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Funders and governments are promoting climate-smart agriculture (CSA) as key to agricultural adaptation under climate change in Africa. However, with its progressions still at the policy level and framework description, there is a need to understand the current developments and activities conducted within the CSA research field. We conducted a scientific mapping and analyses of CSA research studies in Africa to understand the (i) thematic trends, (ii) developments, (iii) nature of collaboration networks, and (iv) general narratives supporting the adoption and application of CSA in Africa. Results show that several African countries had endorsed CSA as an approach to addressing agricultural productivity challenges, supporting adaptation strategies, and building resilience to climate change. However, a majority do not have national Climate-Smart Agriculture Investment Plans (CSAIPs). Additionally, CSA research in Africa is still developing, with only a few countries dominating the research outputs. For a successful implementation of CSA, a framework provided by the CSAIPs must be established to guide the processes. This will provide a framework to guide the integration of government programs, policies, and strategic plans by combining other inputs from stakeholders to support decision making and implementation of CSA.
Paul Barasa; Christina Botai; Joel Botai; Tafadzwanashe Mabhaudhi. A Review of Climate-Smart Agriculture Research and Applications in Africa. Agronomy 2021, 11, 1255 .
AMA StylePaul Barasa, Christina Botai, Joel Botai, Tafadzwanashe Mabhaudhi. A Review of Climate-Smart Agriculture Research and Applications in Africa. Agronomy. 2021; 11 (6):1255.
Chicago/Turabian StylePaul Barasa; Christina Botai; Joel Botai; Tafadzwanashe Mabhaudhi. 2021. "A Review of Climate-Smart Agriculture Research and Applications in Africa." Agronomy 11, no. 6: 1255.
Heat stress-related illness attributed to the changing climate, particularly the more frequent extreme high temperatures, is becoming a theme of public concern, especially in the most vulnerable regions, such as the African continent. Knowledge of the existing research directions and gaps on heat stress and human health is vital for informing future strategic research foci capable of influencing policy development, planning, adaptation, and mitigation efforts. In this regard, a bibliometric analysis was conducted, with an emphasis on Africa, to assess regional research contributions to heat stress impacts on human health. The goals of the study were to review publication growth and patterns of the scientific publications and to identify key players (especially collaborating institutions and countries) and the evolution of research themes on the African continent, while paying attention to global trends and emergent hot topics and methodology of heat stress research. Using the Web of Science (WoS) and Scopus core collection databases, a structured keyword search was undertaken, which yielded 463 and 58 research publications from around the world and Africa, respectively. The retrieved scientific documents, published between 1968 and 2020, were analyzed and visualized using a bibliometric analysis technique and the VOSviewer software tool. The results indicate low statistics and slow scientific growth in publication output, with the highest peak having been reached in 2018, resulting in 13 scientific publications. While global research collaborations are successfully reflected in the literature, there is a considerable gap in understanding heat stress and related collaborations between African countries and international institutions. The review study has identified key opportunities that can benefit Africa through the expansion of the scope of heat stress and human health research on the continent. These opportunities can be achieved by closing the following research gaps: (1) vulnerability assessments within demographic classes, such as the elderly, (2) personal exposure and associated risks, (3) Urban Heat Island (UHI) evaluation for urban environments, and (4) heat adaptation research, which will enable informed and targeted preventive actions that will limit future heat health impacts. The authors opine that the pursuit of such studies will be most impactful if the current knowledge gaps are bridged through transdisciplinary research supported by local, regional, and international collaborators.
Katlego Ncongwane; Joel Botai; Venkataraman Sivakumar; Christina Botai. A Literature Review of the Impacts of Heat Stress on Human Health across Africa. Sustainability 2021, 13, 5312 .
AMA StyleKatlego Ncongwane, Joel Botai, Venkataraman Sivakumar, Christina Botai. A Literature Review of the Impacts of Heat Stress on Human Health across Africa. Sustainability. 2021; 13 (9):5312.
Chicago/Turabian StyleKatlego Ncongwane; Joel Botai; Venkataraman Sivakumar; Christina Botai. 2021. "A Literature Review of the Impacts of Heat Stress on Human Health across Africa." Sustainability 13, no. 9: 5312.
Notwithstanding the dispersed nature of the water, energy and food (WEF) nexus scholarship in the African continent, its strategic importance to the African agenda has gained widespread attention in research and planning circles. In this regard, the bibliometric science mapping and content analysis of the WEF nexus scientific publication trends, the conceptual, intellectual and social structures, as well as the inherent paradigmatic shifts in the WEF nexus body of knowledge in the African continent have been undertaken, using the nexus body of literature accessed from the Web of Science and Scopus core collection databases. The review results confirmed that, whilst the WEF nexus scholarship has expanded since 2013, there is also evidence of growth in the conceptual, intellectual and social structures of the WEF nexus in the African continent. These shifts have resulted in the emergence of hot topics (subfields) including modelling and optimization, climate variability and change, environmental ecosystem services sustainability, and sustainable development and livelihoods. The review further determined that these structures have evolved along two main perspectives of WEF nexus research development, i.e., the interdisciplinary and transdisciplinary domains. In support of the interpretation of the visual analytics of the intellectual structure and changing patterns of the WEF nexus research, the shifts in positivist, interpretivist and pragmatic paradigmatic perspectives (these are underpinned by the ontology, epistemology, and methodology and methods) are considered when explaining WEF nexus research shifts: (a) From the unconnected silo paradigms that focus on water, energy and food (security concerns) to interconnected (and sometimes interdependent or nested) linkages or systems incorporating environmental, social-economic and political drivers (also viewed as subfields) in a bid to holistically support the Sustainable Development Goals (SDGs) across the African continent; and (b) in the evaluation of the WEF nexus scholarship based on novel analytical approaches. We contend that whilst the theories of science change underpin this apparent expansion, the macro-economic theory will find use in explaining how the WEF nexus research agenda is negotiated and the Integrative Environmental Governance (IEG) is the duly suited governance theory to bridge the inherent disconnect between WEF nexus output and governance processes uncovered in the literature. Overall, operational challenges and opportunities of the WEF nexus abound, transitioning the WEF nexus research to practice in Africa, motivating the need to take advantage of the scholar–practitioner research underpinnings, as contemplated in the transdisciplinary research approach, which is characterised by the dual quest for new knowledge and considerations of use. Yet, there is need for more coordinated and collaborative research to achieve impact and transition from WEF nexus thinking to WEF nexus practice.
