Articles | Volume 21, issue 1
https://doi.org/10.5194/hess-21-65-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-21-65-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
04 Jan 2017
Research article |
| 04 Jan 2017
Event-scale power law recession analysis: quantifying methodological uncertainty
University of California Berkeley, Department of Civil and Environmental Engineering, Berkeley, CA, USA
Nathaniel J. Karst
Babson College, Department of Mathematics, Wellesley, MA, USA
Kyriakos Charalampous
University of California Berkeley, Department of Civil and Environmental Engineering, Berkeley, CA, USA
University of Bristol, Department of Civil Engineering, Bristol, UK
Andrew Veenstra
University of California Berkeley, Department of Civil and Environmental Engineering, Berkeley, CA, USA
Sally E. Thompson
University of California Berkeley, Department of Civil and Environmental Engineering, Berkeley, CA, USA
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- A review of hydrologic signatures and their applications H. McMillan 10.1002/wat2.1499
- Event‐Based Recession Analysis for Estimation of Basin‐Wide Characteristic Drainage Timescale and Groundwater Storage Trends M. Hameed et al. 10.1029/2023WR035829
- Atmospheric dynamics of extreme discharge events from 1979 to 2016 in the southern Central Andes F. Castino et al. 10.1007/s00382-020-05458-1
- Baseflow estimation based on a self-adaptive non-linear reservoir algorithm in a rainy watershed of eastern China S. He et al. 10.1016/j.jenvman.2023.117379
- Estimation of streamflow recession parameters: New insights from an analytic streamflow distribution model A. Santos et al. 10.1002/hyp.13425
- Decorrelation is not dissociation: There is no means to entirely decouple the Brutsaert-Nieber parameters in streamflow recession analysis B. Biswal 10.1016/j.advwatres.2020.103822
- Seasonal growth potential of Oncorhynchus mykiss in streams with contrasting prey phenology and streamflow G. Rossi et al. 10.1002/ecs2.4211
- Soil frost effects on streamflow recessions in a subarctic catchment S. Ploum et al. 10.1002/hyp.13401
- Characterizing hydrograph recessions from satellite-derived soil moisture S. Basso et al. 10.1016/j.scitotenv.2020.143469
- A multiple hydrograph separation technique for identifying hydrological model structures and an interpretation of dominant process controls on flow duration curves C. Leong & Y. Yokoo 10.1002/hyp.14569
- When good signatures go bad: Applying hydrologic signatures in large sample studies H. McMillan et al. 10.1002/hyp.14987
- Landscape structures regulate the contrasting response of recession along rainfall amounts J. Lee et al. 10.5194/hess-27-4279-2023
- baseflow: a MATLAB and GNU Octave package for baseflow recession analysis M. Cooper & T. Zhou 10.21105/joss.05492
- Hydrograph recession extraction algorithm (HYDRA): Minimizing influence of stage uncertainty in identification of recession events B. Thomas 10.1016/j.advwatres.2021.103937
- A statistical approach for identifying factors governing streamflow recession behaviour H. Li & A. Ameli 10.1002/hyp.14718
- Long-term decline in rainfall causing depletion in groundwater aquifer storage sustaining the springflow in the middle-Himalayan headwaters S. Tarafdar & S. Dutta 10.1007/s12040-023-02136-8
- Recession analysis revisited: impacts of climate on parameter estimation E. Jachens et al. 10.5194/hess-24-1159-2020
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- Changes in nonlinearity and stability of streamflow recession characteristics under climate warming in a large glaciated basin of the Tibetan Plateau J. Wang et al. 10.5194/hess-26-3901-2022
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- Recession curve power-law exponent estimation: is there a perfect approach? D. Sharma & B. Biswal 10.1080/02626667.2022.2070022
- Catchment processes can amplify the effect of increasing rainfall variability M. Müller et al. 10.1088/1748-9326/ac153e
- Recession flow prediction in gauged and ungauged basins by just considering past discharge information C. Reddyvaraprasad et al. 10.1080/02626667.2019.1643465
- Watershed‐Scale Effective Hydraulic Properties of the Continental United States A. Tashie et al. 10.1029/2020MS002440
- Increasing non‐linearity of the storage‐discharge relationship in sub‐Arctic catchments A. Hinzman et al. 10.1002/hyp.13860
- Inferring heavy tails of flood distributions through hydrograph recession analysis H. Wang et al. 10.5194/hess-27-4369-2023
- An Empirical Reevaluation of Streamflow Recession Analysis at the Continental Scale A. Tashie et al. 10.1029/2019WR025448
- Baseflow and transmission loss: A review T. McMahon & R. Nathan 10.1002/wat2.1527
- Universal recession constants and their potential to predict recession flow D. Sharma et al. 10.1016/j.jhydrol.2023.130244
- Impact of climate and NDVI changes on catchment storage–discharge dynamics in southern Taiwan C. Huang & H. Yeh 10.1080/02626667.2022.2114835
