Assessing Crop Coefficients for Natural Vegetated Areas Using Satellite Data and Eddy Covariance Stations

Corbari, Chiara; Ravazzani, Giovanni; Galvagno, Marta; Cremonese, Edoardo; Mancini, Marco

doi:10.3390/s17112664

Cited by 21 publications

(17 citation statements)

References 49 publications

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“…This indicates that the accuracy of the crop coefficient method will be considerably lower than that of shown (Figure 9), in line with several studies (Corbari et al, 2017;de Araújo et al, 2017;Odhiambo & Irmak, 2012 Yan and Shugart (2010), which relates RH and potential ET to actual ET. In parallel with their work, decades of research has been devoted to validate the Bouchet's CR hypothesis since the CR is proven to be valid on any timescale such as half-hourly (Zhu et al, 2016), daily (Kim et al, 2019), 8-day (Yan & Shugart, 2010), or annually (Brutsaert et al, 2020).…”

Section: Arem Versus the Crop Coefficient Methodssupporting

confidence: 86%

“…This indicates that the accuracy of the crop coefficient method will be considerably lower than that of shown (Figure 9), in line with several studies (Corbari et al, 2017;de Araújo et al, 2017;Odhiambo & Irmak, 2012 (Zhu et al, 2016), daily (Kim et al, 2019), 8-day (Yan & Shugart, 2010), or annually (Brutsaert et al, 2020). This will put forward the assumption that there must be a physical meaning behind the interactions found in this study; thus, an attempt for its understanding as a future work is strongly encouraged.…”

Section: Arem Versus the Crop Coefficient Methodssupporting

confidence: 83%

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A meteorological‐based crop coefficient model for estimation of daily evapotranspiration

Varmaghani

Eichinger

Prueger

2021

Hydrological Processes

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Estimation of daily evapotranspiration (ET) over cloudy regions highly desires models which rely on meteorological data only. Notwithstanding, the conventional crop coefficient (K c) method requires detailed knowledge of geo/biophysical properties of the coupled land-vegetation system, precipitation, and soil moisture. Six Eddy Covariance (EC) towers in Iowa, California and New Hampshire of the USA (covering corn, soybeans, prairie, and deciduous forest) were selected. Investigation on 6 years (2007-2012) 15-min micrometeorological records of these sites revealed that there is an indubitable strong interaction between relative humidity (RH), reference ET (ET o), and actual ET at different timescales. This allowed to bypass the need for the non-meteorological inputs and express K c as a second-order polynomial function of RH and ET o , the ambient regression evapotranspiration model (AREM). The coefficients of the empirical function are crop-specific and may require calibration over different soil types. The mean absolute percentage error (MAPE) of the regression against daily EC observations was 17% during the growing season, and 32% throughout the year with root mean square error (RMSE) of 0.74 mm day −1 and coefficient of determination of 0.71. The model was fully operational (MAPE of 34% and RMSE of 0.82 mm day −1) over the four Iowan sites based on inputs from local weather stations and NLDAS-2 forcing data of NASA. AREM was capable of capturing the dynamics of ET at 15-min and daily timescales irrespective of varying complexities associated with biophysical, geophysical and climatological states.

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Section: Arem Versus the Crop Coefficient Methodssupporting

confidence: 86%

“…This indicates that the accuracy of the crop coefficient method will be considerably lower than that of shown (Figure 9), in line with several studies (Corbari et al, 2017;de Araújo et al, 2017;Odhiambo & Irmak, 2012 (Zhu et al, 2016), daily (Kim et al, 2019), 8-day (Yan & Shugart, 2010), or annually (Brutsaert et al, 2020). This will put forward the assumption that there must be a physical meaning behind the interactions found in this study; thus, an attempt for its understanding as a future work is strongly encouraged.…”

Section: Arem Versus the Crop Coefficient Methodssupporting

confidence: 83%

A meteorological‐based crop coefficient model for estimation of daily evapotranspiration

Varmaghani

Eichinger

Prueger

2021

Hydrological Processes

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“…K c is defined as the ratio between the actual evapotranspiration from a crop field and the environmental evaporative demand [3]. One of K c estimation's most reliable sources is vegetation indices (VIs) derived from optical remote sensing [5][6][7][8][9][10][11][12][13][14]. Until recently, this method's application was hampered by the insufficient amount of public domain imagery at a high revisit time with fine spatial resolution.…”

Section: Introductionmentioning

confidence: 99%

Estimating Processing Tomato Water Consumption, Leaf Area Index, and Height Using Sentinel-2 and VENµS Imagery

et al. 2021

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Crop monitoring throughout the growing season is key for optimized agricultural production. Satellite remote sensing is a useful tool for estimating crop variables, yet continuous high spatial resolution earth observations are often interrupted by clouds. This paper demonstrates overcoming this limitation by combining observations from two public-domain spaceborne optical sensors. Ground measurements were conducted in the Hula Valley, Israel, over four growing seasons to monitor the development of processing tomato. These measurements included continuous water consumption measurements using an eddy-covariance tower from which the crop coefficient (Kc) was calculated and measurements of Leaf Area Index (LAI) and crop height. Satellite imagery acquired by Sentinel-2 and VENµS was used to derive vegetation indices and model Kc, LAI, and crop height. The conjoint use of Sentinel-2 and VENµS imagery facilitated accurate estimation of Kc (R2 = 0.82, RMSE = 0.09), LAI (R2 = 0.79, RMSE = 1.2), and crop height (R2 = 0.81, RMSE = 7 cm). Additionally, our empirical models for LAI estimation were found to perform better than the SNAP biophysical processor (R2 = 0.53, RMSE = 2.3). Accordingly, Sentinel-2 and VENµS imagery was demonstrated to be a viable tool for agricultural monitoring.

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“…Crop coefficients for grasses, pines, and beeches were derived from a critical review of the available literature [9,22]. e results of this operation are summarized in Table 2.…”

Section: Data Usedmentioning

confidence: 99%

A Semiempirical Method to Estimate Actual Evapotranspiration in Mediterranean Environments

Chiesi

Battista

Fibbi

et al. 2018

Advances in Meteorology

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Actual evapotranspiration (ET A ) is a major term of site water balance whose knowledge is essential for numerous purposes. e classical ET A estimation approach based on the use of multitemporal crop coefficients (Kc) cannot be applied in water-limited environments without proper correction. Such correction can be theoretically obtained by means of soil water content (SWC) measurements, which, however, are affected by several drawbacks, due to both their technical and operational characteristics. e current paper proposes a method to normalize annual SWC datasets and integrate them in an ET A estimation procedure suitable for monitoring both agricultural and natural Mediterranean ecosystems. Differently from previous approaches, the SWC normalization is obtained using data-specific information, which renders the new method mostly insensitive to the mentioned problems. e method is first described and then applied in three case studies representative of different Mediterranean ecosystems (i.e., grassland, coniferous, and deciduous forests). e results are evaluated versus latent heat measurements taken by eddy covariance flux towers. Satisfactory accuracy is obtained in all three case studies, with advantages and limitations which are discussed in the final concluding sections.

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Assessing Crop Coefficients for Natural Vegetated Areas Using Satellite Data and Eddy Covariance Stations

Cited by 21 publications

References 49 publications

A meteorological‐based crop coefficient model for estimation of daily evapotranspiration

A meteorological‐based crop coefficient model for estimation of daily evapotranspiration

Estimating Processing Tomato Water Consumption, Leaf Area Index, and Height Using Sentinel-2 and VENµS Imagery

A Semiempirical Method to Estimate Actual Evapotranspiration in Mediterranean Environments

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