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Does measuring azimuthal variations in sap flux lead to more reliable stand transpiration estimates?
Author(s) -
Komatsu Hikaru,
Shinohara Yoshinori,
Kume Tomonori,
Tsuruta Kenji,
Otsuki Kyoichi
Publication year - 2016
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/hyp.10780
Subject(s) - azimuth , transpiration , cryptomeria , flux (metallurgy) , tree (set theory) , function (biology) , variation (astronomy) , physics , environmental science , statistics , geodesy , geology , mathematics , japonica , geometry , mathematical analysis , astrophysics , botany , photosynthesis , materials science , evolutionary biology , metallurgy , biology
Stand transpiration ( E ) estimated using the sap‐flux method includes uncertainty induced by variations in sap flux ( F ) within a tree (i.e. radial and azimuthal variations) and those between trees. Unlike radial variations, azimuthal variations are not particularly systematic (i.e. higher/lower F is not always recorded for a specific direction). Here, we present a theoretical framework to address the question on how to allocate a limited number of sensors to minimize uncertainty in E estimates. Specifically, we compare uncertainty in E estimates for two cases: (1) measuring F for two or more directions to cover azimuthal variations in F and (2) measuring F for one direction to cover between‐tree variations in F . The framework formulates the variation in the probability density function for E ( σ E ) based on F recorded in m different azimuthal directions (e.g. north, east, south and west). This formula allows us to determine the m value that minimizes σ E . This study applied the framework to F data recorded for a 55‐year‐old Cryptomeria japonica stand. σ E for m = 1 was found to be less than the values for m = 2, 3 and 4. Our results suggest that measuring F for one azimuthal direction provides more reliable E estimates than measuring F for two or more azimuthal directions for this stand, given a limited number of sensors. Application of this framework to other datasets helps us decide how to allocate sensors most effectively. Copyright © 2016 John Wiley & Sons, Ltd.