Climate change impacts on reference evapotranspiration in South Korea over the recent 100 years

The damage owing to climate change is increasing worldwide. In South Korea, the increase in temperature has exceeded the average global temperature increase. These temperature changes have increased the frequency and damage of droughts. To reduce drought damage, the importance of efficient water management policies and evapotranspiration (an index used for water management policies) is increasing. Generally, the potential evapotranspiration (ET0\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${ET}_{0}$$\end{document}) is estimated by using the FAO-56 Penman–Monteith (PM) equation on meteorological datasets. In this study, long-term meteorological data with a maximum of 100 years were collected from 12 sites to estimate evapotranspiration. The objectives of this study were to (1) estimate the evapotranspiration based on the PM equation, (2) analyze the trends in the temperature and evapotranspiration, and (3) evaluate the relationship between the temperature and evapotranspiration through a correlational analysis. The results improve our understanding of climate change and provide a valuable reference for regional water resource management. It is found that there are generally increasing trends in spring, summer, and autumn, and generally decreasing trends in winter. The results from a seasonal Mann–Kendall test between the temperature and ET0\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${ET}_{0}$$\end{document} show that the maximum temperature exhibits a distinct increase in spring and winter in certain areas. We determined the strengths of the relationships between temperature metrics and ET0\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${ET}_{0}$$\end{document} using Pearson’s correlation coefficient, and the results show that the maximum temperature metric has the strongest relationship.