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- W4386014786 abstract "Precipitation is one of the most important climatic variables for sustaining civilization. It is characterized by extremely high variability in space and time. The magnitude and frequency of precipitation are of great significance in hydrologic and hydraulic design and has wide application in various areas. However, precipitation data is available only in those regions where the rain gauges are installed. The magnitude and frequency of precipitation in ungauged sites can be assessed by grouping areas with similar characteristics. The procedure of grouping of areas having similar behaviour is termed as “regionalization”. Principal component analysis (PCA) which is based on consecutive sieving of stations was initiate for regionalization. PCA used for the reduction of the scale of the data set with minimum reducing of informations. Principal elements (PCs) that are orthogonal to every alternative are derived from inter-station correlation and/or variance matrix of precipitation within the study space. If the primary few leading PCs account for vital % of the full variance, their spatial patterns are analyzed to make undiversified precipitation regions. This approach may involve either plotting the unrotated and/or revolved computer loadings on the map of the study space or representing stations as points in two-dimensional house of leading PCs." @default.
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- W4386014786 date "2023-01-01" @default.
- W4386014786 modified "2023-10-02" @default.
- W4386014786 title "Regionalization of Precipitation in Andhra Pradesh and Telangana State by Using PCA" @default.
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- W4386014786 doi "https://doi.org/10.1007/978-981-99-3691-5_46" @default.
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