Articles | Volume 10, issue 1
https://doi.org/10.5194/hess-10-79-2006
© Author(s) 2006. This work is licensed under
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
https://doi.org/10.5194/hess-10-79-2006
© Author(s) 2006. This work is licensed under
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
14 Feb 2006
Scale invariance of daily runoff time series in agricultural watersheds
X. Zhou
Department of Crop and Soil Sciences, The Pennsylvania State University, University Park, PA 16802, USA
N. Persaud
Department of Crop and Soil Environmental Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA
H. Wang
Soil and Water Science Department, University of Florida, Gainesville, FL 32601, USA
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Cited
18 citations as recorded by crossref.
- The spatio‐temporal variability of annual precipitation and its local impact factors during 1724–2010 in Beijing, China Y. Zhai et al. https://doi.org/10.1002/hyp.9772
- Scaling properties of the runoff variations in the arid and semi-arid regions of China: a case study of the Yellow River basin Q. Zhang et al. https://doi.org/10.1007/s00477-008-0285-8
- Multifractal analysis of streamflow records of the East River basin (Pearl River), China Q. Zhang et al. https://doi.org/10.1016/j.physa.2008.11.025
- Seasonal and spatial variations in the scaling and correlation structure of streamflow data M. Özger et al. https://doi.org/10.1002/hyp.9314
- Hurst Analysis of Hydrologic and Water Quality Time Series S. Koirala et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000357
- Temporal scaling in hydrological variables: Methods, patterns, and comparative insights Y. Zhou et al. https://doi.org/10.1016/j.horiz.2025.100170
- The sampling properties of Hurst exponent estimates C. Ellis https://doi.org/10.1016/j.physa.2006.08.046
- Web data mining for automatic inventory of geohazards at national scale A. Battistini et al. https://doi.org/10.1016/j.apgeog.2013.06.012
- Characteristics and Multifractal Properties of Daily Streamflow in a Semiarid Environment S. Emadi et al. https://doi.org/10.1007/s40996-016-0007-2
- Multiscaling Analysis of Monthly Runoff Series Using Improved MF-DFA Approach X. Yuan et al. https://doi.org/10.1007/s11269-014-0715-y
- Development of Adaptive Time-Weighted Dynamic Time Warping for Time Series Vegetation Classification Using Satellite Images in Solapur District M. Kumawat & A. Khaparde https://doi.org/10.1093/comjnl/bxac057
- MULTIFRACTAL SCALING OF DAILY RUNOFF TIME SERIES IN AGRICULTURAL WATERSHEDS1 X. Zhou et al. https://doi.org/10.1111/j.1752-1688.2006.tb06027.x
- Fractal Analysis of Mining Wastewater Time Series Parameters: Balkhash Urban Region and Sayak Ore District A. Biloshchytskyi et al. https://doi.org/10.3390/urbansci8040200
- The complex nonlinear systems with fractal as well as chaotic dynamics of annual runoff processes in the three headwaters of the Tarim River J. Xu et al. https://doi.org/10.1007/s11442-009-0025-0
- Sudden drop of fractal dimension of electromagnetic emissions recorded prior to significant earthquake S. Potirakis et al. https://doi.org/10.1007/s11069-012-0262-x
- Characterisation of extreme precipitation changes in the upper reaches of the Yangtze River, China T. Chen et al. https://doi.org/10.2166/ws.2024.106
- Analysis of time series data on agroecosystem vegetation using predictive clustering trees M. Debeljak et al. https://doi.org/10.1016/j.ecolmodel.2010.10.021
- Current awareness https://doi.org/10.1002/hyp.6366
18 citations as recorded by crossref.
- The spatio‐temporal variability of annual precipitation and its local impact factors during 1724–2010 in Beijing, China Y. Zhai et al. https://doi.org/10.1002/hyp.9772
- Scaling properties of the runoff variations in the arid and semi-arid regions of China: a case study of the Yellow River basin Q. Zhang et al. https://doi.org/10.1007/s00477-008-0285-8
- Multifractal analysis of streamflow records of the East River basin (Pearl River), China Q. Zhang et al. https://doi.org/10.1016/j.physa.2008.11.025
- Seasonal and spatial variations in the scaling and correlation structure of streamflow data M. Özger et al. https://doi.org/10.1002/hyp.9314
- Hurst Analysis of Hydrologic and Water Quality Time Series S. Koirala et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000357
- Temporal scaling in hydrological variables: Methods, patterns, and comparative insights Y. Zhou et al. https://doi.org/10.1016/j.horiz.2025.100170
- The sampling properties of Hurst exponent estimates C. Ellis https://doi.org/10.1016/j.physa.2006.08.046
- Web data mining for automatic inventory of geohazards at national scale A. Battistini et al. https://doi.org/10.1016/j.apgeog.2013.06.012
- Characteristics and Multifractal Properties of Daily Streamflow in a Semiarid Environment S. Emadi et al. https://doi.org/10.1007/s40996-016-0007-2
- Multiscaling Analysis of Monthly Runoff Series Using Improved MF-DFA Approach X. Yuan et al. https://doi.org/10.1007/s11269-014-0715-y
- Development of Adaptive Time-Weighted Dynamic Time Warping for Time Series Vegetation Classification Using Satellite Images in Solapur District M. Kumawat & A. Khaparde https://doi.org/10.1093/comjnl/bxac057
- MULTIFRACTAL SCALING OF DAILY RUNOFF TIME SERIES IN AGRICULTURAL WATERSHEDS1 X. Zhou et al. https://doi.org/10.1111/j.1752-1688.2006.tb06027.x
- Fractal Analysis of Mining Wastewater Time Series Parameters: Balkhash Urban Region and Sayak Ore District A. Biloshchytskyi et al. https://doi.org/10.3390/urbansci8040200
- The complex nonlinear systems with fractal as well as chaotic dynamics of annual runoff processes in the three headwaters of the Tarim River J. Xu et al. https://doi.org/10.1007/s11442-009-0025-0
- Sudden drop of fractal dimension of electromagnetic emissions recorded prior to significant earthquake S. Potirakis et al. https://doi.org/10.1007/s11069-012-0262-x
- Characterisation of extreme precipitation changes in the upper reaches of the Yangtze River, China T. Chen et al. https://doi.org/10.2166/ws.2024.106
- Analysis of time series data on agroecosystem vegetation using predictive clustering trees M. Debeljak et al. https://doi.org/10.1016/j.ecolmodel.2010.10.021
- Current awareness https://doi.org/10.1002/hyp.6366
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