Joel Botai

Detecting changes in surface water area of Lake Kyoga sub-basin using remotely sensed imagery in a changing climate

Detection of changes in Earth surface features, for example lakes, is important for understanding the relationships between human and natural phenomena in order to manage better the increasingly scarce natural resources. This work presents a procedure of using modified normalised difference water index (MNDWI) to detect fluctuations of lake surface water area and relate it to a changing climate. The study used radiometrically and geometrically rectified Landsat images for 1986, 1995 and 2010 encompassing the Kyoga Basin lakes of Uganda, in order to investigate the changes in surface water area between the respective years. The standard precipitation index (SPI) and drought severity index (DSI) are applied to show the relationship between variability of surface water area and climate parameters. The present analysis reveals that surface water area fluctuation is linked to rainfall variability. In particular, Lake Kyoga sub-basin lakes experienced an increase in surface water area in 2010 compared to 1986. This work has important implications to water resources management for Lake Kyoga and could be vital to water resource managers across Ugandan lakes.

Simulation of biomass burning aerosols mass distributions and their direct and semi-direct effects over South Africa using a regional climate model

In this study, we examine the mass distributions, direct and semi-direct effects of different biomass burning aerosols (BBAs) over South Africa using the 12-year runs of the Regional Climate Model (RegCM4). The results were analyzed and presented for the main BB season (July–October). The results show that Mpumalanga, KwaZulu Natal and the eastern parts of Limpopo are the main local source areas of BBAs in South Africa. In comparison to carbonaceous aerosols, BB-induced sulfate aerosol mass loading and climatic effects were found to be negligible. All carbonaceous aerosols reduce solar radiation at the surface by enhancing local atmospheric radiative heating. The climatic feedback caused by BBAs, resulted in changes in background aerosol concentrations. Thus, on a regional scale, climatic effects of BBAs were also found in areas far away from the BBA loading zones. The feedback mechanisms of the climate system to the aerosol radiative effects resulted in both positive and negative changes to the low-level columnar averaged net atmospheric radiative heating rate (NAHR). Areas that experienced an NAHR reduction showed an increase in cloud cover (CC). During the NAHR enhancement, CC over arid areas decreased; whereas CC over the wet/semi-wet regions increased. The changes in surface temperature (ST) and surface sensible heat flux are more closely correlated with BBA semi-direct effects induced CC alteration than their direct radiative forcing. Furthermore, decreases (or increases) in ST, respectively, lead to the reductions (and enhancements) in boundary layer height and the vice versa on surface pressure. The direct and semi-direct effects of BBAs also jointly promoted a reduction and rise in surface wind speed that was spatially highly variable. Overall, the results suggest that the CC change induced by the presence of radiatively interactive BBAs is important to determine alterations in other climatic variables.

Landsat satellite derived environmental metric for mapping mosquitoes breeding habitats in the Nkomazi municipality, Mpumalanga Province, South Africa

Abstract The advancement, availability and high level of accuracy of satellite data provide a unique opportunity to conduct environmental and epidemiological studies using remotely sensed measurements. In this study, information derived from remote sensing data is used to determine breeding habitats for Anopheles arabiensis which is the prevalent mosquito species over Nkomazi municipality. In particular, we have utilized the normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) coupled with land surface temperature (LST) derived from Landsat 5 TM satellite data. NDVI, NDWI and LST are considered as key environmental factors that influence the mosquito habitation. The breeding habitat was derived using multi-criteria evaluation (MCE) within ArcGIS using the derived environmental metric with appropriate weight assigned to them. Additionally, notified malaria cases were analysed and spatial data layers of water bodies, including rivers and dams, were buffered to further illustrate areas at risk of malaria. The output map from the MCE was then classified into three classes which are low, medium and high areas. The resulting malaria risk map depicts that areas of Komatieport, Malelane, Madadeni and Tonga of the district are subjected to high malaria incidence. The time series analysis of environmental metrics and malaria cases can help to provide an adequate mechanism for monitoring, control and early warning for malaria incidence.

