How Watershed Characteristics Affect Transit Time Distributions

Daniel B. Abrams, Henk M. Haitjema

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The groundwater transit time distribution (TTD) for a watershed provides insight into the migration of non-point source contaminants such as nitrate through an aquifer. The most commonly used TTD is the gamma lumped parameter model (GLPM), which requires calibration of shape and scale parameters to data (typically tritium). Setting the shape parameter to one yields the exponential lumped parameter model (ELPM). The ELPM does not require calibration, but depends on the average aquifer thickness, porosity, and recharge rate. Whether the ELPM or GLPM is more appropriate appears to be related to watershed characteristics. For watersheds where the water table mimics the topography, MODFLOW simulations indicate that the GLPM can be calibrated to match the TTD. Such topography-controlled systems are generally associated with relatively thick, low permeable aquifers. In contrast, relatively thin, high permeable aquifers are more often rechargecontrolled with the water table mounding between streams. Here it is found that the ELPM is a good approximation for the TTD. However, weak sinks (streams that do not receive water from the entire aquifer depth) distort this ELPM by introducing a greater frequency of very short as well as very long transit times. Unfortunately, the shape and scale parameters of the GLPM can only be modified to match either the very young or old range of transit times, but not both. So even in the presence of weak sinks, the ELPM is generally the best choice for recharge-controlled watersheds, particularly at the regional scale where the effects of weak sinks are muted.
Original languageEnglish (US)
Title of host publicationProceedings of the MODFLOW and More 2017 Conference
StatePublished - 2017

Keywords

  • ISWS

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    Abrams, D. B., & Haitjema, H. M. (2017). How Watershed Characteristics Affect Transit Time Distributions. In Proceedings of the MODFLOW and More 2017 Conference