Oral Presentation Australasian Groundwater Conference 2017

Reliability of spatial patterns of groundwater recharge (#219)

Yueqing Xie 1 , Peter G Cook 1 , Russell Crosbie 2 , Daniel Partington 1 , Craig T Simmons 1 , Okke Batelaan 1
  1. National Centre for Groundwater Research and Training & School of the Environment, Flinders University, Bedford Park, South Australia, Australia
  2. Land and Water, CSIRO, Urrbrae, South Australia, Australia

Groundwater recharge is a key factor to understanding groundwater availability. Many methods have been developed with water balance modelling most straightforward. It is commonly recognised that groundwater recharge estimated for a specific site (i.e., absolute recharge) is often highly uncertain because of uncertainty in input parameters and uncertainty in observations for model calibration. However, the uncertainty in absolute recharge may become less important if we are more interested in the sensitivity of recharge to different factors such as vegetation, soil type and climate (i.e., relative recharge). It is possible that relative changes in recharge are more accurate than absolute recharge, but this has not been specifically assessed. This study aims to investigate the reliability of relative changes in groundwater recharge by estimating absolute recharge for different vegetation types, soil types and climate zones. This study chooses the Campaspe catchment in southeast Australia as a study area. The biophysically based modelling code WAter Atmosphere Vegetation Energy and Solutes modelling (WAVES) is used to perform numerical simulations. Three weather zones, two soil zones and four land cover zones are used based on the conditions of the study area. The Monte Carlo method together with the Latin-Hypercube sampling technique is employed to perform uncertainty analysis by comparing modelled results to actual observations derived from MODIS satellite imagery (i.e., actual evapotranspiration and leaf area index). The results will be recharge statistics for different combinations of climate, soil and vegetation. The recharge statistics will inform both the uncertainty in the absolute recharge and the reliability of the relative changes in the recharge.

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