College of Engineering

Permanent URI for this collection


Recent Submissions

Now showing 1 - 5 of 10
  • Item
    Impact of climate change and land use/land cover change on soil fertility in the cotton Basins of Côte d’Ivoire
    (KNUST, 2023-07) Kone, Ismail
    The study assessed the impact of alterations in land use and land cover, as well as fluctuations in climate patterns, on soil fertility within the cotton-producing area of Côte d'Ivoire. The study entails evaluating how farmers perceive and cope with climate change, determining the current state of soil fertility, evaluating land suitability and management options for cotton production, and simulating the way the land in the region will be utilized and the vegetation that will cover it in the future. To evaluate smallholder farmers' perceptions of climate change adaptation options, a structured questionnaire with closed questions was used to collect data from 355 farmers located in the cotton basin of Côte d'Ivoire. The findings revealed that most respondents acknowledged the existence of climate change in the area and its detrimental impact on farmers' livelihoods, leading them to adopt coping mechanisms. To determine the status of soil fertility, the study analyzed 64 soil samples collected in 2013 and 2021 in the same fields where cotton was grown. Specifically, the analysis focused on the physical and chemical properties of the topsoil layer, ranging from 0 to 20 centimeters in depth. Between 2013 and 2021, the chemical properties of the soil (concentrations of Ca2+, Mg2+, K+, and Base Saturation (BS)) saw only a slight improvement, leaving soil fertility as a significant constraint on cotton production. Targeted, site-specific soil management is necessary to address this issue. The study evaluated soil suitability for cotton cultivation in eight villages in the Côte d'Ivoire cotton basin by characterizing two representative soil profiles (0-100 cm) per village which were described in terms of their soil chemical and physical properties. The soils were "moderately suitable" (S2) or "marginally suitable" (S3) due to poor chemical properties, such as the Sum of Basic Cations (SBC) and organic carbon (OC). The study also used Landsat images to track changes in land use and land cover (LULC) between 1998 and 2020 and predicted future LULC for 2035 and 2063 using the TerrSet software and the CA-Markov chain. From 1998 to 2020, there was a reduction in the share of forestland and Savannah with each zone decreased by -11.09 % and -21.56 % respectively at Korhogo, -14.09 % and -1.78 % respectively at Ferkessedougou, -0.33 %, and -14.8 % respectively at Boundiali, and -6.9 % and -31.33 % respectively at Mankono, while water body, cropland, and settlement/bare land increased. From 1998 to 2035, the results revealed that the share of cropland and, settlement/bare land within the department continue to increase in the study area by 4.54 % and 28.2 %, respectively at Korhogo, 5.34 %, and 10.45 % at Ferkessedougou, 14.95 %, and 0.01 % at Boundiali, and 1.12 %, and 37.04 % in the zone at Mankono. From 1998 to 2063, the results revealed that the share of cropland and, settlement/bear with the department's land could continue to increase. The findings of this study could aid in improving and optimizing soil management practices within the cotton-producing region of Côte d'Ivoire.
