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

Freshwater Science
By: , and 

Links

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.

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
Google Analytic Metrics Metrics page
Additional publication details