Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
PROBABILISTIC MODELLING OF ANNUAL d-DAY MAXIMUM RAINFALL
Estimation of rainfall for a desired return period, and different durations, is often required for design of hydraulic and other structures in a region, which can be achieved by probabilistic approach. In the present study, probabilistic modelling is used to fit six different distributions to annual d-day maximum rainfall (ADMR) for different values of ‘d’ such as 1-day, 2-day and 3-day for Devgadhbaria region of Gujarat. Chi-square and Kolmogorov-Smirnov tests are used to judge the applicability of the distributions for modelling of the recorded rainfall data. Model performance indicators such as relative mean square error and correlation coefficient are used to evaluate the performance of the predicted ADMR using different distributions. Diagnostic test, involving D-index, is used for evaluating suitability of the probability distribution for estimation of ADMR for different return periods. The study shows Log Pearson Type III to be the best suited, amongst the six different distributions studied, for modelling annual 1-day maximum rainfall while 2-parameter Lognormal and Extreme Value Type I for annual 2-day and 3-day maximum rainfall respectively for the region under study.
PROBABILISTIC MODELLING OF ANNUAL d-DAY MAXIMUM RAINFALL
Estimation of rainfall for a desired return period, and different durations, is often required for design of hydraulic and other structures in a region, which can be achieved by probabilistic approach. In the present study, probabilistic modelling is used to fit six different distributions to annual d-day maximum rainfall (ADMR) for different values of ‘d’ such as 1-day, 2-day and 3-day for Devgadhbaria region of Gujarat. Chi-square and Kolmogorov-Smirnov tests are used to judge the applicability of the distributions for modelling of the recorded rainfall data. Model performance indicators such as relative mean square error and correlation coefficient are used to evaluate the performance of the predicted ADMR using different distributions. Diagnostic test, involving D-index, is used for evaluating suitability of the probability distribution for estimation of ADMR for different return periods. The study shows Log Pearson Type III to be the best suited, amongst the six different distributions studied, for modelling annual 1-day maximum rainfall while 2-parameter Lognormal and Extreme Value Type I for annual 2-day and 3-day maximum rainfall respectively for the region under study.
PROBABILISTIC MODELLING OF ANNUAL d-DAY MAXIMUM RAINFALL
Vivekanandan, N. (Autor:in) / Mathew, F. T. (Autor:in)
ISH Journal of Hydraulic Engineering ; 16 ; 122-133
01.01.2010
12 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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