Simulating the Uncertainty of Climate Change in Water Balance Models

Abstract

Mine site water balances in GoldSim are considered the ‘de facto’ standard for dynamic, high resolution, probabilistic simulations for conceptual and operational mine water management systems.  Many of these models are projected well out into the future to simulate conditions during long-term closure of the mine.  Industry standards often require the water balance to incorporate probabilistic components and include the impacts of climate change on the system.

By stochastically simulating the climate, including climate change prediction scenarios, and incorporating realistic responses to environmental conditions, the GoldSim mine water balance can simulate the systems response to weather (which is what we get), as opposed to climate (which is what we expect) out to the end of the century, though with a large cloud of uncertainty surrounding the results.

This presentation will focus on:

  • Exploring the key assumptions used in climate change predictions, including ‘how hot will the planet get?’ (Representative Concentration Pathways or RCPs), and ‘how will society respond to changing climate?’ (Shared Socioeconomic Pathways or SSP’s). 
  • How SRK uses around 30 different Global Climate Models (GCM’s) to quantify the cloud of uncertainty around climate change predictions.
  • Incorporating the uncertainties inherent in climate change models into a consistent stochastic time frame instead of just selecting the mean change in climate.
  • Show how SRK uses a variant of the WGEN synthetic climate generator to simulate the uncertainty of day-to-day weather as well as the long-term climate change trends predicted by the Intergovernmental Panel on Climate Change (IPCC).


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