Bivariate Drought Frequency Analysis in The Medjerda River Basin, TunisiaYasser Hamdi1,2, Fateh Chebana3* and Taha B.M.J. Ouarda3,4
- *Corresponding Author:
- Fateh chebana
INRS-ETE, 490 rue de la
Couronne Quebec (QC), G1K 9A9 Canada
E-mail: [email protected]
Received date: April 12, 2016; Accepted date: April 26, 2016; Published date: April 28, 2016
Citation: Hamdi Y, Chebana F, Ouarda TBMJ (2016) Bivariate Drought Frequency Analysis in The Medjerda River Basin, Tunisia. J Civil Environ Eng 6:227. doi:10.4172/2165-784X.1000227
Copyright: © 2016 Hamdi Y, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The climatology provides, for a given location or region, the time series of drought strength, the number, the mean duration, and the maximum duration of droughts of a given intensity. Similarly to most hydrological phenomena, droughts are characterized by a number of features such as their severity, duration and magnitude. Multivariate drought characterization has not been carried out in the various regions of the African continent despite the disastrous environmental, economic and social impacts of droughts. In the present paper, drought characteristics are modeled jointly in a multivariate frequency analysis (FA) framework for a data set from the Medjerda River, the principal watercourse in Tunisia. To identify drought events, the adopted threshold levels are estimated using the Flow Duration Curve (FDC) method. A sensitivity analysis to the threshold level is conducted. Results indicate that the drought features are significantly dependent and should be considered simultaneously for effective and rational modeling. Frank copula is shown to be the most appropriate copula model to represent drought features for the considered data set. The joint probabilities and bivariate return periods, based on the developed two dimensional copula models, are estimated in order to evaluate the contribution and advantages of bivariate modeling of droughts. These results are of practical relevance to hydrologists and water resources managers in Tunisia for applications in drought risk analysis and drought management, and in general for the optimal planning and management of water resources systems.