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Journal ArticleDOI

Regional bivariate modeling of droughts using L-comoments and copulas

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TLDR
In this paper, an optimization-based method along with the adjusted charged system search are introduced and applied to estimate the regional parameters of the copula models for estimating the drought severity and duration.
Abstract
The regional bivariate modeling of drought characteristics using the copulas provides valuable information for water resources management and drought risk assessment. The regional frequency analysis (RFA) can specify the similar sites within a region using L-comoments approach. One of the important steps in the RFA is estimating regional parameters of the copula function. In the present study, an optimization-based method along with the adjusted charged system search are introduced and applied to estimate the regional parameters of the copula models. The capability of the proposed methodology is illustrated by copula functions on drought events. Three commonly used copulas containing Clayton, Frank and Gumbel are employed to derive the joint distribution of drought severity and duration. The result of the new method are compared to the method of moments and after applying several goodness-of-fit tests, the results indicate that the new method provides higher accuracy than the classic one. Furthermore, the results of the upper tail dependence coefficient indicate that the Gumbel copula is the best-fitted copula among the other ones for modeling drought characteristics.

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Citations
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Journal ArticleDOI

Characterization of future drought conditions in the Lower Mekong River Basin

TL;DR: In this article, the authors evaluated future changes to drought characteristics in the Lower Mekong River Basin using climate model projections using univariate analysis to compare drought characteristics associated with different return periods for the historical period 1964-2005 and future scenarios.
Journal ArticleDOI

Probabilistic modelling of drought events in China via 2-dimensional joint copula

TL;DR: Wang et al. as mentioned in this paper employed several relatively new bivariate Archimedean copulas to derive regional and spatial based copula models to appraise drought risk in mainland China over 1961-2013.
Journal ArticleDOI

Prediction of Groundwater Level in Ardebil Plain Using Support Vector Regression and M5 Tree Model

TL;DR: The results indicated that both SVR and M5 decision tree models performed well for the prediction of groundwater level in the Ardebil plain, however, the results obtained from the M4 decision tree model are more straightforward, more easily applied, and simpler to interpret than those from the SVR.
Journal ArticleDOI

Multivariate Drought Frequency Analysis using Four-Variate Symmetric and Asymmetric Archimedean Copula Functions

TL;DR: In this article, a flexible four-variate joint distribution function of the regional stochastic nature of drought was developed, and the best-fitting model for each region was carefully selected using RMSE, AIC, and BIAS goodness-of-fit tests.
Journal ArticleDOI

Compound effects of rainfall and storm tides on coastal flooding risk

TL;DR: Wang et al. as mentioned in this paper investigated the bivariate return period of compounding rainfall and storm tide events based on copula functions and the failure probability is used to assess the variation of bivariate flood risk during the entire project lifetime.
References
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Book

An Introduction to Copulas

TL;DR: This book discusses the fundamental properties of copulas and some of their primary applications, which include the study of dependence and measures of association, and the construction of families of bivariate distributions.
Journal ArticleDOI

Multivariate models and dependence concepts

Harry Joe
- 01 Sep 1998 - 
TL;DR: Introduction.
MonographDOI

Regional Frequency Analysis: An Approach Based on L-Moments

TL;DR: In this paper, the authors present a regional L-moments algorithm for detecting homogeneous regions in a set of homogeneous data points and then select a frequency distribution for each region.
Journal ArticleDOI

A semiparametric estimation procedure of dependence parameters in multivariate families of distributions

TL;DR: In this article, the authors investigated the properties of a semiparametric method for estimating the dependence parameters in a family of multivariate distributions and proposed an estimator, obtained as a solution of a pseudo-likelihood equation, which is consistent, asymptotically normal and fully efficient at independence.
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