Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloUpscaling instantaneous to daily evapotranspiration using modelled daily shortwave radiation for remote sensing applications: an Artificial Neural Network approach
Anno di pubblicazione2016
Autore/iL. Wandera, K. Mallick, G. Kiely, O. Roupsard, M. Peichl, and V. Magliulo
Affiliazioni autoricnr isafom Luxembourg Institute of Science and Technology, Belvaux, Luxembourg
Autori CNR e affiliazioni
  • inglese
AbstractAbstract. Upscaling instantaneous evapotranspiration retrieved at any specific time-of-daytime (ETi) to daily evapotranspiration (ETd) is a key challenge in regional scale vegetation water use mapping using polar orbiting sensors. Various studies have unanimously cited the short wave incoming radiation (RS) to be the most robust reference variable explaining the ratio between ETd and ETi on the terrestrial surfaces. This study aims to contribute in ETi upscaling for global studies using the ratio between daily and instantaneous incoming short wave radiation (RSd/RSi) as a factor for converting ETi to ETd. The approach relies on the availability of RSd measurements that in many cases is hindered if not by cost but due to the environmental conditions such as cloudiness. This paper proposes an artificial neural network (ANN) machine learning algorithm first to predict RSd from RSi followed by using the RSd/RSi ratio to convert ETi to ETd across different terrestrial ecosystem. Using RSi and RSd observations from multiple subnetworks of FLUXNET database spread across different climates and biomes (to represent inputs that would typically be obtainable from remote sensors during the overpass time) in conjunction with some astronomical variables (derived from simple mathematical computation), we developed ANN model for reproducing RSd and further used it to upscale ETi to ETd. The efficiency of the ANN is evaluated for different morning and afternoon time-of-daytime, under varying sky conditions, and also at different geographic locations. Based on the measurements from 126 sites, we found RS-based upscaled ETd to produce a significant linear relation (R2 = 0.65 to 0.69), low bias (-0.31 to -0.56 MJ m-2 d-1) (appx. 4 %), and good agreement (RMSE 1.55 to 1.86 MJ m-2 d-1) (appx. 10 %) with the observed ETd, although a systematic overestimation of ETd was also noted under persistent cloudy sky conditions. An intercomparison with existing upscaling method at daily, 8-day, monthly, and yearly temporal resolution revealed a robust performance of the ANN driven RS method and was found to produce lowest RMSE under cloudy conditions. The overall methodology appears to be promising and has substantial potential for upscaling ETi to ETd for field and regional scale evapotranspiration mapping studies using polar orbiting satellites.
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RivistaHydrology and earth system sciences
Attiva dal 1997
Editore: Copernicus Publ. - Göttingen
Paese di pubblicazione: Germania
Lingua: inglese
ISSN: 1027-5606
Titolo chiave: Hydrology and earth system sciences
Titolo proprio: Hydrology and earth system sciences.
Titolo abbreviato: Hydrol. earth syst. sci.
Titoli alternativi:
  • HESS (Göttingen. Print)
  • Hydrology and earth system sciences (Print)
Numero volume della rivista-
Fascicolo della rivista-
Verificato da refereeSì: Internazionale
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)-
Parole chiaveevapotranspiration; remote sensing; neural networks
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Note/Altre informazionimanuscript hess-2016-344 submitted July 11, 2016
Strutture CNR
  • ISAFoM — Istituto per i sistemi agricoli e forestali del mediterraneo
Moduli/Attività/Sottoprogetti CNR
  • TA.P02.017.001 : Scambi di gas serra delle comunità vegetali a scala locale e territoriale
Progetti Europei
wandera ann HESS
Tipo documento: application/pdf