A soil column model for predicting the interaction between water table and evapotranspiration

Abstract

Lateral waterfluxes are not realistically taken into account in soil column models, although they influence the dynamic evolution of the vertical soil moisture profile. By neglecting these fluxes, the modeling of the soil‐vegetation‐atmosphere continuum is incomplete, and the feedbacks between these three compartments cannot be fully simulated. These fluxes have an importance in the different fields where soil column models are used: hydrology, hydrometeorology, biogeochemical cycles, ecology, and soil weathering. This paper introduces a novel Hydrological Hillslope‐based Soil Column model (H2SC) that simulates the temporal evolution of the water table depth and evapotranspiration fluxes and their interaction. The interconnected processes are infiltration, evapotranspiration, vertical soil water movements, and the nonexplicitly modeled lateral fluxes flowing through the soil column. These lateral fluxes are modeled as a drainage function built from physically based equations that describe a simplified hillslope hydrology. This drainage function can be easily implemented in any soil column model without penalizing computational times. The H2SC model was validated on numerical experiments where a 2‐D hillslope simulation performed with an integrated hydrologic model was compared with simulations using the H2SC 1‐D model. Each of the H2SC simulations represents a specific location of a soil column along the hillslope. Different climate forcings, soil properties, and geometric shapes of the hillslope were tested. The model was then applied at the locations of two piezometers in the Strengbach catchment, France. The model reproduced the temporal evolution of the water table level fairly well for both the numerical experiments and for the real test case.

Upscaling Hydrological Processes for Land Surface Models With a Two‐Hydrologic‐Variable Model: Application to the Little Washita Watershed

“…For these two reasons, and also because we consider transient flow, we assume in our model that the water table elevation varies linearly and makes an angle tan( i ( t )) [−] (Figure 5). This assumption has proved to be efficient in describing water table dynamics in small catchments (Maquin et al., 2017). The water table intersects the soil surface at x = X s ( t ) and the root zone boundary at x = X *( t ).…”

“…Some authors have already started to build such bridges. Maquin et al (2017) have introduced the Hydrologic Hillslope-based Soil Column model (H2SC). This 1D soil column model simulates both vertical flow and lateral flow through, respectively, the Richards equation and a drainage function based on simplified hillslope hydrology.…”

Estimating effluent turbidity in the drinking water flocculation process with an improved random forest model

“…However, the periodicity and complexity of water turbidity prediction data bring great challenges to the successful application of aforementioned turbidity prediction methods. At the same time, public health workers are also looking for new technology for real-time turbidity prediction (Maquin et al 2017;McCurley & Jawitz 2017;Zhang et al 2017;Bernardelli et al 2020).…”

Application of multi-model ensemble averaging techniques for groundwater simulation: synthetic and real-world case studies

“…The successful application and widespread use of MODFLOW have made this model a benchmark approach to simulate groundwater systems (e.g., Guiguer & Franz 1996). So far, MODFLOW has been applied in various case studies such as stream depletion simulation of the aquifer (Ou et al 2016;Minderhoud et al 2017;Fletcher et al 2019), calibration of hydrodynamic components (Xu et al 2017), evaluation of the interaction effects of aquifer recharge and evapotranspiration (Maquin et al 2017), simulation of drawdown in the inclined wells (Batu 2015), assessment of aquifer vulnerability (Pacheco et al 2018), flood propagation and infiltration (Li et al 2019), among others. However, the MODFLOW model can perform best in regular geometry with proper grid flexibility, whereas, for real-world applications with irregular geometry, this approach may poorly perform due to its governing flow approximation which leads to structural uncertainty in simulation (e.g., Strack 2017).…”