Impact assessments of actual and potential land use (LU) changes on hydrology are vital in land use planning, which is a prerequisite for effective water resources management. In this study, impacts of actual, as well as potential, LU changes on the hydrology of the Bonsa catchment (1482 km²), Ghana, West Africa, were assessed using the Agricultural Catchments Research Unit (ACRU) hydrological model. Baseline, current and potential future LU maps for three scenarios, namely, business-as-usual (BAU), economic growth (EG) and economic growth and reforestation (EGR), driven by observed climate between 1990 and 2009, were used for the study. The results indicate that peak and dry season streamflows between 1991 and 2011 have increased by 21% and 37%, respectively, under the current land use in comparison to the baseline due to a decrease in evergreen and secondary forests by 18% and 39%, respectively, and an increase in settlements, mining areas and shrubs/farms by 81%, 310% and 343%, respectively. The potential future LU scenarios suggest that there may be further increases in streamflows, but the historical land use changes between 1991 and 2011 were so substantial that they will continue to impact streamflow changes in any of the future land use scenarios. The study also showed that variability of streamflow changes at the catchment scale was lower than at the subcatchment scale. For the scenarios of potential future LU changes, the BAU shows the highest increases in streamflows, while the EGR shows the least. Policy interventions for effective management of the catchment are recommended.

This study combined logistic regression, Markov chain and the Dyna-CLUE models to simulate land use patterns in the Bonsa catchment of Ghana, West Africa. Historical model validation produced Relative Operating Characteristics (ROC) statistics above 0.69; indicating a significant relationship between the driving factors and the land cover types, and overall accuracy of 71% as well as a Kappa statistic of 55%, indicating a moderate agreement between observed and simulated land uses. The statistics of the historical model were used to simulate three plausible future land use scenarios. The historical simulation revealed that increases in population density, proximity to roads and expansion of mines were the major drivers that significantly increased the probability of settlement expansion and deforestation. Simulations of future land use showed that settlement expansion and deforestation may increase by similar margins for all scenarios, but the increase in secondary forests may be higher for the economic growth and reforestation (EGR) scenario, compared to the economic growth (EG) and the business-as-usual (BAU) scenarios. The mining areas may double in the future for all the scenarios, but shrubs/farms may increase in the BAU scenario, but reduce marginally in the EG and the EGR scenarios. The results of this study can be used to support land use planning and evaluation of the impacts of different future development pathways. Keywords: Bonsa catchment, deforestation, driving factors, Dyna-CLUE, land use, logistic regression, West Africa

Urban land use efficiency is a key indicator of the resilience of a city and its sustainability. However, in Africa and Ghana, information on land use efficiency in cities is lacking. There is little to no understanding as to how urban development is affecting the lives of people, the economy and the environment. In this study, geospatial techniques were used to estimate urban land use efficiency (LUE), the changes in the built-up area per capita and urban sprawl speed (SS) for the Sekondi-Takoradi Metropolitan area. Multi-temporal land use maps and population data were used for this purpose. The results indicate that generally land use efficiency in the city has improved since 2002, from a value of 0.67 between 2002 and 2008 to 0.88 between 2008 and 2016, and that it deteriorated slightly above one (1) between 2016 and 2021. The city has also become more built up over the period, with the rate of sprawling also declining. However, the study shows that land in the city that was either agricultural land or grassland has been converted to built-up land use/land cover, which is indeed a challenge for urban agriculture. The results of this study can be used by city authorities as a guide to urban development.

Despite the suggestions by numerous studies over the years that spatial land use pattern influences travel behaviour, uncertainty remains about the existence, form, and the extent of any causal relationship between spatial land use and urban travel behaviour. This study seeks to provide a new dimension from the perspective of a medium-sized city in Africa by simultaneously incorporating attitudinal and socioeconomic variables in examining the relationship using structural equation model (SEM). Primary data collected using questionnaires from 534 households of adult commuters with private cars and spatial data of the built environment for households in the Greater Sekondi-Takoradi Area (GSTA) in Ghana were used in this study. Principal component analysis (PCA) was used to reduce 25 statements attributed to travel attitude to four. Similarly, 22 statements attributed to neighbourhood preferences were also reduced to three. Latent constructs of four and 20 observed variables were analysed using SEM in LISREL 10.3 software. The fitness of the final model to the data was assessed using absolute, incremental, and parsimonious fit indices. The findings from the study indicated that socio-economic factors had a stronger influence on households’ automobile travel than self-selection, with land use having the least impact. The results are consistent with earlier studies that suggested self-selection has a greater impact than land use on households’ automobile travel. This suggests that land use policies can effectively be used in controlling households’ automobile travel when the effect of self-selection is simultaneously accounted for with the land use.