Data from historical observatories and future simulations were analyzed using the representative concentration pathway (RCP) 8.5 scenario, which covered the period from 1951 to 2100. In order to characterize the drought, three widely used drought indicators were used: the standardized precipitation index (SPI), the reconnaissance drought index (RDI), and the standardized precipitation and evapotranspiration index (SPEI). The ensemble of the seven (7) GCMs that used RCA-4 was able to capture several useful characteristics of Nigeria’s historical climatology. Future climates were forecasted to be wetter than previous periods during the study period based on the output of drought characteristics as determined by SPI. SPEI and RDI predicted drier weather, in contrast. SPEI and RDI’s predictions must have been based on the effect of rising temperatures brought on by global warming as depicted by RCP 8.5, which would then have an impact on the rate of evapotranspiration. According to drought studies using the RCP 8.5 scenario, rising temperatures will probably cause more severe/extreme droughts to occur more frequently. SPEI drought frequency changes in Nigeria often range from 0.75 (2031–2060) to 1.80 (2071–2100) month/year, whereas RDI changes typically range from 0.30 (2031–2060) to 0.60 (2071–2100) month/year. The frequency of drought incidence has recently increased and is now harder to forecast. Since the Sendai Framework for Disaster Risk Reduction 2015–2030 (SFDRR) and the Sustainable Development Goals (SDGs) have few more years left to be completed, drastic efforts must be made to create climate-resilient systems that can tackle the effects that climate change may have on the water resources and agricultural sectors.

Lack of adequate access to safe water, sanitation, and hygiene (WASH) has contributed to increased under-five mortality and morbidity of school-age children in low- and middle-income countries. Despite the global and national intervention programs, access to safe WASH remains a critical challenge in Nigeria. This study employed spatial and non-spatial statistics to establish causal relationships between WASH conditions and household factors in Nigeria. Results show that a large proportion of Nigerian households were still associated with unimproved hygiene (88%), sanitation (47%) and water (25%). Wealth status, literacy level and residency type exhibit significant causal relationships with households’ water sources (α = 0.000). Wealth status and the gender of household head exhibit significant causal relationships with sanitation condition (α = 0.000) and hygiene condition (α = 0.004 and α = 0.345, respectively). However, the computed parameter Degree of Dependence (DoD_j) shows that the choice of water sources mostly depends on residency type (DoD_j = 0.998) compared with the level of education and wealth status (DoD_j = 0.535 and 0.485, respectively). Statistical indices show that the implemented regression models are reliable (with models’ DoD of 0.714–0.996, Adjusted R² of 0.184–0.762 and Akaike Information Criterion (AICc) of 68–103). The study concludes that a high risk of unimproved WASH is associated with rural residence, which is usually characterised by a low level of education, poverty and large household size. It further concludes that the high prevalence of unimproved hygiene, irrespective of the household wealth status and educational level, suggests the need for proper health and hygiene education. This study suggests the need for a more focused policy action towards empowering rural and vulnerable households in Nigeria with relevant preventive environmental and health information and appropriate social support for the communities.

Keywords: Landslides, Susceptibility, Geo-information, Jos South, Nigeria As a result of dearth of relevant information about Landslides Susceptibility in Nigeria, the monitoring and assessment appears intractable. Hence, the study developed a Remote Sensing approach to mapping landslides susceptibility, landuse and landcover analysis in Jos South LGA, Plateau State, Nigeria. Field Observation, SPOT 5 2009 and 2012, ASTER DEM 2009, Geological Map 2006, Topographical Map 1966 were used to map Landslide Susceptibility and Landuse /Lancover Analysis in the study area. Geospatial Analytical Operations employed using ArcGIS 10.3 and Erdas Imagine 2014 include Spatial Modeling, Vectorization, Pre-lineament Extraction, Image Processing among others. Result showed that 72.38 % of the study area is underlain by granitic rocks. The landuse/cover types delineated for the study area include floodplain (29.27 %), farmland (23.96 %), sparsely vegetated land (15.43 %), built up area (13.65 %), vegetated outcrop (8.48 %), light vegetation (5.37 %), thick vegetation (2.39 %), water body (0.58 %), plantation (0.50 %) and mining pond (0.37 %). Landslide Susceptibility Analysis also revealed that 87 % of the study area is relatively at low to very low risk of landslide event. While only 13 % of the study area is at high to very high risk of landslide event. The study revealed that the susceptibility of landslide event is very low in the study area. However, possible landslide event in the hot spots could be pronounced and could destabilize the natural and man-made environmental systems of the study area.