Analysis of monthly average precipitation of Wadi Ouahrane basin in Algeria by using the ITRA, ITPAM, and TPS methods.

Precipitation is one of the most significant components for the basin's hydrological cycle. Numerous features of a basin's water circulation may be affected by the chronological, geographical, and seasonal fluctuation of precipitation. It could be an important factor that influences hydrometeorological phenomena including floods and droughts. In this research, the innovative trend risk analysis (ITRA), innovative trend pivot analysis (ITPAM), and trend polygon star (TPS) methodologies of visualizing precipitation data are used to detect precipitation changes at six stations in Algeria's Wadi Ouahrane basin from 1972 to 2018. ITRA graphs show the direction of the precipitation trend (increasing-decreasing) and the trend risk class. Disparities in the polygons generated by the arithmetic mean and standard deviation ITPAM graphs demonstrate variations in precipitation seasonally and in the seasonal precipitation trends (increasing or decreasing) between sites. The TPS maps depict monthly variations in precipitation and highlight the autumn and spring transitions between the dry and wet seasons.

Design and analysis of statistical probability distribution and non-parametric trend analysis for reference evapotranspiration.

Accurate estimates of reference evapotranspiration are critical for water-resource management strategies such as irrigation scheduling and operation. Therefore, knowledge of events such as spatial and temporal reference evapotranspiration (ETo) and their related principle of statistical probability theory plays a vital role in amplifying sustainable irrigation planning. Spatiotemporal statistical probability distribution and its associated trends have not yet has explored in Pakistan. In this study, we have two objectives: (1) to determine the most appropriate statistical probability distribution that better describes ETo on mean monthly and seasons wise estimates for the design of irrigation system in Khyber Pakhtunkhwa, and (2) to check the trends in ETo on a monthly, seasonal, and annual basis. To check the ETo trends, we used the modified version of the Mann-Kendall and Sen Slope. We used Bayesian Kriging for spatial interpolation and propose a practical approach to the design and study of statistical probability distributions for the irrigation system and water supplies management. Also, the scheme preeminent explains ETo, on a monthly and seasonal basis. The statistical distribution that showed the best fit ETo result occupying 58.33% and 25% performance for the design of irrigation scheme in the entire study region on the monthly level was Johnson SB and Generalized Pareto, respectively. However, according to the Anderson-Darling (AD) and Kolmogorov-Smirnov (KS) goodness of fit measure, seasonal ETo estimates were preferably suited to the Burr, Johnson SB & Generalized Extreme Value. More research work must be conduct to assess the significance of this study to other fields. In conclusion, these findings might be helpful for water resource management and policymaker in future operations.