Crop water productivity studies of leading world crops in California utilizing advanced multispectral remote sensing and modeling on the Google Earth Engine (GEE) cloud

As the global population expands in the 21^st century, demand for food and water are increasing whereas supply of arable land and accessible fresh water are decreasing. A way to mitigate this looming problem is to increase agricultural Crop Water Productivity (CWP) by improving how much yield (e.g., grain, biomass) is produced per unit of water. To produce more crop with less water (more crop per drop) over large scales, a better understanding of measuring, modeling, and mapping CWP of major world crops utilizing multi-sensor remote sensing, meteorological data, crop yield statistics, and cloud based machine learning is needed.  This study aims to establish a novel methodology to measure evapotranspiration and CWP of select crops at 30m resolution. To accomplish this, a benchmark study area within the San Joaquin section of the Central Valley of California, USA was chosen to represent a diverse agricultural growing region. Within this area, leading and high-water consuming world crops were selected and mapped with respective growing seasons determined by NDVI analysis. Actual evapotranspiration (Et_a) as a proxy for water use was determined with new methods to map Evaporative Fraction (Et_f) and Reference Evapotranspiration (Et_o) per crop type. Using the equation Et_a = Et_o x Et_f, a novel approach for hot and cold pixel selection in image analysis was developed to determine Et_f utilizing Landsat thermal bands in conjunction with Google Earth Engine (GEE).

This analysis determined CWP for nine major world crops (almonds, cotton, wheat, pistachios, grapes, barley, rice, corn, and walnuts) specific to individual crop growing seasons. This study also provides the quantum of water that can be saved if CWP is raised by 10, 20, and 30% relative to existing water use, thus establishing a pathway to create potential water banks from the saved water. Although this study focused on California, the application of methods used has potential to expand globally. This methodology provides insight to help ensure water security and potentially implement better water management strategies in the 21^st century.