  • Item
    Crops-Livestock Integration as a Resilience Strategy to Climate Change in Burkina Faso
    (2023-07) Sanou, Charles Lamoussa
    This study titled addressed a topical issue of climate change and its impacts on farmers' livelihoods and the role that an integrated crop-livestock system can play in building resilient farmers and agricultural systems. The research first of all analysed historical climate (rainfall, minimum and maximum temperature) trends across three climatic zones Sudan (Dano), Sudan-Sahel (Niou) and Sahel (Dori)) at annual, seasonal and decadal scales. Climates indices computation was done using the package ClimPACT2 GUI in R software. Annual and seasonal climate were compared using the independent t-test. Decadal climate indices were subjected to a Principal Component Analysis (PCA). The research also analysed the susceptibility or sensibility of crop production and livestock health to climate change. Thirdly, the research developed and/or updated measurement tool known as Crop-Livestock Integration (CLI) indicators for a holistic characterisation of integrated croplivestock system. These indicators were developed based on the information from 589 farmers’ households and secondary data. Above ground, data were collected from 4,733 trees over a total land area of 243.2 ha (80.1 ha, 78.8 ha and 84.3 ha in Sudan, Sudan-Sahel and Sahel zones, respectively). Due to the Sahel zone's insecurity, soil data could be collected only within Sudan and Sudan-Sahel zones. In total, 120 composite soil samples were collected for this purpose and 240 other samples for soil bulk density determination. Results revealed changes in climate conditions, more pronounced in temperature variations than in rainfall. In the Sudan-Sahel and Sahel zones, a re-wetting trends was observed over the last decade supporting the re-greening hypothesis of the Sahel. Despite some positive effects of the climate indices, crop failure was the major impact of climate pejoration across iv zones. Similarly, livestock health was majorly negatively affected by climate deterioration though the resurgence of diseases due to climate change. Climate indices could explain 23.0 - 50.2 % of the variations in crop yield and an increased cases of livestock diseases occurrence by 1-9.4 units due to the deterioration in climate conditions across climatic zones. Changes in climatic conditions may also induce microbial proliferation and host susceptibility to result in the emergence, redistribution, and changes in the incidence and intensity of pest infestations. The study concluded that crop-livestock integration is underperforming in Burkina Faso and can be improved. Majority farmers (91.6 %) in the Sudan-Sahel zone are practising full crop-livestock integration, unlike the Sahel (62.3%) and Sudan (48.2%) zones. However, only 14.8%, 10.5% and 5.1 % showed the effectiveness of integration in the Sudan-Sahel, Sahel and Sudan zones, respectively. CLI was comparatively more effective in Sudan-Sahel (65.9±32.0 %) than Sahel (44.9±29.5 %) and Sudan zones (35.6±35.0 %). Integration indicators were significantly associated with farm emissions, productivity, biodiversity and soils nutrients. CLI is also a tree-based system with high sequestration potential that could significantly counterbalance the whole system emissions. However, the coverage of fodder needs is negatively associated with soils nutrients content indicating field nutrient mining if an appropriate scheme of nutrient return to the soils as manure is not set. An adequate combination of CLI components offers an opportunity to build resilient farming systems in Burkina Faso to adapt to the changing climate.
  • Item
    Adoption and Effects of Climate Change Adaptation, and Land Use Decision of Smallholders Farmers in the Saline Area of Sine-Saloum, Fimela Senegal
    (2023-07) Thiam, Habibatou Ibrahima
    Soil salinity expansion is one of the most severe land degradation issues confronting farmers in Senegal, particularly in coastal areas such as Fimela. With sea level rise, temperature rise, and rainfall decrease, soil salinity is increasing significantly. It has a negative impact on crop yields and farmers' livelihoods. Farmers developed land use adaptation strategies to deal with soil salinity. Nonetheless, despite adaptations, some farmers continue to complain about the negative impact of soil salinity on their outcomes. Then, this study investigates farmers' adaptation, the different factors that influence it, its implications for smallholder farmers' livelihoods, and farmers' perception of soil salinity and its impact. Data from face-to-face interviews of 288 households using the Krejci and Morgan’s formula and GPS coordinates of households and each of their farms was collected. An agent-based model was used to understand land use adaptation to soil salinity expansion by considering farmers' perceptions of soil salinity expansion under climate change for simulation. A sub-model of household decisions, crop yield, and perception of soil salinity was developed and incorporated into the model. Three scenarios were considered to simulate the interaction between household agents and landscape agents over 25 years. Farmers' adoption is influenced by their assets and sociopsychological factors like threat assessment, coping assessment, and subjective norms. Farmers in Fimela do not have maladaptation thinking that may break their willingness to adopt strategies to cope with soil salinity. The ESR model shows that farmers' adoption of strategies to cope with soil salinity has a positive impact on groundnut yields and a negative influence on food security but has no significant effect on their millet yields. These findings have been validated by the simulation results, which show that the yield difference between farmers who perceive soil salinity expansion and those who do not is significant for groundnut but not millet over 25 years. As a result, it is critical to base policies in combating soil salinity effects on providing better methods of soil salinity adaptation strategies through scientific research. Policies should support a few pilot farmers in these precise and effective strategies to trigger other farmers to follow through the village and social influence by the farmer-to-farmer approach to enable farmers access and appropriation of these new methods.