- The Role of Inflow and Infiltration (I/I) in Urban Water Balances and Streamflow Regimes: A Hydrograph Analysis Along the Sewershed‐Watershed Continuum K. Zhang et al. 10.1029/2022WR032529
- Foraging modes and movements of Oncorhynchus mykiss as flow and invertebrate drift recede in a California stream G. Rossi et al. 10.1139/cjfas-2020-0398
- Evaluation of seasonal catchment dynamic storage components using an analytical streamflow duration curve model C. Huang & H. Yeh 10.1186/s42834-022-00161-8
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- A Nonlinear Recession Model for Horizontal Aquifers H. Basha 10.1029/2022WR034297
- Representing Bidirectional Hydraulic Continuum Between the Stream and Hillslope in the National Water Model for Improved Streamflow Prediction M. Hong & B. Mohanty 10.1029/2022MS003325
- On the Effect of Nonlinear Recessions on Low Flow Variability: Diagnostic of an Analytical Model for Annual Flow Duration Curves N. Karst et al. 10.1029/2019WR024912
- Flow dynamics at the continental scale: Streamflow correlation and hydrological similarity A. Betterle et al. 10.1002/hyp.13350
- A probabilistic framework for robust master recession curve parameterization M. Gao et al. 10.1016/j.jhydrol.2023.129922
- Streamflow Recession Analysis Using Water Height E. Jachens et al. 10.1029/2020WR027091
- A proposed composite Boussinesq equation for estimating baseflow recessions and storage-outflow relationship M. Alattar & T. Troy 10.1016/j.jhydrol.2023.130321
- Spatial and Temporal Patterns in Baseflow Recession in the Continental United States A. Tashie et al. 10.1029/2019WR026425
- Time‐Variability of Flow Recession Dynamics: Application of Machine Learning and Learning From the Machine M. Kim et al. 10.1029/2022WR032690
- Stochastic modeling of interannual variation of hydrologic variables D. Dralle et al. 10.1002/2017GL074139
- Age‐Ranked Storage‐Discharge Relations: A Unified Description of Spatially Lumped Flow and Water Age in Hydrologic Systems C. Harman 10.1029/2017WR022304
- Predicting baseflow recession characteristics at ungauged stream locations using a physical and machine learning approach K. Eng et al. 10.1016/j.advwatres.2023.104440
- Large Scale Evaluation of Relationships Between Hydrologic Signatures and Processes H. McMillan et al. 10.1029/2021WR031751
50 citations as recorded by crossref.
- Characterization of Basin-Scale Dynamic Storage–Discharge Relationship Using Daily GRACE Based Storage Anomaly Data D. Sharma et al. 10.3390/geosciences10100404
- A review of hydrologic signatures and their applications H. McMillan 10.1002/wat2.1499
- Event‐Based Recession Analysis for Estimation of Basin‐Wide Characteristic Drainage Timescale and Groundwater Storage Trends M. Hameed et al. 10.1029/2023WR035829
- Atmospheric dynamics of extreme discharge events from 1979 to 2016 in the southern Central Andes F. Castino et al. 10.1007/s00382-020-05458-1
- Baseflow estimation based on a self-adaptive non-linear reservoir algorithm in a rainy watershed of eastern China S. He et al. 10.1016/j.jenvman.2023.117379
- Estimation of streamflow recession parameters: New insights from an analytic streamflow distribution model A. Santos et al. 10.1002/hyp.13425
- Decorrelation is not dissociation: There is no means to entirely decouple the Brutsaert-Nieber parameters in streamflow recession analysis B. Biswal 10.1016/j.advwatres.2020.103822
- Seasonal growth potential of Oncorhynchus mykiss in streams with contrasting prey phenology and streamflow G. Rossi et al. 10.1002/ecs2.4211
- Soil frost effects on streamflow recessions in a subarctic catchment S. Ploum et al. 10.1002/hyp.13401
- Characterizing hydrograph recessions from satellite-derived soil moisture S. Basso et al. 10.1016/j.scitotenv.2020.143469
- A multiple hydrograph separation technique for identifying hydrological model structures and an interpretation of dominant process controls on flow duration curves C. Leong & Y. Yokoo 10.1002/hyp.14569
- When good signatures go bad: Applying hydrologic signatures in large sample studies H. McMillan et al. 10.1002/hyp.14987
- Landscape structures regulate the contrasting response of recession along rainfall amounts J. Lee et al. 10.5194/hess-27-4279-2023
- baseflow: a MATLAB and GNU Octave package for baseflow recession analysis M. Cooper & T. Zhou 10.21105/joss.05492
- Hydrograph recession extraction algorithm (HYDRA): Minimizing influence of stage uncertainty in identification of recession events B. Thomas 10.1016/j.advwatres.2021.103937
- A statistical approach for identifying factors governing streamflow recession behaviour H. Li & A. Ameli 10.1002/hyp.14718
- Long-term decline in rainfall causing depletion in groundwater aquifer storage sustaining the springflow in the middle-Himalayan headwaters S. Tarafdar & S. Dutta 10.1007/s12040-023-02136-8
- Recession analysis revisited: impacts of climate on parameter estimation E. Jachens et al. 10.5194/hess-24-1159-2020
- Including Regional Knowledge Improves Baseflow Signature Predictions in Large Sample Hydrology S. Gnann et al. 10.1029/2020WR028354