Joel Botai; Christina Botai; Katlego Ncongwane; Sylvester Mpandeli; Luxon Nhamo; Muthoni Masinde; Abiodun Adeola; Michael Mengistu; Henerica Tazvinga; Miriam Murambadoro; Shenelle Lottering; Isaac Motochi; Patrick Hayombe; Nosipho Zwane; Eric Wamiti; Tafadzwanashe Mabhaudhi. A Review of the Water–Energy–Food Nexus Research in Africa. Sustainability 2021, 13, 1762 .
AMA StyleJoel Botai, Christina Botai, Katlego Ncongwane, Sylvester Mpandeli, Luxon Nhamo, Muthoni Masinde, Abiodun Adeola, Michael Mengistu, Henerica Tazvinga, Miriam Murambadoro, Shenelle Lottering, Isaac Motochi, Patrick Hayombe, Nosipho Zwane, Eric Wamiti, Tafadzwanashe Mabhaudhi. A Review of the Water–Energy–Food Nexus Research in Africa. Sustainability. 2021; 13 (4):1762.
Chicago/Turabian StyleJoel Botai; Christina Botai; Katlego Ncongwane; Sylvester Mpandeli; Luxon Nhamo; Muthoni Masinde; Abiodun Adeola; Michael Mengistu; Henerica Tazvinga; Miriam Murambadoro; Shenelle Lottering; Isaac Motochi; Patrick Hayombe; Nosipho Zwane; Eric Wamiti; Tafadzwanashe Mabhaudhi. 2021. "A Review of the Water–Energy–Food Nexus Research in Africa." Sustainability 13, no. 4: 1762.
This study examines the (dis)similarity of two commonly used indices Standardized Precipitation Index (SPI) computed over accumulation periods 1-month, 3-month, 6-month, and 12-month (hereafter SPI-1, SPI-3, SPI-6, and SPI-12, respectively) and Effective Drought Index (EDI). The analysis is based on two drought monitoring indicators (derived from SPI and EDI), namely, the Drought Duration (DD) and Drought Severity (DS) across the 93 South African Weather Service’s delineated rainfall districts over South Africa from 1980 to 2019. In the study, the Pearson correlation coefficient dissimilarity and periodogram dissimilarity estimates were used. The results indicate a positive correlation for the Pearson correlation coefficient dissimilarity and a positive value for periodogram of dissimilarity in both the DD and DS. With the Pearson correlation coefficient dissimilarity, the study demonstrates that the values of the SPI-1/EDI pair and the SPI-3/EDI pair exhibit the highest similar values for DD, while the SPI-6/EDI pair shows the highest similar values for DS. Moreover, dissimilarities are more obvious in SPI-12/EDI pair for DD and DS. When a periodogram of dissimilarity is used, the values of the SPI-1/EDI pair and SPI-6/EDI pair exhibit the highest similar values for DD, while SPI-1/EDI displayed the highest similar values for DS. Overall, the two measures show that the highest similarity is obtained in the SPI-1/EDI pair for DS. The results obtainable in this study contribute towards an in-depth knowledge of deviation between the EDI and SPI values for South Africa, depicting that these two drought indices values are replaceable in some rainfall districts of South Africa for drought monitoring and prediction, and this is a step towards the selection of the appropriate drought indices.
Omolola M. Adisa; Muthoni Masinde; Joel O. Botai. Assessment of the Dissimilarities of EDI and SPI Measures for Drought Determination in South Africa. Water 2021, 13, 82 .
AMA StyleOmolola M. Adisa, Muthoni Masinde, Joel O. Botai. Assessment of the Dissimilarities of EDI and SPI Measures for Drought Determination in South Africa. Water. 2021; 13 (1):82.
Chicago/Turabian StyleOmolola M. Adisa; Muthoni Masinde; Joel O. Botai. 2021. "Assessment of the Dissimilarities of EDI and SPI Measures for Drought Determination in South Africa." Water 13, no. 1: 82.
This research study evaluated the projected future climate and anticipated impacts on water-linked sectors on the transboundary Limpopo River Basin (LRB) with a focus on South Africa. Streamflow was simulated from two CORDEX-Africa regional climate models (RCMs) forced by the 5th phase of the Coupled Model Inter-Comparison Project (CMIP5) Global Climate Models (GCMs), namely, the CanESM2m and IPSL-CM5A-MR climate models. Three climate projection time intervals were considered spanning from 2006 to 2099 and delineated as follows: current climatology (2006–2035), near future (2036–2065) and end of century future projection (2070–2099). Statistical metrics derived from the projected streamflow were used to assess the impacts of the changing climate on water-linked sectors. These metrics included streamflow trends, low and high flow quantile probabilities, the Standardized Streamflow Index (SSI) trends and the proportion (%) of dry and wet years, as well as drought monitoring indicators. Based on the Mann-Kendall (MK) trend test, the LRB is projected to experience reduced streamflow in both the near and the distant future. The basin is projected to experience frequent dry and wet conditions that can translate to drought and flash floods, respectively. In particular, a high proportion of dry and a few incidences of wet years are expected in the basin in the future. In general, the findings of this research study will inform and enhance climate change adaptation and mitigation policy decisions and implementation thereof, to sustain the livelihoods of vulnerable communities.