The potential for observing African weather with GNSS remote sensing

When compared to the wide range of atmospheric sensing techniques, global navigation satellite system (GNSS) offers the advantage of operating under all weather conditions, is continuous, with high temporal and spatial resolution and high accuracy, and has long-term stability. The utilisation of GNSS ground networks of continuous stations for operational weather and climate services is already in place in many nations in Europe, Asia, and America under different initiatives and organisations. In Africa, the situation appears to be different. The focus of this paper is to assess the conditions of the existing and anticipated GNSS reference network in the African region for meteorological applications. The technical issues related to the implementation of near-real-time (NRT) GNSS meteorology are also discussed, including the data and network requirements for meteorological and climate applications. We conclude from this study that the African GNSS network is sparse in the north and central regions of the continent, with a dense network in the south and fairly dense network in the west and east regions of the continent. Most stations lack collocated meteorological sensors and other geodetic observing systems as called for by the GCOS Reference Upper Air Network (GRUAN) GNSS Precipitable Water Task Team and the World Meteorological Organization (WMO). Preliminary results of calculated zenith tropospheric delay (ZTD) from the African GNSS indicate spatial variability and diurnal dependence of ZTD. To improve the density and geometry of the existing network, countries are urged to contribute more stations to the African Geodetic Reference Frame (AFREF) program and a collaborative scheme between different organisations maintaining different GNSS stations on the continent is recommended. The benefit of using spaced based GNSS radio occultation (RO) data for atmospheric sounding is highlighted and filling of geographical gaps from the station-based observation network with GNSS RO is also proposed.

Climatic Variables and Malaria Morbidity in Mutale Local Municipality, South Africa: A 19-Year Data Analysis

The north-eastern parts of South Africa, comprising the Limpopo Province, have recorded a sudden rise in the rate of malaria morbidity and mortality in the 2017 malaria season. The epidemiological profiles of malaria, as well as other vector-borne diseases, are strongly associated with climate and environmental conditions. A retrospective understanding of the relationship between climate and the occurrence of malaria may provide insight into the dynamics of the disease’s transmission and its persistence in the north-eastern region. In this paper, the association between climatic variables and the occurrence of malaria was studied in the Mutale local municipality in South Africa over a period of 19-year. Time series analysis was conducted on monthly climatic variables and monthly malaria cases in the Mutale municipality for the period of 1998–2017. Spearman correlation analysis was performed and the Seasonal Autoregressive Integrated Moving Average (SARIMA) model was developed. Microsoft Excel was used for data cleaning, and statistical software R was used to analyse the data and develop the model. Results show that both climatic variables’ and malaria cases’ time series exhibited seasonal patterns, showing a number of peaks and fluctuations. Spearman correlation analysis indicated that monthly total rainfall, mean minimum temperature, mean maximum temperature, mean average temperature, and mean relative humidity were significantly and positively correlated with monthly malaria cases in the study area. Regression analysis showed that monthly total rainfall and monthly mean minimum temperature (R2 = 0.65), at a two-month lagged effect, are the most significant climatic predictors of malaria transmission in Mutale local municipality. A SARIMA (2,1,2) (1,1,1) model fitted with only malaria cases has a prediction performance of about 51%, and the SARIMAX (2,1,2) (1,1,1) model with climatic variables as exogenous factors has a prediction performance of about 72% in malaria cases. The model gives a close comparison between the predicted and observed number of malaria cases, hence indicating that the model provides an acceptable fit to predict the number of malaria cases in the municipality. To sum up, the association between the climatic variables and malaria cases provides clues to better understand the dynamics of malaria transmission. The lagged effect detected in this study can help in adequate planning for malaria intervention.

