Abstract:
Climate change and variability are measures challenges that hinder the economic development of more than 90% of Rwandans that are relying on rain-fed agriculture practices. In Kirehe, the land is insufficient for the farmers with an average of 0.3 ha per smallholder farmer per household as well as the whole country. The scarcity of cultivated land associated with its degradation due to climate change and the population growth rate cause the land to be extremely highly exploited. Environment degradation coupled with temperature trends and rainfall variability both with low correlation coefficients in four decades provides a shift of rainfall seasons to the prolonged dry season in a great part of the Kirehe district where certain sectors pass almost two months without rain in the period that they could have rainfall. Climate change accelerates the level of vulnerability to agriculture practices in the Kirehe district, therefore, I have decided to assess the farmers ‘perception of climate change's impact on adaptation in agriculture practices. The main objective of this work is to improve the kill and knowledge of farmers to the rainfall variability, in the seasonal forecast and temperature time series trends prediction over the Kirehe district that has a huge implication for the provision of food security, promote the use of biodiversity,water resource planning and exploiting ecosystem services to ensure food security and sustainability of better agriculture practices. The date used in works were collected by using structured Questionnaire contains climate change impact statement, and distributed within 206 farmers across twelve sectors of kirehe district, meteorological data such as rainfall and temperature time series from Rwanda meteorological Agency, where data from 8 eight stations were collected rainfall and temperature of kirehe district of period 1983 – 2021. The methodologies used to analyses the data collected and verifying hypothesis test are following ANOVA to test farmers knowledge to climate change for each sample taken from sectors, Chi-Square test analysis to test effectiveness of applied adaptation strategies that are current implemented throughout the farmers. The Mann-Kendall statistics test and Theil Sen’s slop estimator are used to determine the significance and magnitude of the temperature and rainfall time series trend .
The results reveal that farmers from all twelve sectors responded the Questions so that the test hypothesis done for each sector we have rejected the null hypothesis, meaning that P-value calculated or critical value are much smaller than P =0.05 obtained by using ANOVA, therefore farmers have significance perception to climate change impact. The temperature and rainfall time series trends have significance
vi
statistics trends such as table 3 and table 4 ,the regression line reveals different change of rainfall in percentage for annually rainfall -4.008 and correlation coefficient of rainfall is 0.0524 for the temperature change regards graph 20.
