Scientific African最新文献

{"title":"Adsorptive removal of methylene blue as case study of adsorption phenomenon by ceramic filters: experimental study and kinetic modeling","authors":"Akuemaho Virgile Onésime Akowanou ,&nbsp;Hontonho Espérance Justine Deguenon ,&nbsp;Sena Peace Hounkpè ,&nbsp;Mohamed Moukorab Arêmou Daouda ,&nbsp;Martin Pépin Aina","doi":"10.1016/j.sciaf.2025.e02858","DOIUrl":"10.1016/j.sciaf.2025.e02858","url":null,"abstract":"<div><div>Ceramic filters are widely recognized for their effectiveness in removing microorganisms and pathogens from drinking water. However, their ability to eliminate chemical pollutants through adsorption remains underexplored. This study investigates the adsorption of methylene blue (MB) onto ceramic filters made from sintered clay materials. It is a new and detailed experimental investigation of adsorption phenomena in ceramic pot filtration, focusing on the removal of methylene blue as a model pollutant. Adsorption kinetics were examined under varying conditions, including contact time, pH, adsorbent dosage, and agitation speed. The adsorption process followed a pseudo-second-order kinetic model, indicating a strong interaction between the adsorbents and the adsorbate. Isothermal adsorption experiments revealed that the Langmuir model best described the adsorption behavior, with maximum adsorption capacities of 267.5 mg/g, 258.5 mg/g, and 252.5 mg/g for the three clay-based materials studied. This suggests that the adsorption of methylene blue occurs as a monolayer on a homogeneous surface with finite and energetically equivalent sites, highlighting the potential for optimizing surface properties to maximize adsorption efficiency. These findings confirm the significant role of adsorption on ceramic pot filter in pollutant removal by clay based ceramic filters and highlight the potential of optimizing material properties to enhance water treatment efficiency.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"29 ","pages":"Article e02858"},"PeriodicalIF":2.7,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144680319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Knowledge, perceptions, and utilization of Pre-exposure prophylaxis among youth at ntšekhe government hospital, lesotho","authors":"Teboho Lekhutla,&nbsp;Bernard Hope Taderera","doi":"10.1016/j.sciaf.2025.e02857","DOIUrl":"10.1016/j.sciaf.2025.e02857","url":null,"abstract":"<div><h3>Background</h3><div>Pre-Exposure Prophylaxis (PrEP) is an effective biomedical intervention for preventing HIV transmission among high-risk populations. However, despite its proven efficacy, the uptake of PrEP remains low among youth in Lesotho, particularly those accessing services at Ntšekhe Government Hospital. This study aims to assess the knowledge, perceptions, and utilisation of PrEP amongst the youth aged 18–24 years at the hospital.</div></div><div><h3>Methods</h3><div>A cross-sectional survey was conducted from June to July 2024, involving 152 youth who completed structured questionnaires. Descriptive statistics were used to examine socio-demographic data, knowledge levels, and perceptions, while inferential analyses explored the relationships between education, gender, and PrEP utilisation.</div></div><div><h3>Findings</h3><div>The study reveals that 71 % of participants were aware of PrEP, yet only 12.5 % had ever used it. Interestingly, a counterintuitive finding emerged: individuals with higher education, despite demonstrating significantly better knowledge of PrEP (<em>p</em> &lt; 0.001), were less likely to use it, suggesting internal or structural barriers to uptake. This unexpected trend signals a need for further qualitative investigation. Gender disparities were also evident, with males significantly less likely to report PrEP use compared to females (<em>p</em> &lt; 0.001). A moderate positive correlation (<em>r</em> = 0.431, <em>p</em> &lt; 0.001) was found between perceptions of PrEP’s effectiveness and its utilisation.</div></div><div><h3>Interpretations</h3><div>The findings highlight the need for targeted public health interventions to address knowledge gaps, dispel misconceptions, and reduce barriers to PrEP access, particularly among young people in Lesotho. Expanding PrEP education and addressing gender-specific factors are crucial steps in improving PrEP uptake and preventing HIV transmission in this high-risk population.