Monitoring evapotranspiration of irrigated crops using crop coefficients derived from time series of satellite images. I. Method validation

Mateos, Luciano; González‐Dugo, M. P.; Testi, Luca; Villalobos, Francisco J.

doi:10.1016/j.agwat.2012.11.005

Cited by 89 publications

(89 citation statements)

References 38 publications

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“…These models estimate crop ET by subtracting the soil heat flux (G) and sensible heat flux (H) from the net radiation (Rn) at the surface. Such models allow to directly integrating the effects related with soil water deficit or water vapor pressure in the crop ET estimation [7]. Crop coefficients can be further derived considering the ETo [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

“…Crop coefficients can be further derived considering the ETo [8][9][10]. However, these models present greater complexity and larger amount of input data than the Kc-ETo approach [7]. The Kc-ETo approach is commonly accepted for operational and research objectives [11].…”

Section: Introductionmentioning

confidence: 99%

“…Choudhury et al [25] refer that using SAVI instead of NDVI allows extending the range over which the VI respond to the increase in vegetation amount/density beyond a LAI around 3, which is related with NDVI saturation problems for high LAI values. In addition, the NDVI is considered more sensitive than SAVI to soil background reflectance changes due to the moisture of soil surface [7,13,26].…”

Section: Introductionmentioning

confidence: 99%

“…Some examples of this approach consider a linear relationship between Kcb and NDVI [13,20,25,27,28], and between Kcb and SAVI [13,25,26] but an exponential relationship between NDVI and Kc was also considered [29]. A few studies report a Kcb estimation based on fc or LAI obtained through VI, including for field and tree crops [7,30,31]. However, in most studies, the relationship between Kcb and VI was established for non-stressed conditions and for conditions of dry soil surface, which often do not represent the actual conditions of crop management.…”

Section: Introductionmentioning

confidence: 99%

“…However, in most studies, the relationship between Kcb and VI was established for non-stressed conditions and for conditions of dry soil surface, which often do not represent the actual conditions of crop management. VI derived crop coefficients often do not account for the reduction in Kcb due to water or salinity stress [7,11]. Then the above referred stress coefficient Ks should be considered to obtain an actual Kc or Kcb, i.e., Kc act and Kcb act [1].…”

Section: Introductionmentioning

confidence: 99%

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Estimation of Actual Crop Coefficients Using Remotely Sensed Vegetation Indices and Soil Water Balance Modelled Data

et al. 2015

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Abstract:A new procedure is proposed for estimating actual basal crop coefficients from vegetation indices (Kcb VI) considering a density coefficient (Kd) and a crop coefficient for bare soil. Kd is computed using the fraction of ground cover by vegetation (fc VI), which is also estimated from vegetation indices derived from remote sensing. A combined approach for estimating actual crop coefficients from vegetation indices (Kc VI) is also proposed by integrating the Kcb VI with the soil evaporation coefficient (Ke) derived from the soil water balance model SIMDualKc. Results for maize, barley and an olive orchard have shown that the approaches for estimating both fc VI and Kcb VI compared well with results obtained using the SIMDualKc model after calibration with ground observation data. For the crops studied, the correlation coefficients relative to comparing the actual Kcb VI and Kc VI with actual Kcb and Kc obtained with SIMDualKc were larger than 0.73 and 0.71, respectively. The corresponding regression coefficients were close to 1.0. The methodology herein presented and discussed allowed for obtaining information for the whole crop season, including periods when vegetation cover is incomplete, as the initial and development stages. Results show that the proposed methods are adequate for supporting irrigation management. OPEN ACCESSRemote Sens. 2015, 7 2374

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Estimation of Actual Crop Coefficients Using Remotely Sensed Vegetation Indices and Soil Water Balance Modelled Data

et al. 2015

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Crop Evapotranspiration

Todorović¹

2019

Encyclopedia of Water

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Evapotranspiration is a process referring to water transfer from the land to the atmosphere by evaporation, from the soil surface, and by transpiration, through the vegetation. It is a complex process of great relevance for the hydrological balance at different scales. Nevertheless, it is difficult to measure and estimate; hence, almost all evapotranspiration data contains errors. The main biophysical principles of evapotranspiration are described together with the most relevant methods for measurement and estimation. Particular attention is given to crop evapotranspiration used in irrigation scheduling and agricultural water management. The estimation of crop evapotranspiration is presented following the two‐step approach based on crop coefficient and reference evapotranspiration. The concept of reference evapotranspiration is expounded by means of the Penman–Monteith approach that combines surface energy balance and aerodynamic principles of the process. The indicative data of crop coefficient and length of crop growing stages are reported in tables for most relevant agricultural crops and the world growing regions. A detailed description of calculation procedures for the estimation of reference and crop evapotranspiration is presented together with the methods to improve crop coefficient estimate under specific growing conditions. Finally, numerical examples of reference and crop evapotranspiration are given in Appendix 1.

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Crop Water Requirements and Irrigation Scheduling

Todorović¹

2019

Encyclopedia of Water

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Crop water requirements represent the amount of water to be supplied to a field to recover the losses occurred by evaporation and transpiration. Crop water requirements are used for (i) a day‐to‐day on‐field irrigation scheduling, (ii) determination of seasonal water needs of an existing irrigation scheme (i.e. seasonal irrigation planning), and (iii) estimation of water volumes to be supplied to newly irrigated areas (i.e. during the irrigation project design and definition of irrigation network hydraulic characteristics). Irrigation scheduling is a process used by irrigation managers to determine the correct frequency and duration of watering, i.e. when to irrigate and how much water to apply. It is usually focusing on a specific crop cultivated in an area with homogeneous (representative) weather, soil, and irrigation system characteristics. Irrigation scheduling aims to optimize use of water, nutrient, and energy, while achieving the maximum economic benefits of agricultural production, reducing environmental impacts, and ensuring the provision of ecosystem services. The soil–water‐balance method for irrigation scheduling is described together with a practical example of irrigation scheduling strategy. Moreover, the application of innovative technological solutions that integrate field data, sensors, and models in smartphone Apps for control and automation of irrigation process is illustrated.

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Monitoring evapotranspiration of irrigated crops using crop coefficients derived from time series of satellite images. I. Method validation

Cited by 89 publications

References 38 publications

Estimation of Actual Crop Coefficients Using Remotely Sensed Vegetation Indices and Soil Water Balance Modelled Data

Estimation of Actual Crop Coefficients Using Remotely Sensed Vegetation Indices and Soil Water Balance Modelled Data

Crop Evapotranspiration

Crop Water Requirements and Irrigation Scheduling

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