This dataset was supplied to the Bioregional Assessment Programme by a third party and is presented here as originally supplied. Metadata was not provided and has been compiled by the Bioregional Assessment Programme based on known details at the time of acquisition.
The spatial distributions of residual water level errors are presented for 1980, 1990, 2000 and 2010. The mean residual water level is defined such that negative numbers refer to points where predicted groundwater head values are higher than observed and positive values indicate that predicted groundwater head values are lower than observed.
The dataset was generated in the Gippsland Groundwater Model (Beverly et al 2015). The 2010 residual error reflects the difference between the simulated and the measured water level surfaces at groundwater monitoring bores across all aquifers
The purpose of the residual error data layer is to provide an indication of the modelled groundwater level surfaces performance relative measured groundwater level data as of 2010.
"Results .. suggest that the model over predicts the heads in the outcropped regions and under predicts the heads in the lower parts of the landscape. The greatest errors are shown to be in the outcropping regions ....suggesting that the model attribution associated with model layer 23 requires further analysis. This is consistent with observations reported .....that considered the hydraulic conductivities attributed to zones 23-29 were on the lower bounds of previously reported values."
Extract from the Gippsland groundwater model technical report (Beverly et al, 2015)
Measured groundwater level sourced from the Victorian groundwater database and reported as metres above sea level. The 2010 simulated water level sourced from the Gippsland Groundwater Model (Beverly et al 2015). Calculation made by Measured minus Simulated.
Victorian Department of Economic Development, Jobs, Transport and Resources (2015) Mean residual water level error - Gippsland 2010. Bioregional Assessment Source Dataset. Viewed 05 October 2018, http://data.bioregionalassessments.gov.au/dataset/2cb19cb5-2578-4356-8baf-c5e5dad56f13.