In Georgia and many other southeastern states in the USA, the amount of water used by agriculture for irrigation is largely unknown due to the lack of reporting requirements. Recent droughts and a water dispute with the neighboring states that include Alabama and Florida have highlighted the need for an accurate estimate of water use by agriculture. The goal of this study was to evaluate the use of a crop simulation model combined with kriging for estimating the spatial distribution of the monthly irrigation water use for cotton in the Coastal Plain region of Georgia. Farmers' monthly irrigation applications for cotton during the 2002 and 2003 growing seasons were obtained from selected sites of the Agricultural Water Pumping program. We selected 80 fields for 2002 and 51 fields for 2003. For each of these fields, we used the Cropping System Model-CROPGRO-Cotton to simulate farmers' irrigation applications. Ordinary kriging was used to estimate the spatial distribution of monthly total irrigation in the region. We then compared the spatial and temporal distribution of irrigation amounts predicted by the Cropping System Model-CROPGRO-Cotton with the amount of water that the farmers actually applied. The Cropping System Model-CROPGRO-Cotton simulated the temporal pattern of irrigation applications very well during the growing season. The root mean square error (RMSE) between observed and simulated total irrigation for different months ranged from 5 to 23 mm in 2002 and from 2 to 14 mm in 2003. The RMSE values were generally higher in 2002 when the irrigation applications across the region were more variable when compared with 2003. Consequently, a better agreement on the spatial distribution of monthly total irrigation for the observed and simulated was obtained for 2003 than for 2002.
|Original language||English (US)|
|Number of pages||9|
|Journal||Agricultural Water Management|
|State||Published - May 10 2007|
Bibliographical noteFunding Information:
This work was conducted under the auspices of the Southeast Climate Consortium (SECC; secc.coaps.fsu.edu) and supported by a partnership with the United States Department of Agriculture-Risk Management Agency (USDA-RMA), by grants from the US National Oceanic and Atmospheric Administration-Office of Global Programs (NOAA-OGP) and USDA-Cooperative State Research, Education, and Extension Service (USDA-CSREES) and by State and Federal funds allocated to Georgia Agricultural Experiment Stations Hatch projects GEO01654.
Copyright 2008 Elsevier B.V., All rights reserved.
- Crop models
- Crop water management
- Decision support systems