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In this study, a land suitability index for crop production in three northern regions of Ghana is spatially generated using a land suitability analysis through the integration of AHP and GIS. The study further exploited actual maize and groundnut yield obtained by farmers in the study area by integrating it with the land suitability index to spatially generate potential maize and ground yield. The actual and potential maize and groundnut yields were overlayed in GIS to produce potential yield losses for maize and groundnuts. Factors of precipitation, slope of land, LULC, soil erosion, OM and the soil type were identified through expert opinion in literature, and assigned weights through AHP for the land suitability analysis. Results obtained from the land suitability index indicates about 19.2 % of land in the three regions is highly suitable for crop production, about 20.8 % is moderately suitable, about 27.0 % is less suitable and about 33 % unsuitable due to settlements and depleted lands. Potential yield loss due to difference in actual and potential maize and groundnuts yields were 70 % and 63 % for maize and groundnuts respectively for the Northern Region, 83 % and 66 % for maize and groundnuts respectively for the North-East Region, and then 66 % and 59 % for maize and groundnuts respectively for the Savannah Region. The AHP and GIS-based land suitability analysis techniques are potentials and effective tools for determining the suitability of land for crop production thereby enhancing sustainable agricultural development through enhancing food security and creation of new jobs.

Effective management of reservoir sedimentation requires models that can predict sedimentation of the reservoirs. In this study, linear regression, non-linear exponential regression and artificial neural network models have been developed for the forecasting of annual storage capacity loss of reservoirs in the Guinea Savannah Ecological Zone (GSEZ) of Ghana. Annual rainfall, inflows, trap efficiency and reservoir age were input parameters for the models whilst the output parameter was the annual sediment volume in the reservoirs. Twenty (20) years of reservoirs data with 70% data used for model training and 30% used for validation. The ANN model, the feed-forward, back-propagation algorithm Multi-Layer Perceptron model structure which best captured the pattern in the annual sediment volumes retained in the reservoirs ranged from 4-6-1 at Karni to 4-12-1 at Tono. The linear and nonlinear exponential regression models revealed that annual sediment volume retention increased with all four (4) input parameters whilst the rate of sedimentation in the reservoirs is a decreasing function of time. All the three (3) models developed were noted to be efficient and suitable for forecasting annual sedimentation of the studied reservoirs with accuracies above 76%. Forecasted sedimentation up to year 2038 (2019–2038) using the developed models revealed the total storage capacities of the reservoirs to be lost ranged from 13.83 to 50.07%, with 50% of the small and medium reservoirs filled with sediment deposits if no sedimentation control measures are taken to curb the phenomenon. HIGHLIGHTS The study developed two mathematical models using linear regression.; The study developed non-linear exponential regression.; The study developed an artificial neural network (ANN) model.; The study forecasted sedimentation up to year 2038 using the developed models.; The study revealed that the total storage capacities of the reservoirs to be lost ranged from 13.83 to 50.07%.

Soil erosion is a global problem with severe consequences, which has become a widespread environmental challenge in the northern parts of Ghana in recent times. This research integrated RUSLE into GIS to estimate the annual soil erosion rates for the Northern, North-East, and Savannah Regions of Ghana. A soil erosion map was generated with an annual soil erosion rate of 4.0 t ha−1y−1 for the Northern Region, 5.0 t ha−1y−1 for the North-East Region, and 7.0 t ha−1y−1 for the Savannah Region. Relatively higher erosion rates were observed in the Tatale Sangule and Kpandai districts of the Northern Region, with rainfall erosivity being the main driving factor. There was a landuse/cover erosion reduction effect of 66% in the Northern Region, 70% in the Northeast Region, and 58% in the Savannah Region. The cover management (C) factor was overwhelmingly the main erosion-reducing factor in erosion control as opposed to land conservation (P) factor.

Owing to the benefits of biochar in soil sustainability, this study considered the effect of applying rice husk biochar as a substitute for inorganic fertilizer on soil properties and maize growth ...

