Flood Frequency Analysis of Tel Basin of Mahanadi River System, India Using Annual Maximum and POT Flood Data
Flood Frequency Analysis of Tel Basin of Mahanadi River System, India Using Annual Maximum and POT Flood Data
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DOI：
10.1016/j.aqpro.2015.02.057
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
N. Guru;R. Jha
中科院分区：
文献类型：
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作者：
N. Guru;R. Jha
洪水频率分析显示了流域特征、水的可用性和可能的极端水文条件，如任何河流系统不同位置的洪水和干旱。过去曾利用长期的年最大洪水系列进行过此类研究，以便对任何种类的灾害进行预警、备灾、减灾和减灾。在本研究中，年最大（AM）洪水系列和超过阈值（POT）洪水系列进行洪水频率分析，印度Mahanadi河系统的Tel流域。根据（a）常用的标准实践和（B）在印度Mahanadi河流系统中破坏下游地区并造成灾害的洪水值，考虑POT值。为了识别洪水频率分布尾部行为的异常，并选择合适的洪水频率分布，使用分位数-分位数图（Q-Q图）。对印度Mahanadi河系Tel流域Kesinga（上游）和Kantamal（下游）两个水文站1972-2009年的洪水系列数据进行了分析。14个不同的洪水频率分布进行了尝试AM和POT洪水系列数据为31年的Kesinga和38年的Kantamal。广义Pareto（GP）分布的结果表明，AM洪水数据序列的拟合优度检验的结果更好。然而，对于POT洪水数据系列，LogNormal（3 P）分布显示出最好的结果，其次是GP分布与所有拟合优度检验。最适合POT数据集的分布与全球洪水预报所用的分布相同。
Flood frequency analysis indicates the catchment characteristics, water availability and possible extreme hydrological conditions like floods and droughts at various locations of any river system. Such studies have been done in the past using long term annual maximum flood series for early warning, preparedness, mitigation and reduction of any kind of disasters. In the present study, Annual Maximum (AM) flood series and Peak over Threshold (POT) flood series were used to carry out flood frequency analysis for Tel basin of Mahanadi river system, India. The POT values were considered based on (a) commonly used standard practice and (b) flood values damaging the downstream areas and causing disaster in Mahanadi river system, India. To recognize the anomalies in tail behavior of the flood frequency distribution and for selecting appropriate flood frequency distributions, Quantile-Quantile plots (Q-Q plots) were used. The analysis was carried out for flood series data of two gauging stations Kesinga (upstream) and Kantamal (downstream) of Tel basin, Mahanadi river system, India for the years 1972-2009. Fourteen different flood frequency distributions were tried for AM and POT flood series data for 31 years for Kesinga and 38 years for Kantamal. The results obtained using Generalized Pareto (GP) distribution shows better results for AM flood data series with all goodness of fit tests. However, for POT flood data series LogNormal (3P) distribution showed best results followed by GP distributions with all goodness of fit test. The distributions most suitable for POT data sets are same for the distribution being used globally for flood forecasting.