Assessing the impacts of evapotranspiration and gross primary production on the overall accuracy of ECOSTRESS WUE in Kentucky: A case study using field observations and satellite imagery
Wednesday, August 4, 2021
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Bassil El Masri, Earth and Envrionmental Sciences, Murray State University, Murray, KY, Sydney Abbott, Earth and Environmental Sciencess, Murray State University, Murray, KY, Wei Ren, Bo Tao and Yawen Huang, Department of Plant & Soil Sciences, College of Agriculture, Food and Environment, University of Kentucky, Lexington, KY, Maheteme Gebremedhin and Ian Ries, KSU/CAFSSS, Joshua B. Fisher, Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA, Joshua B. Fisher, NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA
Bassil El Masri
Earth and Envrionmental Sciences, Murray State University Murray, KY, USA
Background/Question/Methods Terrestrial ecosystems assimilate atmospheric carbon dioxide (CO2) through photosynthesis, where carbon (C) uptake is accompanied by loss of water to the atmosphere as regulated by leaf stomata. Water use efficiency (WUE) is a key physiological parameter that quantifies the amount of water that terrestrial ecosystems use relative to C gained. WUE is also an important indicator of the ability of the plant to adapt to changing environmental conditions, such as precipitation and temperature. Alternatively, a low WUE can indicate sufficient soil moisture or precipitation and enhanced CO2 uptake and tree growth. Our main scientific goal is to evaluate ECOSTRESS WUE product for two vegetation types in Kentucky and to gain a better understanding of the ability to detect plant WUE in response to changing climate from space. To achieve our objectives we: i) Evaluate ECOSTRESS WUE against observations from two eddy covariance flux tower sites; ii) Investigate the impacts of errors in MODIS GPP and ECOSTRESS ET on the overall accuracy of ECOSTRESS WUE at daily and seasonal timescales; and iii) investigate the use of solar-induced florescence for improving ECOSTRESS WUE. Based on previous studies, we hypothesize: 1) ECOSTRESS WUE errors will be mostly dominated by MODIS GPP algorithm errors; 2) GPP estimated from SIF will result in improved WUE estimates; and 3) ECOSTRESS WUE will show high agreements and more accuracy when compared observed WUE at the forest site than the pasture site Results/Conclusions Our preliminary results showed that ECOSTRESS WUE can depict the general trend in flux tower WUE for both the forest and pasture sites. Statistical analysis revealed that the mean absolute errors and mean bias for ECOSTRESS WUE are dominated by MODIS GPP. We conclude that MODIS GPP is the major error contributor to the overall error in ECOSTRESS WUE, validating our hypothesis. We note that this analysis is based on two flux tower sites and the results might be different once a larger number of sites representative of different ecosystem types are used. Nevertheless, this experiment demonstrates the robustness of our approach for comprehensive analysis of ECOSTRESS WUE and more importantly provides for the first time a methodology for detecting and quantifying whether ECOSTRESS ET or MODIS GPP is the major contributor to the overall ECOSTRESS WUE error.