Refinement of rooting depths using satellite-based evapotranspiration seasonality for ecosystem modeling in California
2009
Ichii, Kazuhito | Wang, Weile | Hashimoto, Hirofumi | Yang, Feihua | Votava, Petr | Michaelis, Andrew R. | Nemani, Ramakrishna R.
Accurate determination of rooting depths in terrestrial biosphere models is important for simulating terrestrial water and carbon cycles. In this study, we developed a method for optimizing rooting depth using satellite-based evapotranspiration (ET) seasonality and an ecosystem model by minimizing the differences between satellite-based and simulated ET. We then analyzed the impacts of rooting depth optimization on the simulated ET and gross primary production (GPP) seasonality in California, USA. First, we conducted a point-based evaluation of the methods against flux observations in California and tested the sensitivities of the simulated ET seasonality to the rooting depth settings. We then extended it spatially by estimating spatial patterns of rooting depth and analyzing the sensitivities of the simulated ET and GPP seasonalities to the rooting depth settings. We found large differences in the optimized and soil survey (STATSGO)-based rooting depths over the northern forest regions. In these regions, the deep rooting depths (>3m) estimated in the study successfully reproduced the satellite-based ET seasonality, which peaks in summer, whereas the STATSGO-based rooting depth (<1.5m) failed to sustain a high ET in summer. The rooting depth refinement also has large effects on simulated GPP; the annual GPP in these regions is increased by 50-100% due to sufficient soil water during the summer. In the grassy and shrubby regions of central and southern California, the estimated rooting depths are similar to those of STATSGO, probably due to the shallow rooting depth in these ecosystems. Our analysis suggests that setting a rooting depth is important for terrestrial ecosystem modeling and that satellite-based data could help both to estimate the spatial variability of rooting depths and to improve water and carbon cycle modeling.
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