Background Modelling aboveground biomass (AGB) in forest and woodland ecosystems is critical for accurate estimation of carbon stocks. However, scarcity of allometric models for predicting AGB remains an issue that has not been adequately addressed in Africa. In particular, locally developed models for estimating AGB in the tropical woodlands of Ghana have received little attention. In the absence of locally developed allometric models, Ghana will continue to use Tier 1 biomass data through the application of pantropic models. Without local allometric models it is not certain how Ghana would achieve Tier 2 and 3 levels under the United Nations programme for reducing emissions from deforestation and forest degradation. The objective of this study is to develop a mixed-species allometric model for use in estimating AGB for the tropical woodlands in Ghana. Destructive sampling was carried out on 745 trees (as part of charcoal production) for the development of allometric equations. Diameter at breast height (dbh, i.e. 1.3 m above ground level), total tree height (H) and wood density (ρ) were used as predictors for the models. Seven models were compared and the best model selected based on model efficiency, bias (%) and corrected Akaike Information Criterion. The best model was validated by comparing its results with those of the pantropic model developed by Chave et al. (Glob Chang Biol 20:3177–3190, 2014) using equivalence test and conventional paired t-test. Results The results revealed that the best model for estimating AGB in the tropical woodlands is AGB = 0.0580ρ((dbh)2H)0.999. The equivalence test showed that this model and the pantropic model developed by Chave et al. (Glob Chang Biol 20:3177–3190, 2014) were equivalent within ±10% of their mean predictions (p-values t-tests for both lower and upper bounds at 5% significant level), while the paired t-test revealed that the mean (181.44 ± 18.25 kg) of the model predictions of the best model of this study was significantly (n = 745, mean diff. = 16.50 ± 2.45 kg; S.E. = 1.25 kg; p Conclusion The model developed in this study fills a critical gap in estimating AGB in tropical woodlands in Ghana and other West African countries with similar ecological conditions. Despite the equivalence with the pantropic model it remains superior to the model of Chave et al. (Glob Chang Biol 20:3177–3190, 2014) for the estimation of AGB in local tropical woodlands. It is a relevant tool for the attainment of Tier 2 and 3 levels for REDD+. The model is recommended for use in the tropical woodlands in Ghana and other West African countries in place of the use of pantropic models.

The impacts of climate change on food security have increased interest in research and investments in irrigation technologies and agricultural water management. Agricultural practices such as mulching help to conserve soil moisture by reducing evaporation and mitigate the adverse effects of water stress on crops, especially in semi-arid environments. This study investigated the combined effects of irrigation schedules and different mulching technologies on the growth and yield of two varieties of chilli pepper – Legon 18 (Capsicum frutescens L.) and Kpakpo shito (Capsicum chinense) – in the Guinea Savannah agro-ecological zone of Ghana. Soil temperature and moisture content as well as plant growth parameters were collected over the growth period. The number of days taken for first and 50% flowering and fruiting were also recorded. Total fruit yield and crop water productivity were estimated after harvest. Results show that the combination of irrigation at 100% E T c r o p every three days and rice straw mulch ensured optimal soil temperature and moisture content that improved vegetative growth, shortened the number of days to flowering and fruiting, and significantly improved yield and water use efficiency compared to the other treatment combinations. Fruit yield for this treatment combination was up to 19,042.2 kg/ha and 19,074.6 kg/ha whereas crop water productivity was up to 6.08 kg/m3 and 6.09 kg/m3 for Legon 18 and Kpakpo shito, respectively. Plastic film mulch under each irrigation schedule produced higher growth and yield-related parameters than no mulch treatments. Although findings from this study cannot be directly generalized for the entire Guinea Savannah agro-ecological zone of Ghana due to spatial variability of soil and other climatic variables, the combination of irrigation schedule at 100% E T c r o p every three days and rice straw mulch is recommended for improved yield and water use efficiency in dry season chilli pepper production in semi-arid environments with sandy loam soils.

This study used thespatially integrated RUSLE to estimate annual soil loss and spatial distribution of soil loss severity classes for nine (9) reservoir catchments in northern Ghana.This model is an empirical model with five (5)main input parameters: rainfall erosivity, soil erodibility, slope length/steepness, landcover management and erosion management practice factors. Estimated annual soil loss rate ranged from 0 – 96.30 t/ha/y. Estimated mean annual soil loss ranged from 3.71 – 8.17 %. The severity of annual soil loss rates ranged from very low class (0.0 – 1.0 t/ha/y) to very high class (> 60.0 t/ha/y). Across the nine (9) catchments, the very low soil loss severity class was noted to constitute a larger portion of between 36.70 to 67.50 %. The moderate soil severity class was noted as the highest contributor to total annual soil loss. Soil and water conservation measures are required in the watershed to reduce soil loss. Keywords: Watershed, soil loss, Integrated GIS-based RUSLE model, surface water resources, lixisols

Adongo TA, Kyei-Baffour N, Abagale FK, Agyare WA. 2019. Assessment of reservoir sedimentation of irrigation dams in northern Ghana. Lake Reserv Manage. XX:XXX–XXX. Sedimentation in reservoi...

