Using High-Spatiotemporal Thermal Satellite ET Retrievals for Operational Water Use and Stress Monitoring in a California Vineyard

Abstract

In viticulture, deficit irrigation strategies are often implemented to control vine canopy growth and to impose stress at critical stages of vine growth to improve wine grape quality. To support deficit irrigation scheduling, remote sensing technologies can be employed in the mapping of evapotranspiration (ET) at the field to sub-field scales, quantifying time-varying vineyard water requirements and actual water use. In the current study, we investigate the utility of ET maps derived from thermal infrared satellite imagery over a vineyard in the Central Valley of California equipped with a variable rate drip irrigation (VRDI) system which enables differential water applications at the 30 × 30 m scale. To support irrigation management at that scale, we utilized a thermal-based multi-sensor data fusion approach to generate weekly total actual ET (ETa) estimates at 30 m spatial resolution, coinciding with the resolution of the Landsat reflectance bands. Crop water requirements (ETc) were defined with a vegetative index (VI)-based approach. To test capacity to capture stress signals, the vineyard was sub-divided into four blocks with different irrigation management strategies and goals, inducing varying degrees of stress during the growing season. Results indicate derived weekly total ET from the thermal-based data fusion approach match well with observations. The thermal-based method was also able to capture the spatial heterogeneity in ET over the vineyard due to a water stress event imposed on two of the four vineyard blocks. This transient stress event was not reflected in the VI-based ETc estimate, highlighting the value of thermal band imaging. While the data fusion system provided valuable information, latency in current satellite data availability, particularly from Landsat, impacts operational applications over the course of a growing season.

Mapping Daily Evapotranspiration at Field Scale Using the Harmonized Landsat and Sentinel-2 Dataset, with Sharpened VIIRS as a Sentinel-2 Thermal Proxy

“…These sites include three vineyard domains within California, USA, part of the USDA-ARS Grape Remote Sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX) [56], including the Barrelli vineyard in Sonoma County near Cloverdale, Sierra Loma near Lodi in Sacramento County, and Ripperdan in Madera County near Fresno. The domains sample a north-south climate gradient due to variations in cloud cover, temperature, and humidity [24,26,28,57,58]. This study uses three flux towers installed in irrigated vineyards in the three domains as part of GRAPEX: Bar012 (Barrelli), SLM001 (Sierra Loma), and Rip760 (Ripperdan).…”

“…In real-time applications, this will not be the case and value added by additional ET samples may be larger than in the retrospective case in that the interval of extrapolation from the last available sample and the prediction date is reduced. We tested this scenario, focusing on weekly ET estimation for irrigation management, following conventions developed for a variable rate drip irrigation (VRDI) system by [28]. In that study, weekly ET was defined as a summation of daily ET from the prior Friday to Thursday for delivery Friday morning for the next week's irrigation scheduling.…”

“…In addition, performance for real-time applications may be further limited by latencies in Landsat product availability, and the need for extrapolation beyond the last available Landsat overpass to the current date. The fusion of ET timeseries from Landsat 8 and MODIS for operational applications was tested by [28].…”

Using Satellite Thermal-Based Evapotranspiration Time Series for Defining Management Zones and Spatial Association to Local Attributes in a Vineyard

“…These approaches have been used extensively and have been validated over many landcover types. A subset of ET mapping algorithms, including the Atmosphere-Land Exchange Inverse (ALEXI) model [27,30] and associated flux disaggregation technique (DisALEXI) [31,32] have been applied over vineyards, showing promising results [33][34][35][36][37].…”

“…Quantification of ET over space is commonly represented on a daily scale, thus involving hundreds of images. Research in the past years has focused on mapping field characteristics, such as canopy cover and ET, at the field/landscape scale for each time step [37,47]. Alternatively, defining MZs based on within-field spatial variability provides information regarding the spatial heterogeneity in the field [48,49].…”