</div></div><div><h3>Funding</h3><div>This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"29 ","pages":"Article e02857"},"PeriodicalIF":2.7,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144702973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data-driven prediction of hemispherical solar distiller performance: Optimizing water production with machine learning","authors":"Swellam W. Sharshir ,&nbsp;Ahmed Sedik ,&nbsp;Mohamed A. Hamada ,&nbsp;T. Medhat ,&nbsp;Moustafa M. Nasralla ,&nbsp;Haleem Farman ,&nbsp;Manal E. Ali","doi":"10.1016/j.sciaf.2025.e02851","DOIUrl":"10.1016/j.sciaf.2025.e02851","url":null,"abstract":"<div><div>Artificial intelligence has found applications in numerous research domains, notably in the field of mechanical engineering. This research work introduces a novel data-driven approach to predict the thermal performance of a Hemispherical Solar Still (HSS) using five machine learning models: Decision Tree (DT), Random Forest (RF), Gradient Boosting (GB), Support Vector Machine (SVM), and K-Nearest Neighbor (KNN). The proposed prediction models are built using real experimental data that has been recorded. Leveraging real experimental data, these models were rigorously evaluated for predicting hourly productivity and instantaneous efficiency, using five statistical error metrics to assess their performance. The DT model emerged as the most accurate and efficient, achieving near-ideal R² and EVS values near to one, alongside minimal statistical error values (MSE, NAE, and Median Absolute Error). Notably, DT predicted average hourly productivity at 0.477 L/m²/day—closely matching experimental averages (0.478 L/m²)—with 45.2 % average instantaneous efficiency, outperforming other models (SVM: 46.4 %, RF: 46.4 %, KNN: 44.8 %, GB: 45.2 %). Therefore, this work demonstrates that DT-based prediction can reliably estimate HSS performance, eliminating costly and time-consuming experimental iterations. The proposed framework provides a robust, scalable solution for solar still optimization, advancing AI applications in sustainable water production.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"29 ","pages":"Article e02851"},"PeriodicalIF":2.7,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144662150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Potential of omics workflows for harnessing molecular-grade DNA polymerase and DNA-binding protein isoforms from African thermophilic microbiomes","authors":"Reuben S. Maghembe ,&nbsp;Abdalah Makaranga ,&nbsp;Samweli Bahati ,&nbsp;Deogratius Mark ,&nbsp;Christina Kidulile ,&nbsp;Emmanuel Haule ,&nbsp;Tusajigwe Mwakalinga ,&nbsp;Damian Dogbert Kalekayo ,&nbsp;Joseph Ndunguru","doi":"10.1016/j.sciaf.2025.e02854","DOIUrl":"10.1016/j.sciaf.2025.e02854","url":null,"abstract":"<div><div>Since its inception in 1983 by Kary Banks Mullis, polymerase chain reaction (PCR), has been relevant in molecular biology laboratories for detection, identifying and modifying genetic material, diagnostic research to cloning, sequencing, and mutagenesis. DNA polymerase from <em>Thermus aquaticus</em> (<em>Taq</em>), also known as <em>Taq</em> polymerase, has been the most common enzyme used globally to amplify DNA in molecular laboratories. This has leaped economies of laboratories that have successfully purified and chemically optimized the <em>Taq</em> polymerase. On the other hand, single-strand DNA-binding protein (SSB) is useful in holding one of the melted (denatured) DNA strands apart from the complementary counterpart. This allows effective DNA amplification by promoting primer annealing and preventing DNA strand rehybridization and rewinding. While these experiments work better at higher temperatures, the most reliable DNA polymerase and SSB isoforms should be sourced from similarly high temperature organisms, the thermophiles. Although Africa harbors many hot springs, African laboratories remain dependent on advanced multinational companies for <em>Taq polymerase</em> and other molecular reagents. Here we discuss the potential of omics workflows for effective bioprospecting of thermophilic microbiomes for PCR-grade DNA polymerase and SSB isoforms. We pinpoint the most recent advances in omics workflows and their relevance to the African setting. Additionally, we highlight essential conditions for molecular laboratories with capacity to utilize omics for sustainable experiments and mass production of proteins. Finally, we discuss the most forefront opportunities and challenges related to efforts to combine interdisciplinary bioinformatics to transition from basic science to innovative initiatives under the low-resource setting of Africa.