Application of Remote Sensing and Geoinformatics Techniques in Erosion Mapping and Groundwater Management in the River Amba Watershed, Central Nigeria

This research integrated easy-to-handle remote sensing data and geoinformatics techniques for erosion mapping and groundwater management in the River Amba watershed, central Nigeria. It is aimed at: (a) the determination of the erosion-prone areas and (b) the estimation of the groundwater potential contamination risk under current and future anthropogenic activities. Rainfall intensity was evaluated from monthly rainfall data (2001 - 2011) from the station located within the River Amba Watershed. Digital Elevation Model (DEM) for the terrain was created using the 3D Analyst tool (Surfer 14) and was used to determine the flow direction and lineament features in each raster cells. Remote sensing data (aerial photographs and LANDSAT imagery) were used to develop a land-use map, while geological mapping was used to determine the local geology of the watershed area. The contributions of the various factors to the erosion hazardous areas are: elevation 31.49 %, land use 21 %, slope 14 %, geology 12.52 %, rainfall intensity 10.5 % and flow accumulation 10.5 %. The combined influences of these factors to erosion susceptibility as either: very high, high, moderate, low, and very low with the south-western part characterized as high while other parts of the study area moderate to very low erosion vulnerability. The groundwater level is shallow (4.0 –28.5 m) and discharges through the Amba river and many springs. These springs along with boreholes and wells supply drinking water to Lafia and the environs.

Use of Geoinformatics Techniques for the Assessment and Mapping of Soil Salinity: Concepts and Applications

Irrigated agriculture has a major impact on the environment, especially soil degradation. Soil salinity is a critical environmental problem, which has great impact on soil fertility and overall agricultural productivity. Since, soil salinity processes are highly dynamic, the methods of detecting soil salinity hazards should also be dynamic. Remote sensing data are modern tools that provide information on variation over time essential for environmental monitoring and change detection, as they also help in the reduction of conventional time-consuming and expensive field sampling methods, which is the traditional method of monitoring and assessment. This chapter thus reviewed the concepts and applications of remote sensing, GIS-assisted spatial analysis and modelling of the salinity issue in irrigation fields. Generally, compared to the labour, time and money invested in field work devoted to collecting soil salinity data and analysis, the availability and ease of acquiring satellite imagery data and analysis made this concept very attractive and efficient.