Poster Presentation Australasian Groundwater Conference 2017

Quantifying impacts of groundwater pumping using a nonlinear transfer function time-series model in the southwest Victoria (#78)

Xiang Cheng 1 , Tim J Peterson 2 , Bruce Gill 1
  1. Department of Economic Development, Job, Transport and Resources, Victoria, Australia
  2. Department of Infrastructure Engineering, The University of Melbourne, Parkville, Victoria, Australia

Assessing the impacts of groundwater abstractions is an essential part of groundwater resources management. Traditionally, the assessment has been undertaken by using numerical groundwater models such as MODFLOW. However, meaningful numerical groundwater modelling requires reliable information on hydraulic property, aquifer geometry and other data sets (e.g. recharge) which are often not available. Furthermore, numerical groundwater modelling is often resource-intensive, time consuming, and it is not practical for day-to-day groundwater management (e.g. assessing interference from pumping wells). This paper extends an approach which uses a nonlinear transfer function groundwater time-series model (Peterson & Western 2014; Shapoori et al. 2015) to assess impact of groundwater pumping on groundwater head. The time-series model consists of a soil-moisture layer to account for non-linearity between rainfall and recharge, and several pumping response functions to account for pumping from production wells (freely available in HydroSight With only observed groundwater hydrograph, groundwater pumping information and climate data as input data, this approach can separate the contribution of climate and each production well on groundwater level variation.

This approach was applied to the Nullawarre Water Supply Protection Area in the southwest Victoria. The model clearly separated the contribution of climate and each of over 60 production wells on groundwater level variation. The results showed that the impact of the increasing groundwater abstraction on the groundwater level trend has been negligible across the study area over the period from 1985 to 2015. The slightly declining trend in groundwater level was primarily due to climate variation. While this application has demonstrated that the time-series model was an effective and robust tool for assessing impact of groundwater abstraction, there were uncertainties associated with inaccurate input data, in particular estimates of the daily groundwater pumping rates. Accounting for these uncertainties would help to avoid unintended and undesirable management decisions.

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