A Statistical Analysis of Wind Distribution and Wind Power Potential in the Coastal Region of South Africa

Background: COVID-19 cases have been reported as a global threat and several studies are being conducted using various modelling techniques to evaluate patterns of disease dispersion in the upcoming weeks. Here we propose a simple statistical model that could be used to predict the epidemiological extent of community spread of COVID-19from the explicit data based on optimal ARIMA model estimators. Methods: Raw data was retrieved on confirmed cases of COVID-19 from Johns Hopkins University (https://github.com/CSSEGISandData/COVID-19) and Auto-Regressive Integrated Moving Average (ARIMA) model was fitted based on cumulative daily figures of confirmed cases aggregated globally for ten major countries to predict their incidence trend. Statistical analysis was completed by using R 3.5.3 software. Results: The optimal ARIMA model having the lowest Akaike information criterion (AIC) value for US (0,2,0); Spain (1,2,0); France (0,2,1); Germany (3,2,2); Iran (1,2,1); China (0,2,1); Russia (3,2,1); India (2,2,2); Australia (1,2,0) and South Africa (0,2,2) imparted the nowcasting of trends for the upcoming weeks. These parameters are (p, d, q) where p refers to number of autoregressive terms, d refers to number of times the series has to be differenced before it becomes stationary, and q refers to number of moving average terms. Results obtained from ARIMA model showed significant decrease cases in Australia; stable case for China and rising cases has been observed in other countries. Conclusion: This study tried their best at predicting the possible proliferate of COVID-19, although spreading significantly depends upon the various control and measurement policy taken by each country.

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A STATISTICAL ANALYSIS OF THE DEMAND FOR MAIZE IN SOUTH AFRICA

Agrekon ◽

10.1080/03031853.1986.9524080 ◽

1986 ◽

Vol 25 (3) ◽

pp. 45-51 ◽

Cited By ~ 13

Author(s):

J. VAN ZYL

Keyword(s):

South Africa ◽

Statistical Analysis

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Statistical Analysis of Ethiopian Wind Power Potential at Selected Sites

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering - Advances of Science and Technology ◽

10.1007/978-3-030-80618-7_25 ◽

2021 ◽

pp. 370-381

Author(s):

Abdulbasit Mohammed ◽

Hirpa G. Lemu ◽

Belete Sirahbizu

Keyword(s):

Statistical Analysis ◽

Wind Power

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Impact of sea-level fluctuations on the sedimentation patterns of the SE African margin: implications for slope instability

Geological Society London Special Publications ◽

10.1144/sp500-2019-172 ◽

2019 ◽

Vol 500 (1) ◽

pp. 267-276 ◽

Cited By ~ 2

Author(s):

Aaron Micallef ◽

Aggeliki Georgiopoulou ◽

Andrew Green ◽

Vittorio Maselli

Keyword(s):

South Africa ◽

Sea Level ◽

Coastal Region ◽

Passive Margin ◽

Slope Instability ◽

Bottom Current ◽

The South ◽

Sea Level Fluctuations ◽

International Ocean Discovery Program ◽

Seismic Reflection Profiles

AbstractThe sheared-passive margin offshore Durban (South Africa) is characterized by a narrow continental shelf and steep slope hosting numerous submarine canyons. Supply of sediment to the margin is predominantly terrigenous, dominated by discharge from several short but fast-flowing rivers. International Ocean Discovery Program Expedition 361 provides a unique opportunity to investigate the role of sea-level fluctuations on the sedimentation patterns and slope instability along the South African margin. We analysed >300 sediment samples and downcore variations in P-wave, magnetic susceptibility, bioturbation intensity and bulk density from site U1474, as well as regional seismic reflection profiles to: (1) document an increase in sand input since the Mid-Pliocene; (2) associate this change to a drop in sea-level and extension of subaerial drainage systems towards the shelf-edge; (3) demonstrate that slope instability has played a key role in the evolution of the South Africa margin facing the Natal Valley. Furthermore, we highlight how the widespread occurrence of failure events reflects the tectonic control on the morphology of the shelf and slope, as well as bottom-current scour and instability of fan complexes. This information is important to improve hazard assessment in a populated coastal region with growing offshore hydrocarbon activities.

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An Assessment of Wind Energy Potential for the Three Topographic Regions of Eritrea

Energies ◽

10.3390/en13071846 ◽

2020 ◽

Vol 13 (7) ◽

pp. 1846 ◽

Cited By ~ 2

Author(s):

Teklebrhan Negash ◽

Erik Möllerström ◽

Fredric Ottermo

Keyword(s):

Wind Speed ◽

Wind Energy ◽

Wind Power ◽

Power Density ◽

Coastal Region ◽

Energy Potential ◽

Wind Power Density ◽

Prevailing Wind Direction ◽

Central Highland ◽

Wind Energy Potential

This paper presents the wind energy potential and wind characteristics for 25 wind sites in Eritrea, based on wind data from the years 2000–2005. The studied sites are distributed all over Eritrea, but can roughly be divided into three regions: coastal region, western lowlands, and central highlands. The coastal region sites have the highest potential for wind power. An uncertainty, due to extrapolating the wind speed from the 10-m measurements, should be noted. The year to year variations are typically small and, for the sites deemed as suitable for wind power, the seasonal variations are most prominent in the coastal region with a peak during the period November–March. Moreover, Weibull parameters, prevailing wind direction, and wind power density recalculated for 100 m above ground are presented for all 25 sites. Comparing the results to values from the web-based, large-scale dataset, the Global Wind Atlas (GWA), both mean wind speed and wind power density are typically higher for the measurements. The difference is especially large for the more complex-terrain central highland sites where GWA results are also likely to be more uncertain. The result of this study can be used to make preliminary assessments on possible power production potential at the given sites.

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