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Across diverse biomes and climate types, plants use water stored in bedrock to sustain plant transpiration. Bedrock water storage (Sbedrock), in addition to soil moisture, thus plays an important role in water cycling and should be accounted for in the context of surface energy balances and streamflow generation. Yet, the extent to which bedrock water storage impacts hydrologic partitioning and influences latent heat fluxes has yet to be quantified at large scales. This is particularly important in Mediterranean climates, where the majority of precipitation is offset from energy delivery and plants must rely on water retained from the wet season to support summer growth. Here we present a simple and modified water balance approach to quantify the role of Sbedrock on controlling hydrologic and energy partitioning. Specifically, we tracked evapotranspiration in excess of precipitation and mapped soil water storage capacity (Ssoil, mm) across the western US in the context of Budyko's water partitioning framework. Our findings indicate that Sbedrock is necessary to sustain plant transpiration across forests in the Sierra Nevada—some of the most productive forests on Earth—as early as April every year, which is counter to the current conventional thought that bedrock is exclusively used late in the dry season under extremely dry conditions. We found that the proportion of water that returns to the atmosphere would decrease dramatically without access to Sbedrock. When converted to latent heat energy, the median monthly flux associated with evapotranspiration of Sbedrock can exceed 100 W/m2 during the dry season. Plain Language Summary: Plants frequently use water stored in bedrock (Sbedrock) in order to grow. However, the proportion of precipitation that returns to the atmosphere (evapotranspiration) versus to streams (runoff), and the amount of latent heat—the energy associated with evaporating water—used as a result of access to Sbedrock has not been measured. In Mediterranean climates, such as parts of the western US, the majority of energy (sunlight) is received during the dry season and plants must rely on water stored belowground during the wet season to sustain summer growth. In this study, we present two methods for calculating how much Sbedrock influences the amount of water returning to the atmosphere versus streams and what that corresponds to in terms of latent heat energy at the surface. We use gridded data to compare the amount of water entering (precipitation) and exiting (evapotranspiration) the area and use a mapped soil water storage capacity product to draw conclusions about the timing and magnitude of plant transpiration that is a result of access to bedrock water. Our findings indicate that some of the Earth's most productive forests use Sbedrock early in the growing season, consuming over 100 W/m2 of latent heat energy in the summer. Key Points: Plant use of bedrock storage impacts water partitioning in seasonally dry climatesIn many parts of the western United States, root‐zone storage deficits do not reset annuallyPlants may exhaust soil water storage and require bedrock water as early as April each year [ABSTRACT FROM AUTHOR]

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 soil 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 temperate mixed broadleaf–needleleaf evergreen 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

A common parameter in hydrological modeling frameworks is root-zone water storage capacity (SR[L]), which mediates plant-water availability during dry periods and the partitioning of rainfall between runoff and evapotranspiration. Recently, a simple flux-tracking based approach was introduced to estimate the value of SR (Wang-Erlandsson et al., 2016). Here, we build upon this original method, which we argue may overestimate SR in snow-dominated catchments due to snow melt and evaporation processes. We propose a simple extension to the method presented by Wang-Erlandsson et al. (2016), and show that the approach provides a more conservative minimum estimate of SR in snow-dominated watersheds. This SR dataset is available at 1 km resolution for the continental United States, along with the full analysis code, on Google Colaboratory and Earth Engine platforms. We highlight differences between the original and new methods across the rain-snow transition in the Southern Sierra Nevada, California, USA. As climate warms and precipitation increasingly arrives as rain instead of snow, the subsurface may be an increasingly important reservoir for storing plant-available water between wet and dry seasons; improved estimates of SR will therefore better clarify the future role of the subsurface as a storage reservoir that can sustain forests during seasonal dry periods and episodic drought. [ABSTRACT FROM AUTHOR]