http://repository.pauwes-cop.net/handle/1/215 2026-07-26T17:35:45Z http://repository.pauwes-cop.net/handle/1/596 Assessing Future Climate Change on maize Crop Productivity using Aquacrop Model in Southern Mali KONE, Lassina Dit Papa This thesis investigates the seasonal crop biomass and grain yield of rainfed maize in N’Tarla, situated in the southern region of Mali, through simulation using aquacrop model. The average biomass and grain yield of maize under historical period spanning from 1991 to 2020, encompassing a period of 30 years were found to be 5.14 and 2.16 t/ha, respectively. Trendline analyses reveal a slight decreasing trend for both maize biomass and grain yield, indicating potential challenges to future agricultural productivity. Moreover, significant changes in maize yields were observed. In addition, the ability of CanESM2 downscaled by RCA4 to simulate the future climate of the region was evaluated, demonstrating satisfactory performance. The projected climate trends indicate a continual rise in global temperatures, with the region experiencing increases of up to 6.0°C and 2.7°C in minimum and maximum temperatures, respectively, by 2080 under the RCP 8.5 scenario. Furthermore, rainfall is expected to decrease by 41.6% within the region by 2050 under the RCP 4.5 scenario. The future scenarios highlight the influence of changing rainfall patterns and temperature rise on maize crop yield. A decrease of 0.3% and 1.6% in grain yield was observed under the RCP 4.5 scenarios for the periods 2021-2050 and 2051-2080, respectively, compared to the reference period of 1991-2020. Similarly, all scenarios demonstrated a decrease in biomass yield compared to the baseline period, with the most significant reductions observed under the RCP 4.5 and RCP 8.5 scenarios for the period 2051-2080. Given these findings, it is imperative to adopt adaptation strategies to mitigate the adverse effects of climate change on maize production. Such strategies may include selecting more resilient crop varieties, enhancing water and nutrient management practices, and diversifying production systems to ensure food security and sustainable agricultural development in the face of changing climatic conditions 2024-03-01T00:00:00Z http://repository.pauwes-cop.net/handle/1/595 Spatio-temporal study of rainfall and temperatures in Guinea: case of N'Zérékoré TRAORE, Sidiki The Spatio-temporal study of rainfall and temperatures is capital importance for understanding climatic variations in Guinea, particularly in N’Zérékoré prefecture. The main objective of this research is to understand the climatic trends observed over time in N’Zérékoré prefecture. The applied methodologies include trend analysis using the Mann-Kendall test and Sen's slope estimator, as well as statistical analyses, and were calculated by XLSTAT software included in Excel. Global climate models, such as MIROC6 and ACCESS-CM2, have been used to study future climate projections. Data was collected from various sources, including the N'Zérékoré meteorological station and global climate models were downloaded from the website https://www.worldclim.org/data/cmip6/cmip6climate.html. This study uses various formulas and methods to analyze climate data using MATLAB. Formulas such as Pearson’s correlation, RMSE, MSE, standard deviation, and standardized precipitation and temperature index (Tmax and Tmin), as well as data normalization and arithmetic mean, are essential to evaluate and characterize precisely the statistical series dispersion. GIS software, with the use of its ArcGIS 10.8 version, generates maps of the study area and future projections based on different climate models. The results obtained revealed significant interannual variability in rainfall and maximum and minimum temperatures, highlighting the trends of decreasing rainfall and increasing temperatures signifying the climate change impact on N’Zérékoré region. Seasonal variations of precipitation and temperature (Tmax and Tmin), were also examined, providing valuable information on seasonal climate patterns in the prefecture. The evaluation of different models allowed us to identify MIROC6 and ACCESS-CM2 models for climate scenarios. We used MIROC6 model for precipitation projections and maximum temperature and ACCESS-CM2 model for minimum temperature. In sum, the results of its projections clearly showed that in N’Zérékoré, the clues and signals related to climate change are perceptible in this city with future increases in temperatures (Tmax and Tmin) in the 20s, 40s, 60s, and 80s years to come 2024-01-01T00:00:00Z http://repository.pauwes-cop.net/handle/1/593 ASSESSMENT OF FOREST COVER CHANGES IN SIMIEN MOUNTAIN NATIONAL PARK UNDER CURRENT CLIMATE CHANGE IN NORTHERN ETHIOPIA ACHENEF, DESTAW FENTIE Climate change poses a serious threat to forest