Do Farmers Perceive the Trends of Local Climate Variability Accurately? An Analysis of Farmers’ Perceptions and Meteorological Data in Myanmar

Assessing long-term rainfall trends and changes in a tropical watershed Brantas, Indonesia: an approach for quantifying the agreement among satellite-based rainfall data, ground rainfall data, and small-scale farmers questionnaires

The agreement between meteorological data and societal perception is essential in supporting a robust policy making and its implementation. In humid tropic watersheds like Brantas, such consensus is important for water resources management and policies. This study exemplifies an effort to understand the long-term rainfall characteristics within the watershed and to build a common link among the differing data sources: CHIRPS rainfall satellite data, rain gauge data, and farmers perceptions. Six rainfall characteristics were derived using statistical measures from the scientific data and then were translated to a series of structured questionnaires given to small-scale farmers. A consensus matrix was built to examine the level of agreement among three data sources, supporting the spatial pattern of the meteorological data and farmers perception. Two rainfall attributes were classified with high agreement, four with moderate and one with low agreement. The agreements and discrepancies of rainfall characteristics were found in the study area. The discrepancies originated from the accuracy in translating scientific measurements to practical meanings for farmers, complexity of the farming system, the nature of phenomena in questions, and farmers' ability to record long-term climatic events. This study shows an implication that a combined approach to link scientific data and societal data is needed to support powerful climate policy making.

Evidences of climate change presences in the wettest parts of southwest Ethiopia

Climate change has been identified as a major challenge of rainfed agriculture. To contextualize whether there is climate change footprint, identification of rainfall and temperature trend at regional and local scale is helpful for designing long-term adaptation and mitigation strategies. The present study therefore aims to assess evidences of climate change presences in terms of, climate variability and trend in the wettest parts of Southwest Ethiopia. Daily and monthly historical gridded rainfall and temperature data (1983–2016) of ten stations were provided by Ethiopian National Metrological Agency. Moreover, long years historical recorded climate data of Nekemte and Bedele (1971–2020) and Sekoru (1981–2020) were used in the present study. Coefficient of variation, the Mann-Kendall non-parametric statistical test and Sen's slope estimator, linear regression analysis and the precipitation concentration index were applied to detect the presence of climate change in the southwest parts of Ethiopia. In this study, the trend package of open R software employed for trend identification and rate of change per year. The results indicate that the annual rainfall has declining trend at five stations with statistically significant at one station while the mean maximum and minimum temperature shows a statistically significant increasing trend at eight and six stations, respectively. At a seasonal scale, the amount of rainfall in the main rainy season (June to August) is dominated by a downward trend (eight out of ten stations) while, the autumn season (September to November) shows an increasing trend in all stations with statistically significant at one station. The precipitation concentration index analysis revealed that inconsistent and significantly irregular precipitation is observed at six stations (60%) of the ten stations. This study concludes that the climate of the wettest parts of Ethiopia is getting warmer and the amount of rainfall in the main rainy season has declined in the vast majority of the study area.

Climate change impacts on cattle production: analysis of cattle herders’ climate variability/change adaptation strategies in Nigeria

The study examines the seasonality in climate and extreme weather events, and its effect on cattle production in the Guinea Savannah ecological zone of Nigeria. The study uses both quantitative and qualitative approaches. Climate data of 34 years were used to examine the trends in rainfall pattern and climate variability while household survey was used to appraise the herders’ awareness of climate variability/change impacts and adaptation strategies. Cumulative Departure Index (CDI) method was used to assess the extreme weather events while descriptive statistics and multinomial logistic (MNL) regression model were used to identify the factors that determined herders’ adaptation strategies to climate change. The results revealed a significant spatiotemporal variation in both rainfall and temperature with CDI ranging from -1.39 to 3.3 and -2.3 to 1.81 respectively. The results revealed a reduction in the amount of water available for cattle production. From survey results, 97.5% of the herders identified drought as the major extreme weather event affecting livestock productivities in the study region. In the herder’s perception, the droughts are more severe in recent years than 34 years ago. The results from MNL revealed that extreme weather events, such as drought, has a positive likelihood on migration, at a 10% level of significance, the events has led to migration of cattle herders from the northern part of the study area toward the southern part in recent years.