Societies in much of the Horn of Africa are affected by variability in two distinct rainy seasons: the March-May (MAM) “long” rains and the October-December (OND) “short” rains. The region is the driest area of the tropics, while its societies are heavily dependent on the rainfall cycle. Especially worrying are anomalously dry conditions, which, together with other factors, contribute to food insecurity in the region. The recent 2020-2023 5-season drought, associated with the concurrent “triple-dip” La Niña and resulting in tens of millions of people facing “high levels of food insecurity” (cf: IGAD), renewed fears of long-term and possibly anthropogenically-forced drying trends, especially during the MAM long rains. A long-term decline in the long rains beginning in the early 1980s and lasting until the 2010s had indeed been noted in studies examining historical station-based observations, satellite observations, and farmer recollections in the region, though seasonal average rainfall has since partially recovered. Consequently, global climate models (GCMs) are increasingly used to project changes in rainfall characteristics under global warming scenarios and associated impacts on societies, such as agricultural production, groundwater resources, and urban infrastructure, in addition to providing seasonal forecasts used for near-term decision-making. However, GCMs uniformly predict long-term wetting in both seasons despite observed drying trends in the long rains, an “East African Paradox” that complicates the ability of decisionmakers to plan for future rainfall conditions. Previous generations of GCMs have known biases in key dynamics of the regional hydroclimate. Decisionmakers relying on projections of future rainfall in the GHA therefore need to know whether current GCM projections are trustworthy. In other words, can we be confident in future modeled wetting trends in both the long and short rains? This thesis pursues this question in three parts. Chapter 2 seeks to understand the fundamental dynamics affecting the East African seasonal rainfall climatology, which is unique for its latitude in both its aridity and for the dynamical differences between its two rainy seasons. I explain these characteristics through the climatology of moist static stability, estimated as the difference between surface moist static energy h? and midtropospheric saturation moist static energy h*. In areas and at times when this difference, h? − h*, is higher, rainfall is more frequent and more intense. However, even during the rainy seasons, h? − h* < 0 on average and the atmosphere remains largely stable, in line with the region’s aridity. The seasonal cycle of h? − h*, to which the unique seasonal cycles of surface humidity, surface temperature, and midtropospheric temperature all contribute, helps explain the double-peaked nature of the regional hydroclimate. Despite tropospheric temperature being relatively uniform in the tropics, even small changes in h* can have substantial impacts on instability; for example, during the short rains, the annual minimum in regional h* lowers the threshold for convection and allows for instability despite surface humidity anomalies being relatively weak. This h? − h* framework can help identify the drivers of interannual variability in East African rainfall or diagnose the origin of biases in climate model simulations of the regional climate. Chapter 3 applies these results to conduct a process-based model evaluation of the ability of GCMs from the 6th phase of the Coupled Model Intercomparison Project (CMIP6, the latest GCM generation) to simulate the historical climatology and variability in the East African long and short rains. I find that key biases from the 5th phase of the Coupled Model Intercomparison Project (CMIP5) remain or are worsened, including long rains that are too short and weak and short rains that are too long and strong. Model biases are driven by a complex set of related oceanic and atmospheric factors, including simulations of the Walker Circulation. h? − h* is too high in models, requiring more instability for the same amount of rainfall than in observations. Biased wet short rains in models are connected with Indian Ocean zonal sea surface temperature (SST) gradients that are too warm in the west and convection that is too deep. Models connect equatorial African winds with the strength of the short rains, though in observations a robust connection is primarily found in the long rains. Model mean state biases in the timing of the western Indian Ocean SST seasonal cycle are associated with certain rainfall timing biases, though both biases may be due to a common source. Simulations driven by historical SSTs (so-called ‘AMIP’ runs) often have larger biases than fully coupled runs. However, models generally respond to teleconnections with the Indian Ocean Dipole and the El Niño Southern Oscillation in particular as expected, maintaining the possibility that trends in the long and short rains may also respond correctly to simulated trends in large-scale dynamics. Finally, Chapter 4 applies these results to directly tackle the East African Paradox by analyzing model trends across the entire observational record to identify under what conditions they fail to reproduce observed trends. Since even with perfect models and observational records model output may differ from observations due to internal variability, I analyze the full spread of CMIP6 output, including Large Ensembles and totalling 598 runs from 47 models. I find that while observed trends are always within the model spread if all runs from all Large Ensembles are considered, the Paradox remains in CMIP6 models, since GCMs substantially underproduce strong drying trends compared to observations. Within the observational record, the Paradox is limited to the time period with the most anomalous drying trends (especially in the years 1980-2010); the recent recovery in rainfall falls comfortably within the range of GCM simulations. The Paradox is not visible in AMIP runs forced with observed historical SSTs, suggesting that biases in simulations of SSTs may be part of the explanation, though clear causality remains elusive. The transition towards more biased trends from SST-forced to coupled runs can also be seen in output from hindcasts from seasonal forecast models, where trends calculated from short-lead-time projections (when the ocean state resembles observations) do not feature the Paradox, while lead times starting with 1.5 months do. More broadly, I show that climate model simulations of observed trends alone cannot be used to reject model predictions of increased (or decreased) precipitation under future forcings. Decision-makers relying on future projections of rainfall trends in East Africa will likely need to consider the possibility of further drying in addition to wetting trends from GCMs.

