Characterizing hydraulic heterogeneity of Bayin River Basin using river stage tomography

The drastic spatial and temporal variations of water resources are one of the causes of the fragile ecological environment in the Bayin River Basin. While the temporal variation is less predictable, a detailed spatial distribution of hydrological parameters of the basin is invaluable for developing guidance for allocating and utilizing water resources in the Bayin River Basin. This study estimates the two-dimensional spatial distribution of hydraulic diffusivity (D) of the Bayin River Basin through the relationship between river flow and groundwater using limited available river stages data along the river. It first conducted a wavelet analysis to illustrate strong correlations between river flow and groundwater during the flood season in the basin. Subsequently, it used a simple linear model to estimate temporal and spatial variations of the river stage along the river due to flood. Then, the study applied a recently developed river stage tomography (RST) to the alluvial fan to estimate the spatial distribution of the D values. The RST treats the flood river stage as a signal pressure transmitter, and the groundwater fluctuation recorded in the observation wells as the images of the aquifer heterogeneity between the river and observation wells. The RST then synthesizes these images to characterize the heterogeneous distribution of D in the alluvial fan in the Bayin River Basin. The results show that the northeast area of the alluvial fan has a relatively high D, while the D is relatively low in the tail and the southwest area of the fan. These findings are consistent with the general concept of alluvial fan evolution. Moreover, the predicted groundwater levels during the flood event in 2019 based on the RST-estimated D is more accurate than the preliminary stratigraphic survey, confirming that capturing groundwater responses at various parts of a basin caused by some disturbances could reveal hydraulic connectivity, which the prior geologic information cannot. This result is essential to advancing aquifer characterization technologies and affirming the contribution of RST and the view toward the future subsurface sciences advocated by Yeh et al. (2008).