Catchment‐scale Richards equation‐based modeling of evapotranspiration via boundary condition switching and root water uptake schemes

Abstract

In arid and semiarid climate catchments, where annual evapotranspiration (ET) and rainfall are typically comparable, modeling ET is important for proper assessment of water availability and sustainable land use management. The aim of the present study is to assess different parsimonious schemes for representing ET in a process-based model of coupled surface and subsurface flow. A simplified method for computing ET based on a switching procedure for the boundary conditions of the Richards equation at the soil surface is compared to a sink term approach that includes root water uptake, root distribution, root water compensation, and water and oxygen stress. The study site for the analysis is a small pasture catchment in southeastern Australia. A comprehensive sensitivity analysis carried out on the parameters of the sink term shows that the maximum root depth is the dominant control on catchment-scale ET and streamflow. Comparison with the boundary condition switching method demonstrates that this simpler scheme (only one parameter) can successfully reproduce ET when the vegetation root depth is shallow (not exceeding approximately 50 cm). For deeper rooting systems, the switching scheme fails to match the ET fluxes and is affected by numerical artifacts, generating physically unrealistic soil moisture dynamics. It is further shown that when transpiration is the dominant contribution to ET, the inclusion of oxygen stress and root water compensation in the model can have a considerable effect on the estimation of both ET and streamflow; this is mostly due to the water fluxes associated with the riparian zone.

Understanding Catchment‐Scale Forest Root Water Uptake Strategies Across the Continental United States Through Inverse Ecohydrological Modeling

“…Yang et al (2016) demonstrated that the rooting depth of vegetation influenced continental water balances globally, though this effect was estimated through the simplified model of Donohue et al (2012), which lacks a mechanistic foundation. Camporese et al (2015) reached similar conclusions with a physically based subsurface model applied to a water-limited catchment in southern Australia. Our research suggests that functional RWU strategies influence catchment transpiration (Figure 4a) particularly in northern forests (Figures 3a and 3c) during the growing season (Figure 4c), highlighting the conditional sensitivity of catchment-scale water and energy balances to forest rooting strategies.…”

Water balance complexities in ephemeral catchments with different land uses: Insights from monitoring and distributed hydrologic modeling

“…Actual evapotranspiration ( ET a ) is computed using a sink term ( S ) in the Richards equation to account for root water uptake, as in Camporese et al . []. Potential transpiration is distributed across the root depth as a function of the root distribution, β , which is expressed as: where z is depth (i.e., positive downward), z m is the maximum rooting depth, and p z is an empirical shape parameter [ Vrugt et al ., ].…”

“…Root water uptake compensatory mechanisms were not included here, contrasting with Camporese et al . [].…”

Simulated response of an intermittent stream to rainfall frequency patterns

“…The data set was divided into three parts for warm-up ( The parameters listed in Table 1 were varied in the sensitivity analysis (Camporese et al, 2010;Camporese et al, 2014;Camporese et al, 2015). Each of the parameters was increased and decreased by 20% of their initial value, whereas the other parameters remained unchanged.…”

“…A number of studies modelled intermittent catchments (e.g., Ye et al, 1997;Ye et al, 1998;O'Toole et al, 2018;Risva et al, 2018) using lumped models because of low data requirements, simplicity of application, and ability of simulation at short timescales (Ivkovic et al, 2009). Integrated surface-subsurface hydrological models (ISSHMs) have recently received increasing attention in modelling intermittent catchments (e.g., Saber et al, 2015;Camporese et al, 2015;Dean et al, 2016;Maref & Seddini, 2018). Conversely, detailed hydrological modelling of natural catchments requires dealing with complex topography and geology, multiple nonlinear dynamics, and heterogeneous parameters (Gauthier et al, 2009;Fatichi et al, 2016).…”