Interplay of weather patterns and Wildfire in Tsavo Conservation Area, Kenya.

Abstract

<title>Abstract</title> <bold>Background:</bold> Wildfires, in recent years have caused devastating destructions in many parts of the world due to extreme weather conditions. Wildfire trend in Tsavo Conservation Area in Kenya is not well understood and published articles on wildfires in the region are limited. Our study aimed at establishing the relationship between weather and Wildfire pattern in Tsavo Conservation Area, which is in southeastern side of Kenya. Such information could be useful in predicting the likelihood of Wildfire occurrence. Hence making Wildfire management easier and sustainable. <bold>Results: </bold>We obtained secondary data for Wildfire occurrence and climatic factors to establish: Relationship between Wildfires and weather patterns, Wildfire seasons, Wildfire predictive models and Wildfire indicators combination matrix model. Our study obtained remote sensed Wildfires data for 19-year period from 2002 – 2020 from National Aeronautical and Space Administration website. We also obtained weather data for the same period from the Kenya Meteorological Department. The data provided by Kenya Meteorological Department included temperature, rainfall, wind speed, and humidity. Our study used Generalized Additive Model with poison distribution and Spearman Correlation to analyze the relationship between Wildfire occurrence and weather variables. The year 2020 recorded the highest number of Wildfire of 481 during the study period. We established the wildfire season for the Tsavo Conservation Area to be from June to October. September recorded the highest average number of Wildfires of 690 within the 19-year period. Humidity is the best predictor for wildfires in Tsavo Conservation Area. Our study also came up with a Matrix Model that could be used to identify months of the year that are likely to experience high Wildfire occurrence. <bold>Conclusion:</bold> The findings would be very useful in Wildfire management as they provide new knowledge on Wildfire occurrences in the area. Humidity factors being the best in predicting Wildfires and June-October being the Wildfire season for Tsavo Conservation Area forms such knowledge. The Matrix Model provide the basis for further studies in Wildfire forecast.