Articles | Volume 11, issue 2
https://doi.org/10.5194/hess-11-851-2007
© Author(s) 2007. 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-11-851-2007
© Author(s) 2007. This work is licensed under
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
06 Feb 2007
Detecting long-memory: Monte Carlo simulations and application to daily streamflow processes
W. Wang
Faculty of Civil Engineering & Geosciences, Section of Hydraulic Engineering, Delft University of Technology, 2628 CN Delft, Netherlands
State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, 210098, China
P. H. A. J. M. Van Gelder
Faculty of Civil Engineering & Geosciences, Section of Hydraulic Engineering, Delft University of Technology, 2628 CN Delft, Netherlands
J. K. Vrijling
Faculty of Civil Engineering & Geosciences, Section of Hydraulic Engineering, Delft University of Technology, 2628 CN Delft, Netherlands
X. Chen
State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, 210098, China
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Cited
23 citations as recorded by crossref.
- Comparison of standard long memory time series H. Silva et al. https://doi.org/10.1080/00949655.2023.2280804
- Understanding Persistence to Avoid Underestimation of Collective Flood Risk F. Serinaldi & C. Kilsby https://doi.org/10.3390/w8040152
- All in order: Distribution of serially correlated order statistics with applications to hydrological extremes F. Serinaldi et al. https://doi.org/10.1016/j.advwatres.2020.103686
- The role of climatic variables in winter cereal yields: a retrospective analysis Q. Luo & L. Wen https://doi.org/10.1007/s00484-014-0834-4
- Complexity–entropy analysis of daily stream flow time series in the continental United States F. Serinaldi et al. https://doi.org/10.1007/s00477-013-0825-8
- Detection of changes in hydrologic system memory associated with urbanization in the Great Lakes region G. Yang & L. Bowling https://doi.org/10.1002/2014WR015339
- Unraveling the long-term persistence of streamflow in China and its controlling factors T. Cui et al. https://doi.org/10.1016/j.ejrh.2026.103397
- Impact of EMD decomposition and random initialisation of weights in ANN hindcasting of daily stream flow series: An empirical examination G. Napolitano et al. https://doi.org/10.1016/j.jhydrol.2011.06.015
- Temporal Analysis of the Flows of the Rivers that form the Hydrographic Basin of Moquegua (Peru) O. Toledo et al. https://doi.org/10.1142/S0219477522500596
- Does Pegging Affect Market Efficiency? Assessing Long Memory in Stablecoin and Cryptocurrency Markets Q. Yan et al. https://doi.org/10.1111/infi.70020
- Do general elections affect fractal structure of stock market? C. Cheong et al. https://doi.org/10.1080/09720510.2020.1776943
- Multisite daily precipitation simulation in Singapore S. Suroso et al. https://doi.org/10.1051/matecconf/201819505007
- Non-asymptotic distributions of water extremes: much ado about what? F. Serinaldi et al. https://doi.org/10.5194/hess-29-1159-2025
- When will Lake Mead go dry? T. Barnett & D. Pierce https://doi.org/10.1029/2007WR006704
- How are rescaled range analyses affected by different memory and distributional properties? A Monte Carlo study L. Kristoufek https://doi.org/10.1016/j.physa.2012.04.005
- A Blueprint for Full Collective Flood Risk Estimation: Demonstration for European River Flooding F. Serinaldi & C. Kilsby https://doi.org/10.1111/risa.12747
- Understanding long-term persistence and multifractal behaviors in river runoff: A detailed study over eastern China W. Wu et al. https://doi.org/10.1016/j.physa.2019.122042
- Assessment of impact of climate change on water resources: a long term analysis of the Great Lakes of North America E. McBean & H. Motiee https://doi.org/10.5194/hess-12-239-2008
- Characterization of river flow fluctuations via horizontal visibility graphs A. Braga et al. https://doi.org/10.1016/j.physa.2015.10.102
- Structural break or long memory: an empirical survey on daily rainfall data sets across Malaysia F. Yusof et al. https://doi.org/10.5194/hess-17-1311-2013
- Deterministic versus stochastic trends: Detection and challenges S. Fatichi et al. https://doi.org/10.1029/2009JD011960
- Global estimation of long-term persistence in annual river runoff Y. Markonis et al. https://doi.org/10.1016/j.advwatres.2018.01.003
- Quantifying multi-year hydrological memory with Catchment Forgetting Curves A. de Lavenne et al. https://doi.org/10.5194/hess-26-2715-2022
23 citations as recorded by crossref.
