Research on Identification of Deep Leakage Channels in Karst Pumped Storage Reservoirs Based on Multi Field Data Fusion

AbstractThe most prominent engineering geological problem of pumped storage power station reservoirs in karst areas is karst leakage, the development of karst leakage channels has a significant impact on the selection of reservoir locations, layout of engineering buildings, design of anti-seepage measures, and engineering costs. Therefore, the survey and evaluation of reservoir leakage channels are the foundation for the construction of pumped storage power station reservoirs in karst areas. The field analysis method plays an important role in karst leakage survey. Traditional karst groundwater field analysis methods, based on the representative indicators of each field measured and determined by experience, fail to fully reflect the temporal and spatial change information of each field indicator, and the data cannot be fully utilized and compared for verification. The multi field data fusion analysis method for karst groundwater proposed in this article comprehensively considers the relationship between measured field indicators and leakage sources, natural conditions, adjacent spaces, and different time field indicators， and obtains the characteristic values of the tracer index, background index, gradient index, and time series index of each field, and overlay calculation of single field comprehensive eigenvalues and multi field composite eigenvalues, which can realize the fusion of multiple fields and multiple indicators, amplify the abnormal location signal of seepage, and delineate the location of centralized seepage, so as to quantitatively determine the location information of the seepage channel of karst groundwater. This method is applied to the survey of karst leakage in the lower reservoir of a pumped storage power station in Guizhou Province, field data fusion analysis shows that there is an abnormal seepage field in the anti-seepage curtain line of the site, and there is good evidence for the temperature and conductivity field data. There is a deep karst leakage channel in the reservoir; The burial depth of the channel is more than 170 m below the normal water level. The research results can provide support for subsequent anti-seepage methods and engineering treatments, as well as relevant engineering experience for other projects.