Modeling Irrigation Effects on Surface Fluxes and Land-Air-Cloud Interactions


U.S. Department of Energy researchers at Pacific Northwest National Laboratory, in collaboration with Nanjing University, China, incorporated a method for representing irrigation in the Noah land surface model. This model was then used in combination with the Weather Research and Forecasting (WRF) model to study the effects of irrigation on land-atmosphere interactions, which may affect cloud properties. A series of simulations, with and without irrigation, focused on the Southern Great Plains (SGP) for an extremely dry (2006) and wet (2007) year. Model simulations were compared to data from the Atmospheric Radiation Measurement (ARM) program and the Oklahoma Mesonet, a network of environmental monitoring stations. The team found that including irrigation reduces model biases in soil moisture and surface latent heat (LH) and sensible heat (SH) fluxes, especially during a dry year. (Latent and sensible heat are types of energy released or absorbed in the atmosphere. Latent heat is related to changes in phase between liquids, gases, and solids. Sensible heat is related to changes in temperature of a gas or object with no change in phase.) Irrigation adds additional water to the surface, leading to changes in the planetary boundary layer. The increase in soil moisture leads to increases in the surface evapotranspiration and near-surface specific humidity but decreases in the SH and surface temperature. Those changes are local and occur during daytime. There is an irrigation-induced decrease in both the lifting condensation level (ZLCL) and mixed-layer depth. The decrease in ZLCL is larger than the decrease in mixed-layer depth, suggesting an increasing probability of shallow clouds. The simulated precipitation changes induced by irrigation are highly variable in space, and average precipitation over the SGP region only slightly increases. Larger soil moisture values in the irrigated simulation due to irrigation in late spring and summer persist into the early fall, suggesting that irrigation-induced soil memory could last a few weeks to months. The results demonstrate the importance of incorporating and improving irrigation parameterization for climate studies and process-level understanding of the role human activities play in modulating land–air–cloud interactions.


Qian, Y., M. Huang, B. Yang, and L. K. Berg. 2013. “A Modeling Study of Irrigation Effects on Surface Fluxes and Land-Air-Cloud Interactions in the Southern Great Plains,” Journal of Hydrometeorology 14, 700–721. DOI: 10.1175/JHM-D-12-0134.1.