Trend and change-point analyses of meteorological variables using Mann–Kendall family tests and innovative trend assessment techniques in New Bhupania command (India)

Abstract

ABSTRACT Climate change (CC) significantly influences agricultural water productivity, it is advisable to consider the adapting irrigation regimes to observed changes in precipitation patterns. This study aim is to assess trends and change point analysis of weather variables, namely temperature (T), precipitation (R), and reference evapotranspiration (ETo), utilizing 31 years of long-term data for a semi-arid climate. The analysis was carried out using Mann-Kendall (MK), Modified Mann-Kendall (MMK), Innovative Trend Analysis (ITA), and Innovative Polygon Trend Analysis (IPTA) methods. Homogeneity tests, including Pettitt's test, Standard Normal Homogeneity Test (SNHT), Buishand range test, and Von Neumann Ratio Test (VNRT), were employed to detect change points (CPs) in the time series data. The results indicated that, for maximum temperature (Tmax), MK and MMK revealed a positive trend for September and July, respectively, while minimum temperatures (Tmin) indicated Increasing trends in August and September. Precipitation exhibited an increasing trend during the Zaid season (April-May). ETo exhibited a negative trend in January. ITA and IPTA displayed a greater potential to detect the trends across months and seasons. Change point analysis revealed that for Tmax, the CP occurred in 1998 for April month time series data. Likewise, for Tmin, change points for April and August time series found in 1997. This study underscores shifting climatic parameters, emphasizing the importance of accounting for these changes in agricultural and water management strategies to ensure sustainability and resilience.