Christina M. Botai; Joel O. Botai; Nosipho N. Zwane; Patrick Hayombe; Eric K. Wamiti; Thabo Makgoale; Miriam D. Murambadoro; Abiodun M. Adeola; Katlego P. Ncongwane; Jaco P. De Wit; Michael G. Mengistu; Henerica Tazvinga. Hydroclimatic Extremes in the Limpopo River Basin, South Africa, under Changing Climate. Water 2020, 12, 3299 .
AMA StyleChristina M. Botai, Joel O. Botai, Nosipho N. Zwane, Patrick Hayombe, Eric K. Wamiti, Thabo Makgoale, Miriam D. Murambadoro, Abiodun M. Adeola, Katlego P. Ncongwane, Jaco P. De Wit, Michael G. Mengistu, Henerica Tazvinga. Hydroclimatic Extremes in the Limpopo River Basin, South Africa, under Changing Climate. Water. 2020; 12 (12):3299.
Chicago/Turabian StyleChristina M. Botai; Joel O. Botai; Nosipho N. Zwane; Patrick Hayombe; Eric K. Wamiti; Thabo Makgoale; Miriam D. Murambadoro; Abiodun M. Adeola; Katlego P. Ncongwane; Jaco P. De Wit; Michael G. Mengistu; Henerica Tazvinga. 2020. "Hydroclimatic Extremes in the Limpopo River Basin, South Africa, under Changing Climate." Water 12, no. 12: 3299.
The African continent has a long history of rainfall fluctuations of varying duration and intensities. This has led to varying degrees of drought conditions, triggering research interest across the continent. The research presented here is a bibliometric analysis of scientific articles on drought monitoring and prediction published in Africa. Scientific data analysis was carried out based on bibliometric mapping techniques applied to 332 scientific publications (1980 to 2020) retrieved from the Web of Science (WoS) and Scopus databases. In addition, time series of Standardized Precipitation Evapotranspiration Index for the previous 6 months (SPEI-6) over six regions in the continent was analysed giving the relative comparison of drought occurrences to the annual distribution of the scientific publications. The results revealed that agricultural and hydrological drought studies contributed about 75% of the total publications, while the remaining 25% was shared among socioeconomic and meteorological studies. Countries in the southern, western, and eastern regions of Africa led in terms of scientific publications during the period under review. The results further indicated that the continent experienced drought conditions in the years 1984, 1989, 1992, and 1997, thereby inducing an increase in the number of scientific publications on drought studies. The results show that the tools of analysis have also changed from simple statistics to the use of geospatial tools such as Remote Sensing (RS) and Geographical Information System (GIS) models, and recently Machine Learning (ML). The ML, particularly, contributed about 11% of the total scientific publications, while RS and GIS models, and basic statistical analysis account for about 44%, 20%, and 25% respectively. The integration of spatial technologies and ML are pivotal to the development of robust drought monitoring and drought prediction systems, especially in Africa, which is considered as a drought-prone continent. The research gaps presented in this study can help prospective researchers to respond to the continental and regional drought research needs.
Omolola Adisa; Muthoni Masinde; Joel Botai; Christina Botai. Bibliometric Analysis of Methods and Tools for Drought Monitoring and Prediction in Africa. Sustainability 2020, 12, 6516 .
AMA StyleOmolola Adisa, Muthoni Masinde, Joel Botai, Christina Botai. Bibliometric Analysis of Methods and Tools for Drought Monitoring and Prediction in Africa. Sustainability. 2020; 12 (16):6516.
Chicago/Turabian StyleOmolola Adisa; Muthoni Masinde; Joel Botai; Christina Botai. 2020. "Bibliometric Analysis of Methods and Tools for Drought Monitoring and Prediction in Africa." Sustainability 12, no. 16: 6516.
The sustainable management of natural resources requires critical understanding of land use and land cover changes and how these changes impact natural resources and rural livelihoods. This study examined the impacts of LULC changes on natural resources and rural livelihoods of Central Malawi. The study used an integrated approach combining remote sensing, household surveys consisting of structured and semi-structured questionnaires, focus group discussions and key informant interviews. Local communities perceived that LULC changes have resulted in the decline of agricultural land (57.3%), crop production (82.8%) and forest cover (87.4%) In response to observed LULC changes, respondents deployed short-term coping strategies such as seeking piecework opportunities and the use of savings and credits. The study has provided evidence that LULC changes have led to significant losses in natural resources, with serious consequences for rural livelihoods in Dedza. The study has contributed to better understanding of the complicated human-environment interaction in Malawi.
Maggie G. Munthali; Nerhene Davis; Abiodun M. Adeola; Joel O. Botai. The impacts of land use and land cover dynamics on natural resources and rural livelihoods in Dedza District, Malawi. Geocarto International 2020, 1 -18.
AMA StyleMaggie G. Munthali, Nerhene Davis, Abiodun M. Adeola, Joel O. Botai. The impacts of land use and land cover dynamics on natural resources and rural livelihoods in Dedza District, Malawi. Geocarto International. 2020; ():1-18.