This study aimed to assess the historical Land use/land cover (LULC) changes and project the future (2025) LULC pattern in the Vea catchment based on Business as Usual (BAU) and afforestation scenarios of land use. Landsat Imagery of 1990, 2001, 2011 and 2016 were classified at overall accuracy assessment of 82%, 86%, 85% and 88% respectively. Major transitions were modeled using the Multi-layer Perceptron Neural Network algorithm, and the future scenarios maps of LULC were projected based on the Markov chain after validation of the Land Change Modeler. The results indicate the conversion of forest/mixed vegetation (23.1%) and grassland (76.9%) to cropland as the dominant LULC conversion from 1990 to 2016. An increase in cropland, built-up areas, and water bodies were observed while grassland and forest/ mixed vegetation decreased over the last 27 years. The 2025 LULC simulation indicates continuous expansion of cropland at the expense of forest/mixed vegetation which is projected to decrease by 4.5% in 2025 for the BAU scenario. Under afforestation scenario, where forest/mixed vegetation and grassland are expected to increase, cropland is projected to decrease by 20% in 2025. These findings set a reference ground for sustainable land use governance through responsible planning and management of land and water resources by considering trade-offs between cropland expansion and ecosystems’ preservation in the Vea catchment.

This study analyses forest reference level in terms of loss, gain and transitions among forest, cocoa agroforestry, cassava, maize, settlement and others in the Kloto district (Togo) for REDD+ and sustainable forest and agriculture. The pixel-based classification was adopted and combined with the extended change matrix quantity and intensity analysis using 32-year (1985–2017) Landsat data and land use information from land owners and farmers. Results indicate an active forest loss (19.5%) with dormant gain (0.8%). Forest is involved in most transitions as the most targeted category with the largest transition being a forest to cocoa agroforestry while the avoiding transition was from forest, cocoa agroforestry, maize, cassava and settlement to unclassified classes (e.g. road, water body) and vice versa. Other targeting categories were from forest to settlement, cassava and maize Thus, both cash and food crops are major contributors of forest loss. The study concludes that cropland land degradation is the main reason that explains the significant conversion of forest lands to stable agricultural lands. Therefore, review of the existing cropping and farming systems by promoting agroecology systems (e.g. agroforestry, rotational cropping, mixing cropping with pulses) to sustain and restore soil degradation while mitigating climate change, forest degradation and provide food security for the rural communities is recommended. Economic measures such as: trade-off compensations for agroecology practices and afforestation and reforestation through farmer’s association initiatives could be encouraged to limit forest extensions.

Climate change represents a major potential threat to the viability of rural households’ livelihoods in sub-Saharan Africa. This study focused on the perceptions of climate change and adaptation strategies of local cotton farmers in Côte d'Ivoire, identified as particularly vulnerable to climate change. A survey was conducted among 355 smallholder farmers distributed in four departments of the cotton basin of Côte d'Ivoire (Korhogo, Boundiali, Ferkessédougou and Mankono). Using changes in weather pattern as indicators of climate change, the results showed that majority of respondents believe climate change is evident in the study area and has negative effects on their livelihoods. Respondents reported an increase in temperature and decrease in rainfall amount in Korhogo and Boundiali departments, which were consistent with the climate data. The main coping strategies implemented by the farmers were shifting of planting dates and timing of cultural activities, adopting new crop varieties, ploughing before planting, diversifying crops and making specific sacrifices to divine powers depending on the type of belief of the farmer. The farmers’ adoption of adaptation strategy depended on their perception of climate change and the available coping strategy. Lack of sufficient knowledge and government support were the major constraints that hindered cotton farmers to adapt effectively, leading to low cotton productivity in the study area. Therefore, policy implications will be crucial to help farmers make better adaptation choices in the face of climate change.

