Groundwater serves as a source of freshwater for agricultural, industrial and domestic purposes and it accounts for about 42%, 27% and 36% respectively. As it remains the only source of all-year-round supply of freshwater globally, it is of vital importance as regards water security, human survival and sustainable agriculture. The main goal of this study is to identify the main cause-effect relationship between human activities and the state of groundwater quality using a communication tool (the DPSIR Model; Drivers, Pressures, State, Impact and Response). A total of twenty-one samples were collected from ten peri-urban communities scattered across three conterminous Local Government Areas in Southwestern Nigeria. Each of the groundwater samples was tested for twelve parameters - total dissolved solids, pH, bicarbonate, chloride, lead, electrical conductivity, dissolved oxygen, nitrate, sulphate, magnesium and total suspended solids. The study revealed that the concentrations of DO and Pb were above threshold limits, while pH and N were just below the threshold and others elements were within acceptable limits based on Guidelines for Drinking Water Quality and Nigeria Standard for Drinking Water Quality. The study revealed that groundwater quality levels from the sampled wells are under pressure leading to reduction in the amount of freshwater availability. This is a first-order setback in achieving access to freshwater as a sustainable development goal across Less Developed Communities (LDCs) globally. To combat this threat, there is the need for an integrated approach in response towards groundwater conservation and sustainability by all stakeholders.
Vegetation cover over Nigeria has been on the decrease recently, hence the need for adequate monitoring using geo-information technology. This study examined the spatio-temporal variation of vegetation cover over Nigeria for thirty years with a view to developing a strategy for enhancing environmental sustainability. In order to predict the spatial extent of vegetation cover in 2030, the study utilised satellite images from between 1981 and 2010 using the Normalised Difference Vegetation Index (NDVI) coupled with cellular automata and Markov chain techniques in ArcGIS 10.3. The results showed that dense vegetal areas decreased in area from 358,534.2 km2 in 1981 to 207,812 km2 in 2010, while non-vegetal areas increased from 312,640.8 km2 in 1981 to 474,436.4 km2 in 2010 with a predicted increase to 501,504.9 km2 by 2030, i.e. an increase of about 27,068.4 km2 between 2010 and 2030. The study concluded that geoinformation techniques are effective in monitoring long-term intra- and inter-annual variability of vegetation and also useful in developing sustainable strategies for combating ecological hazards.