Abstract
Regional-scale estimates of groundwater recharge are inherently uncertain, but this uncertainty is rarely quantified. Quantifying this uncertainty provides an understanding of the limitations of the estimates, and being able to reduce the uncertainty makes the recharge estimates more useful for water resources management. This paper describes the development of a method to constrain the uncertainty in upscaled recharge estimates using a rejection sampling procedure for baseflow and remotely sensed evapotranspiration data to constrain the lower and upper end of the recharge distribution, respectively. The recharge estimates come from probabilistic chloride mass-balance estimates from 3,575 points upscaled using regression kriging with rainfall, soils and vegetation as covariates. The method is successfully demonstrated for the 570,000-km2 Cambrian Limestone Aquifer in northern Australia. The method developed here is able to reduce the uncertainty in the upscaled chloride mass-balance estimates of recharge by nearly a third using data that are readily available. The difference between the 5th and 95th percentiles of unconstrained recharge across the aquifer was 31 mm/yr (range 5–36 mm/yr) which was reduced to 22 mm/yr for the constrained case (9–31 mm/yr). The spatial distribution of recharge was dominated by the spatial distribution of rainfall but was comparatively reduced in areas with denser vegetation or finer textured soils. Recharge was highest in the north-west in the Daly River catchment with a catchment average of 101 (61–192) mm/yr and lowest in the south-east Georgina River catchment with 6 (4–12) mm/yr.
Highlights
Groundwater recharge is one of the most difficult components of the water balance to estimate as it is impossible to directly measure and must be inferred from other measurements
The Normalised Difference Vegetation Index (NDVI) is correlated with rainfall, causing the positive correlation with log recharge without taking the rainfall into account
The uncertainty in the recharge estimates using the chloride mass balance (CMB) are largely due to the uncertainty in the chloride deposition, and it is difficult to measure this over appropriate time scales with the spatial resolution needed
Summary
Groundwater recharge is one of the most difficult components of the water balance to estimate as it is impossible to directly measure and must be inferred from other measurements. It is often recommended to use multiple methods when estimating recharge to acknowledge the inherent uncertainty in estimating something that cannot be measured directly (Scanlon et al 2002). The chloride mass balance (CMB) method (Anderson 1945) is the most widely used approach for estimating recharge, both globally (Scanlon et al 2006) and in Australia (Crosbie et al 2010). It is popular because it is robust over many climate zones and is cost effective, requiring only analyses of chloride in groundwater and rainfall.
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