Dataset: State Transmissivity Estimates for Hydrogeology Cross-Cutting Project


Description

Abstract

The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

A method for estimating Transmissivity from Specific Capacity data which can be commonly found in Australian state groundwater databases was tested. Results indicated that the method generally is accurate to within an order of magnitude of Transmissivity values derived from time-drawdown pump test data. The method was therefore deemed suitable for application across the available state groundwater databases (NSW, QLD and Vic) to obtain approximate Transmissivity values. The method was applied to the available data, yielding greater than 25,000 Transmissivity estimates across NSW, QLD and Vic. These may be particularly useful in data poor areas of the bioregional assessment regions, and may also prove useful for constraining the estimation of hydraulic properties between data rich areas. Attention is also drawn to the potential for applying this method for identifying zones of enhanced aquifer permeability resulting from the presence of fractures and faults within aquifers.

Dataset History

This dataset used state groundwater databases as source data (see lineage) and followed the following methodology to produce final transmissivity estimates:

(Bradbury and Rothschild 1985) developed a method to estimate Transmissivity from specific capacity based on the Cooper-Jacob approximation to the Theis equation. The solution requires that a storage coefficient value be assumed. The solution is considered to be relatively insensitive to S (Bradbury and Rothschild 1985); (McLin 2005). The Theis solution is for a confined aquifer. The marginal error introduced to the T estimate by using the Theis solution for an unconfined aquifer is small relative to the other sources of error (pers.comm. Ken Bradbury, 2012) e.g. airlift data is generally of poor quality. There are solutions for either partially penetrating wells or fully penetrating wells. Knowledge of the hydrostratigraphy at each borehole is required in order to account for partial penetration. Additionally, without hydrostratigraphic interpretation of each borehole, it is not possible to assign the results to particular hydrostratigraphic units. Thus, it is proposed that the cross-cutting work be aimed towards estimating the Transmissivity for all bores with available data to do so. It becomes the responsibility of the project teams to assign these results to hydrostratigraphic units and then to undertake statistical analysis to understand the variation of hydraulic conductivity in each hydrostratigraphic unit and interpret/ use these results in a meaningful way.

This method cannot be considered a substitute for a dedicated pumping test; errors should be considered potentially significant. The TGUESS approach (Bradbury and Rothschild 1985) enables sensitivity analysis to be undertaken in a relatively straight-forward way. (McLin 2005) notes that the value of applying this method may assist with recognising uncertainty in the estimation process.

T=Q/4πs ln(2.25Tt/(r_w^2 S))

where, T = transmissivity [L2/t]; Q= discharge [L2/t]; s= drawdown in the well [L]; t= pumping time [t]; S= storage coefficient [dimensionless]; rw= radius of the well [L]

For full methodology and more information see the word document report within this dataset

Dataset Citation

Bioregional Assessment Programme (XXXX) State Transmissivity Estimates for Hydrogeology Cross-Cutting Project. Bioregional Assessment Derived Dataset. Viewed 31 May 2018, http://data.bioregionalassessments.gov.au/dataset/db6643ff-f4ec-4aa3-9f5d-afdce1bce5b1.

Dataset Ancestors

General Information

Distributions