The World Bank
This paper examines potential regional-scale impacts of climate change on sustainability of irrigated agriculture, focusing on the western San Joaquin Valley in California. We consider potential changes in irrigation water demand and supply, and quantify impacts on the hydrologic system, soil and groundwater salinity with associated crop yield reductions. Our analysis is based on archived output from General Circulation Model (GCM) climate projections through 2100, which were downscaled to the 1,400 km2 study area. We account for uncertainty in GCM climate projections by considering two different GCM's, each using three greenhouse gas emission scenarios. Significant uncertainty in projected precipitation creates large uncertainty in surface water supply, ranging from a decrease of 26% to an increase of 14% in 2080-2099. Changes in projected irrigation water demand ranged from a decrease of 13% to an increase of 3% at the end of the 21st century. Greatest demand reductions were computed for the dry and warm scenarios, because of increased land fallowing with corresponding decreased total crop water requirements. A decrease in seasonal crop ET by climate warming, despite an increase in evaporative demand, was attributed to faster crop development with increasing temperatures. Simulations of hydrologic response to climate-induced changes suggest that the salt-affected area will be slightly expanded. However, irrespective of climate change, salinity is expected to increase in downslope areas, thereby limiting crop production to mostly upslope areas of the simulation domain. Results show that increasing irrigation efficiency may be effective in controlling salinization, by reducing groundwater recharge and improving soil drainage, and in mitigating climate warming effects, by reducing the need for groundwater pumping to satisfy crop water requirements.
Girvetz, E.H., E.P. Maurer, P. Duffy, A. Ruesch, B. Thrasher, C. Zganjar, 2013, Making Climate Data Relevant to Decision Making: The important details of Spatial and Temporal Downscaling, The World Bank, March 27, 2013