研究期間：10108~10207;The pumping-induced land subsidence generally exists in an aquifer that is created by lake or river surficial deposit processes. Such aquifer generally includes fine materials that are relatively highly compressible. Previous investigations have indicated that the long-term trend of a land subsidence area reveals the irreversible situation for the aquifer deformations even if the amount of the pump water are significantly reduced or stopped. Therefore, the effective and accurate predictions of land subsidence mechanisms are key references for future water resource managements and homeland security planning. The studies of land subsidence are multidisciplinary sciences. In addition to accurate monitoring data, the understanding of interactions between groundwater flow and soil compaction/consolidation, the detail processes of groundwater flow and subsidence simulations, and the accurate estimations of flow and compaction parameters are important factors to develop accurate and reliable technologies for land subsidence analyses. Motivated by the requirements for such key issues for land subsidence analysis, the objectives of the three-year project are (1) to quantify the accuracy of the integrated data obtained by using multiple monitoring technologies, (2) to analyze the characteristics of time series data from different monitoring systems, (3) to develop inverse models for soil compaction parameters, and (4) to apply the integrated data and the estimated parameters for simulations of a field-scale problem. This study will use Choushui River Alluvial fan to be the study area. With the well developed monitoring systems (compaction monitoring wells and groundwater monitoring network), the available subsidence data (InSAR, GPS, and leveling), and sophisticated analyzing technologies (invers model, spectral analysis, numerical subsidence models), the research team include researchers in the fields of surface deformation and soil mechanics and are expected to develop efficient procedures to integrate spatio-temporal monitoring data with multiple scales and resolutions. Additionally, the project is expected to quantify the differences of parameters and values of subsidence from different inverse models and integration strategies.