The increasing demand of Ghana's renewable energy sector requires a comprehensive evaluation of sky conditions that may be favourable for the efficient harnessing of solar energy resources. However, data for such evaluation are typically scarce due to instrumentation challenges. Empirical estimates using sunshine duration and cloud cover as input data were used to evaluate the solar energy resources’ potential at 22 synoptic stations distributed across the four climatic zones of Ghana (savannah, transition, forest and coastal) for the period 2015 – 2018. Sunshine duration was recorded using the Campbell-Stokes sunshine recorder while the cloud amount was done manually through visual observation. The modified Angstrom-Prescot sunshine model was used to estimate the monthly mean global solar radiation. The cloudiness index was then computed as the ratio of the mean cloud cover to the global solar radiation. A modified Steyn-method, based on sunshine duration, was used to estimate the sky view factor. Ordinary kriging was used to interpolate mean quarterly stationary values of the sky condition parameters into spatial distribution over Ghana. Results show that the dry periods (November to April) are characterised by high solar radiations, clear and visible skies as a result of high temperatures, less cloud cover, and low relative humidity, whereas the opposite conditions are observed in the wet periods (May to October). The savannah and coastal zones recorded higher solar radiations with up to 22 MJ m−2 day−1 in the dry season compared to the forest and transition zones. Cloudiness index was above 0.3 and below 0.2 in the wet and dry seasons respectively, for the forest, transition and coastal zones, whereas the index was between 0.15 and 0.3 in the wet season and below 0.1 in the dry season for the savannah zone. Sky view factor was consistently between 0.7 and 0.8 in the dry season, with low values below 0.7 in August for all the climatic zones. Spatial interpolation of the sky condition parameters revealed that the savannah, coastal and eastern transition climatic zones observe high solar radiations, clear and visible skies and are therefore more favourable for harnessing solar energy. These locations may be more appropriate for setting up large-scale solar farms, though dust associated with the Harmattan dry season can be a hinderance.

This study presents a multi-level analysis of land cover change in the Kintampo Municipality of Ghana using Landsat TM, ETM + and Landsat 8 images from 1986, 2001 and 2014, respectively. The expected and observed annual rates of land cover change for the periods 1986 to 2001 and 2001 to 2014 were analyzed at temporal and intra and inter-land cover levels using post-classification change detection. The results reveal that the expected annual rate of land cover change for the time intervals is 2.55 %. The observed annual rate of change from 2001 to 2014 is 2.63 %, which is greater than the expected value. This shows that land cover changed faster than expected in this period. The observed intra-land cover gains and losses for woodland is 2.49 % which is less than expected for the change periods. This suggests that the observed gain and loss in woodlands are attributable to random changes. The inter-land cover level changes for both periods reveal that when woodland gained or lost, it did not target shrub/grassland. This shows that the process of gain or loss in woodland in both periods was random. This is an indication that woodland cover is sustained by a slow, natural regeneration process and not by anthropogenic activities. The findings highlight the relevance of multilevel land cover analysis in land cover assessment. The temporal level highlights the need to relate changes in land cover to anthropogenic activities for a better understanding of the changes. The study also revealed that multi-level land cover analysis can facilitate management decisions on whether to reduce loss in woodland or increase gain in woodland cover from shrub land.

The shapes and forms of piezometric hydrographs arising from the recharging and discharging of unconfined aquifers offer a hydrological tool for the classifications of inland valley bottoms in Ghana for crop production. A two-year measured water table fluctuations at Besease wetlands were plotted on a reference scale of time in months on the x-axis and hydraulic head on the y-axis. The water table fluctuation method was used to evaluate the seasonal and annual variations in the water level rise and to estimate the groundwater recharge. The monthly slopes segment of the water table fluctuations were used as a base for the classification of the heads. Results from the study showed that the estimated recharge for the study area ranged from 133 to 467 mm for the fourteen (14) piezometers, representing 9 to 31% of 2009 annual rainfall and 47.6 to 427.9 mm in 2010 representing 4 to 34% of the annual rainfall. The Results also showed that most of the piezometers had their monthly slopes dominated by the acute segment followed by the obtuse segment, flat segment and right-angled segment in that order. It can be inferred that most of the piezometric areas dominated by acute forms become relatively dry during the dry season; however, these areas may still have some water to support crops. The hydrograph representation of the monthly slopes were employed to classify the studied Inland Valley Bottoms into three hydrological regimes as a management tool for developing wetlands for crop production. The regimes were Water table fluctuation (WTF) Class I - acute slopes segment varying from 0 to 30%, WTF Class II - acute slopes segment varying from 30 to 45% and WTF Class III - acute slope segment > 45%. It is concluded that a controlled water table offers a distinguishing criterion for the development of Inland Valley Bottoms for year round crop production in Ghana. Key words: Water table fluctuation, hydrological regimes, inland valley bottoms, slope segments, crop production.

