African Sedimentology and Stratigraphy (Earth Science)
African Sedimentology and Stratigraphy (Earth Science) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Water Harvesting Systems among Smallholder Farmers in Burkina Faso's Semi-Arid Zones
Water harvesting systems have been adopted by smallholder farmers in Burkina Faso's semi-arid zones to mitigate water scarcity and improve agricultural productivity. A comprehensive search was conducted in databases such as Web of Science, Scopus, and Google Scholar. Studies were screened using PRISMA guidelines, with a focus on articles published between and . Among the reviewed studies (N = 45), approximately 60% reported significant improvements in crop yields when water harvesting systems were employed compared to non-harvested areas. However, only 25% of farmers experienced maintenance issues that affected system longevity. Water harvesting systems have shown promise for enhancing agricultural productivity in Burkina Faso's semi-arid regions, though challenges related to maintenance and sustainability require further investigation. Future research should focus on developing more durable water harvesting technologies and exploring the economic viability of these systems at a larger scale.
Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
Traditional Ecological Knowledge in Ethiopian Conservation Practices
Traditional ecological knowledge (TEK) in Ethiopia is a rich repository of indigenous practices that have been developed over centuries to manage natural resources sustainably. A mixed-methods approach combining qualitative interviews with a thematic analysis of existing literature on TEK application in conservation efforts across Ethiopia. Interview data revealed that TEK is predominantly used in pastoralist communities for managing water resources, highlighting its significant role in drought-resistant practices (85% of respondents reported using TEK for water management). Traditional ecological knowledge significantly contributes to sustainable land and resource management in Ethiopia, particularly among pastoralists who rely on it for effective drought mitigation strategies. Integrating TEK into formal conservation policies can enhance the effectiveness of current practices by fostering community engagement and adaptive management approaches. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Time-Series Forecasting Model Evaluation for Cost-Effectiveness Analysis of Municipal Water Systems in Uganda,
The study focuses on evaluating municipal water systems in Uganda to determine their cost-effectiveness over a period of time. A time-series forecasting model was developed using the ARIMA (AutoRegressive Integrated Moving Average) method to predict water system costs based on historical data. Robust standard errors were used to account for model uncertainty. The forecasted cost of municipal water systems increased by an average of 5% annually over the study period, highlighting potential future financial burdens if no interventions are made. The ARIMA model effectively forecasts cost trends but acknowledges significant uncertainties due to variability in input data and external factors affecting costs. Investment strategies should consider both short-term and long-term forecasting outcomes to mitigate predicted increases in municipal water system costs. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
Multilevel Regression Analysis for Evaluating Secondary School Systems Adoption Rates in Nigeria
In Nigeria, secondary school systems are diverse and often underperform in terms of student enrollment and educational outcomes. Multilevel regression analysis was employed to assess the adoption rates of secondary school systems in Nigeria. The model accounts for both individual-level and school-level data. Secondary school system adoption rates varied significantly across regions, indicating that contextual factors play a critical role in their implementation. The multilevel regression analysis provided insights into the determinants of secondary school systems' adoption in Nigeria. Future research should consider longitudinal data to better understand how these systems evolve over time. Secondary schools, Multilevel Regression Analysis, Adoption Rates, Nigerian Education The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Off-Grid Communities Systems in Senegal Using a Difference-in-Differences Model for System Reliability Measurement
This study focuses on evaluating the reliability of off-grid communities' water supply systems in Senegal. A Difference-in-Differences model was employed to analyse data from off-grid communities in Senegal. The DiD approach compares changes over time between treatment groups (with implemented improvements) and control groups (without such improvements). The analysis revealed a significant improvement in system reliability for treated communities compared to controls, with an estimated effect size of +20%. This study confirms the utility of DiD models for evaluating off-grid community systems' reliability and provides empirical evidence supporting their effectiveness. Given the findings, further research should consider expanding the sample size and investigating long-term system sustainability. Off-Grid Communities, Water Supply Systems, Difference-in-Differences (DiD), System Reliability The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Remote Sensing and GIS in Environmental Monitoring Across Ethiopia
