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 km 2 ), 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.

Hydrological modelling is a challenge in the rainforest dominated Bonsa catchment (1482 km 2) in Ghana, West Africa, because of data scarcity and rapidly changing land uses. The objective of this study was to assess the suitability of the daily time step physical-conceptual ACRU model for hydrological modelling in the Bonsa catchment. Since the catchment is data poor, model calibration was conducted using a careful parameterization and sensitivity analysis, using initial values obtained from literature and field observations, as well as climate data for the period 1987-1999 and 1991 land use. The model performance during calibration and validation was satisfactory, with a monthly NSE of 0.6 and 0.5 and R 2 of 0.8 and 0.7, respectively. The model simulated the rise and the recession of the hydrograph well, but during the validation the accumulated monthly streamflows were underestimated by 10%. The main conclusion from this study is that the ACRU hydrological model is suitable for exploring basic hydrological responses to land use and climate in the Bonsa and similar catchments.

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Abstract. This study analysed the separate and the combined impacts of climate and land use changes on hydrology on the Bonsa catchment in Ghana, West Africa, using the ACRU hydrological model. The study used five RCP8.5 climate change scenarios (wet, 25th percentile, 75th percentile, dry and a multi-model median of nine GCMs) from the CMIP5 AR5 models for near (2020 -2039)

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The characterisation of rainfall variability, spatially and temporally, is essential for hydrological and ecological analyses. Inherently, this variability is distinctly more obvious in mountainous areas compared to lowlands. The objective of this study was to ascertain if the use of the regression-Kriging technique would provide improved estimates and understanding of the rainfall distribution across the Cathedral Peak catchments in the Drakensberg escarpment region, South Africa. Findings showed longitude and altitude to be the overall best predictors of the distribution of rainfall for the annual period, wet season and dry season, with longitude explaining 72% and altitude explaining 26% of the rainfall variability for mean annual precipitation, 73% and 26% for the wet season and 50% and 22% for the dry season, respectively. The combination of both longitude and altitude showed a larger coefficient of determination, of 0.73, 0.74 and 0.51, for the annual, wet season and dry season, respectively. Long-term mean annual rainfall patterns showed an overall strong directional distribution from west to east with a distinct pattern observed during the dry season. It was concluded that regression-Kriging is a useful alternative method for characterising rainfall distribution as well as prediction errors for mountainous areas.

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