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An intercomparison of radiation partitioning models in vineyard canopies

  • C. K. Parry
  • H. Nieto
  • P. Guillevic
  • N. Agam
  • W. P. Kustas
  • J. Alfieri
  • L. McKee
  • A. J. McElroneEmail author
OriginalPaper
  • 9 Downloads

Abstract

Multiple radiation transfer models with unique clumping indices (a total of five approaches) were evaluated on two Pinot Noir vineyards in Central California over 3 years. In the first approach, a basic clumping index meant for heterogeneous randomly placed clumped canopies was combined with the Campbell and Norman transfer model (C&N–H). The other four approaches, namely, the Campbell and Norman with rectangular hedgerow clumping index (C&N–R), Campbell and Norman with a geometric elliptical hedgerow model (C&N–E), the 4-stream scattering by arbitrary inclined leaves model (4SAIL) with row-crop clumping index, and the discrete anisotropic radiative transfer (DART) models, account for the unique canopy coverage distribution of the vineyard row-structured canopies. Each modeling approach varied in its complexity to predict transmitted solar radiation at ground level and the outputs were compared to solar radiation observed at the surface with an array of pyranometers. All five modeling approaches showed good agreement with the observed values [correlation coefficients (r) ranged from 0.95 to 0.97]. Model performance varied throughout the season due to their sensitivity to canopy growth. Although r values showed good agreement among all approaches, the C&N–E and DART models showed a better “goodness of fit” with lower root mean squared and bias values.

Notes

Funding

Funding was provided by USDA-ARS CRIS projects.

Supplementary material

271_2019_621_MOESM1_ESM.tif (369 kb)
Supplemental Fig. 1. Image of the placement of sensor placement for transmitted solar radiation measurements. (TIF 368 KB)

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Copyright information

©  This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply. 2019

Authors and Affiliations

  1. 1.USDA-ARS Crops Pathology and Genetics Research UnitDavisUSA
  2. 2.Efficient Use of Water in Agriculture ProgramInstitut de Recerca i Tecnologia Agroalimentàries (IRTA)LleidaSpain
  3. 3.Department of Geographical SciencesUniversity of Maryland, Terrestrial Information Systems Laboratory, NASA Goddard Space Flight CenterGreenbeltUSA
  4. 4.Blaustein Institutes for Desert ResearchBen-Gurion University of the NegevBeershebaIsrael
  5. 5.USDA ARS, Hydrology and Remote Sensing LaboratoryBeltsvilleUSA
  6. 6.Department of Viticulture and EnologyUniversity of CaliforniaDavisUSA

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