The impacts of charcoal production on woodland were assessed in the Forest-Savannah Transition Zone of Ghana to facilitate policy formulation for a win-win situation for both sustainable woodland management and charcoal production. Twenty-three harvested sites in two charcoal producing communities were assessed in terms of the extent of harvested sites, changes in biomass carbon stock and tree basal area. The boundary of each site earmarked for charcoal production was mapped with a hand-held Global Positioning System, and the diameters at breast height ( d bh ) and the heights of trees of d bh ≥ 5 cm were measured, prior to harvest. The extent of harvested sites was compared with the Intergovernmental Panel on Climate Change criterion of “devegetation” using Wilcoxon test, while the biomass carbon and basal area of the harvested trees were compared with those of the remnant trees using Mann Whitney t-test. The median of the extent of harvested sites ( M = 0.23 ha, P = 1.00) was significantly higher than 0.05 ha, the Intergovernmental Panel on Climate Change minimum criterion for “devegetation”, while the difference between median basal area of harvested and remnant trees was significantly greater than zero (G h − G r = 2.6 m 2 ha −1 ; P = 0.001) at 95% significant level. The Mann Whitney test also provided sufficient evidence (n = 23; M hc − M rc = 12.07 t ha − 1 ; P per se . Therefore, the evidence of the impact of charcoal production on woodlands shown in this study should be basis for sustainable woodlands management and not basis for halting charcoal production in the study area.

This study examined the trends in annual rainfall and temperature extremes over the Vea catchment for the period 1985&ndash, 2016, using quality-controlled stations and a high resolution (5 km) Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data. The CHIRPS gridded precipitation data&rsquo, s ability in reproducing the climatology of the catchment was evaluated. The extreme rainfall and temperature indices were computed using a RClimdex package by considering seventeen (17) climate change indices from the Expert Team on Climate Change Detection Monitoring Indices (ETCCDMI). Trend detection and quantification in the rainfall (frequency and intensity) and temperature extreme indices were analyzed using the non-parametric Mann&ndash, Kendall (MK) test and Sen&rsquo, s slope estimator. The results show a very high seasonal correlation coefficient (r = 0.99), Nash&ndash, Sutcliff efficiency (0.98) and percentage bias (4.4% and &minus, 8.1%) between the stations and the gridded data. An investigation of dry and wet years using Standardized Anomaly Index shows 45.5% frequency of drier than normal periods compared to 54.5% wetter than normal periods in the catchment with 1999 and 2003 been extremely wet years while the year 1990 and 2013 were extremely dry. The intensity and magnitude of extreme rainfall indices show a decreasing trend for more than 78% of the rainfall locations while positive trends were observed in the frequency of extreme rainfall indices (R10mm, R20mm, and CDD) with the exception of consecutive wet days (CWD) that shows a decreasing trend. A general warming trend over the catchment was observed through the increase in the annual number of warm days (TX90p), warm nights (TN90p) and warm spells (WSDI). The spatial distribution analysis shows a high frequency and intensity of extremes rainfall indices in the south of the catchment compared to the middle and northern of part of the catchment, while temperature extremes were uniformly distributed over the catchment.

