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The Pra river catchment in Ghana is adversely affected by perennial flooding from high-intensity rainfall events. To aid in flood management at the catchment, the Gumbel extreme value distribution has been used to estimate the return periods of maxima rainfall, flood, and consecutive dry and wet days (CDD and CWD) for a period of 5 to 100 years. The results revealed an expected increase in maxima rainfall, CDD and CWD. Maxima rainfall favours the south of the catchment while the CDD decreases northward. Furthermore, an increase in the magnitude of CWD observed at the centre of the catchment had a maximum of approximately 30 days for the 100 year return period, while lower flood volumes had a higher recurrence of 50% to 100% for 1 to 2 year return periods. The inclusion of a projected increase in anthropogenic activities and climate factors at the catchment will slightly affect the magnitude of these variables for the various return periods. Nonetheless, the findings in this study will be of essential input to policy implementation of the Integrated Water Resource Management Plan for river catchments in Ghana, West Africa., Maxima rainfall; Maxima flood; Maximum wet and dry days; Gumbel's distribution; Return period

Assessing the evolution of surface to near-surface atmospheric fluxes is key to improving our understanding of their interactions, while further advancing climate applications. In this paper, an overview of the diurnal to seasonal evolution of some surface to near-surface atmospheric fluxes, coupled with their interactions, have been provided. Fluxes of downwelling and upwelling radiation ( $$SW_\downarrow$$ , $$SW_\uparrow$$ , $$LW_\downarrow$$ , $$LW_\uparrow$$ ), soil heat flux ( $$\Delta H$$ ), relative humidity (RH), rainfall (RR) and surface air temperature (T), measured from two different locations (Owabi and KNUST) and at a temporal resolution of 10 min, encompassing the quantifying weather and climate impact (QWeCI) Project period (2011–2013), were used to assess their relationship on diurnal to seasonal scales. First, diurnal assessments of the various profiles were performed. These provided information on the relatively active daytime, with the earth surface exposed to substantial $$SW_\downarrow$$ , initiating rising and sinking thermals which subsequently increased T and $$\Delta H$$ , with reductions in RH until few hours after midday, beyond which a reversal was observed. Also, $$\Delta H$$ from the vegetative terrain (Owabi) was found to be directed into the surface at daytime, and released from the sub-surface layer back into the atmosphere at night time, compensating the energy loss by $$LW_\uparrow$$ from the surface. Furthermore, rainfall (RR) in both locations were found to be generally convective and occurring mostly between 1500 GMT and 2300 GMT. The relationship between net radiation ( $$R_N$$ ) and RR is presently statistically unclear, although rainfall peaks were found to be occurring at low $$R_N$$ and relatively warmer T, accompanied by high RH. Thereafter, seasonal assessments were performed to capture the monthly-averaged diurnal variabilities in the measured surface to near-surface parameters. These showed heightened daytime T, $$\Delta H$$ and $$R_N$$ , coupled with relatively low RH within the dry seasons, and more reduced profiles within the monsoon season. Additionally, countrywide assessments were performed using ERA-5 datasets which showed similarities with the in situ data. However, convective rains over the domain were not fully resolved in ERA-5. Nonetheless, the findings of this study are essential to understanding surface energy balance processes in tropical, humid climates, which is important for various climate-impact modeling applications and policy formulations over the region.

Climate affects the quantity of soil moisture within the surface of the earth and this is obtained by affecting the amount of radon flux density escaping from the land surface. This chapter contains the evaluation of climate change conditions as it affects the variability of soil water for the purpose of estimating the health effects of radon flux density within Ogbomoso metropolis. The simulated soil moisture content around Ogbomoso was done for a period of 34 years using the hydrological model, Soil Water Assessment Tool (SWAT). The calibration and validation of the SWAT model was done using the daily observed soil moisture content. The simulated daily soil moisture within Ogbomoso showed good performance when calibrated and validated. A 20 years prediction of the daily soil moisture content was done using the SWAT model. The estimation of the radon flux density for the study area was obtained using the simulated soil temperature and soil moisture from the SWAT model. In this chapter, the UNSCEAR radon flux formula was used for the radon flux estimate. The result showed that the UNSCEAR radon flux formula performed well in estimating the radon flux density in the study area. The mean value of the radon flux density of 15.09 mBqm−2 s−1 falls below the estimated world average of 33 mBqm−2 s−1 by UNSCEAR stipulated for land surface. The results showed that Ogbomoso region is not prone to high risk of radon exposure to the public. The estimation of the radon flux density value suggested that there is no radiological health hazard such as lung cancer or any other respiratory tract diseases to the inhabitant of Ogbomoso, Nigeria.

