LAUSR

Rainfall patterns are bound to change as a result of global warming and climate change impacts. Rainfall events are dependent on geographic location, geomorphology, coastal area closeness and general circulation air movements. Accordingly, there are increases and decreases at different meteorology station time-series records leading to extreme events such as droughts and floods. This paper suggests a methodology in terms of envelope curves for monthly extreme rainfall event occurrences at a set of risk levels or return periods that may trigger the extreme occurrences at meteorology station catchments. Generally, in many regions, individual storm rainfall records are not available for intensity–duration–frequency (IDF) curve construction. The main purpose of this paper is, in the absence of individual storm rainfall records, to suggest monthly envelope curves, which provide a relationship between return period and monthly extreme rainfall values. The first step is to identify each monthly extreme rainfall records probability distribution function (PDF) for risk level and return period calculations. Subsequently, the return period rainfall amount relationships are presented on double-logarithmic graphs with the best power model as a set of envelope curves. The applications of these methodologies are implemented for three Hodna drainage basin meteorology station rainfall records in northern Algeria. It is concluded that the most extreme rainfall risk months are June, August and September, which may lead to floods or flash floods in the study area. A new concept is presented for the possible extreme value triggering months through the envelope curves as ‘low’, ‘medium’ and ‘high’ class potentials.