This study investigates proximate drivers of cropland and forest degradation in Kloto district (Togo, West Africa) as, way of, exploring integrated sustainable landscape approaches in respect to socio-economic and environmental needs and requirements. Net change analysis of major cash and food crops based on three time steps Landsat data (1985–2002, 2002–2017 and 1985–2017) and quantitative analysis from participatory survey data with farmers and landowners are used. Study underlines poor agricultural systems and cassava farming as major impediments to alarming forest losses between 1985–2017. Significant net loss in forests cover by 23.6% and surface areas under cultivation of cocoa agroforestry and maize by 12.99 and 10.1% from 1985 to 2017, due to, intensive cassava cropping (38.78%) and settlement expansions (7.84%). Meanwhile, loss in forest cover between 2017 and 2002 was marginal (8.36%) compared to the period 1985–2002 for which the loss was considerable (15.24%). Based on participatory surveys, majority of agricultural lands are threatened by erosion or physical deterioration (67.5%), land degradation or salt deposits and loss of micro/macro fauna and flora at 56.7%, declining in soil fertility (32.5%), soil water holding capacity (11.7%) and changes in soil texture (3.3%). Majority of farmers adhere to the adoption of the proposed climate smart practices with emphasis on cost effective drip irrigation systems (45.83%), soil mulching (35%) and adoption of drought resilient varieties (29.17%) to anticipate drought spells adverse. The study concludes that low adoption of improved soil conservation, integrated water management and harvesting systems and low productive and adaptive cultivars entail extreme degradation of croplands and crops productivity decline. Therefore, farmers are forced to clear more forests in search of stable and healthy soils for production and extraction of forest products to meet their food demands and improve their livelihoods conditions. Capacity building on integrated pathways of soil and land management practices are therefore needed to ensure sustainable and viable socio-ecological systems at local scale.

Accurate forest reference and emission level (FRL, FREL) with related policies and regulations are the key determinants in establishing sustainable forest ecosystem management programmes (e.g. REDD+). This fundamental is for promoting and sustaining climate smart agricultural practices in a changing climate. With the aim to deliver better knowledge to the scientific community and policy makers on regulations and existing tools for more rigorous scientific communication when it comes to FRL and FREL accountability and policies. Thus, this review investigates forest in the changing climate and policies and underlines the performance of land use transition and intensity analysis towards deforestation with some key examples and achievements (e.g. Togo). Simply put, (i) forest as break of greenhouse gas (GHGs) and ecosystem regulator, (ii) policies and REDD+ actions, (iii) potential drivers and (iv) transition and intensity analysis approach for their accountability are discussed. In sum, impressive studies, policies and regulations are under initiations and implementations regarding the role, place and evaluation of forest losses and its ecosystem functions and services. However, there are still some gaps when it comes to: the choice of the evaluation methods in the real context of a specific ecosystem as well as the firm implementations of formulating policies in developing countries. This paper concludes with some policy measures for forest sustainability, carbon enhancement and accountability.

The yield of lowland paddy rice (Oryza sativa L.) is sensitive to water application regimes, which can be affected by irrigation management. This study assessed the impacts of different irrigation applications on rice yield using the AquaCrop model. Experiments were conducted at two sites (On-station and On-farm) during the 2012/2013 and 2013/2014 dry seasons using five different irrigation treatments: field capacity (FC) moisture content (W 1 ), saturated soil moisture content (SC; W 2 ), continuous flooding (CF; W 3 ), 10ETc (crop water requirement) (W 4 ), and 15ETc (W 5 ). A 115-day rice variety, Gbewaa (Jasmine 85), was transplanted with a spacing of 20 cm × 20 cm for the experiments. The AquaCrop model was calibrated in terms of green canopy cover (CC), aboveground dry biomass, harvest index (HI), and paddy rice yield. The model was validated using various efficiency criteria (coefficient of determination, root mean square error (RMSE), RMSE–observations, standard deviation ratio, index of agreement, and Nash–Sutcliffe efficiency), and satisfactory simulation results were obtained for biomass, HI, yield, and green CC. The AquaCrop model proved to be robust and applicable for paddy rice under various irrigation methods, although it underestimated dry biomass and grain yield for all treatments except FC. The simulated rice yield was highly sensitive to the maximum CC. This study represents the first site-specific application of the AquaCrop model to paddy rice in Northern Ghana; therefore, the model should be further tested for different climatic conditions, soil types, and crop varieties in Ghana.

