Modeling future land use and water demand in California's Central Coast

California's Central Coast has historically been plagued by competing land uses vying for ever limited water supplies. Given recent, long-term drought and subsequent water shortages, coupled with expected population growth, increased water use, and projected climate warming, the region is poised to reach a pivotal juncture where water demand is likely to exceed currently available supply. To determine the potential future land-use related water demand for San Benito, Santa Cruz, Monterey, San Luis Obispo, and Santa Barbara Counties, we developed a business-as-usual (BAU) scenario and a recent-modern (RM) scenario based on historical, empirical datasets. The Land Use and Carbon Scenario Simulator (LUCAS), a stochastic, spatially-explicit (270 m²) state-and-transition simulation model, was used to model these scenarios for the years 2001-2100 across 40 Monte Carlo simulations. The model was parameterized using local datasets and stakeholder input to better inform and identify where land change would and would not occur giving current zoning ordinances and local mandates. Land change in the BAU scenario was randomly sampled from the full historical land change record (1992-2016), whereas the RM scenario sampled only from 2002-2016. Preliminary results indicated water demand increased under a BAU land change scenario by an estimated ~ 491 million cubic meters (398,000 acre feet) by 2100, driven by the continuation of perennial cropland expansion and urbanization. The RM land change scenario (2002-2016), resulted in much lower estimated increases at ~104 million cubic meters (~ 85,000 acre feet) of added water demand by century's end. Recent mandates on water restrictions, many implemented since around 2002, altered the magnitude and amount of land change, which is well captured in our preliminary RM scenario. Our modeling approach can provide water managers and policy makers with information on diverging land use and water use futures, based on observed land change and water use trends and local knowledge, helping better inform land and resource management decisions.