- Comparison of standard long memory time series H. Silva et al. https://doi.org/10.1080/00949655.2023.2280804
- Understanding Persistence to Avoid Underestimation of Collective Flood Risk F. Serinaldi & C. Kilsby https://doi.org/10.3390/w8040152
- All in order: Distribution of serially correlated order statistics with applications to hydrological extremes F. Serinaldi et al. https://doi.org/10.1016/j.advwatres.2020.103686
- The role of climatic variables in winter cereal yields: a retrospective analysis Q. Luo & L. Wen https://doi.org/10.1007/s00484-014-0834-4
- Complexity–entropy analysis of daily stream flow time series in the continental United States F. Serinaldi et al. https://doi.org/10.1007/s00477-013-0825-8
- Detection of changes in hydrologic system memory associated with urbanization in the Great Lakes region G. Yang & L. Bowling https://doi.org/10.1002/2014WR015339
- Unraveling the long-term persistence of streamflow in China and its controlling factors T. Cui et al. https://doi.org/10.1016/j.ejrh.2026.103397
- Impact of EMD decomposition and random initialisation of weights in ANN hindcasting of daily stream flow series: An empirical examination G. Napolitano et al. https://doi.org/10.1016/j.jhydrol.2011.06.015
- Temporal Analysis of the Flows of the Rivers that form the Hydrographic Basin of Moquegua (Peru) O. Toledo et al. https://doi.org/10.1142/S0219477522500596
- Does Pegging Affect Market Efficiency? Assessing Long Memory in Stablecoin and Cryptocurrency Markets Q. Yan et al. https://doi.org/10.1111/infi.70020
- Do general elections affect fractal structure of stock market? C. Cheong et al. https://doi.org/10.1080/09720510.2020.1776943
- Multisite daily precipitation simulation in Singapore S. Suroso et al. https://doi.org/10.1051/matecconf/201819505007
- Non-asymptotic distributions of water extremes: much ado about what? F. Serinaldi et al. https://doi.org/10.5194/hess-29-1159-2025
- When will Lake Mead go dry? T. Barnett & D. Pierce https://doi.org/10.1029/2007WR006704
- How are rescaled range analyses affected by different memory and distributional properties? A Monte Carlo study L. Kristoufek https://doi.org/10.1016/j.physa.2012.04.005
- A Blueprint for Full Collective Flood Risk Estimation: Demonstration for European River Flooding F. Serinaldi & C. Kilsby https://doi.org/10.1111/risa.12747
- Understanding long-term persistence and multifractal behaviors in river runoff: A detailed study over eastern China W. Wu et al. https://doi.org/10.1016/j.physa.2019.122042
- Assessment of impact of climate change on water resources: a long term analysis of the Great Lakes of North America E. McBean & H. Motiee https://doi.org/10.5194/hess-12-239-2008
- Characterization of river flow fluctuations via horizontal visibility graphs A. Braga et al. https://doi.org/10.1016/j.physa.2015.10.102
- Structural break or long memory: an empirical survey on daily rainfall data sets across Malaysia F. Yusof et al. https://doi.org/10.5194/hess-17-1311-2013
- Deterministic versus stochastic trends: Detection and challenges S. Fatichi et al. https://doi.org/10.1029/2009JD011960
- Global estimation of long-term persistence in annual river runoff Y. Markonis et al. https://doi.org/10.1016/j.advwatres.2018.01.003
- Quantifying multi-year hydrological memory with Catchment Forgetting Curves A. de Lavenne et al. https://doi.org/10.5194/hess-26-2715-2022
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