HR: 16:00h
AN: H42M-01    [PDF]
TI: Assessing the Importance of Incorporating Spatial and Temporal Variability of Soil and Plant Parameters into Local Water Balance Models for Precision Agriculture: Investigations within a California Vineyard
AU: * Hubbard, S
EM: sshubbard@lbl.gov
AF: Lawrence Berkeley National Laboratory, 1 Cyclotron Road MS 90-1116, Berkeley, CA 94720 United States
AU: Pierce, L
EM: larspierce@csumb.edu
AF: California State University, Monterey Bay, Seaside, CA 93955 United States
AU: Grote, K
EM: krgrote@lbl.gov
AF: Dept. of Civil and Environmental Engineering, UC Berkeley, Berkeley, CA 94720 United States
AU: Rubin, Y
EM: rubin@ce.berkeley.edu
AF: Dept. of Civil and Environmental Engineering, UC Berkeley, Berkeley, CA 94720 United States
AB: Due Due to the high cash crop nature of premium winegrapes, recent research has focused on developing a better understanding of the factors that influence winegrape spatial and temporal variability. Precision grapevine irrigation schemes require consideration of the factors that regulate vineyard water use such as (1) plant parameters, (2) climatic conditions, and (3) water availability in the soil as a function of soil texture. The inability to sample soil and plant parameters accurately, at a dense enough resolution, and over large enough areas has limited previous investigations focused on understanding the influences of soil water and vegetation on water balance at the local field scale. We have acquired several novel field data sets to describe the small scale (decimeters to a hundred meters) spatial variability of soil and plant parameters within a 4 acre field study site at the Robert Mondavi Winery in Napa County, California. At this site, we investigated the potential of ground penetrating radar data (GPR) for providing estimates of near surface water content. Calibration of grids of 900 MHz GPR groundwave data with conventional soil moisture measurements revealed that the GPR volumetric water content estimation approach was valid to within 1 percent accuracy, and that the data grids provided unparalleled density of soil water content over the field site as a function of season. High-resolution airborne multispectral remote sensing data was also collected at the study site, which was converted to normalized difference vegetation index (NDVI) and correlated to leaf area index (LAI) using plant-based measurements within a parallel study. Meteorological information was available from a weather station of the California Irrigation management Information System, located less than a mile from our study area. The measurements were used within a 2-D Vineyard Soil Irrigation Model (VSIM), which can incorporate the spatially variable, high-resolution soil and plant-based information. VSIM, which is based on the concept that equilibrium exists between climate, soils, and LAI, was used to simulate vine water stress, water use, and irrigation requirements during a single year for the site. Using the simple water-balance model with the dense characterization data, we will discuss: (1) the ability to predict vineyard soil water content at the small scales of soil heterogeneity that are observed in nature at the local-scale, (2) the relative importance of plant, climate, and soil information to predictions of the soil water balance at the site, (3) the influence of crop cover in the water balance predictions.
DE: 0689 Wave propagation (4275)
DE: 1842 Irrigation
DE: 1851 Plant ecology
DE: 1866 Soil moisture
DE: 1878 Water/energy interactions
SC: Hydrology [H]
MN: 2003 Fall Meeting