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"29 ","pages":"Article e02854"},"PeriodicalIF":2.7,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144654760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decision tree-based statistical learning and quantile regression adjustment: Insights from pregnant women in Benin","authors":"Yémalin Bill-Lucas Kintomonho ,&nbsp;Mintodê Nicodème Atchadé ,&nbsp;Donatien Daddah","doi":"10.1016/j.sciaf.2025.e02832","DOIUrl":"10.1016/j.sciaf.2025.e02832","url":null,"abstract":"<div><div>This research investigated factors influencing pregnancy outcomes (stillbirth or live birth) and newborn weight distribution among pregnant women in Benin. It covered 1,048 pregnant women who attended the five referral hospitals in Couffo in 2020, with data on 952 live births. We used random forests for feature selection, CART decision trees for pregnancy outcome prediction, and quantile regression to examine newborn weight distribution. The CART model identified key risk factors for adverse pregnancy outcomes, including young maternal age (18–24 years), a history of HIV, two or more prior stillbirths, and multiparity (four or more living children). In contrast, favorable pregnancy outcomes were associated with maternal age (25–40 years), at least three prenatal consultations, and the absence of major medical conditions. The neonatal death rate was 91.6 per 1000 live births. Quantile regression analysis revealed that low birth weight was associated with young maternal age (14–24 years), strenuous maternal occupation, paternal occupation, pregnancy complications (hypertension, preeclampsia, anemia, premature rupture of membranes), twin pregnancy, late prenatal care (third trimester), fewer than four prenatal visits, and a history of cesarean section. Macrosomia was linked to maternal age (25–45 years), parental occupation, and the absence of medical or pregnancy-related complications. Notably, macrosomia was strongly associated with a high cesarean section rate (64.44%). These findings highlight critical factors influencing pregnancy risks and newborn health, emphasizing the need for targeted prenatal care strategies in Benin.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"29 ","pages":"Article e02832"},"PeriodicalIF":2.7,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144632481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Control strategies of hybrid RESs for off-grid water pumping technologies: An overview","authors":"Haneen M. Bawayan ,&nbsp;Mohamed A. Enany ,&nbsp;Mahmoud M. Elymany ,&nbsp;Ahmed A. Shaier ,&nbsp;Marwa M. Ahmed","doi":"10.1016/j.sciaf.2025.e02856","DOIUrl":"10.1016/j.sciaf.2025.e02856","url":null,"abstract":"<div><div>Hybrid Renewable Energy Systems (HRESs) that combine photovoltaic (PV) and wind energy (WE) offer a sustainable solution for off-grid water pumping, particularly in remote or agricultural areas with limited or unreliable grid access. This review critically examines control strategies used in Hybrid Renewable Energy Water Pumping Systems (HREWPS), focusing on improvements in energy efficiency, reliability, cost-effectiveness, and adaptability to changing environmental conditions. The manuscript categorizes and compares a range of control methodologies. These include maximum power point tracking (MPPT) algorithms such as perturb and observe (P&amp;O), incremental conductance (IC), fuzzy logic, artificial neural networks (ANN), adaptive neuro-fuzzy inference system (ANFIS), and swarm intelligence techniques. Advanced motor control methods like field-oriented control (FOC), direct torque control (DTC), scalar control, and sliding mode control are also reviewed. These techniques are evaluated across motor types including induction motors (IM), brushless DC motors (BLDCM), permanent magnet synchronous motors (PMSM), switched reluctance motors (SRM), synchronous reluctance motors (SynRM), and open-end induction motors (OEIM). This study also emphasizes battery-less configurations, hybrid storage systems, and AI-enhanced energy management frameworks that optimize real-time performance and increase system resilience. Emerging technologies such as model predictive control (MPC), IoT-based remote monitoring, and blockchain-enabled microgrid energy trading are discussed as future enablers for advanced HREWPS. By integrating recent advancements and experimental findings, this review outlines a roadmap for sustainable, intelligent, and adaptive off-grid water pumping systems. It underscores the role of smart control solutions in addressing global water and energy challenges.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"29 ","pages":"Article e02856"},"PeriodicalIF":2.7,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144654758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The dynamics of hepatitis B virus via a stochastic epidemic model","authors":"Tahir Khan ,&nbsp;II Hyo Jung ,&nbsp;Gul Zaman ,&nbsp;Ebenezer Bonyah","doi":"10.1016/j.sciaf.2025.e02837","DOIUrl":"10.1016/j.sciaf.2025.e02837","url":null,"abstract":"<div><div>Hepatitis B is a highly contagious disease affecting approximately two billion people globally. Mathematical modeling of hepatitis B virus (HBV) transmission is crucial not only for understanding its current spread but also for predicting future dynamics. In this study, we develop a stochastic differential equation (SDE) model that captures the key