Sometimes it is a challenge to involve a diverse audience in the modeling process of a complex system. It is important that you adequately reflect the complexities of the system while at the same time present the results clearly and concisely for people that have different perspectives. Recently, Ryan Morrison (USGS) and Mark Stone (Assistant professor at UNM) were able to leverage the visual and dynamic strengths of GoldSim to successfully involve a diverse group of stakeholders in evaluating flow alternatives for the Rio Chama basin, New Mexico. I wanted to highlight this modeling application because of its unique approach within the world of dynamic simulation and to demonstrate the utility of GoldSim's new scenario management capability.
Showing posts with label economic. Show all posts
Showing posts with label economic. Show all posts
June 2, 2015
January 26, 2015
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.
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.
Subscribe to:
Posts (Atom)