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Open AccessFeature PaperArticle

Ubiquitous Fractal Scaling and Filtering Behavior of Hydrologic Fluxes and Storages from A Mountain Headwater Catchment

1
Department of Hydrology and Atmospheric Sciences, The University of Arizona, Tucson, AZ 85721, USA
2
Vermont EPSCoR, The University of Vermont, Burlington, VT 05405, USA
3
Southwest Watershed Research Center, USDA-Agricultural Research Service, Tucson, AZ 85719, USA
4
School of Geography and Development, The University of Arizona, Tucson, AZ 85721, USA
5
Department of Geosciences (retired), The University of Arizona, Tucson, AZ 85721, USA
6
Biosphere 2, The University of Arizona, Tucson, AZ 85739, USA
7
School of Natural Resources and the Environment, The University of Arizona, Tucson, AZ 85721, USA
8
Department of Ecosystem Science and Management, Texas A&M University, TX 77843, USA
9
Laboratory of Tree-Ring Research, The University of Arizona, Tucson, AZ 85721, USA
10
Mt. Lemmon Water District, Tucson, AZ 85751, USA
11
Department of Environmental Science, The University of Arizona, Tucson, AZ 85721, USA
*
Author to whom correspondence should be addressed.
Water 2020, 12(2), 613; https://doi.org/10.3390/w12020613
Received: 17 January 2020 / Revised: 19 February 2020 / Accepted: 20 February 2020 / Published: 24 February 2020
We used the weighted wavelet method to perform spectral analysis of observed long-term precipitation, streamflow, actual evapotranspiration, and soil water storage at a sub-humid mountain catchment near Tucson, Arizona, USA. Fractal scaling in precipitation and the daily change in soil water storage occurred up to a period of 14 days and corresponded to the typical duration of relatively wet and dry intervals. In contrast, fractal scaling could be observed up to a period of 0.5 years in streamflow and actual evapotranspiration. By considering long-term observations of hydrologic fluxes and storages, we show that, in contrast to previous findings, the phase relationships between water balance components changed with component period and were not perfectly in or out of phase at all periods. Self-averaging behavior was apparent, but the temporal scales over which this behavior was applicable differed among the various water balance components. Conservative tracer analysis showed that this catchment acted as a fractal filter by transforming white noise in the precipitation input signal to a 1/f flicker in the streamflow output signal by means of both spatial and temporal subsurface advection and dispersion processes and soil wetting properties. This study provides an improved understanding of hydrological filtering behavior in mountain critical zones that are critical sources of water and ecosystem services throughout the world. View Full-Text
Keywords: spectral analysis; wavelet analysis; self-averaging behavior; time series analysis; fractal filter; fractal scaling; phase spectrum; catchment water balance spectral analysis; wavelet analysis; self-averaging behavior; time series analysis; fractal filter; fractal scaling; phase spectrum; catchment water balance
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Dwivedi, R.; Knowles, J.F.; Eastoe, C.; Minor, R.; Abramson, N.; Mitra, B.; Wright, W.E.; McIntosh, J.; Meixner, T.; “Ty” Ferre, P.A.; Castro, C.; Niu, G.-Y.; Barron-Gafford, G.A.; Stanley, M.; Chorover, J. Ubiquitous Fractal Scaling and Filtering Behavior of Hydrologic Fluxes and Storages from A Mountain Headwater Catchment. Water 2020, 12, 613.

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