- Changes in nonlinearity and stability of streamflow recession characteristics under climate warming in a large glaciated basin of the Tibetan Plateau J. Wang et al. 10.5194/hess-26-3901-2022
- Detecting Permafrost Active Layer Thickness Change From Nonlinear Baseflow Recession M. Cooper et al. 10.1029/2022WR033154
- An improved method to estimate the rate of change of streamflow recession and basin synthetic recession parameters from hydrographs M. Gao et al. 10.1016/j.jhydrol.2021.127254
- Recession curve power-law exponent estimation: is there a perfect approach? D. Sharma & B. Biswal 10.1080/02626667.2022.2070022
- Catchment processes can amplify the effect of increasing rainfall variability M. Müller et al. 10.1088/1748-9326/ac153e
- Recession flow prediction in gauged and ungauged basins by just considering past discharge information C. Reddyvaraprasad et al. 10.1080/02626667.2019.1643465
- Watershed‐Scale Effective Hydraulic Properties of the Continental United States A. Tashie et al. 10.1029/2020MS002440
- Increasing non‐linearity of the storage‐discharge relationship in sub‐Arctic catchments A. Hinzman et al. 10.1002/hyp.13860
- Inferring heavy tails of flood distributions through hydrograph recession analysis H. Wang et al. 10.5194/hess-27-4369-2023
- An Empirical Reevaluation of Streamflow Recession Analysis at the Continental Scale A. Tashie et al. 10.1029/2019WR025448
- Baseflow and transmission loss: A review T. McMahon & R. Nathan 10.1002/wat2.1527
- Universal recession constants and their potential to predict recession flow D. Sharma et al. 10.1016/j.jhydrol.2023.130244
- Impact of climate and NDVI changes on catchment storage–discharge dynamics in southern Taiwan C. Huang & H. Yeh 10.1080/02626667.2022.2114835
- The Role of Inflow and Infiltration (I/I) in Urban Water Balances and Streamflow Regimes: A Hydrograph Analysis Along the Sewershed‐Watershed Continuum K. Zhang et al. 10.1029/2022WR032529
- Foraging modes and movements of Oncorhynchus mykiss as flow and invertebrate drift recede in a California stream G. Rossi et al. 10.1139/cjfas-2020-0398
- Evaluation of seasonal catchment dynamic storage components using an analytical streamflow duration curve model C. Huang & H. Yeh 10.1186/s42834-022-00161-8
- Storage-Discharge Relationships under Forest Cover Change in Ethiopian Highlands S. Gebrehiwot et al. 10.3390/w13162310
- A new method for effective parameterization of catchment-scale aquifer through event-scale recession analysis M. Hong & B. Mohanty 10.1016/j.advwatres.2023.104408
- Transpiration and subsurface controls of streamflow recession characteristics A. Tashie et al. 10.1002/hyp.13530
- A Nonlinear Recession Model for Horizontal Aquifers H. Basha 10.1029/2022WR034297
- Representing Bidirectional Hydraulic Continuum Between the Stream and Hillslope in the National Water Model for Improved Streamflow Prediction M. Hong & B. Mohanty 10.1029/2022MS003325
- On the Effect of Nonlinear Recessions on Low Flow Variability: Diagnostic of an Analytical Model for Annual Flow Duration Curves N. Karst et al. 10.1029/2019WR024912
- Flow dynamics at the continental scale: Streamflow correlation and hydrological similarity A. Betterle et al. 10.1002/hyp.13350
- A probabilistic framework for robust master recession curve parameterization M. Gao et al. 10.1016/j.jhydrol.2023.129922
- Streamflow Recession Analysis Using Water Height E. Jachens et al. 10.1029/2020WR027091
- A proposed composite Boussinesq equation for estimating baseflow recessions and storage-outflow relationship M. Alattar & T. Troy 10.1016/j.jhydrol.2023.130321
- Spatial and Temporal Patterns in Baseflow Recession in the Continental United States A. Tashie et al. 10.1029/2019WR026425
- Time‐Variability of Flow Recession Dynamics: Application of Machine Learning and Learning From the Machine M. Kim et al. 10.1029/2022WR032690
- Stochastic modeling of interannual variation of hydrologic variables D. Dralle et al. 10.1002/2017GL074139
- Age‐Ranked Storage‐Discharge Relations: A Unified Description of Spatially Lumped Flow and Water Age in Hydrologic Systems C. Harman 10.1029/2017WR022304
- Predicting baseflow recession characteristics at ungauged stream locations using a physical and machine learning approach K. Eng et al. 10.1016/j.advwatres.2023.104440
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Latest update: 13 Nov 2024
Short summary
The streamflow recession is the period following rainfall during which flow declines. This paper examines a common method of recession analysis and identifies sensitivity of the technique's results to necessary, yet subjective, methodological choices. The results have implications for hydrology, sediment and solute transport, and geomorphology, as well as for testing numerous hydrologic theories which predict the mathematical form of the recession.
The streamflow recession is the period following rainfall during which flow declines. This paper...
