The study attempted to assess land surface temperature (LST) 4.91±0.7, 3.53±0.3, 3.14±0.2 and 1.87±0.3 respectively, with their respective yearly temperature increase estimated at 0. 21°C, 0.15°C, 0.14°C and 0.08°C between 1991 and 2015
Identifying landscapes having comparable hydrological characteristics is valuable for the determination of dominant runoff process (DRP) and prediction of flood. Several approaches used for DRP-mapping vary in relation to data and time requirement. Manual approaches which are based on field investigation and expert knowledge are time demanding and difficult to implement at regional scale. Automatic GIS-based approach on the other hand require simplification of data but is easier to implement and it is applicable on a regional scale.In this study, GIS-based automated approach was used to identify the DRPs in Anambra area. The result showed that Hortonian overland flow (HOF) has the highest coverage of 1508.3 km 2 (33.5%) followed by deep percolation (DP) with coverage of 1455.3 km 2 (32.3%). Subsurface flow (SSF) is the third dominant runoff process covering 920.6 km 2 (20.4%) while saturated overland flow (SOF) covers the least area of 618.4 km 2 (13.7%) of the study area. The result reveal that considerable amount of precipitated water would be infiltrated into the subsurface through deep percolation process contributing to groundwater recharge in the study area. However, it is envisaged that HOF and SOF will continue to increase due to the continuous expansion of builtup area. With the expected increase in HOF and SOF, and the change in rainfall pattern associated with perpetual problem of climate change, it is paramount that groundwater conservation practices should be considered to ensure continued sustainable utilization of groundwater in the study area.
The city of Lagos, Nigeria has undergone rapid increase in population due to economic and commercial activities. As a result of this, there has been a persistent change in Land use/Land cover (LULC) of the city and shoreline through the years. This observation necessitated the use of multi-temporal satellite data to characterize shoreline changes between 1984 and 2016. Therefore, the study attempts to determine the shoreline change during the study period and the coastal land use and land cover (LULC) of the study area. Satellite data was acquired andsubjected to some image processing techniques such as image enhancement, supervised classification, and shoreline extraction. The digital shoreline analysis system (DSAS) in ArcGIS environment was utilized to cast transects and calculate statistical parameters for the shoreline and spatial data used was Landsat TM, ETM and OLI for the years 1984, 1990, 2000, 2004 and 2016 respectively. The results indicate that LULC changes in builtup areas increases rapidly during the years (1984-2015) from 12.2 -36.2%, water bodies increased from (1984- 1990-2000) from 52%, 54%, 52% and reduces to 47.4% in the year 2015 while vegetation cover reduces drastically through the year range from 36%, 33%, 29%, 24% and 16%. A total of 1034 transects were generated with 100m spacing and the average rate of change was calculated for the 32 year period (1984-2016). The linear regression rate (LRR) shoreline result shows a mean of -0.59m/year where 73.1% of transect fall under erosion and 61.8% accretion respectively. The end point rate (EPR) and net shoreline movement (NSM) analysis revealed mean shoreline change of -0.57m/year and -18.1m/period respectively from 1984-2016. The EPR and NSM results both revealed that 231 transect or 22.3% experienced erosion, and 805 transect or 77.9% with accretion. It was observed that significant accretion rate recorded along most sections of the shorelines is attributed to beach nourishment activities.
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