No abstract

No abstract

Land use change is the most precise method used to understand the past and future land use dynamics of an area. Based on historical land use change, this study simulated the spatial patterns of land use in 2030, 2040, and 2050 using the CA-Markove model in Tersset. Land use classification maps from 1986, 1996, 2006, and 2020 were used in the Markov chain analysis to predict future maps. The simulated land cover map for 2020 was validated by comparing it with the classified map of the same year. The Overall Kappa value was 0.8878, indicating satisfactory performance. Future land use changes were quantitatively and spatially analyzed and the results revealed an increase in farmland from 38.7% in 2030 to 53.1% in 2050 to the detriment of savannah forest and Savanah Woodland, which is projected to decline from 21.7–13.4% and 33.0–22.2% respectively within the same period. The major transitions that occurred over the study period include, transition from farmland to savannah woodlands and savannah forest to savannah woodlands. Savannah forest persisted in the Northern part of the catchment and along the rivers. Conversion from savannah forest to farmland was observed to be prominent around the Tono reservoir, which is cause for concern. Hence, timely management measures need to be taken by policymakers to protect and sustainably manage forest resources in the catchment to safeguard water resources downstream. Study findings provide a scientific basis for decision-making for the catchment’s forest-water resources management.

Reservoirs are significant freshwater sources. Meanwhile, reservoir storage is compromised by sedimentation for which reason reservoir sedimentation has become an important matter in reservoir operation and management. This paper aimed to assess land cover change in two catchments in Northern Ghana in relation to the sedimentation of reservoirs located downstream of their catchments. The two reservoirs comprise a small-sized (Vea reservoir) and a large-sized reservoir (Tono). First, bathymetric surveys were performed on reservoirs to calculate the loss of storage capacity between 1985 and 2020. Then satellite imagery from 1986, 1996, 2006, and 2020 was used to classify land cover in catchments for the respective years. The results revealed an annual sedimentation rate of 0.17% and 0.304% for Tono and Vea, hence indicating a higher sedimentation rate in the smaller reservoir (Vea). During the study period, savannah forest decreased from 34.7% to 21.6% in Tono and a more drastic decline from 29.4%(1985) to 9.9%(2020) in Vea. This reduction was largely influenced by the expansion of farmlands from 18.7% to 47.9% in Vea and 19.2% to 39% in Tono. According to these observations, watershed land cover characteristics have a significant bearing on the rate of sedimentation in reservoirs located downstream of their catchments. Morso, small-sized reservoirs are known to be more vulnerable to sedimentation but the severity of sedimentation in them is exacerbated by extensive tree cover removal in their catchments since that would result in higher sediment generation. Hence, adopting a multisectorial approach to dealing with vegetation change patterns is necessary to sustain reservoirs' storage.

Land-use change influences watershed hydrology and eventually, the sustainability of reservoirs. Understanding how reservoir catchment land use dynamic influences hydrology is imperative to devise effective land management and planning strategies for sustainable management of reservoir storage. This study evaluated the response of hydrological components of the Vea reservoir catchment (a sub-catchment of the White Volta Basin in West Africa) to past, present, and future land-use change scenarios (1985, 1996, 2006, 2020, 2030, 2040) using the Soil Water Assessment Tool (SWAT). The model performed satisfactorily with NSE values of 0.738 and 0.782 for calibration and validation respectively. The land cover change analysis revealed a continuous increase in farmland and built-up areas from 1986 to the projected 2040 resulting in increased Curved Numbers (CN). The model results revealed that an increase in CN from 81.26 to 86.06 between 1986 and projected 2040 resulted in a -7.8% and − 26.2% decrease in ET and base flow respectively, 46.9%, and 5.1% increase in surface runoff, and water yield respectively. Despite the general decline in base flow, the seasonal trend shows that base flow extends to January, indicating that the shallow aquifer store enough water that can be extracted for dry season gardening. While vegetation restoration is critical to reducing eroded sediment yield from the catchment to guarantee reservoir storage, constructing dams and dugouts within the catchment to harness the high surface runoff water for irrigation and livestock watering in the long dry season is also needful.