Investigation of hydrological time series using copulas for detecting catchment characteristics and anthropogenic impacts

Global climate change can have impacts on characteristics of rainfall–runoff events and subsequently on the hydrological regime. Meanwhile, the catchment itself changes due to anthropogenic influences. However, it is not easy to prove the link between the hydrology and the forcings. In this context,...

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Main Authors: T. Sugimoto, A. Bárdossy, G. G. S. Pegram, J. Cullmann
Format: Article
Language:English
Published: Copernicus Publications 2016-07-01
Series:Hydrology and Earth System Sciences
Online Access:http://www.hydrol-earth-syst-sci.net/20/2705/2016/hess-20-2705-2016.pdf
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spelling doaj-501dd5b890f84a6a9cca675225fc1e392020-11-25T00:10:04ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382016-07-012072705272010.5194/hess-20-2705-2016Investigation of hydrological time series using copulas for detecting catchment characteristics and anthropogenic impactsT. Sugimoto0A. Bárdossy1G. G. S. Pegram2J. Cullmann3Institute for Modelling Hydraulic and Environmental Systems, University of Stuttgart, Stuttgart, GermanyInstitute for Modelling Hydraulic and Environmental Systems, University of Stuttgart, Stuttgart, GermanyCivil Engineering Program, University of KwaZulu-Natal, Durban, South AfricaWater & Climate Department, World Meteorological Organization, Geneva, SwitzerlandGlobal climate change can have impacts on characteristics of rainfall–runoff events and subsequently on the hydrological regime. Meanwhile, the catchment itself changes due to anthropogenic influences. However, it is not easy to prove the link between the hydrology and the forcings. In this context, it might be meaningful to detect the temporal changes of catchments independent from climate change by investigating existing long-term discharge records. For this purpose, a new stochastic system based on copulas for time series analysis is introduced in this study.<br><br>A statistical tool like copula has the advantage to scrutinize the dependence structure of the data and, thus, can be used to attribute the catchment behavior by focusing on the following aspects of the statistics defined in the copula domain: (1) copula asymmetry, which can capture the nonsymmetric property of discharge data, differs from one catchment to another due to the intrinsic nature of both runoff and catchment; and (2) copula distances can assist in identifying catchment change by revealing the variability and interdependency of dependence structures.<br><br>These measures were calculated for 100 years of daily discharges for the Rhine River and these analyses detected epochs of change in the flow sequences. In a follow-up study, we compared the results of copula asymmetry and copula distance applied to two flow models: (i) antecedent precipitation index (API) and (ii) simulated discharge time series generated by a hydrological model. The results of copula-based analysis of hydrological time series seem to support the assumption that the Neckar catchment had started to change around 1976 and stayed unusual until 1990.http://www.hydrol-earth-syst-sci.net/20/2705/2016/hess-20-2705-2016.pdf
collection DOAJ
language English
format Article
sources DOAJ
author T. Sugimoto
A. Bárdossy
G. G. S. Pegram
J. Cullmann
spellingShingle T. Sugimoto
A. Bárdossy
G. G. S. Pegram
J. Cullmann
Investigation of hydrological time series using copulas for detecting catchment characteristics and anthropogenic impacts
Hydrology and Earth System Sciences
author_facet T. Sugimoto
A. Bárdossy
G. G. S. Pegram
J. Cullmann
author_sort T. Sugimoto
title Investigation of hydrological time series using copulas for detecting catchment characteristics and anthropogenic impacts
title_short Investigation of hydrological time series using copulas for detecting catchment characteristics and anthropogenic impacts
title_full Investigation of hydrological time series using copulas for detecting catchment characteristics and anthropogenic impacts
title_fullStr Investigation of hydrological time series using copulas for detecting catchment characteristics and anthropogenic impacts
title_full_unstemmed Investigation of hydrological time series using copulas for detecting catchment characteristics and anthropogenic impacts
title_sort investigation of hydrological time series using copulas for detecting catchment characteristics and anthropogenic impacts
publisher Copernicus Publications
series Hydrology and Earth System Sciences
issn 1027-5606
1607-7938
publishDate 2016-07-01
description Global climate change can have impacts on characteristics of rainfall–runoff events and subsequently on the hydrological regime. Meanwhile, the catchment itself changes due to anthropogenic influences. However, it is not easy to prove the link between the hydrology and the forcings. In this context, it might be meaningful to detect the temporal changes of catchments independent from climate change by investigating existing long-term discharge records. For this purpose, a new stochastic system based on copulas for time series analysis is introduced in this study.<br><br>A statistical tool like copula has the advantage to scrutinize the dependence structure of the data and, thus, can be used to attribute the catchment behavior by focusing on the following aspects of the statistics defined in the copula domain: (1) copula asymmetry, which can capture the nonsymmetric property of discharge data, differs from one catchment to another due to the intrinsic nature of both runoff and catchment; and (2) copula distances can assist in identifying catchment change by revealing the variability and interdependency of dependence structures.<br><br>These measures were calculated for 100 years of daily discharges for the Rhine River and these analyses detected epochs of change in the flow sequences. In a follow-up study, we compared the results of copula asymmetry and copula distance applied to two flow models: (i) antecedent precipitation index (API) and (ii) simulated discharge time series generated by a hydrological model. The results of copula-based analysis of hydrological time series seem to support the assumption that the Neckar catchment had started to change around 1976 and stayed unusual until 1990.
url http://www.hydrol-earth-syst-sci.net/20/2705/2016/hess-20-2705-2016.pdf
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