The Effects of Gully Erosion on Socio-Economic Development in Kaltungo Local Government, Gombe State Nigeria

Erosion is one of the major environmental challenges affecting sustainable development in Kaltungo Local Government Area, Gombe State, Nigeria. This study examines the causes, effects, and implications of erosion in Kaltungo LGA. The area, with a total land area of 881 km² and a projected population of 268,600 as of 2022, experiences two distinct seasons and an estimated annual rainfall of 1000 mm, which contributes to both water and gully erosion. The study adopts both primary and secondary data. Data were collected through field observation, questionnaire administration, and review of relevant literature and government reports. Findings reveal that the major causes of erosion in Kaltungo LGA include heavy rainfall, poor drainage systems, deforestation, poor agricultural practices, and uncontrolled construction activities. The effects of erosion in the study area are both environmental and socio-economic. Environmentally, erosion leads to loss of fertile topsoil, formation of gullies, destruction of vegetation, and siltation of water bodies. Socio-economically, it results in loss of farmlands, destruction of houses and roads, displacement of communities, reduction in agricultural productivity, and increased poverty among residents. Key infrastructure such as roads linking Kaltungo town to other wards including Awak, Tula Baule, Tula Wange and others villages have also been threatened. Details field work was carried out to collect all the necessary data to be use for this study, which will involve the collection of the following primary data such as the geographic location of eroded areas within the study area. A total number of one hundred and fifty (150) questionnaires was distributed proportionally and randomly based on the population size of the various sampled communities. Landsat images was classified using the supervised image classification technique. A supervised classification method was carried out using training samples. This process enables us to assign each pixel of an image to a particular land cover group or class. Maximum Likelihood Algorithm was employed to detect the land cover types using ArcGIS 10.8 software, map analysis and production was also carried out in AcrGIS 10.8 software and statistical analysis were carried out in Microsoft 2013 version.The study concludes that if erosion is not properly managed, it will continue to undermine agriculture, infrastructure, and livelihoods in Kaltungo LGA. It recommends afforestation, construction of drainage channels, public enlightenment, terracing, and government intervention through erosion control projects as sustainable measures to mitigate the problem.