Coupled water and energy balance models have become increasingly popular for estimating groundwater recharge, because of the integration of energy and water balances and sometimes carbon balance. The additional balances are thought to constrain the water balance and as a result should help reduce the uncertainty of groundwater recharge. However, these models usually have a large number of parameters. The uncertainty of these parameters may result in a large uncertainty in groundwater recharge estimates. This study aims to assess the potential uncertainty of groundwater recharge estimated from a widely used water and energy model. It is largely based on annual pasture vegetation in the lower part of the Campaspe catchment in southeast Australia. A Monte Carlo analysis method was employed to examine potential uncertainties introduced by different types of errors. The results show that for a mean rainfall of 398 mm/y and using a particular set of pedotransfer functions for deriving soil hydraulic parameters, the estimated recharge ranged from 7 to 144 mm/y due to the uncertainty in vegetation parameters. This upper bound of the recharge range increased to 236 mm/y when using different sets of pedotransfer functions. Through several synthetic test cases, this study shows that soil moisture time series may not offer much help for reducing recharge uncertainty, whereas evapotranspiration time series are able to reduce recharge uncertainty by more than 50%. The reduction in recharge uncertainty steadily improves as the uncertainty in observations reduces.
- Groundwater recharge
- Soil water balance
- Uncertainty analysis
- Water and energy balance model