Analysis of Precipitation Data Using Innovative Trend Pivot Analysis Method and Trend Polygon Star Concept: A Case Study of Soan River Basin, Potohar Pakistan

Abstract

The trend analysis approach is adopted for the prediction of future climatological behavior and climate change impact on agriculture, the environment, and water resources. In this study, the innovative trend pivot analysis method (ITPAM) and trend polygon star concept method were applied for precipitation trend detection at 11 stations located in the Soan River basin (SRB), Potohar region, Pakistan. Polygon graphics of total monthly precipitation data were created and trends length and slope were calculated separately for arithmetic mean and standard deviation. As a result, the innovative methods produced useful scientific information and helped in identifying, interpreting, and calculating monthly shifts under different trend behaviors, that is, increase in some stations and decrease in others of precipitation data. This increasing and decreasing variability emerges from climate change. The risk graphs of the total monthly precipitation and monthly polygonal trends appear to show changes in the trend of meteorological data in the Potohar region of Pakistan. The monsoonal rainfall of all stations shows a complex nature of behavior, and monthly distribution is uneven. There is a decreasing trend of rainfall in high land stations of SRB with a significant change between the first dataset and the second dataset in July and August. It was examined that monsoon rainfall is increasing in lowland stations indicating a shifting pattern of monsoonal rainfall from highland to lowland areas of SRB. The increasing and decreasing trends in different periods with evidence of seasonal variations may cause irregular behavior in the water resources and agricultural sectors.