Predictability and Quantification of Complex Groundwater Table Dynamics Driven by Irregular Surface Water Fluctuations

Abstract

Shallow groundwater interacts strongly with surface water across a quarter of global land area, affecting significantly the terrestrial eco‐hydrology and biogeochemistry. We examined groundwater behavior subjected to unimodal impulse and irregular surface water fluctuations, combining physical experiments, numerical simulations, and functional data analysis. Both the experiments and numerical simulations demonstrated a damped and delayed response of groundwater table to surface water fluctuations. To quantify this hysteretic shallow groundwater behavior, we developed a regression model with the Gamma distribution functions adopted to account for the dependence of groundwater behavior on antecedent surface water conditions. The regression model fits and predicts well the groundwater table oscillations resulting from propagation of irregular surface water fluctuations in both laboratory and large‐scale aquifers. The coefficients of the Gamma distribution function vary spatially, reflecting the hysteresis effect associated with increased amplitude damping and delay as the fluctuation propagates. The regression model, in a relatively simple functional form, has demonstrated its capacity of reproducing high‐order nonlinear effects that underpin the surface water and groundwater interactions. The finding has important implications for understanding and predicting shallow groundwater behavior and associated biogeochemical processes, and will contribute broadly to studies of groundwater‐dependent ecology and biogeochemistry.

Diagnostic Analysis of Bank Storage Effects on Sloping Floodplains

“…The drainage porosity of the vadose zone n e [−] (or effective porosity) is the difference between S s and S r . The specific yield S y is defined by the difference between S s and C r [−], where C r is the specific retention (Bear, ), although relationship between these parameters may be more complicated (Xin et al, ). S y is commonly smaller than n e because specific retention is larger than the residual water content of soil during drainage.…”

“…(a) Observed river stage hydrograph (circles) in the laboratory experiments of Xin et al () and the approximated hydrograph with linear segments (solid curves) and (b) the comparisons of the observed (circles) and calculated hydraulic heads using 1‐D semianalytical solution (solid curves) and 2‐D numerical solution (dashed curves) at x = 1 and 2 m.…”

Effects of Temperature on Tidally Influenced Coastal Unconfined Aquifers

“…Water Resources Research Genuchten (1980) soil water retention parameters for laboratory-scale simulations were adopted from Xin et al (2018) who used the same sand for their experiment (the residual water saturation S Wres = 0.05, α = 11 m −1 , and n = 6). For field-scale simulations, the typical values for coastal sand from Carsel and Parrish (1988) were used (S Wres = 0.1, α = 14.5 m −1 , and n = 2.68).…”

Effects of Tidally Varying Salinity on Groundwater Flow and Solute Transport: Insights From Modelling an Idealized Creek Marsh Aquifer

“…Finally, the temporal variations in forcing such as spring-neap tidal cycles (Robinson, Li, & Barry, 2007) and seasonal changes in the inland hydrologic cycle (Charette, 2007;Heiss & Michael, 2014;Michael et al, 2005) were not considered in this study. In addition, recent studies by Xin et al (2018) reported that irregular fluctuations of surface water level could be considered as an independent variable, which influences groundwater behavior. Similarly, the irregular variation of salinity or other chemical constituents in surface water in real creek marsh systems increases the model complexity, which involves comprehensive considerations of variable ambient input of upstream freshwater, episodic rainfall and evaporation.…”