The Application of Mixture Distribution for the Estimation of Extreme Floods in Controlled Catchment Basins

Abstract

In the estimation of distribution of annual maximum flows it is a generally accepted assumption that the sequence of observations originates from a homogeneous population. This assumption, however, is rarely met. The observed annual maximum flow are only in part generated by flood events. The remaining ones are the result of the effect of other hydrological processes that do not have that character. For this reason, a new solution to this problem is proposed in the paper. It is assumed that the sought distribution is a mixture of two probability distributions: a three-parameter GEV distribution, describing flows generated by events with flood character, and a two-parameter gamma distribution, accounting for maximum annual flows that do not have such a character. The paper presents both the method of estimation of the mixture distribution and its application for gauging stations selected so as to take into account possible the most diverse conditions of meteorological, hydrological and geomorphological character. The area with such a high diversification, selected for the study, is the catchment basin of upper and central river Odra (South-West Poland). In the studied water gauge profiles the proposed mixture distribution indicates correct fit. Its advantages and limitations are presented through a comparative analysis with results obtained during estimation of distributions of maximum annual flows by means of standard methods.

Simulating Marginal and Dependence Behaviour of Water Demand Processes at Any Fine Time Scale

“…Furthermore, mixture type distributions provide enhanced flexibility, at a cost of few parameters, to account simultaneously for low, moderate and high amounts of the under study variable. This approach has found fertile ground to adequately model hydrological extremes which is of high importance in many engineering applications (e.g., [77][78][79]). Furthermore, as discussed in Section 1, the whole range of water demand flows, further to the peak values, are often involved in WDS applications, and thus the reproduction of the entire probabilistic behaviour of residential water demand consists a conditio sine qua non.…”

Simulation of the minimum annual river flows based on the RCP climatic scenario, time horizon up to 2060-2080 and the Kaczawa River

“…Modeling of spatial phenomena, especially flows in the rivers described here, requires high quality data simulated by a weather generator [25][26][27][28][29][30][31][32]. A high quality weather generator means that the generated data has the same probability distributions as the observed climatic data.…”

The Development of a Novel Decision Support System for the Location of Green Infrastructure for Stormwater Management

“…Climate change could have a significant impact on urban socio-environmental systems [1][2][3], which impact over half of the global population [4]. There are many different environmental aspects that influence the urban metabolism which are mainly related with temperature [5][6][7][8], atmospheric precipitation [9][10][11][12][13], or the synergy between climate elements and human activity [14,15]. In order to reduce the urban vulnerability to these phenomena, a new pathway for cities is promoted on the supranational level-one which is based on urban adaptation to climate change [16][17][18].…”