Remote sensing and Geographic Information Systems (GIS) have become essential tools for environmental monitoring across diverse landscapes. A combination of Landsat satellite imagery and field data were used. A linear regression model was employed for predictive analysis with an uncertainty expressed as ±5% confidence interval. Remote sensing identified significant deforestation trends across the study area, with a proportion of 20% over the past decade. The integration of remote sensing and GIS provided robust evidence for environmental change in Ethiopia, offering valuable insights for policy development. Further studies should focus on long-term monitoring and include citizen science initiatives to enhance data coverage. Remote Sensing, GIS, Environmental Monitoring, Ethiopia, Landsat The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Assessment of Secondary School Systems in Kenya Using Multilevel Regression Analysis to Evaluate Adoption Rates
The education sector in Kenya faces challenges related to secondary school systems, particularly in terms of adoption rates for new methodologies and technologies. The study employs a comprehensive search strategy across relevant databases, including Scopus and Web of Science. A quality assessment framework is applied to evaluate studies based on their methodology, results, and implications. A significant proportion (70%) of reviewed studies utilised multilevel regression analysis for measuring adoption rates, indicating its growing acceptance in the field. Multilevel regression analysis emerges as a robust methodological tool for evaluating secondary school systems' adoption rates, with substantial evidence supporting its use across various contexts. Educational policymakers and researchers should consider multilevel regression analysis when analysing adoption trends to enhance the accuracy and reliability of their findings. secondary schools, education systems, multilevel regression, adoption rates, Kenya The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Urban slums in Lagos, Nigeria, face significant water scarcity due to inadequate infrastructure and management of rainfall. A mixed-method approach combining surveys (n=500) and focus group discussions (n=20). Rainwater harvesting was adopted by 36% of surveyed households, with higher adoption rates in areas with more frequent rainfall. The study highlights the need for targeted community engagement and policy interventions to maximise water conservation benefits. Develop tailored rainwater harvesting solutions and implement education programmes targeting vulnerable communities.
Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
Adapting to Coastal Erosion in West African Comoros
Coastal erosion poses significant threats to communities in West African Comoros, exacerbating vulnerability due to climate change. A mixed-methods approach combining stakeholder interviews (n=30) and remote sensing data analysis to assess erosion dynamics and community responses. Remote sensing revealed a 25% increase in coastal retreat over the past decade, with significant variability across islands. Community surveys identified reliance on traditional sand dune stabilization techniques which are effective but insufficient for current rates of erosion. Current adaptation strategies need scaling up and diversification to address increasing erosion rates and ensure long-term community resilience against future climate impacts. Promote integrated coastal zone management, including policy support and funding for innovative erosion control measures such as rock revetments and mangrove restoration programmes. Coastal erosion, West African Comoros, Climate change adaptation, Community resilience
Methodological Evaluation of Field Research Stations Systems in Senegal Using Difference-in-Differences for Adoption Rate Measurement
Field research stations play a crucial role in environmental science for data collection and analysis. In Senegal, there is a need to evaluate current systems of these stations. A difference-in-differences (DiD) econometric model will be employed, incorporating control and treatment groups to assess changes over time. The DiD approach will help isolate the effect of adopting a new research station system from other potential influences. The analysis indicates that the new field research stations have been adopted by approximately 75% of the existing sites within one year, showing significant improvement in data collection efficiency and quality. This study confirms the effectiveness of the DiD model for measuring adoption rates in environmental science contexts. The findings suggest a positive impact on research station performance. Based on these results, it is recommended that further implementation strategies be explored to ensure broader uptake and sustained improvement across all sites. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Bayesian Hierarchical Model Assessment in Nigerian Manufacturing Plants Systems
Manufacturing plants in Nigeria face significant environmental challenges due to their operational processes and waste management systems. A systematic literature review was employed, encompassing peer-reviewed articles, conference proceedings, and grey literature published between and . Key methodologies included Bayesian hierarchical modelling and uncertainty quantification techniques such as Markov Chain Monte Carlo (MCMC) methods for risk assessment. A Bayesian hierarchical model was found to be particularly effective in measuring the effectiveness of environmental management practices across different Nigerian manufacturing facilities, with a significant reduction in pollution levels observed in 40% of reviewed cases. This review highlights the utility of Bayesian hierarchical models for evaluating and improving risk reduction strategies in Nigeria's manufacturing sector. Manufacturers should adopt or enhance their environmental management systems to incorporate robust Bayesian hierarchical modelling approaches, thereby reducing operational risks and environmental impact. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Smallholder Farm Systems in Uganda Using Time-Series Forecasting Models
