Amirkabir University of Technology AUT Journal of Civil Engineering 2588-2899 10 4 2026 10 01 Relative Humidity Forecasting as an Influent Factor in Hydro-climatology 6164 10.22060/ajce.2026.23975.5909 EN Yaser Sabzevari Department of Water Science and Engineering, College of Agriculture, Isfahan University of Technology, 8415683111, Iran Institute of Hydrology, Slovak Academy of Sciences, Dúbravská cesta 9, 84104, Bratislava, Slovakia 0000-0002-3805-2792 Saeid Eslamian Department of Water Science and Engineering, College of Agriculture, Isfahan University of Technology, 8415683111, Iran Saeid Okhravi Institute of Hydrology, Slovak Academy of Sciences, Dúbravská cesta 9, 84104, Bratislava, Slovakia Journal Article 2025 03 05 Climate change is one of the major environmental challenges of the present era. Among the key climatic parameters, atmospheric humidity plays a crucial role in defining weather conditions, agriculture, human health, and various economic activities. Therefore, This study explores the forecasting of relative humidity (RH) as a significant factor in hydro-climatology using the ARIMA(0,1,1) model. The research utilizes historical RH data from 1993 to 2022, coupled with the Mann-Kendall test for trend analysis and time series techniques, to evaluate both past and future RH trends. The results indicate that while RH experienced a decreasing trend over the past three decades, this trend was not statistically significant because of Z statistical equal= -0.01 that is fewer than 1.96 threshold. Further analysis using the ARIMA model forecasts a slight increase in RH in the coming years. These findings suggest that, despite the absence of significant past trends, RH may show modest upward changes, which could influence future hydro-climatic conditions. The study highlights the importance of incorporating RH forecasting into hydro-climatological models for more accurate predictions of climate behavior and water resource management. Additionally, the research underscores the utility of time series analysis in understanding long-term climate variables and their implications for environmental planning. https://ajce.aut.ac.ir/article_6164_2d5951d1e3b31dfb7fd2dcc172df17fd.pdf