Exploring Temperature Trends and Evapotranspiration Modelling for Effective Water Management: A Comprehensive Analysis Using Mann-Kendall Test and Seasonal ARIMA Model

Abstract

The variations in temperature have a profound impact on the irrigation requirement during various stages of the crops. This study aimed to analyse the temperature trends using the Mann Kendall test and also modelled various meteorological parameters by Seasonal Autoregressive Moving Average (SARIMA) model, influencing evapotranspiration (ET). The model was validated for water requirement of wheat crop in Junagadh region of Gujarat during 2023 and 2024. February, March, and April consistently exhibited a highly significant positive trend with Mann Kendall test statistic of 3.325. 2.852 and 3.131 respectively whereas July, August, and November showed no distinct trend in minimum temperatures. A conspicuously significant trend in maximum temperature was not discerned throughout any of the months. SARIMA models (2,0,0)(2,1,1)12, (1,0,0)(0,1,1)12, (1,0,1)(0,1,1)12, (1,0,0)(0,1,1)12, and (2,0,2)(0,1,1)12 were selected from a range of candidate models based on their AIC values and performance on test data for meteorological parameters including minimum temperature, maximum temperature, relative humidity, wind speed, and bright sunshine, respectively. The study estimated the climatic parameters using Penmen Monteith method, allowing us to predict reference evapotranspiration for 2023 and 2024. For the year 2024, the highest ET0 of 188.7 mm was estimated in April followed by ET0 of 186.6 mm in May 2024. The reference evapotranspiration predicted by the models were utilized to calculate the water requirement of wheat in the study area, resulting in an estimated value of 371 mm. These findings are useful for agricultural policymakers for making decisions pertaining to agricultural water management for optimal crop growth.