|Booker, J -|
|Molling, Christine -|
Submitted to: National Cotton Council Beltwide Cotton Conference
Publication Type: Proceedings
Publication Acceptance Date: October 15, 2010
Publication Date: January 7, 2011
Citation: Booker, J.D., Lascano, R.J., Molling, C.C. 2011. Incorporation of Monitoring Systems to Model Irrigated Cotton at a Landscape Level. National Cotton Council Beltwide Cotton Conference. January 4-7, 2011, Atlanta, Georgia. p. 1389-1396. Technical Abstract: Advances in computer speed, industry IT core capabilities, and available soils and weather information have resulted in the need for “cropping system models” that address in detail the spatial and temporal water, energy and carbon balance of the system at a landscape scale. Many of these models have been upgraded from column, i.e., two dimensions to distributed or three-dimensional models associated with GIS systems, supporting the use of readily accessible grid based data, i.e., elevation and soil survey. These GIS linked models are thus tools that can be used to manage agronomic inputs in a cotton system. Furthermore, the increased adoption of pivot monitoring systems, which provide continuous position and flow measurements of irrigation water, is producing yet another temporal and spatial dataset that will likely improve the accuracy to model the water balance in irrigated cotton systems. Since these pivot irrigation systems can take several days to complete a circuit around the field, accurate representation of the spatial and temporal dynamics of the water balance (inputs and outputs), i.e., rainfall, irrigation, and soil water evaporation and transpiration across the field, is needed to adequately model the cotton system. This objective is the subject of a project among Texas Tech University, USDA-ARS (Bushland and Lubbock, Texas), and the University of Wisconsin-Madison which is to combine two models, PALMS and Cotton2K, to simulate the growth of cotton irrigated with a center-pivot across the landscape. Specific examples of the modeling efforts using spatially and temporally representative irrigation data will be presented.