Modeling the effects of irrigation on land surface fluxes and states over the conterminous United States: Sensitivity to input data and model parameters
Article first published online: 11 SEP 2013
©2013. American Geophysical Union. All Rights Reserved.
Journal of Geophysical Research: Atmospheres
Volume 118, Issue 17, pages 9789–9803, 16 September 2013
How to Cite
2013), Modeling the effects of irrigation on land surface fluxes and states over the conterminous United States: Sensitivity to input data and model parameters, J. Geophys. Res. Atmos., 118, 9789–9803, doi:10.1002/jgrd.50792., , , , , and (
- Issue published online: 9 OCT 2013
- Article first published online: 11 SEP 2013
- Accepted manuscript online: 29 AUG 2013 12:00AM EST
- Manuscript Accepted: 25 AUG 2013
- Manuscript Revised: 13 AUG 2013
- Manuscript Received: 20 FEB 2013
 Previous studies on irrigation impacts on land surface fluxes/states were mainly conducted as sensitivity experiments, with limited analysis of uncertainties from the input data and model irrigation schemes used. In this study, we calibrated and evaluated the performance of irrigation water use simulated by the Community Land Model version 4 (CLM4) against observations from agriculture census. We investigated the impacts of irrigation on land surface fluxes and states over the conterminous United States (CONUS) and explored possible directions of improvement. Specifically, we found large uncertainty in the irrigation area data from two widely used sources and CLM4 tended to produce unrealistically large temporal variations of irrigation demand for applications at the water resources region scale over CONUS. At seasonal to interannual time scales, the effects of irrigation on surface energy partitioning appeared to be large and persistent, and more pronounced in dry than wet years. Even with model calibration to yield overall good agreement with the irrigation amounts from the National Agricultural Statistics Service, differences between the two irrigation area data sets still dominate the differences in the interannual variability of land surface responses to irrigation. Our results suggest that irrigation amount simulated by CLM4 can be improved by calibrating model parameter values and accurate representation of the spatial distribution and intensity of irrigated areas. Furthermore, through a set of numerical experiments, the deficiency in the current parameterization is evaluated and a critical path forward to a realistic assessment of irrigation impacts using an earth system modeling approach is recommended.