NH14A-03:
Mapping Drought Impacts on Agricultural Production in California's Central Valley
Monday, 15 December 2014: 4:30 PM
Forrest S Melton1,2, Alberto Guzman1,2, Lee Johnson1,2, Carolyn Rosevelt2, James P Verdin3, John L Dwyer4, Rick Mueller5, Audra Zakzeski5, Prasad S Thenkabail6, Cynthia Wallace6, Jeanine Jones7, Sean Windell2, John Urness2, Aimee Teaby2, David Hamblin2, Kirk Matthew Post1,2 and Ramakrishna R Nemani8, (1)NASA ARC-CREST, Moffett Field, CA, United States, (2)California State University Monterey Bay, Seaside, CA, United States, (3)USGS/EROS, Boulder, CO, United States, (4)U.S. Geological Survey EROS Center, Department of the Interior, Sioux Falls, SD, United States, (5)USDA Washington DC, Washington, DC, United States, (6)USGS Arizona Water Science Center, Tucson, AZ, United States, (7)California Department of Water Resources, Sacramento, CA, United States, (8)NASA Ames Research Center, Moffett Field, CA, United States
Abstract:
The ongoing drought in California has substantially reduced surface water supplies for millions of acres of irrigated farmland in California's Central Valley. Rapid assessment of drought impacts on agricultural production can aid water managers in assessing mitigation options, and guide decision making with respect to requests for local water transfers, county drought disaster designations, and allocation of emergency funds to mitigate drought impacts. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and increases in idle acreage associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. We describe an approach for monthly and seasonal mapping of uncultivated agricultural acreage developed as part of a joint effort by USGS, USDA, NASA, and the California Department of Water Resources to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach.
To provide quantitative measures of uncultivated agricultural acreage from satellite data early in the season, we developed a decision tree algorithm and applied it to timeseries of data from Landsat TM, ETM+, OLI, and MODIS. Our effort has been focused on development of indicators of drought impacts in the March - August timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted across 640 fields from March - September, 2014. We present the algorithm along with updated results from the accuracy assessment, and discuss potential applications to other regions.
