Effect of bedrock permeability on stream base flow mean transit time scaling relationships: 2. Process study of storage and release

Effect of bedrock permeability on stream base flow mean transit time scaling relationships: 2. Process study of storage and release

In Part 1 of this two‐part series, Hale and McDonnell (2016) showed that bedrock permeability controlled base flow mean transit times (MTTs) and MTT scaling relations across two different catchment geologies in western Oregon. This paper presents a process‐based investigation of storage and release...

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Bibliographic Details
Published in:Water resources research Vol. 52; no. 2; pp. 1375 - 1397
Main Authors: Hale, V. Cody, McDonnell, Jeffrey J., Stewart, Michael K., Solomon, D. Kip, Doolitte, Jim, Ice, George G., Pack, Robert T.
Format: Journal Article
Language:English
Published: Washington John Wiley & Sons, Inc 01-02-2016
Subjects:
Alluvial plains
Base flow
Bedrock
bedrock groundwater
Catchment areas
catchment storage
Groundwater dating
groundwater/surface water interaction
isotope hydrology
mean transit time
Permeability
Stormwater
Stream discharge
Stream flow
Subsurface water
INE, USA, Oregon
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Summary:In Part 1 of this two‐part series, Hale and McDonnell (2016) showed that bedrock permeability controlled base flow mean transit times (MTTs) and MTT scaling relations across two different catchment geologies in western Oregon. This paper presents a process‐based investigation of storage and release in the more permeable catchments to explain the longer MTTs and (catchment) area‐dependent scaling. Our field‐based study includes hydrometric, MTT, and groundwater dating to better understand the role of subsurface catchment storage in setting base flow MTTs. We show that base flow MTTs were controlled by a mixture of water from discrete storage zones: (1) soil, (2) shallow hillslope bedrock, (3) deep hillslope bedrock, (4) surficial alluvial plain, and (5) suballuvial bedrock. We hypothesize that the relative contributions from each component change with catchment area. Our results indicate that the positive MTT‐area scaling relationship observed in Part 1 is a result of older, longer flow path water from the suballuvial zone becoming a larger proportion of streamflow in a downstream direction (i.e., with increasing catchment area). Our work suggests that the subsurface permeability structure represents the most basic control on how subsurface water is stored and therefore is perhaps the best direct predictor of base flow MTT (i.e., better than previously derived morphometric‐based predictors). Our discrete storage zone concept is a process explanation for the observed scaling behavior of Hale and McDonnell (2016), thereby linking patterns and processes at scales from 0.1 to 100 km2. Key Points: Distinct subsurface storage zones with unique water ages identified Dynamic mixture of storage zones sets stream water mean transit time Subsurface permeability contrasts dictate storage zone discretization
Bibliography:[2016], doi
Hale and McDonnell
.
Companion to
10.1002/2014WR016124
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0043-1397
1944-7973
DOI:10.1002/2015WR017660