Capturing field-scale variability in crop performance across a regional-scale climosequence

Monday, 15 December 2014
Erin S Brooks1,2, Matteo Poggio3, Todd R Anderson4, Caley Gasch5, Matthew Allen Yourek1, Nicole Kristine Ward1, Troy Sehlin Magney1, David J Brown3 and David Rhys Huggins6, (1)University of Idaho, Moscow, ID, United States, (2)University of Idaho, Biological and Agricultural Engineering, Moscow, ID, United States, (3)Washington State University, Crop and Soil Sciences, Pullman, WA, United States, (4)Mount Holyoke College, Environmental Studies, South Hadley, MA, United States, (5)Washington State University, Pullman, WA, United States, (6)USDA-ARS, Land Management and Water Conservation Research, Pullman, WA, United States
With the increasing availability of variable rate technology for applying fertilizers and other agrichemicals in dryland agricultural production systems there is a growing need to better capture and understand the processes driving field scale variability in crop yield and soil water. This need for a better understanding of field scale variability has led to the recent designation of the R. J. Cook Agronomy Farm (CAF) (Pullman, WA, USA) as a United States Department of Agriculture Long-Term Agro-Ecosystem Research (LTAR) site. Field scale variability at the CAF is closely monitored using extensive environmental sensor networks and intensive hand sampling. As investigating land-soil-water dynamics at CAF is essential for improving precision agriculture, transferring this knowledge across the regional-scale climosequence is challenging. In this study we describe the hydropedologic functioning of the CAF in relation to five extensively instrumented field sites located within 50 km in the same climatic region. The formation of restrictive argillic soil horizons in the wetter, cooler eastern edge of the region results in the development of extensive perched water tables, surface saturation, and surface runoff, whereas excess water is not an issue in the warmer, drier, western edge of the region. Similarly, crop and tillage management varies across the region as well. We discuss the implications of these regional differences on field scale management decisions and demonstrate how we are using proximal soil sensing and remote sensing imagery to better understand and capture field scale variability at a particular field site.