2008/02/04 by M. Ribatet, Mathieu Ribatet, Taha B. M. J. Ouarda +5
Environmental Science · Mathematics · #Duration (music) #Estimation #Flood Risk Assessment and Management #Flood myth #Hydrological modelling #Hydrology and Drought Analysis #Hydrology and Watershed Management Studies #Inference #Maxima #Quantile #stat.AP
paper · pdf · doi:10.1029/2007wr006322
arxiv created 2008/02/04 · openalex publication_date 2009/03/01 · arxiv updated 2009/12/01 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/05
Flood quantile estimation is of great importance for several types of engineering studies and policy decisions. However, practitioners must often deal with the limited availability of data and with short‐length observation series. Thus, the information must be used optimally. During the last decades, to make better use of available data, inferential methodology has evolved from annual maxima modeling to peaks over a threshold. To mitigate the lack of data, peaks over a threshold are sometimes combined with additional information, mostly regional or historical information. However, the most important information for the practitioner remains the data available at the target site. In this study, a model that allows inference on the whole time series is introduced. In particular, the proposed model takes into account the dependence between successive extreme observations using an appropriate extremal dependence structure. Results show that this model leads to more accurate flood peak quantile estimates than conventional estimators. In addition, as the time dependence is taken into account, inferences on other flood characteristics can be performed. An illustration is given with flood duration data. Our analysis shows that the accuracy of the proposed models to estimate flood duration is related to specific catchment characteristics. Some suggestions to increase the flood duration predictions are presented.