Climate Data Analysis For Climate Change Mitigation In The City Of Quevedo, Ecuador

Abstract

This study examines climate behavior in the city of Quevedo, Ecuador, with the objective of understanding the effects of climate change and proposing mitigation strategies. Through the analysis of historical meteorological data collected over the last three decades, significant trends were identified, such as a gradual increase in temperature and a decrease in precipitation. These changes have particularly affected agricultural activity, with a negative impact on crops such as bananas, which show an inverse correlation with thermal increase. Technological tools such as Python and QGIS were used to process climatic and socioeconomic data. In addition, surveys and interviews with farmers and local experts were applied to gain first-hand knowledge of the observed effects and current adaptation strategies. Predictive models, such as Random Forest, allowed highly accurate forecasting of extreme events such as floods and droughts, which is key for the design of early warnings. The study also used clustering methods K-means to classify zones with similar climatic characteristics, thus facilitating the prioritization of actions. It is concluded that, to address climate challenges, it is essential to promote efficient water management, the use of sustainable technologies, and environmental education as an awareness-raising tool. The integration of data science and community participation emerges as a promising avenue for strengthening local resilience to climate change in Quevedo.