A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Trivariate Flood Frequency Analysis Using Discharge Time Series with Possible Different Lengths: Cuyahoga River Case Study
A common approach to multivariate flood frequency analysis is to apply discharge time series records with the same length (i.e., one upstream and one downstream discharge gauge in the same river for bivariate flood frequency analysis, and multivariate flood frequency analysis at the confluence of river systems). However, in reality the gauged discharge time series records may have different lengths due to different activation times of the gauges. In addition, there exists one common assumption for flood frequency analysis, that is, the discharge time series may be considered as a stationary signal. However, due to land-use and land-cover (LULC) and climate changes, the stationary assumption may need to be justified. To answer the above questions, this paper investigates (1) the full-length discharge record at each discharge gauge; (2) the dependence structure of bivariate and multivariate discharge time series with different lengths using the copula theory; (3) employment of the vine copula for multivariate flood frequency analysis (i.e., ); and (4) the validation of the proposed method and comparison of its performance with asymmetric, symmetric Archimedean, and meta-elliptical copulas using the discharge time series from the Cuyahoga River basin, Ohio, as a case study.
Trivariate Flood Frequency Analysis Using Discharge Time Series with Possible Different Lengths: Cuyahoga River Case Study
A common approach to multivariate flood frequency analysis is to apply discharge time series records with the same length (i.e., one upstream and one downstream discharge gauge in the same river for bivariate flood frequency analysis, and multivariate flood frequency analysis at the confluence of river systems). However, in reality the gauged discharge time series records may have different lengths due to different activation times of the gauges. In addition, there exists one common assumption for flood frequency analysis, that is, the discharge time series may be considered as a stationary signal. However, due to land-use and land-cover (LULC) and climate changes, the stationary assumption may need to be justified. To answer the above questions, this paper investigates (1) the full-length discharge record at each discharge gauge; (2) the dependence structure of bivariate and multivariate discharge time series with different lengths using the copula theory; (3) employment of the vine copula for multivariate flood frequency analysis (i.e., ); and (4) the validation of the proposed method and comparison of its performance with asymmetric, symmetric Archimedean, and meta-elliptical copulas using the discharge time series from the Cuyahoga River basin, Ohio, as a case study.
Trivariate Flood Frequency Analysis Using Discharge Time Series with Possible Different Lengths: Cuyahoga River Case Study
Zhang, Lan (author) / Singh, Vijay P. (author)
2014-03-22
Article (Journal)
Electronic Resource
Unknown
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