Modelling the IDF curves using the temporal stochastic disaggregation BLRP model for precipitation data in Najaf City

Precipitation data for long period with short time scales extending from limited minute to daily time steps is the principal requirement in water resources engineering for planning, design, and operation of water resources projects. However, the availability of measurements of these data faced several obstacles in various places in the world. In this study, the Intensity Duration Frequency (IDF) relationships of precipitation amount at Najaf city region in Iraq are generated based on a stochastic technique for disaggregation of daily time scale precipitation into fine-scale durations, i.e. the modified Bartlett-Lewis rectangular pulses of the seven parameters (BLRP) model (λ, κ, φ, α, υ, μχ, and σχ). The model applied for daily precipitation over a period of 35 years by employing the Climate Forecast System Reanalysis (CFSR) grid station data after implementing bias correction with respect to the monthly available data at Najaf city meteorological station. Eight sub-daily precipitation data sets with storm durations of 5, 10, 20, 30, 60, 120, 360, and 720 min were generated by using Hyetos-Minute R-package. Three statistical continuous distributions used to fit the estimation of extreme values data sets which included the Generalised Extreme Value (GEV), Gumbel (EV-1), and Log-Pearson type III (LP-3). Finally, the IDF curves were generated based on GEV and LP-3 for six return periods (2, 5, 10, 25, 50, and 100 years) using Sherman equation for each return period. The goodness of fit between the theoretical and developed distributions was tested by applying the Kolmogorov–Smirnov, Anderson–Darling and chi-squared test at 5% significance level. Results showed affirmative agreements between the both datasets from the three distributions at 5% significance level. Furtherly, the probabilistic model selection by two numerical criteria AIC and BIC nominated that GEV and LP-3 as appropriate models for simulation extreme precipitation values at Najaf city for different return periods. © 2021, Saudi Society for Geosciences.