Periodic climate zoning is an essential classification of land cover to account for anthropogenic activities resulting from population increase and urbanization that affect key climate response parameters. Rainfall, relative humidity (RH), maximum (T_max) and minimum temperature (T_min) data from the Ghana Meteorological Agency were used to zone Ghana by adopting cluster and PCA analysis methods and verifying the groupings with the seasonal trend and Tukey Honestly Significance Difference (HSD) analysis. The cluster analysis grouped the synoptic stations into four major homogenous clusters while the PCA distributed them into three sub‐divisions with reference to 1976–2018. Rainfall, RH, T_max and T_min were characterized by five, three, two and three factors with factor loadings in the range of 0.71–0.78, 0.53–0.70, 0.54–0.74 and 0.50–0.72, respectively. HSD found transition stations like Bole and Kete Krachi in cluster 1 and 2 to have no significant difference with cluster 1, while Wenchi, Sunyani, Sefwi Bekwai and Koforidua in cluster 2 had no significant difference with cluster 3. Accra station which was classified in cluster 3 showed the seasonal pattern of cluster 4 and was confirmed by HSD to belong in cluster 4. Therefore, Ghana‐based on‐point analysis is climatically grouped into Savannah (11°0′0′′N–7°46′11′′N), Forest (from 7°46′11′′N to the coast) and Coastal (about 30 km from the Gulf of Guinea coastline) based on the assessed parameters. These findings are vital for planners and decision‐makers especially for industries that depend on weather and climatic conditions for their activities.

Purpose: This study aims to assess gender-based differences on farmers’ perception of impacts and vulnerability to climate change and the implementation of adaptation strategies in the Pra River Basin of Ghana, while also providing lessons for other Sub-Saharan nations and regions with similar conditions. Design/methodology/approach: The study used semi-structured interviews and questionnaires to collect data from 344 farmers, 64 participants in focus group discussions and 6 agriculture extension officers (key informants) from 10 districts in the Pra River Basin of Ghana. Findings: Results showed several differences in how climate change is perceived and tackled by male and female genders. In the perception of male farmers, for example, they were found to be more vulnerable to increased temperature, and changes in rainfall and growing season, whereas female farmers on average were considered to be less resilient to floods and droughts for different reasons. Moreover, floods posed higher risks to farming than other climate change impacts. Gender roles had a significant correlation with the type of adaptation strategies practised. Men adopted agrochemicals more often than women, as an adaptation strategy. Research limitations/implications: Gender-differentiated interventions should be incorporated in the national climate change action plan for sustainable development in a rain-fed agricultural economy such as Ghana. The study recommends several actions to promote gender equity in the assessed region. Originality/value: This research assessed the gender differentials in climate trends, impact, vulnerability and adaptation based on primary data collected between April and May 2019 and compared the results with climate data in the basin for the period 1991–2014. It is an empirical study focused on primary data analysis obtained in loco by authors, involving approximately 400 participants.

HIGHLIGHTS. Surface water are mainly used for crop production in the Pra River Basin.Mercury, Copper, Arsenic and Iron concentration levels exceed the permissib

This study was to assess and predict soil organic carbons stocks (SOCS) under the major land use/cover types in Kintampo North Municipal located in the Guinea savanna through the transition agro-ecological zone of Ghana. Random field sampling was done on 34 plots and 24 sample points at depths 0–10 cm, 10–20 cm and 20–30 cm per plot with soil corer. Soil bulk density, pH, particle size distribution and SOC were determined using standard laboratory procedures and computations. Results were subjected to both statistical and Geo-statistical analyses. The SOCS in each land use decreased with depth. The mean SOC for the five land-use systems studied were 11.33 t/ha, 7.95 t/ha and 6.08 t/ha at 0–10 cm, 10–20 cm and 20–30 cm, respectively. The vertical variability in SOC distribution across the considered land use/cover types was statistically significant (p < 0.05) but the statistical difference amongst land use/cover types was insignificant. The determined mean SOCS were 30.02 (±13.20) t/ha for savanna woodland as the highest and 22.01 (±8.92) t/ha for cashew plantation as the lowest at total depth (0–30 cm). The spatial distribution of SOC stocks ranged between 12 t/ha to about 33 t/ha.

This work compares future projections of rainfall over the Pra River Basin (Ghana) using data from five climate models for the period 2020–2049, as referenced to the control period 1981–2010. Bias-correction methods were applied where necessary and models' performances were evaluated with Nash–Sutcliffe Efficiency, root-mean-square error and coefficient of determination. Standardised Anomaly Index (SAI) was used to determine variability. The onset and cessation dates and length of the rainy season were determined by modifying the Walter–Olaniran method. The ensemble means of the models projected a 1.77% decrease in rainfall. The SAI showed that there would be drier than normal years with the likelihood of drought occurrence in 2021, 2023, 2031 and 2036. The findings showed that high-resolution models (≤25 km) were more capable of simulating rainfall at the basin scale than mid-resolution models (26–150 km) and projected a 20.13% increase. Therefore, the rainfall amount is expected to increase in the future. However, the projected increase in the length of the dry season by the ensemble of the models suggested that alternative sources of water would be necessary to supplement rainfed crop production for food security.