characteristics of HBV transmission, acknowledging its inherent randomness. The model incorporates two infectious compartments: acutely infected and chronically infected individuals, reflecting the clinical significance of both groups. Notably, some individuals may progress directly to the chronic stage without a prior acute phase. Successfully vaccinated individuals are considered recovered, given that the hepatitis B vaccine provides protective immunity in approximately 95% of cases. We establish the model’s well-posedness by proving the existence and uniqueness of solutions, and we analyze conditions for disease extinction and persistence. Sensitivity analysis is also performed to evaluate the impact of key epidemiological parameters on disease dynamics. Finally, numerical simulations are conducted using the stochastic Runge–Kutta (SRK) method to validate and support the analytical findings.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"29 ","pages":"Article e02837"},"PeriodicalIF":2.7,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144606103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Processor-in-the-loop validation of a super-twisting algorithm for enhanced direct power control of a variable-speed DFIG using dSPACE 1104 controller board","authors":"Mourad Yessef ,&nbsp;Habib Benbouhenni ,&nbsp;El Hanafi Arjdal ,&nbsp;Ahmed Lagrioui ,&nbsp;Badre Bossoufi ,&nbsp;Ayman Alhejji","doi":"10.1016/j.sciaf.2025.e02855","DOIUrl":"10.1016/j.sciaf.2025.e02855","url":null,"abstract":"<div><div>Direct Power Control (DPC) technique applied to a Doubly-Fed Induction Generators (DFIG) presents numerous benefits, although encounters difficulties concerning power calculation and susceptibility to changes in system parameters. This novel paper addresses these restrictions by the utilization of Super-Twisting Sliding Mode Control (STSMC) method. The typical hysteresis comparators in classical Direct Power Control (DPC) are substituted with a Direct Power Control utilizing a Super-Twisting Controller (DPC-STC), and the customary switching table is replaced with Pulse Width Modulation (PWM) to provide enhanced smoothness and robustness in control. The suggested DPC-STC-PWM approach enhances control accuracy and guarantees superior tracking performance under step wind profiles and fluctuating wind conditions. The suggested control technique was initially designed and assessed through MATLAB/Simulink simulations under multiple wind speed profile conditions to determine its efficacy. The obtained results were compared to those of conventional DPC approah in terms of active power undulations/ripples, response time, Total Harmonic Distortion (THD) of supplied stator currents, and Steady-State Error (SSE). To verify the robustness of the studied proposed strategy againt the DFIG parameters changes, it was subjected to a robustness test with a varied wind profile. Despite modifications of DFIG system parameters, the finding confirm that the suggested control technique can maintain consistent and accurate high performance. In the three tests, the STC-based DPC-PWM outperformed classical conventional DPC technique by a very wide margin, reducing THD value by 79.83 %, 81.34 %, and 75.85 %, respectively, when the wind profile changed. Three separate reductions in the SSE for active power were achieved: 78.49 %, 71.14 %, and 85.57 % for the three tests. In addition, reactive power overshoot was reduced by 92.28 %, 96.87 %, and 89.50 %, and active power fluctuations were reduced by 66.66 %, 68.52 %, and 53.33 %, respectively.</div><div>The real-time Processor-in-the-Loop (PIL) test validation was realized with the dSPACE 1104 controller embedded card to further validate these findings, during which varied wind speeds were used. The experimental results closely aligned with the simulation outcomes, validating the efficacy of the STC-DPC method in alleviating the constraints of traditional DPC in DFIG-based wind energy conversion systems. The proposed novel technique proved itself as a durable and dependable alternative for improving the performance and stability of DFIG-based power conversion systems. The proposed method provides an effective and feasible solution for the growing wind energy sector in Morocco and across Africa, where grid stability and robust control are crucial.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"29 ","pages":"Article e02855"},"PeriodicalIF":2.7,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144633339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the use of complementary and alternative medicine among cancer patients in Africa: A systematic review","authors":"Abdulgafar O. Jimoh ,&nbsp;Shuaibu A. Hudu ,&nbsp;Usman M. Aliyu ,&nbsp;Adamu A Adamu ,&nbsp;Nura Bello ,&nbsp;Albashir Tahir ,&nbsp;Nura Abubakar","doi":"10.1016/j.sciaf.2025.e02852","DOIUrl":"10.1016/j.sciaf.2025.e02852","url":null,"abstract":"<div><h3>Background</h3><div>Complementary and Alternative Medicine (CAM) is widely practiced by cancer patients globally, and in Africa, where the influence of cultural beliefs, limited access to healthcare, and personal preferences enhance its use. This systematic review explored the prevalent of CAM use, the various types of CAM practiced, and the reasons behind its use among cancer patients in Africa.