Persistent droughts are the new normal in the Southwestern United States. Several states in the region are experiencing lower than average precipitation amounts, deficient soil moisture levels, and decreasing streamflow yields and water storage. The effects of persistent droughts have been more pronounced in recent years. There is a consensus among the sciences that climate change will exacerbate the magnitude, frequency, and duration of the droughts in the region, which is even more alarming. Droughts in general and persistent droughts specifically present a severe environmental and economic challenge, expected to result in more significant risks to society, agricultural and industrial sectors. These threats across the sectors from the expected increasing frequency of droughts, point to the need for simulation tools that can incorporate these risks as a function of the changing climate and long-term droughts. This study summarizes the results and performance of a stochastic weather generator with a new approach to modeling droughts based on historical drought observations in a case study region in the Southwestern US. The process has been applied and tested using the GoldSim dynamic simulation platform with an implementation of the US National Weather Service’s Weather Generation tool, “WGEN.” Initial results show that historical observations of precipitation can be used to build a robust simulation and forecasting tool to evaluate ranges of plausible drought scenarios using Monte Carlo simulation.
