The University of Southampton
University of Southampton Institutional Repository

Detection time for plausible changes in annual precipitation, evapotranspiration, and streamflow in three Mississippi River sub-basins

Detection time for plausible changes in annual precipitation, evapotranspiration, and streamflow in three Mississippi River sub-basins
Detection time for plausible changes in annual precipitation, evapotranspiration, and streamflow in three Mississippi River sub-basins

We use diagnostic studies of off-line variable infiltration capacity (VIC) model simulations of terrestrial water budgets and 21st-century climate change simulations using the parallel climate model (PCM) to estimate the time required to detect predicted changes in annual precipitation (P), evapotranspiration (E), and discharge (Q) in three sub-basins of the Mississippi River Basin. Time series lengths on the order of 50-350 years are required to detect plausible P, E, and Q trends in the Missouri, Ohio, and Upper Mississippi River basins. Approximately 80-160, 50, and 140-350 years, respectively, are needed to detect the predicted P, E, and Q trends with a high degree of statistical confidence. These detection time estimates are based on conservative statistical criteria (α = 0.05 and β = 0.10) associated with low probability of both detecting a trend when it is not occurring (Type I error) and not detecting a trend when it is occurring (Type II error). The long detection times suggest that global-warming-induced changes in annual basin-wide hydro-climatic variables that may already be occurring in the three basins probably cannot yet be detected at this level of confidence. Furthermore, changes for some variables that may occur within the 21st century might not be detectable for many decades or until the following century - this may or may not be the case for individual recording station data. The long detection times for streamflow result from comparatively low signal-to-noise ratios in the annual time series. Finally, initial estimates suggest that faster detection of acceleration in the hydrological cycle may be possible using seasonal time series of appropriate hydro-climatic variables, rather than annual time series.

0165-0009
17-36
Ziegler, Alan D.
6698a535-0582-4fa6-9fed-17de7f752249
Maurer, Edwin P.
0e34ce05-e351-4c20-bf76-9916e5c47f91
Sheffield, Justin
dd66575b-a4dc-4190-ad95-df2d6aaaaa6b
Nijssen, Bart
fb1f5dcf-5fe0-483f-8570-81ab59b49353
Wood, Eric F.
8352c1b4-4fd3-42fe-bd23-46619024f1cf
Lettenmaier, Dennis P.
c3ae7db6-9f48-4875-8052-9e16fd099c09
Ziegler, Alan D.
6698a535-0582-4fa6-9fed-17de7f752249
Maurer, Edwin P.
0e34ce05-e351-4c20-bf76-9916e5c47f91
Sheffield, Justin
dd66575b-a4dc-4190-ad95-df2d6aaaaa6b
Nijssen, Bart
fb1f5dcf-5fe0-483f-8570-81ab59b49353
Wood, Eric F.
8352c1b4-4fd3-42fe-bd23-46619024f1cf
Lettenmaier, Dennis P.
c3ae7db6-9f48-4875-8052-9e16fd099c09

Ziegler, Alan D., Maurer, Edwin P., Sheffield, Justin, Nijssen, Bart, Wood, Eric F. and Lettenmaier, Dennis P. (2005) Detection time for plausible changes in annual precipitation, evapotranspiration, and streamflow in three Mississippi River sub-basins. Climatic Change, 72 (1-2), 17-36. (doi:10.1007/s10584-005-5379-4).

Record type: Article

Abstract

We use diagnostic studies of off-line variable infiltration capacity (VIC) model simulations of terrestrial water budgets and 21st-century climate change simulations using the parallel climate model (PCM) to estimate the time required to detect predicted changes in annual precipitation (P), evapotranspiration (E), and discharge (Q) in three sub-basins of the Mississippi River Basin. Time series lengths on the order of 50-350 years are required to detect plausible P, E, and Q trends in the Missouri, Ohio, and Upper Mississippi River basins. Approximately 80-160, 50, and 140-350 years, respectively, are needed to detect the predicted P, E, and Q trends with a high degree of statistical confidence. These detection time estimates are based on conservative statistical criteria (α = 0.05 and β = 0.10) associated with low probability of both detecting a trend when it is not occurring (Type I error) and not detecting a trend when it is occurring (Type II error). The long detection times suggest that global-warming-induced changes in annual basin-wide hydro-climatic variables that may already be occurring in the three basins probably cannot yet be detected at this level of confidence. Furthermore, changes for some variables that may occur within the 21st century might not be detectable for many decades or until the following century - this may or may not be the case for individual recording station data. The long detection times for streamflow result from comparatively low signal-to-noise ratios in the annual time series. Finally, initial estimates suggest that faster detection of acceleration in the hydrological cycle may be possible using seasonal time series of appropriate hydro-climatic variables, rather than annual time series.

This record has no associated files available for download.

More information

Published date: September 2005
Additional Information: Funding Information: This work is supported by NASA grants NAG5-9414, NAG5-9886. PCM data were downloaded with permission from the UCAR website (http://www.cgd.ucar. edu/pcm/). A special thanks to Ross A. Sutherland for tying up some loose ends in the notation.

Identifiers

Local EPrints ID: 480735
URI: http://eprints.soton.ac.uk/id/eprint/480735
ISSN: 0165-0009
PURE UUID: 68d362e6-751f-4452-842a-5024bc9d9d82
ORCID for Justin Sheffield: ORCID iD orcid.org/0000-0003-2400-0630

Catalogue record

Date deposited: 09 Aug 2023 16:49
Last modified: 18 Mar 2024 03:33

Export record

Altmetrics

Contributors

Author: Alan D. Ziegler
Author: Edwin P. Maurer
Author: Bart Nijssen
Author: Eric F. Wood
Author: Dennis P. Lettenmaier

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×