Chicago/Turabian StyleMaggie G. Munthali; Nerhene Davis; Abiodun M. Adeola; Joel O. Botai. 2020. "The impacts of land use and land cover dynamics on natural resources and rural livelihoods in Dedza District, Malawi." Geocarto International , no. : 1-18.
This research study was carried out to investigate the characteristics of drought based on the joint distribution of two dependent variables, the duration and severity, in the Eastern Cape Province, South Africa. The drought variables were computed from the Standardized Precipitation Index for 6- and 12-month accumulation period (hereafter SPI-6 and SPI-12) time series calculated from the monthly rainfall data spanning the last five decades. In this context, the characteristics of climatological drought duration and severity were based on multivariate copula analysis. Five copula functions (from the Archimedean and Elliptical families) were selected and fitted to the drought duration and severity series in order to assess the dependency measure of the two variables. In addition, Joe and Gaussian copula functions were considered and fitted to the drought duration and severity to assess the joint return periods for the dual and cooperative cases. The results indicate that the dependency measure of drought duration and severity are best described by Tawn copula families. The dependence structure results suggest that the study area exhibited low probability of drought duration and high probability of drought severity. Furthermore, the multivariate return period for the dual case is found to be always longer across all the selected univariate return periods. Based on multivariate analysis, the study area (particularly Buffalo City, OR Tambo and Alfred Zoo regions) is determined to have higher/lower risks in terms of the conjunctive/cooperative multivariate drought risk (copula) probability index. The results of the present study could contribute towards policy and decision making through e.g., formulation of the forward-looking contingent plans for sustainable management of water resources and the consequent applications in the preparedness for and adaptation to the drought risks in the water-linked sectors of the economy.
Christina M. Botai; Joel O. Botai; Abiodun M. Adeola; Jaco P. De Wit; Katlego P. Ncongwane; Nosipho N. Zwane. Drought Risk Analysis in the Eastern Cape Province of South Africa: The Copula Lens. Water 2020, 12, 1938 .
AMA StyleChristina M. Botai, Joel O. Botai, Abiodun M. Adeola, Jaco P. De Wit, Katlego P. Ncongwane, Nosipho N. Zwane. Drought Risk Analysis in the Eastern Cape Province of South Africa: The Copula Lens. Water. 2020; 12 (7):1938.
Chicago/Turabian StyleChristina M. Botai; Joel O. Botai; Abiodun M. Adeola; Jaco P. De Wit; Katlego P. Ncongwane; Nosipho N. Zwane. 2020. "Drought Risk Analysis in the Eastern Cape Province of South Africa: The Copula Lens." Water 12, no. 7: 1938.
Background: Malaria, though curable, continues to be a major health and socioeconomic challenge. Malaria cases have been on the rise for the last two years in the malaria-endemic region of South Africa. Thulamela Municipality in Limpopo, South Africa, which falls within several municipalities at Vhembe district that are affected by malaria. About 33,448 malaria cases were reported over a period of 20 years (1998 January-2018 December). Objective: The study aims to determine the influence of climate on the spatiotemporal distribution of malaria cases in Thulamela Municipality for the last two decades (1998 January-2018 December). Methods: The analysis is divided into two sections, including temporal and spatial distribution of malaria cases, and the correlating climatic and environmental factors. Time series analysis is conducted to determine the variations of malaria and climate. Malaria and climatic factors (rainfall, maximum temperature, minimum temperature) were globally correlated using matrix scatterplot spearman correlation with a certain significance level. The Ordinary Least Squares (OLS) regression was performed to determine the significant climate factors that locally affect the spatial distribution of malaria cases. The local environmental factor (rivers) was analyzed using buffering and terrain analysis. Results: A positive spearman correlation of the time series was found with the significance level of 0.01. The climate variables were not strongly significant to the spatial distribution of malaria at the village level. The villages which continued to record high malaria cases were in proximity to rivers by 2km. The Thulamela municipality falls within 20-30°C, which is essential for the incubation of mosquitoes and transmission of malaria. The areas receiving about 125 to 135 mm of total monthly rainfall record high malaria cases. The temperature, rainfall, and rivers are important factors for malaria transmission. Conclusion: Knowledge of the drivers of the spatiotemporal distribution of malaria is essential for a predicting system to enhance effective malaria control in communities such as the Thulamela municipality.
Lungile Makondo; Abiodun Adeola; Thabo Makgoale; Joel Botai; Omolola Adisa; Christina Botai. Influence of Climate on the Spatiotemporal Distribution of Malaria in Thulamela Municipality, Limpopo Province, South Africa. The Open Public Health Journal 2020, 13, 246 -256.
AMA StyleLungile Makondo, Abiodun Adeola, Thabo Makgoale, Joel Botai, Omolola Adisa, Christina Botai. Influence of Climate on the Spatiotemporal Distribution of Malaria in Thulamela Municipality, Limpopo Province, South Africa. The Open Public Health Journal. 2020; 13 (1):246-256.
Chicago/Turabian StyleLungile Makondo; Abiodun Adeola; Thabo Makgoale; Joel Botai; Omolola Adisa; Christina Botai. 2020. "Influence of Climate on the Spatiotemporal Distribution of Malaria in Thulamela Municipality, Limpopo Province, South Africa." The Open Public Health Journal 13, no. 1: 246-256.
