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  • DP-1 : Flood frequency analysis using power transformation 
    Seth, S. M.; Perumal, M. (National Institute of Hydrology, 1982)
    The purpose of the programme is (1) to transform the given independent and homogeneous annual maximum peak flood series to near normal distribution using Box-Cox transformation and (2) ...
  • DP-2 : Rating curve analysis 
    Seth, S. M.; Palaniappan, A. B. (National Institute of Hydrology, 1982)
    Many hydrologic analyses are made using discharge data of a river at a site. Often these discharge values are obtained from stage measurements. In order to compute the discharge from the ...
  • DP-3 : Best fit distribution 
    Seth, S. M.; Goyal, S. K. (1982)
    The documentation of the computer programme for best fit distribution using normalization procedures and chi-square criterion includes listing of source programme, data file and output file with ...
  • DP-4 : Ordering the series and interpolation 
    Seth, S. M.; Nirupama, P. (1983)
    The documentation for ordering the series describes the comparative studies carried out using four subroutines available in the literature. The comparison is made on the basis of compilation time, ...
  • DP-5 : Flood routing (Muskingum cunge procedure) 
    Seth, S. M.; Palaniappan, A. B. (National Institute of Hydrology, 1982)
    Flood routing in a natural river is complicated by the presence of irregularities of cross-section and by the presence of lateral flow. It is now possible to quantify the effect of irregularities in the ...
  • DP-6 : Multiple linear regression 
    Seth, S. M.; Goel, N. K. (National Institute of Hydrology, 1983)
    The association of three or more variables can be Investigated by multiple linear regression and correlation analysis. The derivation of relationships among hydrologic variables is of importance for ...
  • DP-7 : Polynomial regression 
    Seth, S. M.; Goel, N. K. (National Institute of Hydrology, 1983)
    For any non linear function Y = f(x) regression may be obtained by fitting a polynomial. The general form of the polynomial regression is as given under: Y=a0+a1X + a2X²+................... ...

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