Evapotranspiration Estimate over an Almond Orchard Using Landsat Satellite Observations

Ruyan He,Blake Sanden,Maziar Kandelous,Daniele Zaccaria,Jan Hopmans,Jinbao Jiang,Richard Snyder,Yufang Jin

doi:10.3390/rs9050436

Abstract

California growers face challenges with water shortages and there is a strong need to use the least amount of water while optimizing yield. Timely information on evapotranspiration (ET), a dominant component of crop consumptive water use, is critical for growers to tailor irrigation management based on in-field spatial variability and in-season variations. We evaluated the performance of a remote sensing-based approach, Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC), in mapping ET over an almond orchard in California, driven by Landsat satellite observations. Reference ET from a network of weather stations over well-watered grass (ETo) was used for the internal calibration and for deriving ET at daily and extended time period, instead of alfalfa based reference evapotranspiration (ETr). Our study showed that METRIC daily ET estimates during Landsat overpass dates agreed well with the field measurements. During 2009–2012, a root mean square error (RMSE) of 0.53 mm/day and a coefficient of determination (R2) of 0.87 were found between METRIC versus observed daily ET. Monthly ET estimates had a higher accuracy, with a RMSE of 12.08 mm/month, a R2 of 0.90, and a relatively small relative mean difference (RMD) of 9.68% during 2009–2012 growing seasons. Net radiation and Normalized Difference Vegetation Index (NDVI) from remote sensing observations were highly correlated with spatial and temporal ET estimates. An empirical model was developed to estimate daily ET using NDVI, net radiation (Rn), and vapor pressure deficit (VPD). The validation showed that the accuracy of this easy-to-use empirical method was slightly lower than that of METRIC but still reasonable, with a RMSE of 0.71 mm/day when compared to ground measurements. The remote sensing based ET estimate will support a variety of State and local interests in water use and irrigation management, for both planning and regulatory/compliance purposes, and it provides the farmers observation-based guidance for site-specific and time-sensitive irrigation management.

Highlights

Almond has become the first leading revenue-generating crop commodity in California, with a total value of annual production over 5.9 billion dollars in 2014
Water use by almond orchards has not been well studied, especially under various cropping conditions, and this knowledge gap limits the capacity for growers to achieve resource-efficient water management
We found that reference ETo had an exponential relationship with Rn (R2 = 0.95) and tower measurements, and with a R2 and root mean square error (RMSE) of 0.98 and 0.27 mm/day (n = 7436 pixels) when reconstructed

Summary

Introduction

Almond has become the first leading revenue-generating crop commodity in California, with a total value of annual production over 5.9 billion dollars in 2014. Ground-based flux measurement methods such as eddy covariance (EC) [2], Bowen ratio (BR) [3], and most recently surface renewal (SR) [4], can provide half-hourly, hourly, and daily ET measurements and offer guidance to growers for time sensitive irrigation scheduling. These measurements are limited by the small scale of the footprint area of the measurement stations and they cannot capture heterogeneity within each agriculture field, and sometimes cannot represent the entire field or orchard conditions.

Methods

Results

Conclusion