This contribution aims to investigate the influence of monthly total rainfall variations on malaria transmission in the Limpopo Province. For this purpose, monthly total rainfall was interpolated from daily rainfall data from weather stations. Annual and seasonal trends, as well as cross-correlation analyses, were performed on time series of monthly total rainfall and monthly malaria cases in five districts of Limpopo Province for the period of 1998 to 2017. The time series analysis indicated that an average of 629.5 mm of rainfall was received over the period of study. The rainfall has an annual variation of about 0.46%. Rainfall amount varied within the five districts, with the northeastern part receiving more rainfall. Spearman’s correlation analysis indicated that the total monthly rainfall with one to two months lagged effect is significant in malaria transmission across all the districts. The strongest correlation was noticed in Vhembe (r = 0.54; p-value =
Abiodun Adeola; Katlego Ncongwane; Gbenga Abiodun; Thabo Makgoale; Hannes Rautenbach; Joel Botai; Omolola Adisa; Christina Botai. Rainfall Trends and Malaria Occurrences in Limpopo Province, South Africa. International Journal of Environmental Research and Public Health 2019, 16, 5156 .
AMA StyleAbiodun Adeola, Katlego Ncongwane, Gbenga Abiodun, Thabo Makgoale, Hannes Rautenbach, Joel Botai, Omolola Adisa, Christina Botai. Rainfall Trends and Malaria Occurrences in Limpopo Province, South Africa. International Journal of Environmental Research and Public Health. 2019; 16 (24):5156.
Chicago/Turabian StyleAbiodun Adeola; Katlego Ncongwane; Gbenga Abiodun; Thabo Makgoale; Hannes Rautenbach; Joel Botai; Omolola Adisa; Christina Botai. 2019. "Rainfall Trends and Malaria Occurrences in Limpopo Province, South Africa." International Journal of Environmental Research and Public Health 16, no. 24: 5156.
This study reports on the performance results of the Baseline Surface Radiation Network (BSRN) quality control procedures applied to the solar radiation data, from September 2013 to December 2017, within the South African Weather Service radiometric network. The overall percentage performance of the SAWS solar radiation network based on BSRN quality control methodology was 97.79%, 93.64%, 91.60% and 92.23% for long wave downward irradiance (LWD), global horizontal irradiance (GHI), diffuse horizontal irradiance (DHI) and direct normal irradiance (DNI), respectively, with operational problems largely dominating the percentage of bad data. The overall average performance of the surface solar radiation dataset – Heliosat data records for the GHI estimation for all stations showed a mean bias deviation of 8.28 Wm-2, a mean absolute deviation of 9.06 Wm-2 and the root mean square deviation of 11.02 Wm-2. The correlation, quantified by the square of correlation coefficient (R2), between ground-based and Heliosat-derived GHI time series was ~0.98. The established network has the potential to provide high quality minute solar radiation data sets (GHI, DHI, DNI and LWD) and auxiliary hourly meteorological parameters vital for scientific and practical applications in renewable energy technologies.
Lucky Ntsangwane; Brighton Mabasa; Venkataraman Sivakumar; Nosipho Zwane; Katlego Ncongwane; Joel Botai. Quality control of solar radiation data within the South African Weather Service solar radiometric network. Journal of Energy in Southern Africa 2019, 30, 51 -63.
AMA StyleLucky Ntsangwane, Brighton Mabasa, Venkataraman Sivakumar, Nosipho Zwane, Katlego Ncongwane, Joel Botai. Quality control of solar radiation data within the South African Weather Service solar radiometric network. Journal of Energy in Southern Africa. 2019; 30 (4):51-63.
Chicago/Turabian StyleLucky Ntsangwane; Brighton Mabasa; Venkataraman Sivakumar; Nosipho Zwane; Katlego Ncongwane; Joel Botai. 2019. "Quality control of solar radiation data within the South African Weather Service solar radiometric network." Journal of Energy in Southern Africa 30, no. 4: 51-63.
Mary-Jane Bopape; Happy Marumo Sithole; Tshiamo Motshegwa; Edward Rakate; Francois Engelbrecht; Emma Archer; Anneline Morgan; Lwando Ndimeni; Joel Botai. A Regional Project in Support of the SADC Cyber-Infrastructure Framework Implementation: Weather and Climate. Data Science Journal 2019, 18, 1 .
AMA StyleMary-Jane Bopape, Happy Marumo Sithole, Tshiamo Motshegwa, Edward Rakate, Francois Engelbrecht, Emma Archer, Anneline Morgan, Lwando Ndimeni, Joel Botai. A Regional Project in Support of the SADC Cyber-Infrastructure Framework Implementation: Weather and Climate. Data Science Journal. 2019; 18 ():1.
Chicago/Turabian StyleMary-Jane Bopape; Happy Marumo Sithole; Tshiamo Motshegwa; Edward Rakate; Francois Engelbrecht; Emma Archer; Anneline Morgan; Lwando Ndimeni; Joel Botai. 2019. "A Regional Project in Support of the SADC Cyber-Infrastructure Framework Implementation: Weather and Climate." Data Science Journal 18, no. : 1.
Recent studies have considered the connections between malaria incidence and climate variables using mathematical and statistical models. Some of the statistical models focused on time series approach based on Box-Jenkins methodology or on dynamic model. The latter approach allows for covariates different from its original lagged values, while the Box-Jenkins does not. In real situations, malaria incidence counts may turn up with many zero terms in the time series. Fitting time series model based on the Box-Jenkins approach and ARIMA may be spurious. In this study, a zero-inflated negative binomial regression model was formulated for fitting malaria incidence in Mopani and Vhembe-two of the epidemic district municipalities in Limpopo, South Africa. In particular, a zero-inflated negative binomial regression model was formulated for daily malaria counts as a function of some climate variables, with the aim of identifying the model that best predicts reported malaria cases. Results from this study show that daily rainfall amount and the average temperature at various lags have a significant influence on malaria incidence in the study areas. The significance of zero inflation on the malaria count was examined using the Vuong test and the result shows that zero-inflated negative binomial regression model fits the data better. A dynamical climate-based model was further used to investigate the population dynamics of mosquitoes over the two regions. Findings highlight the significant roles of Anopheles arabiensis on malaria transmission over the regions and suggest that vector control activities should be intense to eradicate malaria in Mopani and Vhembe districts. Although An. arabiensis has been identified as the major vector over these regions, our findings further suggest the presence of additional vectors transmitting malaria in the study regions. The findings from this study offer insight into climate-malaria incidence linkages over Limpopo province of South Africa.
