Changrang Zhou, Ronald van Nooijen, A. Kolechkina, Emna Gargouri, F. Slama, N. C. van de Giesen
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引用次数: 0
Abstract
ABSTRACT The dependency structure between hydrological variables is of critical importance to hydrological modelling and forecasting. When a copula capturing that dependence is fitted to a sample, information on the uncertainty of the fit is needed for subsequent hydrological calculations and reasoning. A new method is proposed to report inferential uncertainty in a copula parameter. The method is based on confidence curves constructed with the use of a pseudo maximum likelihood estimator for the copula parameter. The method was tested on synthetic data and then used as a tool in two hydrological examples. The first examines the probability of major floods in two locations on the Rhine River and its tributaries in the same calendar year. In the second example, rainfall–runoff from a karst region in Tunisia was analysed to determine a confidence interval for the delay between precipitation and runoff.
期刊介绍:
Hydrological Sciences Journal is an international journal focused on hydrology and the relationship of water to atmospheric processes and climate.
Hydrological Sciences Journal is the official journal of the International Association of Hydrological Sciences (IAHS).
Hydrological Sciences Journal aims to provide a forum for original papers and for the exchange of information and views on significant developments in hydrology worldwide on subjects including:
Hydrological cycle and processes
Surface water
Groundwater
Water resource systems and management
Geographical factors
Earth and atmospheric processes
Hydrological extremes and their impact
Hydrological Sciences Journal offers a variety of formats for paper submission, including original articles, scientific notes, discussions, and rapid communications.