This study used annual rainfall records from three stations within the North East Arid Zone of Nigeria for the period (1957-2017) to measure the extent of the rainfall recovery by comparing the drought decades and post drought decades rainfall patterns. Monthly rainfall records from Potiskum, Maiduguri and Nguru Stations were used. Descriptive and inferential statistical tools were employed in analysing the data. The findings of the study revealed a significant year-to-year variability in rainfall characteristics around 61 years (1957-2017) averages. The variability was large in 1970s up till 1990s, and lower in 1960s and from 2000 to 2018. Decreasing trend in annual rainfall amount was observed during the study period while a stability in onset and cessation dates were observed. The differences between 1957-1986 and 1987-2017 climatic season were found to be statistically insignificant. The study concluded that the reported rainfall recovery from drought is statistically insignificant and the observed long term mean trend revealed a decreasing trend. Therefore, the theory of Sahel rainfall recovery can be better termed as a ‘’break of the series of drought or decline in frequency and magnitude of occurrence of drought’’ The research recommended the continuations with the drought adaptation and mitigation strategies adopted by local population, decisions makers and organizations following the series Sahelian droughts of 1970s and 1980s.

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Large-scale climatic variability is seriously affecting rainfall and temperature distribution pattern in Sudano-Sahelian parts of Lake Chad Basin. The Kumadugu-gana and Yobe Rivers that drain the south-western part of the Lake Chad Basin now flow for six months only in a year instead of nine, and this has affected the entire ecosystem of the basin. This study examines the spatio-temporal variability of Kumagu-Yobe river basin rainfall. The study used monthly rainfall records for 1981-2017 from five different weather stations that spread across the up-and-downstream parts of the basin. To accomplish the objective of the study descriptive and inferential statistics were used in analyzing the rainfall attributes and temporal distribution pattern for each of the stations during the study period. Linear regression model was used in analyzing the stations rainfall temporal variability trend. The findings of the study revealed a large scale spatio-temporal variability in the distribution of the rainfall attributes during the study period. Generally, the basin recorded increasing trend of rainfall within the study period. Annual increasing trends of 1.1mm, 3.1mm, 17.6mm and 17.2mm were observed at Potiskum, Nguru, Bauchi and Kano stations respectively. Thus, Jos records insignificant decreasing trend of -0.2mm annually. Specifically, a variability of less than 1% was also observed at Jos and Potiskum stations which is statistically insignificant. A variability of 19%, 28% and 44% was observed at Nguru, Kano, Jos, and Bauchi respectively. Overall, throughout the study periods the basin recorded increasing trend of rainfall that is characterised with large scale fluctuations particularly at the upstream section of the basin.  However,  desertification and upstream water abstraction may have reduced any noticeable increase in stream downstream Keywords : River Yobe, Kumadugu-Yobe Basin, Rainfall, Spatio-Temporal variability   Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

The wetlands of the Kumadugu-Yobe River Basin are the economic mainstay of the lower and mid-stream basin population, providing a wide range of ecosystem services and functions. However, series of impediments have been altering the hydrology of the sub-basin wetlands since the early 1970s. In order to understand the extent of the impact of climate variability on the basin wetlands, this study mapped the temporal variability in wetland size from 1982–2018 and examined the wetland's response to rainfall and temperature variability. The study used advanced very high resolution spectroradiometer (AVHRS) and moderate-resolution imaging spectroradiometer (MODIS) NDVI data sets of 1982–2018 rainfall and temperature data from upstream and downstream stations. Geo-spatial technology and statistical tools were used in analysing the collected data. The findings reveal a large-scale annual increasing trend of 337km2 in wetland size between 1982 and 2018, as against the orthodox view of continuous degradation. The result of the analysis revealed that the wetland’s response to a 1% increase in downstream annual rainfall, upstream annual rainfall, Jos August rainfall and downstream temperature was by expanding by 5.2 km2, 7.5 km2, 33 km2 and shrinking by 1,456 km2, respectively. The study concluded that the basin wetlands respond significantly to any slide fluctuations in rainfall and temperature variables. Based on the findings, the research recommended proper water management strategies within the basin, especially in the Kano region. Water diversion into Tiga and Challawa dams from neighbouring basins is thus a key to the contentious existence of the basin wetlands.

Over the years, West African Sahel’s people developed some strategies for predicting the seasonal weather using meteorological indicators to plan for extreme weather events. This study used information on local indicators of seasonal weather prediction and mean monthly rainfall and temperature record (1981-2017) from Nguru weather station located at Latitude 14°N in achieving the aim of the study. Both qualitative and quantitate (descriptive and inferential) statistical tools were employed in analysing the collected data. The study found that the local population of the study area used meteorological indicators in predicting the seasonal weather. The results of the analysis revealed that the variability of the annual rainfall during the study period was large. An increasing trend of 3.1mm annually was observed. While decreasing trend in the cold, dry and hot dry season temperature and an increasing trend in warm moist temperature by 0.025°C, 0.05°C and 0.0004°C respectively, was observed. Annual rainfall amount accounts for 31% and 2% variability in cold dry and warm moist season temperature, respectively. Cold, dry season and warm moist season temperature respond to any 1mm increase in annual rainfall by decreasing by 0.012°C and 0.002°C, respectively. The Hot, dry season temperature also accounts for 4% of the variability in annual rainfall. The model’s result revealed anyone 1°C increase in hot dry season temperature lowers the annual rainfall by 10mm. This study confirmed that the observed relationship between seasons weather conditions by local population exist. Therefore annual rainfall is the major determinant of cold dry seasonal temperature in the study area.