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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #413069
Research Project: From Field to Watershed: Enhancing Water Quality and Management in Agroecosystems through Remote Sensing, Ground Measurements, and Integrative Modeling

Location: Hydrology and Remote Sensing Laboratory

Title: Land surface energy partitioning dominates dry-season water availability uncertainties in Earth System Models

Author
item DONG, J - Tianjin University
item ZHOU, J - Tianjin University
item WEI, L - Nanjing University
item ZHOU, H - Tianjin University
item GAO, M - Tianjin University
item ZHANG, Y - Chinese Academy Of Sciences
item DUAN, Z - Lund University
item Crow, Wade
item CHEN, X - Tianjin University

Submitted to: Water Resources Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/14/2025
Publication Date: 4/29/2025
Citation: Dong, J., Zhou, J., Wei, L., Zhou, H., Gao, M., Zhang, Y., Duan, Z., Crow, W.T., Chen, X. 2025. Land surface energy partitioning dominates dry-season water availability uncertainties in Earth System Models. Water Resources Research. 61(5). Article e2024WR038000. https://doi.org/10.1029/2024WR038000.
DOI: https://doi.org/10.1029/2024WR038000

Interpretive Summary: In most agricultural regions, water availability has a major seasonal component. That is, there is one fixed time of year (i.e., the “dry season”) where availability is typically minimized. Water resource vulnerability to climate change is maximized at these times, and dry-season climate projections provided by earth system models are critical for water use sustainability. Despite this importance, relatively little is known about sources of uncertainty in these dry-season climate projections. Using past and future climate change projections provided by a range of earth system models, this paper provides new insight into sources of uncertainty limiting these models in their ability to project future dry-season climate. Specifically, presented results point to the important role played by the representation of land surface processes in these models. In the future, these results will be used to improve the ability of earth system models to project future climate during dry-season conditions in critical agricultural regions.

Technical Abstract: Accurately characterizing dry-season water availability (Wd) is critical for projecting terrestrial carbon exchange and global water security. However, Earth System Model (ESM) uncertainties in Wd projections can exceed 200% of ensemble ESM averages. Based on a newly proposed framework, we provide process-level identifications of uncertainty sources in ESM Wd projections. Results demonstrate that ESM-based Wd uncertainties are dominated by land surface energy partitioning (summarized by evaporation fraction, denoted as EF), as opposed to precipitation or available energy, since Wd is controlled by water-limited evapotranspiration. Therefore, the fraction of energy used for evapotranspiration is constrained by soil water availability, which determines predicted levels of Wd. As such, EF can serve as a physically based constraint for Wd projections. Compared against data-driven benchmarks, ESMs tend to overestimate dry-season EF – suggesting that Wd is likely to be underestimated for future elevated CO2 conditions. The parameterization of evapotranspiration resistance is the central error source in ESM-based EF, which should be constrained to enhance the reliability of EF, and by extension Wd, projections under future elevated CO2 conditions.