Abstract: The frequency of recurrence of observed distributions is crucial in frequency analysis of hydrologic data for the purpose of plotting observed data, often known as "plotting positions." The appropriate determination of plotting positions has consistently been a contentious topic of conversation. Throughout time, a variety of methods for computing plotting positions have been presented. Through error statistics such as Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE), eight plotting position functions, which involves Hazen, California, Weibull, Beard, Chegodayev, Blom, Gringorten, and Cunnane, have been evaluated in this study for whether they could accurately estimate the magnitudes of annual and seasonal rainfall at Gariyaband district in Chhattisgarh state. Rankings are given to the methods for plotting position based on the that comes before error statistics. In accordance with an evaluation of the effectiveness of different plotting positions investigated in the study in terms of best estimation of magnitudes of seasonal and annual rainfall at Gariyaband District, Chhattisgarh, it is observed that the Cunnane method achieves the overall ranking "1," followed by the Gringorten method. Subsequently, the Cunnane technique is suggested as the best plotting position formula in frequency analysis of hydrologic data in Gariyaband District of Chhattisgarh State.
Abstract: The frequency of recurrence of observed distributions is crucial in frequency analysis of hydrologic data for the purpose of plotting observed data, often known as "plotting positions." The appropriate determination of plotting positions has consistently been a contentious topic of conversation. Throughout time, a variety of methods for computing p...Show More