Variability of time duration analysis for rainfall water using precipitation indexes in Hai town

Abstract

Insufficient rainfall has an impact on a variety of natural resources. This work aims to determine the variability of rainfall and drought in Hai town depending on the standardized rainfall index (SRI), rainfall concentration index (RCI), index of wetness (IW), and coefficient of variation (CV). Rainfall series were taken from the Meteorological Station Directorate of Hai Town, Iraq for a period of 30 years (1989–2018). The results indicated that the years 1996 and 2014 had high SRI and were under extremely wet conditions (IW = 195.93 and 165.93, respectively). However, the lowest SRI value was in 2004, with a wetness index of 35.15, whereas the RCI was strongly irregular in rainfall distribution. Also, the CV was highly variable that ranged between 113.78 and 244.01. Mathematical models were created and confirmed for predicting the wetness index using data-fitting software. Model 1 generated best outcomes (R2 = 99.99%, relative error (RE) = 0.221, root mean square error (RMSE = 0.253) and standard error of estimates (SEE = 0.28). The results demonstrated that rain indicators have significant differences and alteration throughout the study period. Hence, the best model for estimating wetness and droughts in Hai town is recommended. HIGHLIGHTS Variability of rainfall and drought monitoring in Hai town were eveluated.; SRI, RCI, IW, and CV were used.; DataFit program (statistically) was used to predict value index of wetness.; Make statistical models for index of wetness by using the DataFit program, and then the best model was chosen depending on R2, RMSE, SEE, RE.; Differences between predicted value and measured value for index of wetness were recorded.;

Keywords

• coefficient of variation
• datafit software
• index of wetness
• rainfall concentration index
• standardized rainfall index
• statistical analysis