Samiran Das - Academia.edu (original) (raw)
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SRI RAM MURTI SMARAK COLLEGE OF ENGG. 7TECHNOLOGY(BAREILLY)U.P
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Papers by Samiran Das
Water Resources Management, 2020
The framework of regional analysis allows superior discrimination as well as better identificatio... more The framework of regional analysis allows superior discrimination as well as better identification of the shape of a population distribution in a hydrological frequency analysis. The aim of this study is to incorporate the better of regional concept while performing an at-site frequency analysis. The study proposes a new method in the form of sub-sampling technique with the aid of a regional distribution selection procedure to choose an appropriate probability distribution function for frequency analysis. The technique is evaluated against common distribution selection methods: a widely used goodness-of-fit method in Anderson-Darling (AD) and a popular graphical assessment tool in L-moment ratio diagram (LMRD). The performance is evaluated by applying the technique to gauged annual maximum daily precipitation data series of 24 stations located across China. It is found that the technique accomplished a better performance in discriminating among distributions which or else may not be achievable only by the AD or LMRD test. In general, all results indicate that the proposed technique can be an attractive means in discriminating as well as identifying the best distribution for at-site frequency analysis.
Water Resources Management, 2020
The framework of regional analysis allows superior discrimination as well as better identificatio... more The framework of regional analysis allows superior discrimination as well as better identification of the shape of a population distribution in a hydrological frequency analysis. The aim of this study is to incorporate the better of regional concept while performing an at-site frequency analysis. The study proposes a new method in the form of sub-sampling technique with the aid of a regional distribution selection procedure to choose an appropriate probability distribution function for frequency analysis. The technique is evaluated against common distribution selection methods: a widely used goodness-of-fit method in Anderson-Darling (AD) and a popular graphical assessment tool in L-moment ratio diagram (LMRD). The performance is evaluated by applying the technique to gauged annual maximum daily precipitation data series of 24 stations located across China. It is found that the technique accomplished a better performance in discriminating among distributions which or else may not be achievable only by the AD or LMRD test. In general, all results indicate that the proposed technique can be an attractive means in discriminating as well as identifying the best distribution for at-site frequency analysis.