### Abstract

The accuracy of parameter estimation procedures is evaluated for a modified Gauss‐Newton method applied to transient ground‐water flow. Three different approaches of evaluating the sensitivity coefficient matrix are examined, including influence coefficient, sensitivity equation, and variational approaches. The performance of each of the techniques is evaluated by applying a common synthetic data set. The latter two techniques are shown to perform with least sensitivity to starting parameters and extraneous sampling noise. Where either random or systematic noise is added to the time‐series data set, the resulting predictions become increasingly more sensitive to the form of the starting transmissivity vector. It is concluded that the modified Gauss‐Newton method is attractive because of its simplicity, high rate of convergence, and modest computational demands, especially when the number of the parameters to be identified is not large.

Original language | English (US) |
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Pages (from-to) | 662-668 |

Number of pages | 7 |

Journal | Groundwater |

Volume | 33 |

Issue number | 4 |

DOIs | |

State | Published - Jan 1 1995 |

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### All Science Journal Classification (ASJC) codes

- Water Science and Technology
- Computers in Earth Sciences

### Cite this

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*Groundwater*, vol. 33, no. 4, pp. 662-668. https://doi.org/10.1111/j.1745-6584.1995.tb00322.x

**A Modified Gauss‐Newton Method for Aquifer Parameter Identification.** / Li, Jingsheng; Elsworth, Derek.

Research output: Contribution to journal › Article

TY - JOUR

T1 - A Modified Gauss‐Newton Method for Aquifer Parameter Identification

AU - Li, Jingsheng

AU - Elsworth, Derek

PY - 1995/1/1

Y1 - 1995/1/1

N2 - The accuracy of parameter estimation procedures is evaluated for a modified Gauss‐Newton method applied to transient ground‐water flow. Three different approaches of evaluating the sensitivity coefficient matrix are examined, including influence coefficient, sensitivity equation, and variational approaches. The performance of each of the techniques is evaluated by applying a common synthetic data set. The latter two techniques are shown to perform with least sensitivity to starting parameters and extraneous sampling noise. Where either random or systematic noise is added to the time‐series data set, the resulting predictions become increasingly more sensitive to the form of the starting transmissivity vector. It is concluded that the modified Gauss‐Newton method is attractive because of its simplicity, high rate of convergence, and modest computational demands, especially when the number of the parameters to be identified is not large.

AB - The accuracy of parameter estimation procedures is evaluated for a modified Gauss‐Newton method applied to transient ground‐water flow. Three different approaches of evaluating the sensitivity coefficient matrix are examined, including influence coefficient, sensitivity equation, and variational approaches. The performance of each of the techniques is evaluated by applying a common synthetic data set. The latter two techniques are shown to perform with least sensitivity to starting parameters and extraneous sampling noise. Where either random or systematic noise is added to the time‐series data set, the resulting predictions become increasingly more sensitive to the form of the starting transmissivity vector. It is concluded that the modified Gauss‐Newton method is attractive because of its simplicity, high rate of convergence, and modest computational demands, especially when the number of the parameters to be identified is not large.

UR - http://www.scopus.com/inward/record.url?scp=84980314300&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84980314300&partnerID=8YFLogxK

U2 - 10.1111/j.1745-6584.1995.tb00322.x

DO - 10.1111/j.1745-6584.1995.tb00322.x

M3 - Article

AN - SCOPUS:84980314300

VL - 33

SP - 662

EP - 668

JO - Ground Water

JF - Ground Water

SN - 0017-467X

IS - 4

ER -