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Scaling and predicting solute transport processes in streams
Author(s) -
GonzálezPinzón Ricardo,
Haggerty Roy,
Dentz Marco
Publication year - 2013
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/wrcr.20280
Subject(s) - streams , skewness , scaling , continuous time random walk , hydrology (agriculture) , environmental science , moment (physics) , statistical physics , gumbel distribution , random walk , statistics , mathematics , geology , extreme value theory , physics , geometry , geotechnical engineering , computer network , classical mechanics , computer science
We investigated scaling of conservative solute transport using temporal moment analysis of 98 tracer experiments (384 breakthrough curves) conducted in 44 streams located on five continents. The experiments span 7 orders of magnitude in discharge (10 −3 to 10 3 m 3 /s), span 5 orders of magnitude in longitudinal scale (10 1 to 10 5 m), and sample different lotic environments—forested headwater streams, hyporheic zones, desert streams, major rivers, and an urban manmade channel. Our meta‐analysis of these data reveals that the coefficient of skewness is constant over time ( CSK = 1.18 ± 0.08 ,R 2 > 0.98 ). In contrast, the CSK of all commonly used solute transport models decreases over time. This shows that current theory is inconsistent with experimental data and suggests that a revised theory of solute transport is needed. Our meta‐analysis also shows that the variance (second normalized central moment) is correlated with the mean travel time ( R 2 > 0.86 ), and the third normalized central moment and the product of the first two are very strongly correlated ( R 2 > 0.96 ). These correlations were applied in four different streams to predict transport based on the transient storage and the aggregated dead zone models, and two probability distributions (Gumbel and log normal).