The Owabi catchment which is about 69 km2 provides about 20 % of water needs of the Kumasi metropolis has been in recent times prone to high anthropogenic activities that threaten water resource management. The Soil-Water-Assessment-Tool (SWAT) was used to assess the extent of these activities on the hydrology on the catchment from 1986 to 2015. Specifically, the model simulated historic and projected stream-flow and water balance. Initial results revealed the forest and topography played major role in water loss at the catchment as evapotranspiration and surface runoff were the dominant modulating processes. Monthly calibration/validation of the model yielded satisfactory results with NSE (0.66/0.67), R2 (0.67/0.67), PBIAS (8.2 %/8.0 %) and RSR (0.59/0.58). Nine sensitive parameters of which the catchment slope (CN2) ranked principal were found to control runoff amounts into the river. The model uncertainty was also quite low as the 95PPU enveloped about 50 % of the observed streamflow within a width of 0.45–0.55. Furthermore, future streamflow predictions were modelled under RCP2.6, RCP4.5 and RCP8.5 climatic scenarios, and two landuse scenarios, landuse category 1 and 2 (LU1 and LU2). An increasing trend of the downscaled rainfall totals between 2021 to 2050 for all RCPs were observed. This will positively impact streamflow generation at the catchment under LU1. There is an expected deficit of streamflow amounts under LU2 relative to LU1, and a marginal reduction as compared to the baseline. In general, the model proved efficient in determining the hydrology parameters in the catchment and therefore has potential to be used for further modelling of water quality and pollution to aid effective water resource decisions at the catchment.

Satellite rainfall estimates have predominantly been used for climate impact studies due to poor rain gauge network in sub-Saharan Africa. However, there are limited microscale studies within the sub-region that have assessed the performance of these satellite products, which is the focus of the present study. This paper therefore considers validation of Tropical Rainfall Measuring Mission (TRMM) and Famine Early Warning System (FEWS) satellite estimates with rain gauge measurements over Ashanti region of Ghana. First, a consistency assessment of the two gauge data products, the Automatic Rain Gauge (ARG) and Ghana Meteorological Agency (GMet) Standard Rain Gauge (SRG) measurements, was performed. This showed a very good agreement with correlation coefficient of 0.99. Secondly, satellite rainfall products from TRMM and FEWS were validated with the two gauge measurements. Validation results showed good agreement with correlation coefficients of 0.6 and 0.7 for TRMM and FEWS with SRG, and 0.87 and 0.86 for TRMM and FEWS with ARG respectively. Probability Of Detection (POD) and Volumetric Hit Index (VHI) were found to be greater than 0.9. Volumetric Critical Success Index (VCSI) was 0.9 and 0.8 for TRMM and FEWS respectively with low False Alarm Ratio (FAR) and insignificant Volumetric Miss Index (VMI). In general, relatively low biases and RMSE values were observed. The biases were less than 1.3 and 0.8 for TRMM and FEWS-RFE respectively. These indicate high rainfall detection capabilities of both satellite products. In addition, both TRMM and FEWS were able to capture the onset, peak and cessation of the rainy season, as well as the dry spells. Although TRMM and FEWS sometimes under/overestimated rainfall, they have the potential to be used for agricultural and other hydro-climatic impact studies over the region. The Dynamic-Aerosol-Cloud-Chemistry Interactions in West Africa (DACCIWA) project will provide an improved spatial gauge network database over the study area to enhance future validation and other climate impact studies.