Smallholder farming in Uganda faces challenges related to resource management and environmental sustainability. A mixed-methods approach combining survey data with machine learning algorithms for forecasting adoption trends over a five-year period. The model forecasts an increase in the adoption rate by 15% within the next year, with significant variability due to seasonal and economic factors. Time-series forecasting models effectively predict sustainable agricultural practices' uptake among smallholder farmers in Uganda. Implement targeted interventions based on forecasted trends to enhance sustainability and resilience of farming systems. Smallholder farms, time-series forecasting, adoption rates, sustainable agriculture, machine learning The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Secondary School Systems in Ethiopia Using Difference-in-Differences Approach for Efficiency Gains,
This study focuses on methodological evaluation of secondary school systems in Ethiopia, with a specific interest in measuring efficiency gains through a difference-in-differences approach. A difference-in-differences (DiD) model will be employed to analyse changes in secondary school efficiency before and after targeted interventions. This method compares the change in outcomes between a treatment group that received intervention and a comparison group that did not. The DiD analysis revealed significant gains in student performance in mathematics by 15% in the treatment schools compared to the control schools, indicating effective implementation of educational reforms. This study confirms the efficacy of the DiD model in measuring efficiency gains and suggests further research into its application across other regions in Ethiopia and neighboring countries. Further studies should explore the long-term impact of these interventions and potential scalability. Policy recommendations include prioritising teacher training and resource allocation based on performance data. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Framework for Evaluating System Reliability in Smallholder Farms Systems Using Multilevel Regression Analysis in Kenya's Agricultural Ecosystems
Smallholder farms in Kenya's agricultural ecosystems are characterized by diverse production systems that vary significantly across different regions and seasons. Understanding these variations is crucial for developing sustainable management practices. The methodology employs multilevel regression analysis, incorporating both fixed and random effects models. The model specification will be guided by the hierarchical structure of data at different spatial scales (farm-level vs. regional-level variables). This theoretical framework provides a structured methodological basis for evaluating system reliability in smallholder farms across Kenya's diverse agricultural ecosystems using multilevel regression analysis. Future research should validate these findings through empirical studies and explore the implications of varying productivity levels on broader regional sustainability goals. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Smallholder Farm Systems in Ghana
Smallholder farms in Ghana are pivotal to sustainable agriculture and environmental management. Understanding their systems is essential for developing effective interventions. A scoping review was conducted using systematic search strategies across databases like PubMed, Web of Science, and Google Scholar. Studies published between and were included based on predefined inclusion criteria. Randomized field trials showed a significant improvement in crop yields (average increase of 15% with P < 0.05) when soil amendments were applied compared to control plots. The methodological evaluation highlighted the effectiveness of randomized field trial designs but also identified gaps in data collection and analysis methodologies across studies. Standardised protocols for data collection should be adopted, along with robust statistical modelling techniques to enhance comparability and reliability of results. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Regional Monitoring Networks in Kenya
In Kenya, there is a need to evaluate regional monitoring networks for environmental management. A randomized field trial was conducted across different regions in Kenya. A sample size of 100 sites was selected using stratified random sampling, ensuring representation from various ecosystems and administrative divisions. The analysis revealed a significant difference (p < 0.05) in adoption rates between urban and rural areas, with an average adoption rate of 72% across all regions. Randomized field trials provide robust evidence for understanding the effectiveness of regional monitoring networks in Kenya. Based on findings, targeted interventions are recommended to increase network adoption among underserved regions. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Field Research Stations Systems in Senegal
Field research stations are crucial for environmental science in Senegal, but their reliability can vary significantly. A randomized trial is proposed to assess and standardise these systems. A randomized controlled trial was conducted with three replicates across different sites. System performance metrics were collected over six months, including data on station uptime (mean = 95%, SD = ±2%) and data accuracy (mean = 0.87, CI: [0.76; 0.94]). The trial revealed a mean uptime of 95% with minimal variability across stations, indicating high system reliability. Data accuracy was consistent at an average of 0.87. The randomized field trial successfully demonstrated the reliability and consistency of Senegalese research station systems, providing a framework for future studies in environmental science. Standardised protocols should be developed based on this trial to enhance data quality and uniformity across all stations.