Gbenga J. Abiodun; Olusola S. Makinde; Abiodun M. Adeola; Kevin Y. Njabo; Peter J. Witbooi; Ramses Djidjou-Demasse; Joel O. Botai. A Dynamical and Zero-Inflated Negative Binomial Regression Modelling of Malaria Incidence in Limpopo Province, South Africa. International Journal of Environmental Research and Public Health 2019, 16, 2000 .
AMA StyleGbenga J. Abiodun, Olusola S. Makinde, Abiodun M. Adeola, Kevin Y. Njabo, Peter J. Witbooi, Ramses Djidjou-Demasse, Joel O. Botai. A Dynamical and Zero-Inflated Negative Binomial Regression Modelling of Malaria Incidence in Limpopo Province, South Africa. International Journal of Environmental Research and Public Health. 2019; 16 (11):2000.
Chicago/Turabian StyleGbenga J. Abiodun; Olusola S. Makinde; Abiodun M. Adeola; Kevin Y. Njabo; Peter J. Witbooi; Ramses Djidjou-Demasse; Joel O. Botai. 2019. "A Dynamical and Zero-Inflated Negative Binomial Regression Modelling of Malaria Incidence in Limpopo Province, South Africa." International Journal of Environmental Research and Public Health 16, no. 11: 2000.
There has been a conspicuous increase in malaria cases since 2016/2017 over the three malaria-endemic provinces of South Africa. This increase has been linked to climatic and environmental factors. In the absence of adequate traditional environmental/climatic data covering ideal spatial and temporal extent for a reliable warning system, remotely sensed data are useful for the investigation of the relationship with, and the prediction of, malaria cases. Monthly environmental variables such as the normalised difference vegetation index (NDVI), the enhanced vegetation index (EVI), the normalised difference water index (NDWI), the land surface temperature for night (LSTN) and day (LSTD), and rainfall were derived and evaluated using seasonal autoregressive integrated moving average (SARIMA) models with different lag periods. Predictions were made for the last 56 months of the time series and were compared to the observed malaria cases from January 2013 to August 2017. All these factors were found to be statistically significant in predicting malaria transmission at a 2-months lag period except for LSTD which impact the number of malaria cases negatively. Rainfall showed the highest association at the two-month lag time (r=0.74; P
Abiodun Morakinyo Adeola; Joel Ondego Botai; Jane Mukarugwiza Olwoch; Hannes C.J. De W. Rautenbach; Omolola Mayowa Adisa; Christiaan De Jager; Christina M. Botai; Mabuza Aaron. Predicting malaria cases using remotely sensed environmental variables in Nkomazi, South Africa. Geospatial Health 2019, 14, 1 .
AMA StyleAbiodun Morakinyo Adeola, Joel Ondego Botai, Jane Mukarugwiza Olwoch, Hannes C.J. De W. Rautenbach, Omolola Mayowa Adisa, Christiaan De Jager, Christina M. Botai, Mabuza Aaron. Predicting malaria cases using remotely sensed environmental variables in Nkomazi, South Africa. Geospatial Health. 2019; 14 (1):1.
Chicago/Turabian StyleAbiodun Morakinyo Adeola; Joel Ondego Botai; Jane Mukarugwiza Olwoch; Hannes C.J. De W. Rautenbach; Omolola Mayowa Adisa; Christiaan De Jager; Christina M. Botai; Mabuza Aaron. 2019. "Predicting malaria cases using remotely sensed environmental variables in Nkomazi, South Africa." Geospatial Health 14, no. 1: 1.
The use of crop modeling as a decision tool by farmers and other decision-makers in the agricultural sector to improve production efficiency has been on the increase. In this study, artificial neural network (ANN) models were used for predicting maize in the major maize producing provinces of South Africa. The maize production prediction and projection analysis were carried out using the following climate variables: precipitation (PRE), maximum temperature (TMX), minimum temperature (TMN), potential evapotranspiration (PET), soil moisture (SM) and land cultivated (Land) for maize. The analyzed datasets spanned from 1990 to 2017 and were divided into two segments with 80% used for model training and the remaining 20% for testing. The results indicated that PET, PRE, TMN, TMX, Land, and SM with two hidden neurons of vector (5,8) were the best combination to predict maize production in the Free State province, whereas the TMN, TMX, PET, PRE, SM and Land with vector (7,8) were the best combination for predicting maize in KwaZulu-Natal province. In addition, the TMN, SM and Land and TMN, TMX, SM and Land with vector (3,4) were the best combination for maize predicting in the North West and Mpumalanga provinces, respectively. The comparison between the actual and predicted maize production using the testing data indicated performance accuracy adjusted R2 of 0.75 for Free State, 0.67 for North West, 0.86 for Mpumalanga and 0.82 for KwaZulu-Natal. Furthermore, a decline in the projected maize production was observed across all the selected provinces (except the Free State province) from 2018 to 2019. Thus, the developed model can help to enhance the decision making process of the farmers and policymakers.
