Transit Time Distributions Estimation Exploiting Flow-Weighted Time: Theory and Proof-of-Concept

Minseok Kim, Peter A. Troch

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Time-variable transit time distributions (TTDs) have been utilized as a tool to understand how catchments transmit water. However, most of the existing TTD estimation methods require to impose certain structures on those TTDs a priori, which could lead to misinterpreting data. We present a data-based method to estimate time-variable TTDs without imposing their structure a priori. The core of the method is the use of a revised flow-weighted time, where TTDs do not reflect variable external forcings directly. The functional forms of the TTDs are much simpler in flow-weighted time, compared to those in calendar time, and this allows for easier estimation of TTDs. Dynamic (state-dependent) multiple linear regression methods were applied to estimate the time-variable TTDs in flow-weighted time, which can eventually be transformed back to calendar time. The method performs well in a proof-of-concept demonstration with synthetic data sets. We also discuss potential generalizations of the proposed method.

Original languageEnglish (US)
Article numbere2020WR027186
JournalWater Resources Research
Issue number12
StatePublished - Dec 2020


  • age
  • data based
  • dynamic multiple linear regression
  • flow-weighted time
  • transfer function
  • transit time

ASJC Scopus subject areas

  • Water Science and Technology


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