Using Median Point in Keeling Plot to Reduce the Uncertainty of the Isotopic Composition of Evapotranspiration

Yusen Yuan aCenter for Agricultural Water Research in China, China Agricultural University, Beijing, China
bDepartment of Earth and Environmental Sciences, Indiana University Indianapolis, Indianapolis, Indiana
cDepartment of Plant and Environmental Sciences, New Mexico State University, Las Cruces, New Mexico
dDepartment of Environmental Sciences, University of California Riverside, California

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Lixin Wang bDepartment of Earth and Environmental Sciences, Indiana University Indianapolis, Indianapolis, Indiana

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Zhongwang Wei eGuangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China

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Hoori Ajami dDepartment of Environmental Sciences, University of California Riverside, California

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Honglang Wang fDepartment of Mathematical Sciences, Indiana University Indianapolis, Indianapolis, Indiana

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Taisheng Du aCenter for Agricultural Water Research in China, China Agricultural University, Beijing, China

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Abstract

The isotopic composition of evapotranspiration δET is a crucial parameter in isotope-based evapotranspiration (ET) partitioning and moisture recycling studies. The Keeling plot method is the most prevalent method to calculate δET, though it contains large extrapolated uncertainties from the least squares regression. Traditional Keeling regression uses the mean point of individual measurements. Here, a modified Keeling plot framework was proposed using the median point of individual measurements. We tested the δET uncertainty using the mean point [σET (mean)] and median point [σET (median)]. Multiple resolutions of input and output data from six independent sites were used to test the performance of the two methods. The σET (mean) would be greater than σET (median) when the mean value of inverse vapor concentration (1/Cυ¯) is greater than the median value of inverse vapor concentration [1/Cυ(median)]. When applying the filter of r2 > 0.8, around 70% of σET (mean) was greater than σET (median). This phenomenon might be due to the normality of the vapor concentration Cυ producing the asymmetric distribution of 1/Cυ. The median method could perform significantly better than the mean method when inputting high-resolution measurements (e.g., 1 Hz) and when the water vapor concentration Cυ is relatively low. Compared to the mean method, applying the median method could on average reduce 6.88% of ET partitioning uncertainties and could on average reduce 9.00% of moisture recycling uncertainties. This study provided a new insight of the Keeling plot method and emphasized handling model output uncertainty from multiple perspectives instead of only from input parameters.

© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding authors: Yusen Yuan, yuseny@nmsu.edu; Taisheng Du, dutaisheng@cau.edu

Abstract

The isotopic composition of evapotranspiration δET is a crucial parameter in isotope-based evapotranspiration (ET) partitioning and moisture recycling studies. The Keeling plot method is the most prevalent method to calculate δET, though it contains large extrapolated uncertainties from the least squares regression. Traditional Keeling regression uses the mean point of individual measurements. Here, a modified Keeling plot framework was proposed using the median point of individual measurements. We tested the δET uncertainty using the mean point [σET (mean)] and median point [σET (median)]. Multiple resolutions of input and output data from six independent sites were used to test the performance of the two methods. The σET (mean) would be greater than σET (median) when the mean value of inverse vapor concentration (1/Cυ¯) is greater than the median value of inverse vapor concentration [1/Cυ(median)]. When applying the filter of r2 > 0.8, around 70% of σET (mean) was greater than σET (median). This phenomenon might be due to the normality of the vapor concentration Cυ producing the asymmetric distribution of 1/Cυ. The median method could perform significantly better than the mean method when inputting high-resolution measurements (e.g., 1 Hz) and when the water vapor concentration Cυ is relatively low. Compared to the mean method, applying the median method could on average reduce 6.88% of ET partitioning uncertainties and could on average reduce 9.00% of moisture recycling uncertainties. This study provided a new insight of the Keeling plot method and emphasized handling model output uncertainty from multiple perspectives instead of only from input parameters.

© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding authors: Yusen Yuan, yuseny@nmsu.edu; Taisheng Du, dutaisheng@cau.edu
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