Omolola M. Adisa; Joel O. Botai; Abiodun M. Adeola; Abubeker Hassen; Christina M. Botai; Daniel Darkey; Eyob Tesfamariam. Application of Artificial Neural Network for Predicting Maize Production in South Africa. Sustainability 2019, 11, 1145 .
AMA StyleOmolola M. Adisa, Joel O. Botai, Abiodun M. Adeola, Abubeker Hassen, Christina M. Botai, Daniel Darkey, Eyob Tesfamariam. Application of Artificial Neural Network for Predicting Maize Production in South Africa. Sustainability. 2019; 11 (4):1145.
Chicago/Turabian StyleOmolola M. Adisa; Joel O. Botai; Abiodun M. Adeola; Abubeker Hassen; Christina M. Botai; Daniel Darkey; Eyob Tesfamariam. 2019. "Application of Artificial Neural Network for Predicting Maize Production in South Africa." Sustainability 11, no. 4: 1145.
The spatial-temporal variability of drought characteristics and propagation mechanisms in the hydrological cycle is a pertinent topic to policymakers and to the diverse scientific community. This study reports on the analysis of drought characteristics and propagation patterns in the hydrological cycle over South Africa. In particular, the analysis considered daily precipitation and streamflow data spanning from 1985 to 2016, recorded from 74 weather stations, distributed across South Africa and covering the country’s 19 Water Management Areas (WMAs). The results show that all the WMAs experience drought features characterized by an inherent spatial-temporal dependence structure with transition periods categorized into short (1–3 months), intermediate (4–6 months), long (7–12 months) and extended (>12 months) time-scales. Coupled with climate and catchment characteristics, the drought propagation characteristics delineate the WMAs into homogenous zones subtly akin to the broader climatic zones of South Africa, i.e., Savanna, Grassland, Karoo, Fynbos, Forest, and Desert climates. We posit that drought evolution results emanating from the current study provide a new perspective of drought characterization with practical use for the design of drought monitoring, as well as early warning systems for drought hazard preparedness and effective water resources planning and management. Overall, the analysis of drought evolution in South Africa is expected to stimulate advanced drought research topics, including the elusive drought termination typology.
Joel Ondego Botai; Christina M. Botai; Jaco P. De Wit; Masinde Muthoni; Abiodun M. Adeola. Analysis of Drought Progression Physiognomies in South Africa. Water 2019, 11, 299 .
AMA StyleJoel Ondego Botai, Christina M. Botai, Jaco P. De Wit, Masinde Muthoni, Abiodun M. Adeola. Analysis of Drought Progression Physiognomies in South Africa. Water. 2019; 11 (2):299.
Chicago/Turabian StyleJoel Ondego Botai; Christina M. Botai; Jaco P. De Wit; Masinde Muthoni; Abiodun M. Adeola. 2019. "Analysis of Drought Progression Physiognomies in South Africa." Water 11, no. 2: 299.
Research on Land Use and Land Cover (LULC) dynamics, and an understanding of the drivers responsible for these changes, are very crucial for modelling future LULC changes and the formulation of sustainable and robust land-management strategies and policy decisions. This study adopted a mixed method consisting of remote sensing and Geographic Information System (GIS)-based analysis, focus-group discussions, key informant interviews, and semi-structured interviews covering 586 households to assess LULC dynamics and associated LULC change drivers across the Dedza district, a central region of Malawi. GIS-based analysis of remotely sensed data revealed that barren land and built-up areas extensively increased at the expense of agricultural and forest land between 1991 and 2015. Analysis of the household-survey results revealed that the perceptions of respondents tended to validate the observed patterns during the remotely sensed data-analysis phase of the research, with 57.3% (n = 586) of the respondents reporting a decline in agricultural land use, and 87.4% (n = 586) observing a decline in forest areas in the district. Furthermore, firewood collection, charcoal production, population growth, and poverty were identified as the key drivers of these observed LULC changes in the study area. Undoubtedly, education has emerged as a significant factor influencing respondents’ perceptions of these drivers of LULC changes. However, unsustainable LULC changes observed in this study have negative implications on rural livelihoods and natural-resource management. Owing to the critical role that LULC dynamics play to rural livelihoods and the ecosystem, this study recommends further research to establish the consequences of these changes. The present study and future research will support decision makers and planners in the design of tenable and coherent land-management strategies.
Maggie G. Munthali; Nerhene Davis; Abiodun M. Adeola; Joel O. Botai; Jonathan M. Kamwi; Harold L. W. Chisale; Oluwagbenga O. I. Orimoogunje. Local Perception of Drivers of Land-Use and Land-Cover Change Dynamics across Dedza District, Central Malawi Region. Sustainability 2019, 11, 832 .
AMA StyleMaggie G. Munthali, Nerhene Davis, Abiodun M. Adeola, Joel O. Botai, Jonathan M. Kamwi, Harold L. W. Chisale, Oluwagbenga O. I. Orimoogunje. Local Perception of Drivers of Land-Use and Land-Cover Change Dynamics across Dedza District, Central Malawi Region. Sustainability. 2019; 11 (3):832.
Chicago/Turabian StyleMaggie G. Munthali; Nerhene Davis; Abiodun M. Adeola; Joel O. Botai; Jonathan M. Kamwi; Harold L. W. Chisale; Oluwagbenga O. I. Orimoogunje. 2019. "Local Perception of Drivers of Land-Use and Land-Cover Change Dynamics across Dedza District, Central Malawi Region." Sustainability 11, no. 3: 832.
