Nonparametric estimation of groundwater residence time distributions: What can environmental tracer data tell us about groundwater residence time?

摘要: Residence time distributions (RTDs) have been used extensively for quantifying flow and transport in subsurface hydrology. In geochemical approaches, environmental tracer concentrations are conjunction with simple lumped parameter models (LPMs). Conversely, numerical simulation techniques require large amounts of parameterization estimated RTDs certainly limited by associated uncertainties. this study, we apply a nonparametric deconvolution approach to estimate using concentrations. The model is based only on the assumption that steady enough observed well approximated linear superposition input RTD; is, convolution integral holds. Even concentration data, entire shape an RTD remains highly nonunique. However, accurate estimates mean ages some cases prediction young portions may be possible. most useful type data was found use series tritium. This due sharp variations atmospheric short half-life. CFC compounds smoothly varying more prone nonuniqueness. work highlights benefits limitations whole either LPMs or through simulation. ability developed here correct mixing biases appears promising.