Preprints
https://doi.org/10.5194/egusphere-2022-1262
https://doi.org/10.5194/egusphere-2022-1262
 
12 Dec 2022
12 Dec 2022
Status: this preprint is open for discussion.

mesas.py v1.0: A flexible Python package for modeling solute transport and transit times using StorAge Selection functions

Ciaran Harman1,2 and Esther Xu Fei1 Ciaran Harman and Esther Xu Fei
  • 1Department of Environmental Health and Engineering, Johns Hopkins University Baltimore, MD, USA
  • 2Department of Earth and Planetary Sciences, Johns Hopkins University Baltimore, MD, USA

Abstract. StorAge Selection transport theory has recently emerged as a framework for representing material transport through a control volume. It can be seen as a generalization of transit time theories and lumped parameter models to allow for arbitrary time-variability of the rate of material flow in and out of the control volume, and in the transport dynamics. SAS is currently the state-of-the-art approach to interpreting tracer transport. Here we present mesas.py, a Python package implementing the SAS framework. mesas.py allows SAS functions to be specified using several built-in common distributions, as a piecewise-linear CDF, or as a weighted sum of any number of such distributions. The distribution parameters and weights used to combine them can be allowed to vary in time, allowing SAS functions of arbitrary complexity to be specified. mesas.py simulates tracer transport using a novel mass tracking scheme and can account for first order reactions and fractionation. We present a number of analytical solutions to the governing equations and use these to validate the code. For a benchmark problem the timestep-averaging approach of the mesas.py implementation provides a 15 × reduction in mass balance errors compared to a previous implementation of SAS.

Ciaran Harman and Esther Xu Fei

Status: open (until 02 Mar 2023)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-1262', Paolo Benettin, 19 Jan 2023 reply

Ciaran Harman and Esther Xu Fei

Ciaran Harman and Esther Xu Fei

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Short summary
Over the last 10 years scientists have developed a new way of modeling how material is transported through complex systems, called StorAge Selection. Here we present some new code implementing this method that is easy to use, but also flexible and very accurate. We show that for cases where we know exactly what the answer should be, our code gets the right answer. We also show that our code is closer than some other people's code to the right answer in an important way: it conserves mass.