Malaria is a major public health problem especially in the tropics with the potential to significantly increase in response to changing weather and climate. This study explored the impact of weather and climate and its variability on the occurrence and transmission of malaria in Akure, the tropical rain forest area of southwest and Kaduna, in the savanna area of Nigeria. We investigate this supposition by looking at the relationship between rainfall, relative humidity, minimum and maximum temperature, and malaria at the two stations. This study uses monthly data of 7 years (2001-2007) for both meteorological data and record of reported cases of malaria infection. Autoregressive integrated moving average (ARIMA) models were used to evaluate the relationship between weather factors and malaria incidence. Of all the models tested, the ARIMA (1, 0, 1) model fits the malaria incidence data best for Akure and Kaduna according to normalized Bayesian information criterion (BIC) and goodness-of-fit criteria. Humidity and rainfall have almost the same trend of association in all the stations while maximum temperature share the same negative association at southwestern stations and positive in the northern station. Rainfall and humidity have a positive association with malaria incidence at lag of 1 month. In all, we found that minimum temperature is not a limiting factor for malaria transmission in Akure but otherwise in the other stations.

State is in the South East geopolitical zone of Nigeria. The major occupation of the people in this region is trading and farming, which depends on rainfall and other climatic factors. This paper presents statistical and trend analyses of the rainfall in some selected stations in Anambra State, which includes Ifite-Ogwari, Awka, Onitsha and Ihiala. Rainfall data for a period of 1971-2010 were obtained from Climate Research Unit (CRU). The existence of trend and statistical analyses was conducted on monthly total rainfalls using non-parametric techniques. The study revealed that overall averages of yearly and monthly total rainfall were 5798.

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Floods are water induced disasters that lead to temporary inundation of dry land and cause serious damages in the affected location such as loss of lives and properties and destruction of infrastructures. They have become common occurrences in every part Nigeria and the recorded impacts of flooding on the inhabitants are alarming, causing hundreds of deaths and rendering thousands homeless. The impact of floods on people globally has led to the development of mitigation measures that could reduce the associated risk of floods to a manageable point. The management of flood risk begins with identification of areas prone to flood. This study used the scientific technique of GIS to identify flood risk areas along the River Niger-Benue basin. Satellite imageries SRTM DEM that covers the study area was used in this research. Monthly rainfall data was used to generate maps of standardized precipitation index (SPI) for thirty years (1978 to 2007). The SPI maps were used to determine the degree of precipitation condition across Nigeria and also to identify the locations where flood events are being triggered. The SRTM DEM was used to generate the flow direction and flow accumulation maps. Flow direction and Flow accumulation were used to generate the watershed and flood risk map. The flood risk map shows that 45% of Nigeria towns and villages are within the flood risk zone. Finally, some recommendations were made which will help the policy makers improve on flood management in the country.

Objective: Malaria is one of the leading cause of morbidity and mortality in the developing countries, most especially in the sub-Saharan Africa where the transmission rates are very high. Despite some intervention by government, many people are still infected by the disease. Therefore, this study seeks to evaluate the environmental risk factors affecting malaria prevalence and the spatial-temporal distribution of malaria incidence, in order to delineate the most severely affected area in Ibadan, Southwest and Nigeria. Methodology: The data and materials used include Monthly reported cases of malaria for ten years, 2006-2015, meteorological data (Rainfall, relative humidity and Temperature) and remotely sensed data such as Landsat 8 Operational Land Imager (OLI), Shuttle Radar Topography Mission (SRTM) and soil map of the study area. The relationship between malaria incidence and climate variables were evaluated. The result obtained from climatemalaria correlation was used in ranking the selected climatic factors in developing malaria risk map. Mapping of different spatial clustering patterns like hot spots, high risk and cold spots over the entire study area was done by Hotspot analysis. Result: The results showed that there is a strong relationship between climatic factors and malaria incidence especially maximum temperature and relative humidity. It was also observed that the intensity of clustering of high values (hot spot) and low value (cold spot) was low and varied throughout the study period, but relatively high in the year 2010, 2011 and 2014. The statistically significant hotspots of malaria were consistently detected in southern and eastern part of Ibadan central urban area (Ibadan SouthWest , Ibadan SouthEast and Ibadan NorthEast LGAs) and except Ibadan NorthEast LGA once in 2011. However, Ibadan North and Ibadan NorthWest LGAs remained malaria coldspot throughout the study period. The results could help government agencies, health practitioners and policy makers to plan in the prevention and control of malaria prevalence in the area.