</div></div><div><h3>Methods</h3><div>Databases including PubMed, Scopus, EMBASE, AJOL, and Google Scholar were comprehensively searched to retrieve relevant studies using selected keywords and synonyms. Studies focusing on CAM usage patterns among cancer patients in Africa and published in English were considered. Relevant data were extracted, and the quality of the studies was evaluated using the CASP critical appraisal tool. Findings were narratively synthesized and reported according to PRISMA guidelines.</div></div><div><h3>Results</h3><div>A total of 21 studies from 12 African countries, involving 8,945 cancer patients, were included. The prevalence of CAM use was reported to range from 36% to 80%, indicating widespread reliance on these practices in Africa. The use of herbal medicine, spiritual healing, and dietary supplements were identified as the most common CAM modalities. CAM use was found to be more frequent among women, rural residents, and patients in advanced stages of cancer. Reasons for CAM use were reported to include cultural beliefs, limited trust in conventional treatments, and the hope of improved health outcomes.</div></div><div><h3>Discussion</h3><div>CAM is widely practised among African cancer patients, driven by various cultural, economic, and healthcare-related factors, offering emotional and psychological benefits. However, its unregulated use could potentially result in delays in receiving proper cancer treatment. Governments, healthcare providers, and researchers should work together to ensure that CAM practices are safe, evidence-based, and integrated into healthcare systems where appropriate. Public education on CAM use is also crucial to improve cancer care outcomes.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"29 ","pages":"Article e02852"},"PeriodicalIF":2.7,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144654771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Flood hazard vulnerability assessment in the Sile-Sago watershed, Rift Valley Basin, Ethiopia","authors":"Asnake Boyana Ayele ,&nbsp;Abiyot Legesse ,&nbsp;Abera Uncha ,&nbsp;Abren Gelaw","doi":"10.1016/j.sciaf.2025.e02846","DOIUrl":"10.1016/j.sciaf.2025.e02846","url":null,"abstract":"<div><div>Flood hazards (FHs) are exacerbated by heavy rainfall and pose serious threats to life, social amenities, and the environment. This study was targeted at identifying and mapping factors triggering, analyzing, and mapping vulnerabilities of FHs in the Sile-Sago watershed. Data were acquired from the field, interviews, and satellite images. The 13 parameters contributing to FH's vulnerability included rainfall, soil types, elevation, slope, proximity to rivers, drainage density, population density, land use or cover, topographic wetness index, vegetation density, etc. Data were resampled into 30 m resolution before conducting the weighted overlay process. The research utilized MCDM and AHP models, based on literature, survey, and expert evaluation, to establish weight scores for ranking factors, enhancing its uniqueness and establishing the relative importance of each factor. Then the weighted overlay operation was used to map the vulnerability levels of the FHs in ArcGIS environment. The study results revealed that nearly one-third (32.5 %) of the area falls in the high (21.5 %) and very high (11 %) vulnerability zones. These areas are characterized by intense rainfall, dense human settlements, and the highest drainage density. The model was validated with a consistency ratio (CR) of 0.034 (3.4 %) and a receiver operating curve with an area under curve value (ROC-AUC) of model prediction accuracy of 0.81 (81 %). Both the CR and ROC-AUC values indicate that the model performance is highly acceptable. Successful management of floods hinges on anticipatory prediction, early warning systems, preparedness, and disaster risk management strategies. Building gabions, canals, bridges, and other physical structures must be constructed by individuals, local and regional governments, and non-governmental organizations as recommended protection and prevention strategies for FHs in the watershed.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"29 ","pages":"Article e02846"},"PeriodicalIF":2.7,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144633338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}