Combining a Weather Forecast with a Stochastic Weather Generator

Posted by Jason Lillywhite

A couple of years ago, I blogged about the application of the GoldSim WGEN model for producing probabilistic time histories of precipitation and temperature data. WGEN is useful for modeling natural systems impacted by uncertain climate influences. This model can also be used for simulating future scenarios and forecasting.

Even though the results of a WGEN model are probabilistic and uncertain, they are based on historical observed records and tied to the latitude of the earth. This allows us to produce realistic future simulations. But if you plan to use WGEN for short-term forecasting (less than 6 months), it might be helpful to incorporate a weather forecast for the first part of the simulation. Read more to see how a web service forecast model is combined with WGEN to produce a more reasonable forecast for a specific location without having to manually download the forecast.

Reservoir Inflow Forecasting

Posted by Jason Lillywhite

Last month, at the annual symposium hosted by the Arizona Hydrologic Society, I presented on probabilistic reservoir forecasting using GoldSim. This model combines many existing components available in our library to forecast snowmelt driven runoff inflows to a reservoir and estimates risk of spills and/or shortages.

How Big Will Melbourne Australia be in 2035?

Posted by Jason Lillywhite

Many of you may be familiar with GoldSim models that incorporate simple population growth (e.g., in order to compute water demands in the future), but may not have seen complex demographic models that fully incorporate all the details required to accurately simulate the population growth for a large urban area. One of our recently showcased models on our website does just that. It probabilistically simulates the population of the City of Melbourne, Australia for the next 20 years. I found this model to be a highly effective population simulator, and believe the approach could potentially be applied to population forecasts for a variety of models.