Articles | Volume 20, issue 7
https://doi.org/10.5194/hess-20-2705-2016
© Author(s) 2016. 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-20-2705-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
11 Jul 2016
Research article |
| 11 Jul 2016
Investigation of hydrological time series using copulas for detecting catchment characteristics and anthropogenic impacts
Takayuki Sugimoto
CORRESPONDING AUTHOR
Institute for Modelling Hydraulic and Environmental Systems, University of
Stuttgart, Stuttgart, Germany
András Bárdossy
Institute for Modelling Hydraulic and Environmental Systems, University of
Stuttgart, Stuttgart, Germany
Civil Engineering Program, University of KwaZulu-Natal, Durban, South
Africa
Geoffrey G. S. Pegram
Civil Engineering Program, University of KwaZulu-Natal, Durban, South
Africa
Johannes Cullmann
Water & Climate Department, World Meteorological Organization,
Geneva, Switzerland
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Cited
17 citations as recorded by crossref.
- Temporal asymmetry in precipitation time series and its influence on flow simulations in combined sewer systems T. Müller et al. 10.1016/j.advwatres.2017.06.010
- Copulas and hydro-economic models for assessing the impacts of climate change in irrigated agriculture I. El ouadi et al. 10.1051/e3sconf/202449204002
- Universal framework for hydrological time series probabilistic forecasting S. Yanfang et al. 10.18307/2018.0303
- Development of an ensemble Bayesian inference‐based copula approach for bivariate risk evaluation of extreme precipitation under climate change L. Sun et al. 10.1002/joc.7768
- Characteristic Analysis and Uncertainty Assessment of the Joint Distribution of Runoff and Sediment: A Case Study of the Huangfuchuan River Basin, China X. Huang & L. Qiu 10.3390/w15142644
- Risk assessment through multivariate analysis on the magnitude and occurrence date of daily storm events in the Shenzhen bay area J. Han et al. 10.1007/s00477-020-01793-1
- Copulas for hydroclimatic analysis: A practice‐oriented overview F. Tootoonchi et al. 10.1002/wat2.1579
- Constructing multivariate distribution of rainfall characteristics: A Bayesian vine algorithm A. Sharma et al. 10.1016/j.jhydrol.2024.131392
- A methodology to estimate flow duration curves at partially ungauged basins E. Ridolfi et al. 10.5194/hess-24-2043-2020
- Estimation of the River Flow Synchronicity in the Upper Indus River Basin Using Copula Functions L. Sobkowiak et al. 10.3390/su12125122
- Detection and forecast of climate change effect on siltation using copulas W. El Hannoun et al. 10.1007/s00704-022-03981-1
- The Devil Is in the Tail Dependence: An Assessment of Multivariate Copula‐Based Frameworks and Dependence Concepts for Coastal Compound Flood Dynamics R. Phillips et al. 10.1029/2022EF002705
- Data pre-processing effect on ANN-based prediction intervals construction of the evaporation process at different climate regions in Iran V. Nourani et al. 10.1016/j.jhydrol.2020.125078
- On the Relationship between Suspended Sediment Concentration, Rainfall Variability and Groundwater: An Empirical and Probabilistic Analysis for the Andean Beni River, Bolivia (2003–2016) I. Ayes Rivera et al. 10.3390/w11122497
- Spatiotemporal variability and empirical Copula-based dependence structure of modeled and observed coupled water and energy fluxes M. Soltani et al. 10.2166/nh.2018.163
- Using a Groundwater Adjusted Water Balance Approach and Copulas to Evaluate Spatial Patterns and Dependence Structures in Remote Sensing Derived Evapotranspiration Products M. Soltani et al. 10.3390/rs13050853
- A Bayesian-Model-Averaging Copula Method for Bivariate Hydrologic Correlation Analysis Y. Wen et al. 10.3389/fenvs.2021.744462
17 citations as recorded by crossref.
- Temporal asymmetry in precipitation time series and its influence on flow simulations in combined sewer systems T. Müller et al. 10.1016/j.advwatres.2017.06.010
- Copulas and hydro-economic models for assessing the impacts of climate change in irrigated agriculture I. El ouadi et al. 10.1051/e3sconf/202449204002
- Universal framework for hydrological time series probabilistic forecasting S. Yanfang et al. 10.18307/2018.0303
- Development of an ensemble Bayesian inference‐based copula approach for bivariate risk evaluation of extreme precipitation under climate change L. Sun et al. 10.1002/joc.7768
- Characteristic Analysis and Uncertainty Assessment of the Joint Distribution of Runoff and Sediment: A Case Study of the Huangfuchuan River Basin, China X. Huang & L. Qiu 10.3390/w15142644
- Risk assessment through multivariate analysis on the magnitude and occurrence date of daily storm events in the Shenzhen bay area J. Han et al. 10.1007/s00477-020-01793-1
- Copulas for hydroclimatic analysis: A practice‐oriented overview F. Tootoonchi et al. 10.1002/wat2.1579
- Constructing multivariate distribution of rainfall characteristics: A Bayesian vine algorithm A. Sharma et al. 10.1016/j.jhydrol.2024.131392
- A methodology to estimate flow duration curves at partially ungauged basins E. Ridolfi et al. 10.5194/hess-24-2043-2020
- Estimation of the River Flow Synchronicity in the Upper Indus River Basin Using Copula Functions L. Sobkowiak et al. 10.3390/su12125122
- Detection and forecast of climate change effect on siltation using copulas W. El Hannoun et al. 10.1007/s00704-022-03981-1
- The Devil Is in the Tail Dependence: An Assessment of Multivariate Copula‐Based Frameworks and Dependence Concepts for Coastal Compound Flood Dynamics R. Phillips et al. 10.1029/2022EF002705
- Data pre-processing effect on ANN-based prediction intervals construction of the evaporation process at different climate regions in Iran V. Nourani et al. 10.1016/j.jhydrol.2020.125078
- On the Relationship between Suspended Sediment Concentration, Rainfall Variability and Groundwater: An Empirical and Probabilistic Analysis for the Andean Beni River, Bolivia (2003–2016) I. Ayes Rivera et al. 10.3390/w11122497
- Spatiotemporal variability and empirical Copula-based dependence structure of modeled and observed coupled water and energy fluxes M. Soltani et al. 10.2166/nh.2018.163
- Using a Groundwater Adjusted Water Balance Approach and Copulas to Evaluate Spatial Patterns and Dependence Structures in Remote Sensing Derived Evapotranspiration Products M. Soltani et al. 10.3390/rs13050853
- A Bayesian-Model-Averaging Copula Method for Bivariate Hydrologic Correlation Analysis Y. Wen et al. 10.3389/fenvs.2021.744462
Saved (preprint)
Latest update: 13 Dec 2024
Short summary
This paper is aims to detect the climate change impacts on the hydrological regime from the long-term discharge records. A new method for stochastic analysis using copulas, which has the advantage of scrutinizing the data independent of marginal, is suggested in this paper. Two measures are used in the copula domain: one focuses on the asymmetric characteristic of data and the other compares the distances between the copulas. These are calculated for 100 years of daily discharges and the results are discussed.
This paper is aims to detect the climate change impacts on the hydrological regime from the...
