Assessing the Impacts of Land Use Land Cover Change In Mutama Bweengwa Catchment 0f Southern Province, Zambia

Climate change and land use land cover directly impact the alteration of hydrological cycles, making water more unpredictable and increasing the frequency and intensity of floods and droughts. However, proper planning of adaptation and mitigation options is hampered by inadequate up-to- date information on land use/Land cover in many catchments and sub-catchments of Zambia and other developing countries. This study assessed the land use change in the Mutama Bweengwa River Catchment of Southern Zambia. The objective of the study was to investigate land use land cover changes (LULCC) in the Mutama Bweengwa Catchment in the Southern Province of Zambia from 2000 to 2021. The data used for the study were satellite images of the area downloaded from the United States Geological Survey (USGS). Specifically, the Landsat images were from path 172/row 71 and path 172/row 72 for the period 2000, 2007, 2014 and 2021. The methods used included data identification and acquisition, image pre-processing, image processing, accuracy assessment, validation and presentation. Image pre- processing was used to correct distortions during image acquisition. The techniques used were: image enhancement for extracting useful information, which involved carrying out band combination and brightness and contrast adjustment when conducting the mosaicking process using ERDAS imagine 2014. Supervised classification based on the maximum likelihood algorithm in ERDAS Imagine was employed to generate the land use land cover classification and later exported in ArcMap 10.7.1 for map creation. The image classification was based on six different LULC classes, which were: water body, build-up/settlement, forest, cultivated land- rainfed/bare land, cultivated land-irrigated, and grasslands. Preliminary results of this study have shown a decrease in the classes of water bodies and forest areas by 0.34% and 55.5%, respectively, over the 21-year period. The accuracy of the resultant land use/land cover maps was evaluated with the kappa statistic and error matrix. The preliminary results have also shown an increase in the land use land cover class categories of cultivated land-irrigated, grassland, cultivated land-rain fed/bare land and built up/settlements by 0.13%, 46.7%, 14.6% and 8.4%, respectively. In conclusion, the supervised classification of the Landsat images indicated pronounced land cover changes over the 21-year period. Although this provides preliminary conclusions, it indicates that immediate actions should be taken to protect the sub-catchment from further loss of land cover by strengthening the regulatory framework. Further work on the project is expected to bring out some of the factors that have contributed to this change.