Toward an Earth System Modeling Approach to Simulate Irrigation Effects


World agriculture consumes about 87% of global freshwater withdrawals, significantly impacting the global water cycle. Understanding irrigation impacts on land surface heat and moisture fluxes, surface and subsurface states, and their interactions with atmospheric processes is crucial for understanding historical climate change and modeling future climate at local and regional scales. Previous sensitivity studies of irrigation impacts on land surface show limited analysis of uncertainties from the input data and model irrigation schemes. A team of scientists, led by Department of Energy researchers at Pacific Northwest National Laboratory, improved the performance of the Community Land Model version 4 (CLM4) in simulating irrigation water use and surface fluxes by calibrating the model against data from the agriculture census. They found that by using the irrigation area fraction datasets from two widely used sources as inputs, CLM4 tended to produce unrealistically large temporal variations of irrigation demand for applications at the water resources region scale over the conterminous United States. The results suggest that CLM4-simulated irrigation amount and surface fluxes could be improved by calibrating model parameter values and accurately representing the spatial distribution and intensity of irrigated areas. The research recommends a critical path forward to a realistic assessment of irrigation impacts by developing CLM to include groundwater pumping and irrigation efficiency modules, and coupling CLM with streamflow routing and water management modules to account for all sources of water supply.


Leng, G., M. Huang, Q. Tang, W. J. Sacks, H. Lei, and L. R. Leung. 2013. “Modeling the Effects of Irrigation on Land Surface Fluxes and States over the Conterminous United States: Sensitivity to Input Data and Model Parameters,” Journal of Geophysical Research: Atmospheres 118, 9789-803. DOI:10.1002/jgrd.50792.