Abstract: Ethiopia is a country that heavily relies on rainfall-aided cultivation which is carried out by small-scale landowners, leaving it very vulnerable to climate change and fluctuation. The primary goal of this research is to investigate how climate change affects maize yield in Wolaita zone of Ethiopia. The authors were employed a linear regression method to evaluate the relationship between climate parameters and maize yield. Sen's slope magnitude estimator and the Mann-Kendal trend test were used to assess the significance of climate change. The outcome demonstrated that the temperature extreme indices of warm days and the length of warm days were considerably higher by 37.5% and 3.7% of days per year, however, cold days and cold spells were significantly decreased. Over the 1981-2021 periods, there was a significant upward pattern in TXx and TNn at an average of 0.033°C and 0.034°C. There was a considerable decline of 2.3% in the simple daily precipitation intensity index and 33% decreased in extremely heavy precipitation, respectively. The correlation analysis's findings indicated that growing period precipitation and maize outputs were positively correlated, but negatively correlated with maximum and minimum temperatures. Extreme temperature and precipitation were more explained a maize yield than average climate patterns. 12.4%, 14.76%, 13.08%, and 7.95% of maize output variability was attributed by the growing season mean climate conditions, which include precipitation, mean, minimum, and maximum temperature. The variability of maize output was explained by combined impact of precipitation and temperature extremes were 67.7% and 45.0%, respectively. Therefore, livelihood diversification and relevant policy formulation are suggested to adapt inevitable climate change by implementing irrigation and resistant varieties to improve maize yield production.
Abstract: Ethiopia is a country that heavily relies on rainfall-aided cultivation which is carried out by small-scale landowners, leaving it very vulnerable to climate change and fluctuation. The primary goal of this research is to investigate how climate change affects maize yield in Wolaita zone of Ethiopia. The authors were employed a linear regression me...Show More
Abstract: This research investigates the profound impact of land pollution on soil degradation, stemming from human-made (xenobiotic) chemicals and alterations in soil composition. The framework explains a comprehensive nonlinear fractal fractional order eco-epidemic model, delineating four compartments: Susceptible soil (S), Polluted soil (P), Remediation or recycling of polluted soil (T), and Recovered soil (R). The study rigorously establishes the non-negative and unique existence of solutions using the fixed point theorem while analyzing the local and global stability of equilibrium points under pollution-free equilibrium and pollution extinct equilibrium. Dula’s criterion confirms periodic orbits, while categorizing changes in secondary reproduction numbers provides crucial insights into pollution dynamics, enhancing our understanding of system dynamics. Local and global sensitivity analyses, employing forward sensitivity and the Morris Method, yield essential findings for informed decision-making. Additionally, Adams-Bashforth's method is employed to approximate solutions, facilitating the integration of theoretical concepts with practical applications. Supported by numerical simulations conducted in MATLAB, the study offers a nuanced understanding of parameter roles and validates theoretical propositions, ultimately contributing valuable insights to environmental management and policy formulation.
Abstract: This research investigates the profound impact of land pollution on soil degradation, stemming from human-made (xenobiotic) chemicals and alterations in soil composition. The framework explains a comprehensive nonlinear fractal fractional order eco-epidemic model, delineating four compartments: Susceptible soil (S), Polluted soil (P), Remediation o...Show More