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Effect of bedrock permeability on stream base flow mean transit time scaling relationships: 2. Process study of storage and release
Author(s) -
Hale V. Cody,
McDonnell Jeffrey J.,
Stewart Michael K.,
Solomon D. Kip,
Doolitte Jim,
Ice George G.,
Pack Robert T.
Publication year - 2016
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1002/2015wr017660
Subject(s) - bedrock , mean transit time , base flow , hydrology (agriculture) , scaling , alluvium , geology , permeability (electromagnetism) , drainage basin , groundwater , streams , hydraulic conductivity , soil science , environmental science , geomorphology , geotechnical engineering , soil water , chemistry , geometry , mathematics , geography , perfusion scanning , membrane , biochemistry , perfusion , cardiology , medicine , cartography , computer network , computer science
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 km 2 .