Territory Stories

Development of a Groundwater Model for the Western Davenport Plains

Details:

Title

Development of a Groundwater Model for the Western Davenport Plains

Creator

Knapton, Anthony; CloudGMS Pty Ltd

Commissioned by

Northern Territory. Department of Environment, Parks and Water Security

Collection

E-Publications; E-Books; PublicationNT; WRD Technical Report 27/2017

Date

2018-03

Location

Western Davenport Water Control District

Abstract

CloudGMS has been commissioned by DENR to develop a numerical groundwater model of the aquifers within the central area of the WDWCD to improve confidence in the sustainability of the groundwater resources, as this is the area within the WCD with greatest potential for intensive development.

Notes

Made available by via Publications (Legal Deposit) Act 2004 (NT); Prepared for Dept Environment and Natural resources

Table of contents

Executive summary -- 1 Background -- 2 Physical -- 3 Available data -- 4 Conceptual model -- 5 Model design & construction -- 6 Parameter estimation -- 7 Water balances -- 8 Sensitivity analysis -- 9 Predictive scenarios -- 10 Conclusions -- 11 Reference -- 12 Document history and version control -- Appendix A - Groundwater level hydrographs - Appendix B - Alek range horticultural farm sub-regional modelling

Language

English

Subject

Groundwater; Northern Territory; Western Davenport Water Control District; Conceptual mode

Publisher name

Northern Territory Governmnet

Place of publication

Palmerston

Edition

version 2.0

Series

WRD Technical Report 27/2017

Format

ix, 127 pages : colour illustration and maps ; 30 cm

File type

application/pdf

ISBN

9781743502976

Use

Attribution International 4.0 (CC BY 4.0)

Copyright owner

Northern Territory Government

License

https://creativecommons.org/licenses/by/4.0/

Related links

https://hdl.handle.net/10070/842058 [LANT E-Publications: Development of a Groundwater Model for the Western Davenport Plains, version 1.1]

Parent handle

https://hdl.handle.net/10070/858845

Citation address

https://hdl.handle.net/10070/858846

Page content

Western Davenport WCD Groundwater Model (v2.0) Parameter Estimation CloudGMS 76 software, which, along with extensive documentation, can be downloaded from http://www.pesthomepage.org. The steady state model was completed using the PEST code. Due to factors discussed in section 6.5.1 the transient model parameter estimation was completed using the PEST implementation of the covariance matrix adaptation evolution strategy (CMAES) optimisation code (Hansen et al, 2003). 6.1.2. Objective function The objective function or phi (F) is a measure of the discrepancy between the observed values and the values determined by an estimation model. The smaller the objective function indicates a better fit of the model values to the observed values. The objective function in groundwater models typically comprises many different types of target data, for example, hydraulic heads or gauged flows. In the Western Davenport groundwater model only heads are available. The PEST suite of programs uses the weighted sum of squared residuals (WRSS) as the target objective function. 6.1.3. Measure of goodness of fit' The goodness of fit of the modelled to the observed data is often measured using a simple statistic. Statistics used in this study to describe the fit of final model output values to observed values include: The weighted sum of squared residuals (WSSR). This is the default measure utilised by the PEST suite of programs uses as the target objective function to assess goodness of fit'. <..= = >?<0 A)0 B(#0)CD 1+ 02 where Wi is the ith observation weighting yi is the ith observed value f(xi) is the ith predicted value The root mean squared error (RMS): =E. = F ?<0 A)0 B(#0)CD 1+ 02 H where Wi is the ith observation weighting yi is the ith observed value f(xi) is the ith predicted value The scaled root mean squared error (SRMS) is the RMS divided by the range of measured heads and expressed as a percentage. Weights are sometimes introduced to account for different levels of confidence in different measurements. .=E. = 100 J F ?<0 A)0 B(#0)CD 1+ 02 H where Wi are weights between 0 and 1; and H is the range of measured heads across the model domain.