Publications

Nguyen, NM; Choi, M (2023). Evapotranspiration partitioning and agricultural drought quantification with an optical trapezoidal framework. AGRICULTURAL AND FOREST METEOROLOGY, 338, 109520.

Abstract
The Optical Trapezoidal method is a recently proposed method using solely optical remote sensing data with promising potential in hydroclimatic applications; however, its application in evapotranspiration (ET) parti-tioning is still questionable. This study therefore improved an Optical Trapezoidal-based Evaporative Fraction (OPTREF) model reliant on the physical association between soil surface properties and shortwave infrared transformed reflectance (STR). The proposed model was parameterized using trapezoidal shapes formed by STR and Normalized Difference Vegetation Index (NDVI) retrieved from Sentinel-2 to compute contribution of transpiration to ET (T/ET) in the Central Valley region of California, United States. Results indicated that the OPTREF model efficiently captured regional plant characteristics and seasonal variation of T/ET for three typical land cover types in study region (cropland, grassland, and savanna), particularly T/ET discrepancies rising from alternative cropping systems in cropland. Importantly, predicted T/ET values were in good agreement with previous modelling and empirical reports; for example, T/ET ranges in [0.37-0.75] for cropland, [0.30-0.82] for grassland, and [0.39-0.77] for savanna. In addition, applicability of the OPTREF approach was investigated in tracking agricultural drought using evaporative drought index (EDI), together with analysis of physiological response of T/ET to drought. The OPTREF-based EDI consistently reflected the same drought patterns indicated by records of vegetation health index and drought area percentages data from NOAA. Also, our findings un-covered that under extreme drought, the T/ET ratio is likely to increase and might be approximately equal to 1.0 in areas covered by drought-tolerant plants. Overall, this OPTREF approach offers novelty, simplicity, and versatility to satellite-based remote sensing of ET partitioning and identifying agricultural drought, especially in the context of rapid climate variation.

DOI:
10.1016/j.agrformet.2023.109520

ISSN:
1873-2240