Why Do Large‐Scale Land Surface Models Produce a Low Ratio of Transpiration to Evapotranspiration?

Abstract

Most land surface models (LSMs) used in Earth System Models produce a lower ratio of transpiration (T) to evapotranspiration (ET) than field observations, degrading the credibility of Earth System Model‐projected ecosystem responses and feedbacks to climate change. To interpret this model deficiency, we conducted a pair of model experiments using a three‐dimensional, process‐based ecohydrological model in a subhumid, mountainous catchment. One experiment (CTRL) describes lateral water flow, topographic shading, leaf dynamics, and water vapor diffusion in the soil, while the other (LSM like) does not explicitly describe these processes to mimic a conventional LSM using artificially flattened terrain. Averaged over the catchment, CTRL produced a higher T/ET ratio (72%) than LSM like (55%) and agreed better with an independent estimate (79.79 ± 27%) based on rainfall and stream water isotopes. To discern the exact causes, we conducted additional model experiments, each reverting only one process described in CTRL to that of LSM like. These experiments revealed that the enhanced T/ET ratio was mostly caused by lateral water flow and water vapor diffusion within the soil. In particular, terrain‐driven lateral water flows spread out soil moisture to a wider range along hillslopes with an optimum subrange from the middle to upper slopes, where evaporation (E) was more suppressed by the drier surface than T due to plant uptake of deep soil water, thereby enhancing T/ET. A more elaborate representation of water vapor diffusion from a dynamically changing evaporating surface to the height of the surface roughness length reduced E and increased the T/ET ratio.

Using isotopes to incorporate tree water storage and mixing dynamics into a distributed ecohydrologic modelling framework

“…Across larger spatial scales, averaging over spatial heterogeneities has led to errors in the allocation of net land surface energy into latent heat fluxes and further issues in partitioning latent heat losses between evaporation and transpiration (Chang et al, ; Rouholahnejad Freund & Kirchner, ). A 10‐m horizontal grid resolution was selected to balance the spatial representation of water storage and fluxes with model computational demand.…”

“…Across larger spatial scales, averaging over spatial heterogeneities has led to errors in the allocation of net land surface energy into latent heat fluxes and further issues in partitioning latent heat losses between evaporation and transpiration (Chang et al, 2018;Rouholahnejad Freund & Kirchner, 2017). First, we assumed that extracted stem water was representative of mobile tree-stored water in order to maintain a simplistic approach to the numerical representation of tree-stored water.…”

Soil Fluid Biogeochemical Response to Climatic Events

“…The fact that most of the mineral weathering reactions occurred during episodic periods, rather than continually, further suggests that the time from incipient weathering was likely on the longer end of that range (White & Brantley, ). In comparison, modeled soil residence times for a similar forested catchment in the Santa Catalina Mountains indicated soil residence times range from ~4 to 16 ky (Chang et al, ; Pelletier & Rasmussen, ) for divergent and convergent landscape positions, respectively.…”

Seasonal Evolution of Canopy Stomatal Conductance for a Prairie and Maize Field in the Midwestern United States from Continuous Carbonyl Sulfide Fluxes

“…This has compelled development of a wide variety of tracer‐based, statistical or mechanistic “flux partitioning” approaches including independent estimates of photosynthesis from optical approaches, estimates of respiration from a kinetic model, or deriving transpiration from stable water isotopes (Berkelhammer et al, ; Ferretti et al, ; Reichstein et al, ; Scanlon & Kustas, ; Williams et al, ; Yakir & Wang, ; Yang et al, ). However, the various approaches to flux partitioning have often shown large and systematic discrepancies (Chang et al, ; Wehr et al, ). An alternative approach to assessing model performance would be through a comparison between observed and modeled values of the canopy stomatal conductance (g ), which is analogous to the g value within the big leaf modeling framework.…”