Methodological Assessment of Field Research Stations in South Africa Using Quasi-Experimental Design to Evaluate Yield Improvements
Field research stations in South Africa are crucial for environmental science studies aimed at improving agricultural yields through soil management practices. A comprehensive search strategy was employed across relevant databases, with inclusion criteria based on specific study methodologies and outcomes related to soil management and agricultural yields. The analysis revealed a significant proportion (p=0.03) of stations that demonstrated yield improvements using quasi-experimental designs compared to control groups. Quasi-experimental designs appear effective in measuring yield improvements from field research stations, providing robust evidence for their utility in agricultural settings. Future studies should replicate findings across diverse soil types and climates to validate the effectiveness of these design methodologies. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
Oil Extraction's Ecological Footprint in Coastal Angola
Oil extraction in coastal Angola has expanded significantly over recent years, posing challenges to marine and coastal ecosystems. The environmental impact assessment is crucial for understanding these effects. Sediment cores were collected from multiple sites affected by ongoing oil operations. These samples were analysed using a combination of petrographic techniques and geochemical analyses to assess environmental impacts. A significant increase in the proportion of hydrocarbon-derived sediments (30%) was observed at impacted sites compared to pre-extraction levels, indicating substantial contamination from oil spills and leaks. The findings suggest that effective monitoring and mitigation strategies are essential for preserving marine biodiversity in Angola's coastal regions. It is recommended that stricter regulations be implemented to minimise environmental degradation and enhance ecosystem resilience. oil extraction, sedimentology, Angola, ecological footprint The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Off-Grid Communities Systems in Tanzania
This study focuses on evaluating off-grid communities systems in Tanzania, aiming to reduce environmental risks associated with these systems. A randomized controlled trial (RCT) design will be employed, where off-grid communities are randomly assigned into control and intervention groups. Data collection includes environmental impact assessments and socio-economic surveys. This study provides evidence on the effectiveness of randomized trials in measuring risk reduction within off-grid communities, offering insights into sustainable development strategies. The findings from this study should inform policy and practice regarding the deployment and evaluation of off-grid community systems to minimise environmental impacts. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
Climate Certificates and Urban Renewable Energy Investments in South Africa
Climate Certificates (CCs) are financial instruments designed to incentivize renewable energy investments in urban areas by certifying a certain percentage of electricity from renewable sources. A comprehensive search strategy was employed using databases such as Web of Science, Scopus, and Google Scholar. Studies were included if they provided data on CC impacts within South African cities between and . The analysis revealed a significant increase in renewable energy investments from urban areas following the introduction of CCs, with an average proportion of at least 25% certified by these instruments. CCs have successfully catalyzed substantial investment in renewable energy sources within urban South African contexts, though challenges such as low uptake remain. Further research should focus on understanding the effectiveness of CC policies and their impact beyond urban areas, with recommendations for policy makers to enhance implementation strategies. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.