the equations derived by these studies are only suitable for the study areas without clay layers. In fact, clay layers are commonly distributed in middle-fan and distal-fan. Therefore, this study divides study area, Zhuoshui River Alluvial Fan, into several zones based on the sediment distribution. Each zone has a linear regression equation derived from the pumping test data and formation factors. Moreover, this study applied these equations to develop the hydraulic conductivity distribution of the study area, which locates on the shallow aquifer of the major fan, which is bounded by the Old Zhuoshui River at the north side and by New Hu-Wei River at the south side.
The result shows that the shallow aquifer of the major fan of Zhuoshui River can be divided into two zones, which are top-fan and non-top-fan areas. The regression results show good correlation between hydraulic conductivity and the formation factor in each zone. These regression equations are then used to estimate hydraulic conductivity in the study area. The results are compared between the field measurement and the results obtained from Khalil’s equations. The results indicate that the estimation error, between 11m/day and 58m/day, is much smaller than the estimation error obtained using Khalil’s equation. The results of this study can be further applied to other analyses such as groundwater modeling or water fluctuation method.
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