scholarly journals Uncertainty Analysis of Regional Rainfall Frequency Estimates in Northeast India

2021 ◽  
Vol 7 (11) ◽  
pp. 1817-1835
Author(s):  
Nilotpal Debbarma ◽  
Parthasarathi Choudhury ◽  
Parthajit Roy ◽  
Shivam Agarwal
Keyword(s):  
Genetic Algorithm ◽  
Frequency Analysis ◽  
Information Transfer ◽  
Spatial Information ◽  
Accuracy Assessment ◽  
Regional Growth ◽  
Uncertainty Assessment ◽  
Regional Frequency Analysis ◽  
Regional Estimates ◽  
Regional Frequency

Estimation of rainfall quantile is an important step in regional frequency analysis for planning and design of any water resources project. Related evaluations of accuracy and uncertainty help to further assist in enhancing the reliability of design estimates. In this study, therefore, we investigate the accuracy and uncertainty of regional frequency analysis of extreme rainfall computed from genetic algorithm-based clustering. Uncertainty assessment is explored with prediction of quantiles with a new spatial Information Transfer Index (ITI) and Monte Carlo simulation framework. And, accuracy assessment is done with the comparison of regional growth curves to at-site analysis for each homogenous region. Further, uncertainty assessment with the ITI method is compared with Maximum Likelihood estimation (MLE) optimized by a genetic algorithm (GA) to check the suitability of the method. Results obtained suggest the ITI-based uncertainty assessment for regional estimates outperformed those of at-site estimates. The MLE-GA method based on at-site estimates was found to be better than at-site estimates based on L-moments, suggesting the former as a better alternative to compare with regional frequency estimates. Moreover, minimal bias and least deviation of the regional growth curve were obtained in the rainfall regions. The confidence intervals of regional estimates were seen to be well within the bounds of normality assumptions. Doi: 10.28991/cej-2021-03091762 Full Text: PDF

Bivariate Regional Frequency Analysis of Sea State Conditions

2021 ◽  
Author(s):  
Erik Vanem
Keyword(s):  
Frequency Analysis ◽  
North Atlantic ◽  
North Atlantic Ocean ◽  
Regional Growth ◽  
Wave Period ◽  
Regional Frequency Analysis ◽  
Significant Wave ◽  
The North ◽  
The North Atlantic ◽  
Regional Frequency

Abstract This paper presents a bivariate regional frequency analysis applied to data of extreme significant wave heights and concurrent wave period over an area in the North Atlantic Ocean. It extends previous regional frequency analysis on significant wave height to the bivariate case where the joint distribution of significant wave height and zero up-crossing wave period are analysed. This is believed to be an important extension, as the joint distribution is typically needed for marine design and other ocean engineering applications. The analysis presented in this paper is based on a bivariate index-wave/period approach and assumes a common regional growth curve within homogeneous regions of the overall area. One of the main benefits of performing a regional frequency analysis as opposed to at-site analysis based on data from one location only is that more accurate predictions of extreme conditions can be obtained, due to the increased number of observations that will effectively be available. Moreover, results for locations within the regions where no observations are available can be obtained by interpolation of the index wave/period and utilizing the regional growth curve. This paper outlines the various steps and modelling choices involved in a bivariate regional frequency analysis and presents the results of such an analysis applied to 30 years of data covering the North Atlantic Ocean. Moreover, it is shown how environmental contours can be constructed based on the outcome of the bivariate RFA, corresponding to one particular definition of a bivariate return period.

scholarly journals Region-of-influence approach to a frequency analysis of heavy precipitation in Slovakia

2008 ◽  
Vol 12 (3) ◽  
pp. 825-839 ◽  
Author(s):  
L. Gaál ◽  
J. Kyselý ◽  
J. Szolgay
Keyword(s):  
Frequency Analysis ◽  
Growth Curves ◽  
Heavy Precipitation ◽  
Regional Frequency Analysis ◽  
Design Values ◽  
Site Design ◽  
Specific Alternative ◽  
Method Yield ◽  
Regional Frequency ◽  
Selection Of

Abstract. The paper compares different approaches to regional frequency analysis with the main focus on the implementation of the region-of-influence (ROI) technique for the modelling of probabilities of heavy precipitation amounts in the area of the Western Carpathians. Unlike the conventional regional frequency analysis where the at-site design values are estimated within a fixed pooling group (region), the ROI approach as a specific alternative to focused pooling techniques makes use of flexible pooling groups, i.e. each target site has its own group of sufficiently similar sites. In this paper, various ROI pooling schemes are constructed as combinations of different alternatives of sites' similarity (pooling groups defined according to climatological characteristics and geographical proximity of sites, respectively) and pooled weighting factors. The performance of the ROI pooling schemes and statistical models of conventional (regional and at-site) frequency analysis is assessed by means of Monte Carlo simulation studies for precipitation annual maxima for the 1-day and 5-day durations in Slovakia. It is demonstrated that a) all the frequency models based on the ROI method yield estimates of growth curves that are superior to the standard regional and at-site estimates at most individual sites, and b) the selection of a suitable ROI pooling scheme should be adjusted to the dominant character of the formation of heavy precipitation.

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