Assessing rainfall and temperature trends to guide agricultural adaptation

Impacts of climate change (CC) and variability are prominent in most parts of the world, with the agricultural sector in developing countries being particularly vulnerable due to its limited adaptive capacity. This study was conducted in the Morogoro region of Tanzania to determine trends in rainfall and temperature from 1988 to 2018, aiming to support formulation of suitable climate change adptation strategies in agriculture. Using the Mann-Kendall test and Theil-Sen slope estimator, we observed a statistically significant (p < 0.1) decreasing trend in annual rainfall from − 2 to −16 mm per year and monthly rainfall from − 1 to − 8 mm month year-1. Conversely, the annual maximum temperature showed a significant (p < 0.1) increase from 0.005 to 0.025 ℃ year-1 and the minimum temperature also increased significantly (p < 0.1) from 0.01 to 0.03 ℃ year-1. Our analysis indicates that paddy production is influenced by this variability. Specifically, our regression model results showed that higher maximum (p = 0.006) and minimum (p = 0.004) temperatures were significant predictors of paddy yield, while annual rainfall was not (p = 0.264). We conclude that localized, spatiotemporal trend analysis is crucial for developing effective CC adaptation strategies. This research provides useful, evidence-based climate information needed to design targeted policies that can enhance agricultural resilience and support sustainable development for vulnerable farming communities.