Satellite retrievals of leaf chlorophyll and photosynthetic capacity for improved modeling of GPP

Handle URI:
http://hdl.handle.net/10754/575698
Title:
Satellite retrievals of leaf chlorophyll and photosynthetic capacity for improved modeling of GPP
Authors:
Houborg, Rasmus; Cescatti, Alessandro; Migliavacca, Mirco; Kustas, W.P.
Abstract:
This study investigates the utility of in situ and satellite-based leaf chlorophyll (Chl) estimates for quantifying leaf photosynthetic capacity and for constraining model simulations of Gross Primary Productivity (GPP) over a corn field in Maryland, U.S.A. The maximum rate of carboxylation (V-max) represents a key control on leaf photosynthesis within the widely employed C-3 and C-4 photosynthesis models proposed by Farquhar et al. (1980) and Collatz et al. (1992), respectively. A semi-mechanistic relationship between V-max(5) (V-max normalized to 25 degrees C) and Chl is derived based on interlinkages between V-max(25), Rubisco enzyme kinetics, leaf nitrogen, and Chl reported in the experimental literature. The resulting linear V-max(25) - Chl relationship is embedded within the photosynthesis scheme of the Community Land Model (CLM), thereby bypassing the use of fixed plant functional type (PFT) specific V-max(25) values. The effect of the updated parameterization on simulated carbon fluxes is tested over a corn field growing season using: (1) a detailed Chl time-series established on the basis of intensive field measurements and (2) Chl estimates derived from Landsat imagery using the REGularized canopy reFLECtance (REGFLEC) tool. Validations against flux tower observations demonstrate benefit of using Chl to parameterize V-max(25) to account for variations in nitrogen availability imposed by severe environmental conditions. The use of V-max(25) that varied seasonally as a function of satellite-based Chl, rather than a fixed PFT-specific value, significantly improved the agreement with observed tower fluxes with Pearson's correlation coefficient (r) increasing from 0.88 to 0.93 and the root-mean-square-deviation decreasing from 4.77 to 3.48 mu mol m(-2) s(-1). The results support the use of Chl as a proxy for photosynthetic capacity using generalized relationships between V-max(25) and Chl, and advocate the potential of satellite retrieved Chl for constraining simulations of GPP in space and time. (C) 2013 Elsevier B.V. All rights reserved.
KAUST Department:
Water Desalination and Reuse Research Center
Publisher:
Elsevier BV
Journal:
Agricultural and Forest Meteorology
Issue Date:
Aug-2013
DOI:
10.1016/j.agrformet.2013.04.006
Type:
Article
ISSN:
0168-1923
Sponsors:
This research was supported by the European Union project FP7-ECLAIRE (282910). The authors would like to thank the logistical support in operating and maintaining the OPE3 site as well as data collection and archiving efforts of Dr. Timothy Gish of the USDA-ARS Hydrology and Remote Sensing Lab. The micrometeorological tower data were made available through the efforts of remote sensing specialist Mr. Andrew Russ of the Hydrology and Remote Sensing Laboratory and Dr. John Prueger from the USDA-ARS National Laboratory for Agriculture and the Environment in Ames Iowa.
Appears in Collections:
Articles; Water Desalination and Reuse Research Center (WDRC)

Full metadata record

DC FieldValue Language
dc.contributor.authorHouborg, Rasmusen
dc.contributor.authorCescatti, Alessandroen
dc.contributor.authorMigliavacca, Mircoen
dc.contributor.authorKustas, W.P.en
dc.date.accessioned2015-08-24T08:36:04Zen
dc.date.available2015-08-24T08:36:04Zen
dc.date.issued2013-08en
dc.identifier.issn0168-1923en
dc.identifier.doi10.1016/j.agrformet.2013.04.006en
dc.identifier.urihttp://hdl.handle.net/10754/575698en
dc.description.abstractThis study investigates the utility of in situ and satellite-based leaf chlorophyll (Chl) estimates for quantifying leaf photosynthetic capacity and for constraining model simulations of Gross Primary Productivity (GPP) over a corn field in Maryland, U.S.A. The maximum rate of carboxylation (V-max) represents a key control on leaf photosynthesis within the widely employed C-3 and C-4 photosynthesis models proposed by Farquhar et al. (1980) and Collatz et al. (1992), respectively. A semi-mechanistic relationship between V-max(5) (V-max normalized to 25 degrees C) and Chl is derived based on interlinkages between V-max(25), Rubisco enzyme kinetics, leaf nitrogen, and Chl reported in the experimental literature. The resulting linear V-max(25) - Chl relationship is embedded within the photosynthesis scheme of the Community Land Model (CLM), thereby bypassing the use of fixed plant functional type (PFT) specific V-max(25) values. The effect of the updated parameterization on simulated carbon fluxes is tested over a corn field growing season using: (1) a detailed Chl time-series established on the basis of intensive field measurements and (2) Chl estimates derived from Landsat imagery using the REGularized canopy reFLECtance (REGFLEC) tool. Validations against flux tower observations demonstrate benefit of using Chl to parameterize V-max(25) to account for variations in nitrogen availability imposed by severe environmental conditions. The use of V-max(25) that varied seasonally as a function of satellite-based Chl, rather than a fixed PFT-specific value, significantly improved the agreement with observed tower fluxes with Pearson's correlation coefficient (r) increasing from 0.88 to 0.93 and the root-mean-square-deviation decreasing from 4.77 to 3.48 mu mol m(-2) s(-1). The results support the use of Chl as a proxy for photosynthetic capacity using generalized relationships between V-max(25) and Chl, and advocate the potential of satellite retrieved Chl for constraining simulations of GPP in space and time. (C) 2013 Elsevier B.V. All rights reserved.en
dc.description.sponsorshipThis research was supported by the European Union project FP7-ECLAIRE (282910). The authors would like to thank the logistical support in operating and maintaining the OPE3 site as well as data collection and archiving efforts of Dr. Timothy Gish of the USDA-ARS Hydrology and Remote Sensing Lab. The micrometeorological tower data were made available through the efforts of remote sensing specialist Mr. Andrew Russ of the Hydrology and Remote Sensing Laboratory and Dr. John Prueger from the USDA-ARS National Laboratory for Agriculture and the Environment in Ames Iowa.en
dc.publisherElsevier BVen
dc.titleSatellite retrievals of leaf chlorophyll and photosynthetic capacity for improved modeling of GPPen
dc.typeArticleen
dc.contributor.departmentWater Desalination and Reuse Research Centeren
dc.identifier.journalAgricultural and Forest Meteorologyen
dc.contributor.institutionARS, USDA, Hydrol & Remote Sensing Lab, Beltsville, MD USAen
dc.contributor.institutionCommiss European Communities, JRC, Inst Environm & Sustainabil, Ispra, Italyen
kaust.authorHouborg, Rasmusen
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