The socio-economic sector of West African countries is rain-fed agriculture driven. Information regarding the onset, cessation and duration of the rainy season is thus, very essential. In this paper, a comparison of the onset, cessation and duration of the rainy season has been carried out using simulated rainfall data from the fourth generation Regional Climate Model (RegCM4) and rain gauge measurements from Ghana Meteorological Agency (GMet), covering a period of 1998 to 2012. Similar onset and cessation dates were seen in both the simulated and guage rainfall measurements for the various agro-ecological zones, resulting in similar duration of the rainy season. The average duration of the rainy season were less than 200 days for the savannah and coastal zones whereas the duration of the rainy season were beyond 200 days for the forest and transition zones. The bias of these comparisons was less than 30 days and the root mean square error (RMSE) values were less than 15 days for all stations, except Saltpond. The Pearson's correlation (r) typically ranged between 0.4 and 0.8. However, negative correlations were observed for Tamale in the savannah zone, and the entire coastal zone. These findings are indications that RegCM4 has the potential to clearly simulate the movement of the rain belt, and thus, could fairly determine the onset, cessation and duration of the rainy season. The findings have significant contributions to effective water resource management and food security in Ghana, as the thriving of these sectors depend on the dynamics of the rainfall seasons.

The devastating effects of drought on agriculture, water resources, and other socioeconomic activities have severe consequences on food security and water resource management. Understanding the mechanism that drives drought and predicting its variability is important for enhancing early warning and disaster risk management. In this study, meteorological droughts over six coastal synoptic stations were investigated using three-month Standardized Precipitation Index (SPI). The dry seasons of November-December-January (NDJ), December-January-February (DJF), and January-February-March (JFM) were the focal seasons for the study. Trends of dry seasons SPIs were evaluated using seasonal Mann–Kendall test. The relationship between drought SPI and ocean-atmosphere climate indices and their predictive ability were assessed using Pearson correlation and Akaike Information Criterion (AIC) stepwise regression method to select best climate indices at lagged timestep that fit the SPI. The SPI exhibited moderate to severe drought during the dry seasons. Accra exhibited a significant increasing SPI trend in JFM, NDJ, and DJF seasons. Besides, Saltpond during DJF, Tema, and Axim in NDJ season showed significant increasing trend of SPI. In recent years, SPIs in dry seasons are increasing, an indication of weak drought intensity, and the catchment areas are becoming wetter in the traditional dry seasons. Direct (inverse) relationship was established between dry seasons SPIs and Atlantic (equatorial Pacific) ocean's climate indices. The significant climate indices modulating drought SPIs at different time lags are a combination of either Nino 3.4, Nino 4, Nino 3, Nino 1 + 2, TNA, TSA, AMM, or AMO for a given station. The AIC stepwise regression model explained up to 48% of the variance in the drought SPI and indicates Nino 3.4, Nino 4, Nino 3, Nino 1 + 2, TNA, TSA, AMM, and AMO have great potential for seasonal drought prediction over Coastal Ghana.

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Climate change is having an adverse effect on the environment especially in sub-Sahara Africa, where capacity for natural resource management such as water is very low. The scope of the effect on land use types have to be estimated to inform proper remedy. A combined estimation of transpiration and evaporation from plants and soil is critical to determine annual water requirement for different land use. Evapotranspiration (ET) is a major component in the world hydrological cycle, and understanding its spatial dimensions is critical in evaluating the effects it has on regional land use. A measure of this component is challenging due to variation in rainfall and environmental changes. The mapping evapotranspiration with high resolution and internalized calibration (METRIC) method is employed to create evapotranspiration map for land use, using remotely sensed data by satellite, processed, and analyzed in ArcGIS. Normalized difference vegetation index (NDVI) was related to the availability of water for vegetation on different land use, and the results indicate a high evapotranspiration for vegetated land use with high NDVI than land use with low NDVI.