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A software tool to assess uncertainty in transient-storage model parameters using Monte Carlo simulations

Freshwater Science

By:
, , , , , , , and
https://doi.org/10.1086/690444

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Abstract

Researchers and practitioners alike often need to understand and characterize how water and solutes move through a stream in terms of the relative importance of in-stream and near-stream storage and transport processes. In-channel and subsurface storage processes are highly variable in space and time and difficult to measure. Storage estimates are commonly obtained using transient-storage models (TSMs) of the experimentally obtained solute-tracer test data. The TSM equations represent key transport and storage processes with a suite of numerical parameters. Parameter values are estimated via inverse modeling, in which parameter values are iteratively changed until model simulations closely match observed solute-tracer data. Several investigators have shown that TSM parameter estimates can be highly uncertain. When this is the case, parameter values cannot be used reliably to interpret stream-reach functioning. However, authors of most TSM studies do not evaluate or report parameter certainty. Here, we present a software tool linked to the One-dimensional Transport with Inflow and Storage (OTIS) model that enables researchers to conduct uncertainty analyses via Monte-Carlo parameter sampling and to visualize uncertainty and sensitivity results. We demonstrate application of our tool to 2 case studies and compare our results to output obtained from more traditional implementation of the OTIS model. We conclude by suggesting best practices for transient-storage modeling and recommend that future applications of TSMs include assessments of parameter certainty to support comparisons and more reliable interpretations of transport processes.

Additional publication details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
A software tool to assess uncertainty in transient-storage model parameters using Monte Carlo simulations
Series title:
Freshwater Science
DOI:
10.1086/690444
Volume:
36
Issue:
1
Year Published:
2017
Language:
English
Publisher:
University of Chicago Press
Contributing office(s):
Colorado Water Science Center
Description:
23 p.
First page:
195
Last page:
217