Modeling Choices and the Effects of Water Runoff on Plant Productivity
Understanding differences in modeling soil water will help scientists simulate how this moisture affects the climate.
The Science
The starting point often changes the finish. A team led by researchers at Pacific Northwest National Laboratory modeled runoff, that is, water's movement over the land surface and through the subsurface, using two widely adopted methods. They found that the modeling choices result in differences that ultimately swing results in carbon cycle simulations—by as much as 20%. The differences in modeling runoff methods cause substantial differences in the soil moisture that also changes soil temperature.
The Impact
Moisture is an important element in making sure that the planet provides adequate food and that water is plentiful. It is also a vital ingredient for the climate system’s water, energy, and carbon cycles. This study highlights the significant interactions among these cycles. Discovering their connections will help better represent key water-based parameters in land surface models to better simulate real-world behaviors.
Summary
A team of scientists, led by Pacific Northwest National Laboratory, is seeking to learn how soil moisture influences climate. The investigators studied how uncertainties associated with using two very different representations of soil hydrology affect modeling of plant productivity and the carbon cycle. Using the Community Land Model (CLM) version 4 with two widely adopted runoff-generation parameters, the team found that the global water balance is sensitive to runoff. The two parameters cause a relative difference of about 35% in global mean total runoff and soil moisture, as well as substantial differences in their spatial distribution and seasonal variability. Consequently, the simulated global mean gross primary production differs by 20% because differences in soil moisture simulated between the two models directly influence leaf photosynthesis through soil moisture availability. Soil moisture content also indirectly alters vegetation traits through moisture impacts on soil temperature.
Contact
Maoyi Huang
Pacific Northwest National Laboratory
[email protected]
Funding
This study was supported by the Office of Science of the U.S. Department of Energy (DOE) through the Earth System Modeling program, and in part by National Aeronautics and Space Administration (NASA) as a contribution to the North American Carbon Program. CLM4VIC simulations were performed using the Environmental Molecular Sciences Laboratory (EMSL), a Office of Science User Facility sponsored by the DOE's Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory (PNNL). The Multi-Scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) CLM4 simulations were supported by DOE, Office of Science, Biological and Environmental Research. Huimin Lei was funded by the National Natural Science Funds for Distinguished Young Scholar (Project 51025931) and the National Natural Science Foundation of China (Projects 51209117 and 51139002) during his visit at PNNL.
Publications
H. Lei, M. Huang, L. R. Leung, D. Yang, X. Shi, J. Mao, D. J. Hayes, C. R. Schwalm, Y. Wei, and S. Liu, “Sensitivity of global terrestrial gross primary production to hydrologic states simulated by the Community Land Model using two runoff parameterizations.” Journal of Advances in Modeling Earth Systems 6(3), 658 (2014). [DOI: 10.1002/2013MS000252]
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