The results reveal the value of considering climate variability for flood frequency analysis, especially when non-stationarity is established by homogeneity analysis. The influence of climate variability on flood estimates in the region was linked to the Madden-Julian Oscillation (MJO) climate indices and resulted in increased flood magnitude for regional and direct flood frequency estimates varying from 0% - 35% and demonstrate that multi-decadal changes in atmospheric conditions influence both small and large floods. The Generalized Logistic distribution was fitted to the annual maximum flood series for the 2 homogeneous regions to estimate flood magnitudes and the probability of occurrence while accounting for climate variability. Data from 17 gauging stations within the Ogun-Osun River Basin in Western Nigeria were analysed, resulting in the delineation of 3 sub-regions, of which 2 were homogeneous and 1 heterogeneous. It is written in C++, and offers a number of features outline on the webpage. This study applies regional Flood Frequency Analysis (FFA) to curtail deficiencies in historical data, by agglomerating data from various sites with similar hydro-geomorphological characteristics and is governed by a similar probability distribution, differing only by an “index-flood” as well as accounting for climate variability effect. Engauge Digitizer is an open source digitizing proram available under the terms of the GNU GPL. Such data are seldom available in many developing regions, owing to financial, technical, and organizational drawbacks that result in short-length and inadequate historical data that are prone to uncertainties if directly applied for flood frequency estimation. To mitigate and minimize the impact of such floods now and in the future, effective planning is required, underpinned by analytics based on reliable data and information. DigitizeIt makes it easy to actually get back numbers from such a plot This is a three step process: import the graph from a file or copy it over the clipboard, define the axes system. in most scientific publications only plots but no data values are published. Sometimes it is necessary to extract data values from graphs, e.g. Nigeria, the case-study for this research experiences recurrent flooding, with the most disastrous being the 2012 flood event that resulted in unprecedented damage to infrastructure, displacement of people, socio-economic disruption, and loss of lives. DigitizeIt digitizer software replaces a digitizer tablet. reverse engineers data from a scanned plot, so you can incorporate published data in. Journal of Water Resource and Protection,ĪBSTRACT: Extreme flood events are becoming more frequent and intense in recent times, owing to climate change and other anthropogenic factors. Engauge digitizer polar software Engauge digitizer polar trial. Accounting for the Effects of Climate Variability in Regional Flood Frequency Estimates in Western NigeriaĪUTHORS: Iguniwari Thomas Ekeu-Wei, George Alan Blackburn, Jason GiovannettoneĬlimate Variability, Regional Flood Frequency, Climate-Indices, L-Moment, Madden-Julian Oscillation (MJO), Generalised Logistic (GLO), Climate-Indices
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