Oral Presentation NCGRT/IAH Australasian Groundwater Conference 2019

Spatial data mapping for reduction of uncertainty in groundwater modelling (530)

Xuyan Wang 1
  1. Jacobs, South Brisbane, QLD, Australia

Unbalanced monitoring distribution is always a big challenge in groundwater modelling for assessing the impact of regional groundwater systems on the local human activities. Pilot points as a tool are often used in such groundwater modelling for enhancing information from limit observations but still restricted to the monitoring data distribution. We propose a novel spatial mapping strategy which combines fuzzy set theory and pilot point approach to form a logic potential from relevant spatial hydrogeological information for reduction of data uncertainty in the model calibration. An effective fuzzy logic approach, which incorporates random probability and fuzzy set theory, is introduced to capture the dispersion of the reliable monitoring information from the relevant regional hydrogeological and monitoring data to produce a map of “intensity” scores which allows the modeller to place “smart pilot points” at locations defined by their probability for producing informative constraints on the statistical distributions of the target variables. The method is demonstrated to be successfully applied for groundwater modelling with limit site monitoring data in a remote mine development project. In summary, the proposed approach intends to reduce the data uncertainty in the groundwater model calibration with the information gleaned from borrowing relevant spatial and historical data associated with hydrogeological mapping while reducing the site monitoring costs.