Abstract
Climate change, which is one of the main determinants of agricultural production, has started affecting the pattern of crop growth, productivity, and quality of produce from the last few couple of decades in various agro-climatic zones globally. Any change in climatic factors such as temperature, evapotranspiration (ET), and rainfall is bound to have a significant impact on agricultural production. Thus, climate monitoring, trend analysis, and model-based prediction are highly significant to mitigate the climate change impacts on crop growth patterns, production, and quality traits. A study was thus undertaken at Punjab Agricultural University, Ludhiana, India, to (1) estimate reference evapotranspiration (ETo) using FAO-ETo calculator; (2) study and detect trend in long-term (1970–2019) recorded temperature (Tmin and Tmax), rainfall and ETo using Mann–Kendall’s test, Sen’s slope test, standard normal homogeneity test (SNHT), and Pettitt’s test in XLSTAT software; (3) study correlation of ETo with Tmin, Tmax, and rainfall; and (4) develop regression models for estimating ETo on seasonal and annual basis. All the tests indicated a significant trend in Tmin (increasing) and ETo (decreasing) during all seasons (spring, summer, autumn, and winter), as well as on annual basis at 5% level of significance, whereas no trend was recorded in Tmax and rainfall data. The SNHT and Pettitt’s test confirmed the existence of a change-point in both ETo and Tmin data for all seasons as well as on annual basis. Both Mann–Kendall’s and homogeneity tests indicated no trend or change point in Tmax (except a change-point during spring) and rainfall data. The positive correlation of ETo with Tmax, wind speed (vw), and sunshine hours (SSH) formed an increasing trend in ETo with increase in these variables and vice-versa. The negative correlation of ETo with relative humidity (RHmin and RHmax), rainfall, and Tmin indicated a decreasing trend in ETo. The study offers a basis to predict the futuristic climate scenarios in the region for planning crops and manage irrigation to mitigate the climate change impacts on agricultural production. The statistical comparison indicated that the developed models were sufficiently accurate and would be useful in simplified estimation of ETo on seasonal and annual basis for the study region.
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The authors acknowledge the Department of Climate Change and Agricultural Meteorology, Punjab Agricultural University, Ludhiana, for providing meteorological data.
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Singh, M.C., Satpute, S., Prasad, V. et al. Trend analysis of temperature, rainfall, and reference evapotranspiration for Ludhiana district of Indian Punjab using non-parametric statistical methods. Arab J Geosci 15, 275 (2022). https://doi.org/10.1007/s12517-022-09517-1
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DOI: https://doi.org/10.1007/s12517-022-09517-1