Evaluating the spatial and temporal variations of aquatic weeds (Biomass) on Lower Volta River using multi-sensor Landsat Images and machine learning

Abstract

Aquatic invasive weeds affect hydrological, ecological, and socio-economic activities on freshwater ecosystems. On the Lower Volta River (LVR) of Ghana, invasive aquatic weeds have been known to be nuisance to fishing, navigation, aquaculture, hydropower production and other agricultural practices in the area. While information on the spatial and temporal distribution of aquatic weeds would be beneficial in improving weed management and control measures on the river, such information is very scanty. Also, these aquatic weeds are also biomass resources, that can be transformed to bioenergy. Thus, this study evaluated the spatial and temporal variations of aquatic weeds on the Lower Volta River, and assessed their potential biomass for bioenergy production. Random Forest (RF) algorithm and Landsat images were used to map the distribution of the weeds in 1975, 2003, and 2020, respectively. Accuracy assessment results showed mean Overall Accuracy (OA) of 83.44% and mean User Accuracy (UA) of 79.24%. The results indicated that as of 1975, aquatic weeds covered only 1495 ha and appeared in some specific locations such as Kpong and Ada. However, by 2003, the weeds had spread to most parts of the river covering 5600 ha, which was an increase of approximately 4-fold within a period of 28 years. The area covered by the weeds, however declined by 1505 ha between 2003 and 2020. Thus, in 2020, water hyacinth covered about 36% of the aquatic weeds relative to 28% in 2003. The results showed that, the quantity of the water hyacinth biomass per unit area was 21.5 kg/m2. This result can also be used as the basis for resource assessment as well as determination of its viability for bioenergy production and strategies for its modern utilisation. The conversion of water hyacinth into bioenergy remains one of the best aquatic weed management strategies that must be adopted in LVR.