H12G-08
Modeling future water demand in California from developed and agricultural land uses
Monday, 14 December 2015: 12:05
3011 (Moscone West)
Tamara S Wilson1, Benjamin M Sleeter1 and D. Richard Cameron2, (1)USGS Western Regional Offices Menlo Park, Menlo Park, CA, United States, (2)The Nature Conservancy, San Francisco, CA, United States
Abstract:
Municipal and urban land-use intensification in coming decades will place increasing pressure on water resources in California. The state is currently experiencing one of the most extreme droughts on record. This coupled with earlier spring snowmelt and projected future climate warming will increasingly constrain already limited water supplies. The development of spatially explicit models of future land use driven by empirical, historical land use change data allow exploration of plausible LULC-related water demand futures and potential mitigation strategies. We utilized the Land Use and Carbon Scenario Simulator (LUCAS) state-and-transition simulation model to project spatially explicit (1 km) future developed and agricultural land use from 2012 to 2062 and estimated the associated water use for California’s Mediterranean ecoregions. We modeled 100 Monte Carlo simulations to better characterize and project historical land-use change variability. Under current efficiency rates, total water demand was projected to increase 15.1% by 2062, driven primarily by increases in urbanization and shifts to more water intensive crops. Developed land use was projected to increase by 89.8%-97.2% and result in an average 85.9% increase in municipal water use, while agricultural water use was projected to decline by approximately 3.9%, driven by decreases in row crops and increases in woody cropland. In order for water demand in 2062 to balance to current demand levels, the currently mandated 25% reduction in urban water use must remain in place in conjunction with a near 7% reduction in agricultural water use. Scenarios of land-use related water demand are useful for visualizing alternative futures, examining potential management approaches, and enabling better informed resource management decisions.