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Volume 33 Issue 5
Oct 2022
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Robert E. Criss. Hydrologic Time Scale: A Fundamental Stream Characteristic. Journal of Earth Science, 2022, 33(5): 1291-1297. doi: 10.1007/s12583-022-1655-8
Citation: Robert E. Criss. Hydrologic Time Scale: A Fundamental Stream Characteristic. Journal of Earth Science, 2022, 33(5): 1291-1297. doi: 10.1007/s12583-022-1655-8

Hydrologic Time Scale: A Fundamental Stream Characteristic

doi: 10.1007/s12583-022-1655-8
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  • Corresponding author: Robert E. Criss,
  • Received Date: 22 Jan 2022
  • Accepted Date: 16 Mar 2022
  • Issue Publish Date: 30 Oct 2022
  • A new, fundamental catchment attribute called the hydrologic time scale τ governs the rate of delivery of runoff to a particular site, and is equal to $ \int {Q} dt/ \int|{d} {Q}|$, where Q is discharge and t is time. The value of τ for any gauged site is readily calculated from tabulated discharge data by replacing the integrals with sums. This quantity, coupled with the square root of catchment area, $ \sqrt{\mathit{A}} $, form a coordinate pair that embodies the characteristic time and length scales for any catchment, which govern its flow dynamics. The fitting constants used in several unit hydrograph models are simple multiples of τ, so knowledge of τ allows rapid calibration of these models for the particular site, facilitating flow prediction from rainfall data. Values of τ reflect many different landscape attributes, but for multiple sub-basins in watersheds with homogeneous land use and lithologic conditions, they correlate linearly with $ \sqrt{\mathit{A}} $. The ratio $ \sqrt{\mathit{A}}/\mathit{\tau } $ provides a characteristic velocity that is high for channelized, flood-prone rivers, for flashy urban streams with high impervious cover, and for sites downstream of hydropower dams. Sites with low velocities are resistant to flooding, as their landscapes have a greater ability to delay the delivery of runoff by retention, detention, and infiltration into the groundwater system.


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  • Baker, D. B., Richards, R. P., Loftus, T. T., et al., 2004. A New Flashiness Index: Characteristics and Applications to Midwestern Rivers and STREAMS1. JAWRA Journal of the American Water Resources Association, 40(2): 503–522.
    Bhunya, P. K., Berndtsson, R., Ojha, C. S. P., et al., 2007. Suitability of Gamma, Chi-Square, Weibull, and Beta Distributions as Synthetic Unit Hydrographs. Journal of Hydrology, 334(1/2): 28–38.
    Criss, R. E., 2018. Theoretical Link between Rainfall and Flood Magnitude. Hydrological Processes, 32(11): 1607–1615.
    Criss, R. E., Winston, W. E., 2003. Hydrograph for Small Basins Following Intense Storms. Geophysical Research Letters, 30(6): 1314.
    Criss, R. E., Winston, W. E., 2008. Discharge Predictions of a Rainfall-Driven Theoretical Hydrograph Compared to Common Models and Observed Data. Water Resources Research, 44(10): W10407.
    Ehlmann, B. L., Criss, R. E., 2006. Enhanced Stage and Stage Variability on the Lower Missouri River Benchmarked by Lewis and Clark. Geology, 34(11): 977.
    Frederickson, G. C., Criss, R. E., 1999. Isotope Hydrology and Residence Times of the Unimpounded Meramec River Basin, Missouri. Chemical Geology, 157(3/4): 303–317.
    Funk, J. L., Robinson, J. W., 1974. Changes in the Channel of the Lower Missouri River and Effects on Fish and Wildlife: Missouri Department of Conservation, Aquatic Series 11, Jefferson City
    Luo, M. M., Criss, R. E., 2018. Increasing Stage Variability of the Mississippi River. Journal of Hydrologic Engineering, 23(8): 05018016.
    MSDIS, 2022. Missouri Spatial Data Information Service, State-extent DEM. (last accessed in March 2022).
    Southard, R., Veilleux, A., 2014. Methods for Estimating Annual Exceedance-Probability Discharges and Largest Recorded Floods for Unregulated Streams in Rural Missouri. USGS Scientific Investigations Report, SIR 2014-5165, 39
    USGS, 2022a. USGS Current Water Data for Missouri. (last accessed in March 2022)
    USGS, 2022b. StreamStats: Streamflow Statistics and Spatial Analysis Tools for Water-Resources Applications. (last accessed in March 2022)
    Vineyard, J., Feder, G., 1982. Springs of Missouri. Missouri Geological Survey and Water Resources, WR 29, 212
    Winston, W. E., Criss, R. E., 2016. Dependence of Mean and Peak Streamflow on Basin Area in the Conterminous United States. Journal of Earth Science, 27(1): 83–88.
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