The movement and spreading of contaminated groundwater plumes and their mixing with non-contaminated water is strongly influenced by the heterogeneity of the aquifer properties, which may vary strongly over small spatial scales. Thus, imaging these small-scale features and monitoring transport of tracer plumes at a fine resolution is of interest to characterize transport processes in aquifers. Full-waveform inversion (FWI) of crosshole ground penetrating radar (GPR) measurements can provide an aquifer characterization at decimeter-scale resolution. The method produces images of both relative dielectric permittivity (εr) and bulk electrical conductivity (σb), which related to hydraulic aquifer properties and tracer distributions. To test the potential of time-lapse GPR FWI for imaging tracer plumes, we conducted a numerical experiment of tracer transport in a heterogeneous aquifer. Concentration was converted to saline and desalinated tracers, which changed σb, and to ethanol, which changed both εr and σb. The simulated εr and σb distributions in a crosshole plane were considered to simulate GPR data. These data were subsequently used to reconstruct εr and σb distributions using the crosshole 2D GPR FWI. Tracer concentrations were retrieved from the inverted εr and σb models using information about petrophysical parameters. GPR FWI εr images could recover preferential paths of ~0.2 m width, while the σb images resolved structures up to ~ 0.2-0.3 m. The results highlight that changes in εr, e.g., ethanol and hot water, can be used to image transport processes with high resolution by time-lapse GPR FWI, while the accuracy of the recovery of σb is limited.

In his seminal paper on solution of the infiltration equation, Philip (1957) proposed a gravity time, tgrav, to estimate practical convergence time of his infinite time series expansion, TSE. The parameter tgrav refers to a point in time where infiltration is dominated equally by capillarity and gravity derived from the first two (dominant) terms of the TSE expansion. Evidence that higher order TSE terms describe the infiltration process better for longer times. Since the conceptual definition of tgrav is valid regardless of the infiltration model used, we opted to reformulate tgrav using the analytic approximation proposed by Parlange et al. (1982) valid for all times. In addition to the roles of soil sorptivity (S) and saturated (Ks) and initial (Ki) hydraulic conductivities, we explored effects of a soil specific shape parameter β on the behavior of tgrav. We show that the reformulated tgrav (notably tgrav= F(β) S^2/(Ks - Ki)^2 where F(β) is a β-dependent function) is about 3 times larger than the classical tgrav given by tgrav, Philip= S^2/(Ks - Ki)^2. The differences between original tgrav, Philip and the revised tgrav increase for fine textured soils. Results show that the proposed tgrav is a better indicator for convergence time than tgrav, Philip. For attainment of the steady-state infiltration, both time parameters are suitable for coarse-textured soils, but not for fine-textured soils for which tgrav is too conservative and tgrav, Philip too short. Using tgrav will improve predictions of the soil hydraulic parameters (particularly Ks) from infiltration data as compared to tgrav, Philip.

Tropical peatlands are among the most carbon-dense ecosystems on Earth, and their water storage dynamics strongly control these carbon stocks. The hydrological functioning of tropical peatlands differs from that of northern peatlands, which has not yet been accounted for in global land surface models (LSMs). Here, we integrated tropical peat-specific hydrology modules into a global LSM for the first time, by utilizing the peatland-specific model structure adaptation (PEATCLSM) of the NASA Catchment Land Surface Model (CLSM). We developed literature-based parameter sets for natural (PEATCLSMTrop,Nat) and drained (PEATCLSMTrop,Drain) tropical peatlands. The operational CLSM version (which includes peat as a soil class) and PEATCLSMTrop,Nat were forced with global meteorological input data and evaluated over the major tropical peatland regions in Central and South America, the Congo Basin, and Southeast Asia. Evaluation against a unique and extensive data set of in situ water level and eddy covariance-derived evapotranspiration showed an overall improvement in bias and correlation over all three study regions. Over Southeast Asia, an additional simulation with PEATCLSMTrop,Drain was run to address the large fraction of drained tropical peatlands in this region. PEATCLSMTrop,Drain outperformed both CLSM and PEATCLSMTrop,Nat over drained sites. Despite the overall improvements of both tropical PEATCLSM modules, there are strong differences in performance between the three study regions. We attribute these performance differences to regional differences in accuracy of meteorological forcing data, and differences in peatland hydrologic response that are not yet captured by our model.