  • Item
    Agricultural Land Use Change in the Lowlands of Southern Mali under Climate Variability
    (KNUST, 2023-07) Traore, Alou
    This research investigated agricultural land use change in the lowlands of Southern Mali under climate variability. Four supervised classification techniques, Classification and Regression Tree (CART), Support Vector Machine (SVM), Random Forest (RF) and Gradient Tree Boosting (GTB) in Google Earth Engine (GEE), were used for the image classification. An integrated Cellular Automata-Artificial Neural-Network (CA-ANN) within the MOLUSCE plugin of QGIS was used for future Land Use and Land Cover prediction. The Mann-Kendall test, Sen’s slope, Pettit-test and change-point detection analyse were applied for climate variability assessment. Monthly rainfall and mean temperature extending over a period of 61 years (1960–2020) recorded at Sikasso District were analysed. Annual rainfall varied between 800 mm to 1600 mm and annual mean temperature ranged between 25 oC to 28 oC. Seasonal rainfall ranged between 37-387 mm, March-April-May (MAM), 400-1030 mm, June-July-August (JJA), 77-577 mm September-October-November (SON) and 0-45 mm for December-January-February (DJF). Mean seasonal temperature ranged from 29 oC to 32 oC (MAM), 26.5 oC to 28.5 (JJA) oC and 26 oC to 28 oC (SON). Annual and seasonal rainfall trends increased slightly. Temperature showed a significant increase in both annual and seasonal trends. Out of 395 respondents, 79 % were of the view that annual rainfall decreased while 83 % reported mean temperature increased. Again, respondents perceived late onset rainfall (97 %), early cessation of rainfall (96 %), increased in drought (83 %) and flooding (96 %). Also, 43 % of respondents adopted new varieties to cope with climate variability. The findings showed that physical and socioeconomic driving forces had impact on terrain patterns. Over the past three decades, the study revealed that apart from cropland area which increased from 43.81 % to 52.75 %, the size of the other land uses decreased, forest cover (19.93 % - 13.93 %) shrubs (16 % - 14 %), and streams (6 % - 4 %). However, the forecast for the 2020 to 2030 predicted an increasing trend in forest cover and decreasing trend in agricultural land in the study area due to the ongoing afforestation projects. The study demonstrates the need to reinforce regional land management policies and programmes.
  • Item
    Development of Asphalt Pavement Temperature Prediction Models for the Climatic Conditions of Ghana
    (2023-07) Ntramah, Simon
    Asphalt pavement temperature finds application in several areas of pavement engineering including pavement structural evaluation and design, asphalt mixture design, asphalt material aging characterisation, and asphalt binder grade selection. Predictive models may be used in the estimation of asphalt pavement temperature when necessary, however, such models tend to have limited transferability and applicability to other regions where the environmental conditions are significantly different from those under which the models were developed. To avoid the risk of using foreign-developed models in estimating the temperature of asphalt pavements in Ghana using local data, this research set out to develop asphalt pavement temperature prediction models applicable to the climatic conditions of the country. Two locations in the country, one within the Savannah climatic zone and the other within the Forest climatic zone, were used for the study. Mid-depth and surface asphalt pavement temperatures, along with climatic data, were collected over a 12-month period (May 2022 to April 2023) at the two study locations. The dataset was then used to develop separate asphalt pavement temperature prediction models applicable to each climatic zones. Additional pavement temperature and climatic data were also collected on separate roads within the corresponding climatic zones for model validation. When tested against some high-rated foreign-developed models, using local environmental data inputs, the locally-developed models predicted asphalt pavement temperatures that were much superior in accuracy (R2 ≥ 0.919, RMSE < 2.8 ºC) to those predicted using the best-performing foreign-based model (R2 ≤ 0.905, RMSE ≥ 3.2 ºC). The local models are, therefore, recommended for predicting mid-depth asphalt pavement temperatures in the Forest and Savannah zones of Ghana for pavement engineering purposes.