Maize (Zea mays) is Ghana’s most important cereal crop grown in all agro-ecological zones by smallholder farmers. The average yield of maize (1.7 tha-1) is far below attainable yield of 5.5 tha-1. This is due to reliance on rain fed farming, local seed varieties and low inputs use. Farmers face many challenges in their attempt to adopt the use of fertilizer to improve their maize production. To unearth these challenges, data on the potential and limitations to maize fertilization in the maize belt of Ghana were collected through a farm level survey in October 2011. A four stage randomized sampling procedure was used to select 168 maize farmers who were interviewed using formal questionnaire. Some of the farmers especially, settlers do not have land of their own and have to rely on tenancy arrangements to access land for farming. Farmers were of the view that their crop lands are gradually declining in fertility. Almost 55% of the farmers practise continuous maize cropping. The lack or low accessibility to credit and high cost of fertilizer are the key constraints to farmers’ ability to expand their maize farming. Additionally, the mode and distance needed to transport fertilizer to the farm is a disincentive. Key words: Maize, fertilizer use, Ghana, farmers, continuous cropping.

A study was carried out in the Sudan savanna zone in the Upper East Region of Ghana to assess the rate of sedimentbound nutrient export (NE) into five small reservoirs (Dua, Doba, Zebilla, Kumpalgogo and Bugri) and to analyse the implications of this export. The catchment soils and reservoir sediments from the various study sites were sampled and analysed for their bulk density, particle size distribution and nutrient content. Assessment of the nutrient concentrations indicated that the reservoir sediments were richer not only in nutrients and organic carbon, but also in clay and silt, than the catchment soils, having enrichment ratios >1. Nutrient export rates (NE; kg ha )1 year )1 ) from the reservoir catchments ranged from 0.755 (±0.264) for OC, 0.104 (±0.0245) for N, 0.0020 (±0.0003) for P, 0.016 (±0.0038) for K, 0.009 (±0.0024) for Na, 0.113 (±0.017) for Ca and 0.027 (±0.0093) for Mg. These rates were lower than those of other studies, likely due to the low nutrient content in the catchment soils. The relationships established between NE and specific sediment yield (SSY) indicated the NE was positively correlated with SSY (R 2 = 0.66‐0.98). The derived empirical equations can be satisfactorily used to predict the quantity of sediment-bound plant nutrients lost from similar catchments and subsequently stored in the reservoir sediments. The study results also suggest the need for sustainable land management practices to forestall erosion in the catchment areas and to reduce reservoir sedimentation, for enhancement of the livelihoods of the communities in the study area.

This study investigates proximate drivers of cropland and forest degradation in the Kloto district (Togo, West Africa) as a way of exploring integrated sustainable landscape approaches with respect to socioeconomic and environmental needs and requirements. Net change analysis of major cash and food crops based on Landsat data from three time steps (1985&ndash, 2002, 2002&ndash, 2017, and 1985&ndash, 2017) and quantitative analysis from participatory survey data with farmers and landowners are used. The study underlines poor agricultural systems and cassava farming as major factors contributing to the alarming forest losses between 1985 and 2017. A significant net loss in forest cover of 23.6% and areas under maize and cocoa agroforestry farming of 12.99% and 10.1% between 1985 and 2017, respectively, was noted. These significant losses are due to intensive cassava cropping (38.78%) and settlement expansion (7.87%). Meanwhile, the loss of forest cover between 2002 and 2017 was marginal (8.36%) compared to the period 1985&ndash, 2002, which had a considerable loss of 15.24%. Based on participatory surveys, the majority of agricultural lands are threatened by erosion or physical deterioration (67.5%), land degradation or salt deposits and loss of micro/macro fauna and flora (56.7%), declines in soil fertility (32.5%) and soil water holding capacity (11.7%), and changes in soil texture (3.3%). Most farmers adhere to the proposed climate smart practices, with an emphasis on cost-effective drip irrigation systems (45.83%), soil mulching (35%), and the adoption of drought-resilient varieties (29.17%) to anticipate adverse spells. We conclude that low adoption of improved soil conservation, integrated water management, and harvesting systems and the use of less productive and adaptive cultivars entail extreme degradation of cropland and a decline in crop productivity. Consequently, farmers are forced to clear more forest in search of stable and healthy soil to meet their food demands and improve their livelihood. Capacity building on integrated pathways of soil and land management practices is therefore needed to ensure sustainable and viable socio-ecological systems at a local scale.

