A refined method for rapidly determining the relationship between canopy NDVI and the pasture evapotranspiration coefficient

Abstract The estimation of actual crop evapotranspiration (ETc) from any given land cover or crop type is important for irrigation water management and agricultural water consumption analysis. The main parameter used for such estimations is the crop coefficient (Kc). Spectral reflectance indices, such as the normalized difference vegetation index (NDVI) and the crop coefficient of a specific crop or pasture canopy are important indicators of ‘vigour’, namely the photosynthetic activity and rate of biomass accumulation. Measuring both parameters simultaneously, with a view to understanding how they interact, or for creating optical, surrogate indicators of Kc is very difficult because Kc itself is difficult to measure. In this study a portable enclosed chamber was used to measure ETc of a pasture and subsequently calculated Kc from reference evapotranspiration (ETo) data derived from a nearby automatic weather station (AWS). Calibration of the chamber confirms the suitability of the device to measure the amount of water vapour produced by local plant evapotranspiration, producing a calibration factor (C) close to 1 (C = 1.02, R2 = 0.87). The coincident NDVI values were measured using a portable active optical sensor. In a test involving a pasture (Festuca arundinacea var. Dovey) at two different stages of growth in two consecutive growing seasons, the NDVI and crop coefficients were observed to be strongly correlated (R2 = 0.80 and 0.77, respectively). A polynomial regression (R2 = 0.84) was found to be the best fit for the combined, multi-temporal Kc-NDVI relationship. The main advantages of this method include the suitability of operating at a smaller scale (

[1]  H. Daniel,et al.  Evaluation of an enclosed portable chamber to measure crop and pasture actual evapotranspiration at small scale , 2004 .

[2]  A. Chehbouni,et al.  Monitoring wheat phenology and irrigation in Central Morocco: On the use of relationships between evapotranspiration, crops coefficients, leaf area index and remotely-sensed vegetation indices , 2006 .

[3]  J. A. Tolk,et al.  ET mapping for agricultural water management: present status and challenges , 2008, Irrigation Science.

[4]  Mark A. Weltz,et al.  Partitioning evapotranspiration in sparsely vegetated rangeland using a portable chamber , 2006 .

[5]  Craig Macfarlane,et al.  Application note: An improved evaporation dome for forest environments , 2012 .

[6]  Daniel P. Ames,et al.  Evaluation of a Method for Estimating Irrigated Crop-Evapotranspiration Coefficients from Remotely Sensed Data in Idaho , 2008 .

[7]  Bhaskar J. Choudhury,et al.  Synergism of multispectral satellite observations for estimating regional land surface evaporation , 1994 .

[8]  D. W. Lamb,et al.  Methodology for measuring fAPAR in crops using a combination of active optical and linear irradiance sensors: a case study in Triticale (X Triticosecale Wittmack) , 2014, Precision Agriculture.

[9]  L. S. Pereira,et al.  Crop evapotranspiration : guidelines for computing crop water requirements , 1998 .

[10]  M. El-Shirbeny,et al.  Assessment of wheat crop coefficient using remote sensing techniques , 2014 .

[11]  Dale F. Heermann,et al.  Development of reflectance-based crop coefficients for corn , 1990 .

[12]  Pamela L. Nagler,et al.  High Spatial Resolution WorldView-2 Imagery for Mapping NDVI and Its Relationship to Temporal Urban Landscape Evapotranspiration Factors , 2014, Remote. Sens..

[13]  W. Bausch,et al.  Crop Coefficients Derived from Reflected Canopy Radiation: A Concept , 1987 .

[14]  James E. Ayars,et al.  Weighing Lysimeters for Developing Crop Coefficients and Efficient Irrigation Practices for Vegetable Crops , 2010 .

[15]  J. Nippert,et al.  Stomatal responses to changes in vapor pressure deficit reflect tissue-specific differences in hydraulic conductance. , 2014, Plant, cell & environment.

[16]  A. Kondoh,et al.  Relationship between satellite‐derived spectral brightness and evapotranspiration from a grassland , 2001 .

[17]  Thomas J. Trout,et al.  Satellite NDVI Assisted Monitoring of Vegetable Crop Evapotranspiration in California's San Joaquin Valley , 2012, Remote. Sens..

[18]  Benoît Duchemin,et al.  Combining FAO-56 model and ground-based remote sensing to estimate water consumptions of wheat crops in a semi-arid region , 2007 .

[19]  Glenn J. Fitzgerald,et al.  COTTON IRRIGATION SCHEDULING USING REMOTELY SENSED AND FAO-56 BASAL CROP COEFFICIENTS , 2005 .

[20]  D. Eamus,et al.  A rate equation model of stomatal responses to vapour pressure deficit and drought , 2002, BMC Ecology.