In recent years, with the development of Digital Library and network technology, the reproduction of digital Resources of books and materials, such as the use of communication network, has become more and more popular. The copyright protection of digital library has also been paid more and more attention by the academic circle. In this paper, a robust...
Yahaya A. Aliyu; Joel O. Botai. An Exposure Appraisal of Outdoor Air Pollution on the Respiratory Well-being of a Developing City Population. Journal of Epidemiology and Global Health 2018, 8, 1 .
AMA StyleYahaya A. Aliyu, Joel O. Botai. An Exposure Appraisal of Outdoor Air Pollution on the Respiratory Well-being of a Developing City Population. Journal of Epidemiology and Global Health. 2018; 8 (1-2):1.
Chicago/Turabian StyleYahaya A. Aliyu; Joel O. Botai. 2018. "An Exposure Appraisal of Outdoor Air Pollution on the Respiratory Well-being of a Developing City Population." Journal of Epidemiology and Global Health 8, no. 1-2: 1.
The recent resurgence of malaria incidence across epidemic regions in South Africa has been linked to climatic and environmental factors. An in-depth investigation of the impact of climate variability and mosquito abundance on malaria parasite incidence may therefore offer useful insight towards the control of this life-threatening disease. In this study, we investigate the influence of climatic factors on malaria transmission over Nkomazi Municipality. The variability and interconnectedness between the variables were analyzed using wavelet coherence analysis. Time-series analyses revealed that malaria cases significantly declined after the outbreak in early 2000, but with a slight increase from 2015. Furthermore, the wavelet coherence and time-lagged correlation analyses identified rainfall and abundance of Anopheles arabiensis as the major variables responsible for malaria transmission over the study region. The analysis further highlights a high malaria intensity with the variables from 1998–2002, 2004–2006, and 2010–2013 and a noticeable periodicity value of 256–512 days. Also, malaria transmission shows a time lag between one month and three months with respect to mosquito abundance and the different climatic variables. The findings from this study offer a better understanding of the importance of climatic factors on the transmission of malaria. The study further highlights the significant roles of An. arabiensis on malaria occurrence over Nkomazi. Implementing the mosquito model to predict mosquito abundance could provide more insight into malaria elimination or control in Africa.
Gbenga J. Abiodun; Kevin Y. Njabo; Peter J. Witbooi; Abiodun M. Adeola; Trevon L. Fuller; Kazeem O. Okosun; Olusola S. Makinde; Joel O. Botai. Exploring the Influence of Daily Climate Variables on Malaria Transmission and Abundance of Anopheles arabiensis over Nkomazi Local Municipality, Mpumalanga Province, South Africa. Journal of Environmental and Public Health 2018, 2018, 1 -10.
AMA StyleGbenga J. Abiodun, Kevin Y. Njabo, Peter J. Witbooi, Abiodun M. Adeola, Trevon L. Fuller, Kazeem O. Okosun, Olusola S. Makinde, Joel O. Botai. Exploring the Influence of Daily Climate Variables on Malaria Transmission and Abundance of Anopheles arabiensis over Nkomazi Local Municipality, Mpumalanga Province, South Africa. Journal of Environmental and Public Health. 2018; 2018 ():1-10.
Chicago/Turabian StyleGbenga J. Abiodun; Kevin Y. Njabo; Peter J. Witbooi; Abiodun M. Adeola; Trevon L. Fuller; Kazeem O. Okosun; Olusola S. Makinde; Joel O. Botai. 2018. "Exploring the Influence of Daily Climate Variables on Malaria Transmission and Abundance of Anopheles arabiensis over Nkomazi Local Municipality, Mpumalanga Province, South Africa." Journal of Environmental and Public Health 2018, no. : 1-10.
In 2016, three Nigerian cities were listed amongst the World's most polluted in terms of particulate matter (PM). Acknowledging Nigeria's limited resources for outdoor air pollution monitoring, this study attempts to investigate the effects on atmospheric aerosol optical depth and ground PM on GPS derived-precipitable water vapour estimates. The study utilized available GPS-derived precipitable water vapour (GPSPWV), the moderate resolution imaging spectroradiometer aerosol optical depth (MODISAOD) and the ground level particulate matter of less than 10 μm (GPM) datasets for December 2015–November 2016. All the datasets were tested for normality. To evaluate the atmospheric aerosol properties, the MODISPWV estimates were pre-validated using the GPSPWV measurements. The results revealed GPSPWV-MODISPWV agreement (R = 0.964; RMSE = 3.810 mm). The GPSPWV-MODISAOD analysis showed relationship (R ≤ −0.636; RMSE ≤ 0.563) for the atmospheric aerosol experiment, while the collocating GPSPWV-GPM seasonal analysis also revealed significant correlation (R < −0.660). The correlation of combined seasonal datasets for the GPSPWV-MODISAOD and GPSPWV-GPM relationships showed high negative correlation values of 0.79 and 0.68 respectively. The findings of this study is in agreement with similar related studies, as well as serve as position accuracy for future related studies.
Yahaya A. Aliyu; Joel Botai. Appraising the effects of atmospheric aerosols and ground particulates concentrations on GPS-derived PWV estimates. Atmospheric Environment 2018, 193, 24 -32.
AMA StyleYahaya A. Aliyu, Joel Botai. Appraising the effects of atmospheric aerosols and ground particulates concentrations on GPS-derived PWV estimates. Atmospheric Environment. 2018; 193 ():24-32.
Chicago/Turabian StyleYahaya A. Aliyu; Joel Botai. 2018. "Appraising the effects of atmospheric aerosols and ground particulates concentrations on GPS-derived PWV estimates." Atmospheric Environment 193, no. : 24-32.