Application of geographical information system and remote sensing in malaria research and control in South Africa: a review

This paper presents a review of numerous items of published literature on the use of spatial technology for malaria epidemiology in South Africa between 1930 and 2013. In particular, focus is on the use of statistical and mathematical models as well as geographic information science (GIS) and remote sensing (RS) technology for malaria research. First, the review takes cognisance of the use of predictive models to determine the association between climatic factors and malaria epidemics only in KwaZulu-Natal province. Similar studies in other endemic regions such as Limpopo and Mpumalanga provinces have not been reported in the literature. While the integration of GIS with remote sensing has the potential of identifying, characterising, and monitoring breeding habitats and mapping malaria risk areas in South Africa, studies on the application of spatial technology in malaria research and control in South Africa are inexhaustive and have not been reported in the literature. As a result, a critical robust mal...

Evaluation of spatial and temporal characteristics of GNSS-derived ZTD estimates in Nigeria

This study presents an in-depth analysis to comprehend the spatial and temporal variability of zenith tropospheric delay (ZTD) over Nigeria during the period 2010–2014, using estimates from Global Navigation Satellite Systems (GNSS) data. GNSS data address the drawbacks in traditional techniques (e.g. radiosondes) by means of observing periodicities in ZTD. The ZTD estimates show weak spatial dependence among the stations, though this can be attributed to the density of stations in the network. Tidal oscillations are noticed at the GNSS stations. These oscillations have diurnal and semi-diurnal components. The diurnal components as seen from the ZTD are the principal source of the oscillations. This upshot may perhaps be ascribed to temporal variations in atmospheric water vapour on a diurnal scale. In addition, the diurnal ZTD cycles exhibited noteworthy seasonal dependence, with larger amplitudes in the rainy (wet) season and smaller ones in the harmattan (dry) season. Notably, the stations in the northern part of the country reach very high amplitudes in the months of June, July and August at the peak of the wet season, characterized by very high rainfall. This pinpoints the fact that in view of the small amount of atmospheric water vapour in the atmosphere, usually around 10%, its variations greatly influence the corresponding diurnal and seasonal discrepancies of ZTD. This study further affirms the prospective relevance of ground-based GNSS data to atmospheric studies. GNSS data analysis is therefore recommended as a tool for future exploration of Nigerian weather and climate.

Exploring the Influence of Daily Climate Variables on Malaria Transmission and Abundance of Anopheles arabiensis over Nkomazi Local Municipality, Mpumalanga Province, South Africa

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.

Bayesian modelling of extreme wind speed at Cape Town, South Africa

In the framework of generalized extreme value (GEV) distribution, the frequentist and Bayesian methods have been used to analyse the extremes of annual maxima wind speed recorded by automatic weather stations in Cape Town, Western Cape, South Africa. In the frequentist approach, the GEV distribution parameters were estimated using maximum likelihood, whereas in the Bayesian method the Markov Chain Monte Carlo technique with the Metropolis–Hastings algorithm was used. The results show that the GEV model with trend in the location parameter appears to be a better model for annual maxima data. The paper also discusses a method to construct informative priors empirically using historical data of the underlying process from other weather stations. The results from the Bayesian analysis show that posterior inference might be affected by the choice of priors and hence by the distance between a weather station used to formulate the priors and the point of interest.

A Spatial Analysis of Global Navigation Satellite System Stations Within the Context of the African Geodetic Reference Frame

Permanent Global Navigation Satellite Systems (GNSS) stations that are operating within the African Geodetic Reference Frame (AFREF) are contributing data to the datum realizations at global, regional and local levels. The infrastructure supports development and administrative functions of African governments, the public and investors throughout the African continent. However, African stations with high quality and continuous data that have been acquired over several decades are limited, which result in a non-uniform network. This means that additional station investment are required in Africa for new stations to contribute to the AFREF project. An assessment of the spatial distribution and densification of GNSS stations that contribute to AFREF ensure future geometrical improvements in the network have the most impact. Established GNSS stations within AFREF network contribute data for the realization of the International Terrestrial Reference Frame (ITRF), International GNSS Service (IGS) products and local AFREF solutions.