ecosystems, including the Simien Mountains National Park in Ethiopia. This study examined the impacts of climate change, particularly temperature and precipitation changes, on the park's forest cover dynamics during 1983 2023. By integrating climate data, remote sensing techniques and vegetation indices, the study provided a better understanding of the complex interaction between environmental factors and changes in forest cover. The analysis showed a decreasing trend in annual rainfall, with the minimum recorded value being 832.76 mm in 2023. However, temperatures showed an increasing trend, with the average temperature increasing by 0.033 °C each year and the maximum temperature increasing by 0.059 °C per year. These climate changes were accompanied by a significant 37% decrease in forest cover, from 571.96 units in 1983 to 334.52 units in 2023, and a 22% decrease in the Normalized Vegetation Difference Index (NDVI) from 0.87 in 1983 to 0.68 in 2023. Correlation analyzes showed a moderately positive correlation (R² = 0.562) between precipitation and forest cover, while average temperatures showed a moderately negative correlation (R² = 0.585) with forest cover. The influence of maximum temperatures on forest cover (R² = 0.618) and NDVI (R² = 0.593) was more pronounced than that of minimum temperatures. The results suggested that the increase in maximum temperatures had a significant negative impacted on vegetation dynamics, with a 1°C increase being associated with a 40.62-unit reduction in forest cover. The increase in precipitation generally favored an increase in vegetation productivity, with an increase in NDVI of 0.0003794 per unit increased in precipitation. By quantifying trends and relationships, the study highlighted the park's vulnerability to climate change. The results contributed to the understanding of climate change in mountain forests and provided insights into adaptation strategies with the aim of increasing the resilience of ecosystems 2024-03-22T00:00:00Z http://repository.pauwes-cop.net/handle/1/589 Climate Change Effect on Land Use, Cassava Production and Yield in Nigeria Udochukwu, Promise Delight Climate change is a global challenge affecting human beings, their socioeconomic activities, health, livelihood, and food security. Cassava is Africa‘s most important staple food after maize, in terms of calories consumed and also a major source of calories for roughly two out of every five Africans. Despite being the highest producer of cassava globally with over 9 million ha devoted to cassava production annually, Nigeria‘s yield (tonnes/ha) has progressively declined. There is a need for an investigation of the effects of climate change on the declining yield status of Nigeria. The objectives of this study were to determine the effects of temperature and rainfall variability on cassava land use, production and yield between 1980 and 2021. The study employed the mixed-method (quantitative and qualitative) to analyze the impacts of climate change on land use, cassava production and yield in Nigeria. Data collection for quantitative method utilized time series data covering the period from 1980 to 2021, encompassing two climatic variables, temperature and precipitation. These yearly national climatic data were sourced from the Nigerian Metrological Institute (NIMET). The dataset ranged from 1980 to 2021 for all the stations. The historical datasets on land use, cassava yield and production was sourced from the Food and Agricultural Organization of the United Nations (FAOSTAT). Multiple linear regression was used to model relationships and project future climate impacts. Surveys (n=400 farmers) provided quantitative yield and production data and qualitative perceptions of impacts. Focus groups (n=20) generated qualitative data on adaptation strategies. Results showed increasing temperatures and slightly higher rainfall overall. Quantitative analysis of meteorological data (1980-2021) showed rising temperatures and rainfall trends. Multiple regression modeled relationships between climate variables and yield quantitatively. Results showed that cassava yield increased slowly pre-2000 (9.58 – 9.70 t/ha), increased steeply from 2001 to 2010 (9.60 – 12.22 t/ha), and fell drastically post-2010 (12.22 – 5.84 t/ha). The decline in cassava yield post-2010 was associated with soil degradation, poor access to improved farming materials, pest and diseases, poor management, quality of rainfall rather than amount (regularity and duration) and increase in temperature. Farmers reported delayed rains, excess rain, higher temperatures and longer sun hours as factors that negatively impacted yield. In conclusion, continued adaptation is needed based on quantitative trends and farmers' qualitative experiences in coping with climate risks. 2024-05-01T00:00:00Z