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

Author:
Alam, Muhammad Shahinur, Lamb, David W., Rahman, Muhammad Moshiur
Source:
Computers and electronics in agriculture 2018 v.147 pp. 12-17
ISSN:
0168-1699
Subject:
Festuca arundinacea, biomass production, canopy, crop coefficient, evapotranspiration, growing season, irrigation management, land cover, normalized difference vegetation index, pastures, photosynthesis, reflectance, regression analysis, water vapor
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 m2), in real time and repeatability.
Agid:
5896111