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

Abstract

AbstractThe trend analysis approach is used to estimate changing climate and its impact on the environment, agriculture and water resources. Innovative polygonal trend analyses are qualitative methods applied to detect changes in the environment. In this study, the Innovative Trend Pivot Analysis Method (ITPAM) and Trend Polygon Star Concept Method were applied for temperature trend detection in Soan River Basin (SRB), Potohar region, Pakistan. The average monthly temperature data (1995–2020) for 11 stations were used to create polygon graphics. Trend length and slope were calculated separately for arithmetic mean and standard deviation. The innovative methods produced useful scientific information, with the identification of monthly shifts and trend behaviors of temperature data at different stations. Some stations showed an increasing trend and others showed decreasing behavior. This increasing and decreasing variability is the result of climate change. The winter season temperature is increasing, and the months of December to February are getting warmer. Summer is expanding and pushing autumn towards winter, swallowing the early period of the cold season. The monthly polygonal trends with risk graphs depicted a clear picture of climate change in the Potohar region of Pakistan. The phenomena of observed average temperature changes, indicated by both qualitative methods, are interesting and have the potential to aid water managers’ understanding of the cropping system of the Potohar region.