Soil data serve as an important initialization parameter for hydro-ecological and climatological modeling of water and chemical movement, heat transfer, or land-use change. Most soil hydraulic properties are difficult to measure and therefore have to be estimated in most cases. Efficient methods for estimating soil hydraulic properties are lacking for tropical soils. This study examines and uses easy-to-measure soil properties together with terrain attributes in artificial neural networks (ANNs) to estimate saturated hydraulic conductivity ( K s ), one of the key soil hydraulic properties for two pilot sites in the Volta basin of Ghana. It was observed that good data distribution, range, and amounts are prerequisites for good ANN estimation and, therefore, data preprocessing is important for ANN. With adequate and sensitive data, ANN can be used to estimate K s , using soil properties such as sand, silt, and clay content, bulk density, and organic carbon. Although the inclusion of terrain parameters can improve the estimation of K s using ANN, they cannot be relied on as the sole input parameters as they yield poor results for the scale considered in this study. The source of training data was found to significantly influence the topsoil K s , but the subsoil was not sensitive to training data source.

Crop and livestock production in the Guinea savanna zone of northern Ghana has been declining over the past years as a result of increasing pressure on land. To sustain soil productivity, pigeon pea(Cajanus cajan), a leguminous perennial crop was evaluated for its potential as a short duration fallow crop for fodder and grain, and maize (Zea mays)production. It involved comparing a natural fallow (i.e., control) and four improved fallows of pigeon pea pruned annually at 30 cm, 60 cm and 90 cm from the ground, and unpruned pigeon pea over a two-year period. After this time, the land was cleared manually and planted to maize. The highest mean annual biomass of pigeon pea over the two-year period of 6.1 t ha−1 dry matter (DM) was obtained by pruning at 60 cm. The highest leaf litter production and pigeon pea seed yield was obtained from the no pruning treatment. The mean maize grain yield from the improved fallow (3.02 t ha−1) in the first year after clearing was significantly (P < 0.05) greater than that of the natural fallow (1.54 t ha−1). Considering the biomass of pigeon pea from pruning, pigeon pea seed yield and maize grain yield after the pigeon pea, pruning pigeon pea at 60 cm is the most promising regime for crop-livestock production systems.

Maize has become the most important cereal in northern Ghana serving as cash crop and the main staple for most communities. It is the crop that receives most fertilizer input by farmers in the region, although the recommendations being used are over 20 years old. These recommendations were derived from relationships between crop yields and different applied rates of nutrient obtained from field fertilizer experiments. In most cases the experiments do not take care of the full extent of spatial and temporal variability associated with crop production. In addition the experiments are often very expensive and time consuming as they have to be carried out over many years in varied ecologies to be able to make valid recommendations for a region. Computer simulation model is a useful tool in this regard in reducing cost and time required for such studies, and also taking care of the spatial and temporal variability in the production of the crop. Response of maize to nitrogen in the northern Guinea savanna agro-ecology of Ghana was evaluated using the Seasonal Analysis component of the Decision Support System for Agrotechnoloy Transfer (DSSAT 4.02) – Cropping System Model (CSM). A simulation was performed for crop growth, development and yield of maize run for a site at Nyankpala near the University for Development Studies in the northern savanna agro-ecology. A field trial consisting of five nitrogen rates (0, 30, 60, 90, 120, kg/ha) with 30 kg K2O and 30 kg P2O5/ha was simulated for 24 years using measured daily weather and soil records for the site. The field trial was conducted under rain-fed conditions on a silty clay loam soil (Gleyi-ferric luvisol) in 2006. Quality protein maize (QPM) variety (Obatanpa) was the test crop. The economic analysis of the model took account of weather- and price-related risks, after carrying out a strategic analysis. The results showed that increasing levels of N up to 120 kg/ha increased maize grain yield at a diminishing return. The model accurately simulated maize grain yield up to 90 kg/ha nitrogen application but failed to accurately predict maize grain yield when nitrogen was applied at 120 kg/ha. Excessive water stress induced by high N application negatively affected the growth of maize. Nitrogen was leached most at N application rate of 120 kg/ha. Maize production was not profitable at N application rate ≤ 30 kg/ha on silty clay loam of the Guinea Savannah zone of Ghana. DSSAT-CSM can be used to accurately predict maize growth, development and yield in Ghana if well calibrated.