Preprints
https://doi.org/10.5194/egusphere-2023-2572
https://doi.org/10.5194/egusphere-2023-2572
28 Nov 2023
 | 28 Nov 2023

Inclusion of bedrock vadose zone in dynamic global vegetation models is key for simulating vegetation structure and functioning

Dana A. Lapides, W. Jesse Hahm, Matthew Forrest, Daniella M. Rempe, Thomas Hickler, and David N. Dralle

Abstract. Across many upland environments, soils are thin and plant roots extend into fractured and weathered bedrock where moisture and nutrients can be obtained. Root water extraction from unsaturated weathered bedrock is widespread and, in many environments, can explain gradients in vegetation community composition, transpiration, and plant sensitivity to climate. Despite increasing recognition of its importance, the "rock moisture" reservoir is rarely incorporated into vegetation and Earth system models. Here, we address this weakness in a widely used dynamic global vegetation model (DGVM, LPJ-GUESS). First, we use a water flux-tracking deficit approach to more accurately parameterize plant-accessible water storage capacity across the contiguous United States, which critically includes the water in bedrock below depths typically prescribed by soils databases. Secondly, we exploit field-based knowledge of contrasting plant-available water storage capacity in weathered bedrock across two bedrock types in the Northern California Coast Ranges as a detailed case-study. For the case study in Northern California, climate and soil water storage capacity are similar at the two study areas, but the site with thick weathered bedrock and ample rock moisture supports a mixed evergreen temperate broadleaf-needleleaf forest whereas the site with thin weathered bedrock and limited rock moisture supports an oak savanna. The distinct biomes, seasonality and magnitude of transpiration and primary productivity, and baseflow magnitudes only emerge from the DGVM when a new and simple subsurface storage structure and hydrology scheme is parameterized with storage capacities extending beyond the soil into the bedrock. Across the contiguous United States, the updated hydrology and subsurface storage improve annual evapotranspiration estimates as compared to satellite-derived products, particularly in seasonally dry regions. Specifically, the updated hydrology and subsurface storage allow for enhanced evapotranspiration through the dry season that better matches actual evapotranspiration patterns. While we made changes to both the subsurface water storage capacity and the hydrology, the most important impacts on model performance derive from changes to the subsurface water storage capacity. Our findings highlight the importance of rock moisture in explaining and predicting vegetation structure and function, particularly in seasonally dry climates. These findings motivate efforts to better incorporate the rock moisture reservoir into vegetation, climate, and landscape evolution models.

Dana A. Lapides, W. Jesse Hahm, Matthew Forrest, Daniella M. Rempe, Thomas Hickler, and David N. Dralle

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-2572', Anonymous Referee #1, 05 Dec 2023
    • AC2: 'Reply on RC1', Dana Lapides, 30 Jan 2024
  • RC2: 'Comment on egusphere-2023-2572', Anonymous Referee #2, 19 Dec 2023
    • AC1: 'Reply on RC2', Dana Lapides, 30 Jan 2024
Dana A. Lapides, W. Jesse Hahm, Matthew Forrest, Daniella M. Rempe, Thomas Hickler, and David N. Dralle
Dana A. Lapides, W. Jesse Hahm, Matthew Forrest, Daniella M. Rempe, Thomas Hickler, and David N. Dralle

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Short summary
Water stored in weathered bedrock is rarely incorporated into vegetation and Earth system models, despite increasing recognition of its importance. Here, we add a weathered bedrock component to a widely used vegetation model. Using a case study of two sites in California and model runs across the United States, we show that more accurately representing subsurface water storage and hydrology increases summer plant water use so that it better matches patterns in distributed data products.