Quantifying water stress effect on daily light use efficiency in Mediterranean ecosystems using satellite data

Sergio Sanchez-Ruiz, Alvaro Moreno, Maria Piles, Fabio Maselli, Arnaud Carrara, Steven Running, Maria Amparo Gilabert

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


The capacity of six water stress factors (ε′i) to track daily light use efficiency (ε) of water-limited ecosystems was evaluated. These factors are computed with remote sensing operational products and a limited amount of ground data: ε′1 uses ground precipitation and air temperature, and satellite incoming global solar radiation; ε′2 uses ground air temperature, and satellite actual evapotranspiration and incoming global solar radiation; ε′3 uses satellite actual and potential evapotranspiration; ε′4 uses satellite soil moisture; ε′5 uses satellite-derived photochemical reflectance index; and ε′6 uses ground vapor pressure deficit. These factors were implemented in a production efficiency model based on Monteith’s approach in order to assess their performance for modeling gross primary production (GPP). Estimated GPP was compared to reference GPP from eddy covariance (EC) measurements (GPPEC) in three sites placed in the Iberian Peninsula (two open shrublands and one savanna). ε′i were correlated to ε, which was calculated by dividing GPPEC by ground measured photosynthetically active radiation (PAR) and satellite-derived fraction of absorbed PAR. Best results were achieved by ε′1, ε′2, ε′3 and ε′4 explaining around 40% and 50% of ε variance in open shurblands and savanna, respectively. In terms of GPP, R2 ≈ 0.70 were obtained in these cases.

Original languageEnglish
Pages (from-to)623-638
Number of pages16
JournalInternational Journal of Digital Earth
Issue number6
StatePublished - Jun 3 2017


  • GPP
  • Light use efficiency
  • Mediterranean ecosystems
  • Monteith
  • water stress


Dive into the research topics of 'Quantifying water stress effect on daily light use efficiency in Mediterranean ecosystems using satellite data'. Together they form a unique fingerprint.

Cite this