Evaluation of a Method for Estimating Irrigated Crop-Evapotranspiration Coefficients from Remotely Sensed Data in Idaho

Rafn, Eric; Contor, Bryce A.; Ames, Daniel P.

doi:10.1061/(asce)0733-9437(2008)134:6(722)

Cited by 40 publications

(24 citation statements)

References 11 publications

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“…Those linear regressions were similar to the linear equations of corn reported by other researchers; for example, in [20,[53][54][55], all these authors used alfalfa-reference crop coefficient and NDVI values for generating linear regression equations.…”

Section: Relationship Between Ndvi Andsupporting

confidence: 77%

“…The ET c maps created in this study are in agreement with other researchers; for example, in [2,4,58,59], they generated ET c maps using c derived from remote sensing-based vegetation indices. Other researchers reported that c derived from canopy reflectance based vegetation index had the potential to estimate crop evapotranspiration at regional and field scales, for example, in [17,18,29,55,60,61].…”

Section: 3mentioning

confidence: 99%

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Estimation of Crop Evapotranspiration Using Satellite Remote Sensing-Based Vegetation Index

Reyes-González

Kjaersgaard

Trooien

et al. 2018

Advances in Meteorology

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Irrigation water is limited and scarce in many areas of the world, including Comarca Lagunera, Mexico. Thus better estimations of irrigation water requirements are essential to conserve water. The general objective was to estimate crop water demands or crop evapotranspiration (ET c ) at different scales using satellite remote sensing-based vegetation index. The study was carried out in northern Mexico (Comarca Lagunera) during four growing seasons. Six, eleven, three, and seven clear Landsat images were acquired for 2013, 2014, 2015, and 2016, respectively, for the analysis. The results showed that ET c was low at initial and early development stages, while ET c was high during mid-season and harvest stages. These results are not new but give us confidence in the rest of our ET c results. Daily ET c maps helped to explain the variability of crop water use during the growing season. Based on the results we can conclude that ET c maps developed from remotely sensed multispectral vegetation indices are a useful tool for quantifying crop water consumption at regional and field scales. Using ET c maps at the field scale, farmers can supply appropriate amounts of irrigation water corresponding to each growth stage, leading to water conservation.

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Section: Relationship Between Ndvi Andsupporting

confidence: 77%

Section: 3mentioning

confidence: 99%

Estimation of Crop Evapotranspiration Using Satellite Remote Sensing-Based Vegetation Index

Reyes-González

Kjaersgaard

Trooien

et al. 2018

Advances in Meteorology

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show abstract

“…Extra information is required as well to account for soil surface evaporation resulting from irrigation operations or precipitation. Yet, compared with direct ETa estimation procedures that involve energy balance remote sensing [31], vegetation index methods are more approachable and can be less costly to implement [32]. Further, by avoiding the need for thermal imagery, vegetation index methods can potentially exploit viewing opportunities offered by a larger variety of satellite and airborne imaging systems [33] and can generate output at higher spatial resolution for use on smaller fields.…”

Section: Discussionmentioning

confidence: 99%

Satellite NDVI Assisted Monitoring of Vegetable Crop Evapotranspiration in California’s San Joaquin Valley

2012

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Abstract:Reflective bands of Landsat-5 Thematic Mapper satellite imagery were used to facilitate the estimation of basal crop evapotranspiration (ETcb), or potential crop water use, in San Joaquin Valley fields during 2008. A ground-based digital camera measured green fractional cover (Fc) of 49 commercial fields planted to 18 different crop types (row crops, grains, orchard, vineyard) of varying maturity over 11 Landsat overpass dates. Landsat L1T terrain-corrected images were transformed to surface reflectance and converted to normalized difference vegetation index (NDVI). A strong linear relationship between NDVI and Fc was observed (r 2 = 0.96, RMSE = 0.062). The resulting regression equation was used to estimate Fc for crop cycles of broccoli, bellpepper, head lettuce, and garlic on nominal 7-9 day intervals for several study fields. Prior relationships developed by weighing lysimeter were used to transform Fc to fraction of reference evapotranspiration, also known as basal crop coefficient (Kcb). Measurements of grass reference evapotranspiration from the California Irrigation Management Information System were then used to calculate ETcb for each overpass date. Temporal profiles of Fc, Kcb, and ETcb were thus developed for the study fields, along with estimates of seasonal water use. Daily ETcb retrieval uncertainty resulting from error in satellite-based Fc estimation was <0.5 mm/d, with seasonal uncertainty of 6-10%. Results were compared with FAO-56 irrigation guidelines and prior lysimeter observations for reference. OPEN ACCESSRemote Sens. 2012, 4 440

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“…Crop evapotranspiration (CET) is estimated as CET = PET × K C where K C stands for the crop coefficient. According to Hunsaker et al (2003), Duchemin et al (2006), Rafn et al (2008) and Mutiibwa and Irmak (2013), the crop coefficient is linked with the Normalized Difference Vegetation Index (NDVI) derived from satellite observations (Solano et al, 2010). We can therefore implement it as an appraisal of the crop coefficient time series of the model which was previously obtained through a one-parameter formulation where the parameter was set uniformly to its default value.…”

Section: The Hydrological Mesh Pattern For Sensitive Parameters Derivmentioning

confidence: 99%

Tailor-made spatial patterns for hydrological model parameters combining regionalisation methods

Rouhier

Garavaglia

Lay

et al. 2018

Preprint

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Abstract. Calibration of spatially distributed models is an important issue given their over-parameterisation. Three common regionalisation methods can be distinguished: transposition, prescription and constraint. This paper proposes a strategy where the three methods are combined to provide several spatial patterns depending on the model parameters. On the one hand, insensitive and equifinal parameters are prescribed uniformly while parameters with a physical meaning are prescribed at the mesh scale. On the other hand, parameters linked with a proxy runoff signature are constrained over each sub-basin and the 5 remaining parameters are transposed with a physio-climatic pattern constructed over the calibration sub-basins.The above tailor-made pattern regionalisation is applied over two large French catchments, the Loire catchment at Gien The enhancement appears for the least well-modelled stations and contributes a 20% improvement towards gauged modelling.It also tends to guarantee a minimum performance in an ungauged context since the minimum KGE is now 0.4 whatever runoff signature is used.

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Evaluation of a Method for Estimating Irrigated Crop-Evapotranspiration Coefficients from Remotely Sensed Data in Idaho

Cited by 40 publications

References 11 publications

Estimation of Crop Evapotranspiration Using Satellite Remote Sensing-Based Vegetation Index

Estimation of Crop Evapotranspiration Using Satellite Remote Sensing-Based Vegetation Index

Satellite NDVI Assisted Monitoring of Vegetable Crop Evapotranspiration in California’s San Joaquin Valley

Tailor-made spatial patterns for hydrological model parameters combining regionalisation methods

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