As the debate on the impacts of global climate change goes on at global and regional scale, climate change impacts are already being felt at local level. The thesis aims at exploring climate change as a driver of environmental and smallholder farmers’ livelihood vulnerability in Makonde District of Zimbabwe. Specifically the study seeks to: determine climate change trends and manifestations; evaluate household-level impacts of climate change and associated environmental changes on smallholder farmers’ livelihoods and lastly; to investigate the extent of household-level coping and adaptation strategies to climate change in the Makonde rural community in Zimbabwe, especially farmers in Makonde Communal Lands. Given the fact that the subject under study is multidimensional in scope, a mix of research methods was adopted in this case study. Whilst it is largely qualitative in design, the study involved some quantitative data and thus, a triangulation of different data sources and data gathering instruments was employed. The instruments used include; key informant interviews, structured observations and a household questionnaire survey. The analysis was based on a final sample of 434 out of the originally anticipated 500 households. In addition to the households’ sample, were twenty key informants and transect walk observations. The qualitative data was analyzed by means of coding, memoing, descriptions, typologies, taxonomies and visual representations, whilst quantitative data was processed through the Statistical Package for Social Sciences (SPSS) and complimented by Microsoft Excel to generate various forms of descriptive statistics. The findings suggest that climate change in the Makonde Rural District that includes the Makonde Communal Lands has been significant during the past thirty years. The climate change has contributed to significant local environmental stresses affecting local resources such as forests, fauna, water, pastures and soil among other natural assets. The local livelihoods show high levels of vulnerability to climate change due to notable low adaptive capacity. The high level of vulnerability to changing climate is exposing the study population to increased prevalence of: poverty, crop and livestock failures, food insecurity, malnutrition, disease and rural urban migration among other impacts. The study concludes that the factors creating barriers to climate change adaptation are related those contributing to poverty and holding back sustainable local development. Among the key suggestions to enhance the community’s climate change adaptation capacity, the thesis presents an establishment of a government-driven, multi-dimensional and multi-stakeholder intervention mechanism to help local communities manage their vulnerability. / Environmental Sciences / D. Litt. et Phil. (Environmental Management)

As the debate on the impacts of global climate change goes on at global and regional scale, climate change impacts are already being felt at local level. The thesis aims at exploring climate change as a driver of environmental and smallholder farmers’ livelihood vulnerability in Makonde District of Zimbabwe. Specifically the study seeks to: determine climate change trends and manifestations; evaluate household-level impacts of climate change and associated environmental changes on smallholder farmers’ livelihoods and lastly; to investigate the extent of household-level coping and adaptation strategies to climate change in the Makonde rural community in Zimbabwe, especially farmers in Makonde Communal Lands. Given the fact that the subject under study is multidimensional in scope, a mix of research methods was adopted in this case study. Whilst it is largely qualitative in design, the study involved some quantitative data and thus, a triangulation of different data sources and data gathering instruments was employed. The instruments used include; key informant interviews, structured observations and a household questionnaire survey. The analysis was based on a final sample of 434 out of the originally anticipated 500 households. In addition to the households’ sample, were twenty key informants and transect walk observations. The qualitative data was analyzed by means of coding, memoing, descriptions, typologies, taxonomies and visual representations, whilst quantitative data was processed through the Statistical Package for Social Sciences (SPSS) and complimented by Microsoft Excel to generate various forms of descriptive statistics. The findings suggest that climate change in the Makonde Rural District that includes the Makonde Communal Lands has been significant during the past thirty years. The climate change has contributed to significant local environmental stresses affecting local resources such as forests, fauna, water, pastures and soil among other natural assets. The local livelihoods show high levels of vulnerability to climate change due to notable low adaptive capacity. The high level of vulnerability to changing climate is exposing the study population to increased prevalence of: poverty, crop and livestock failures, food insecurity, malnutrition, disease and rural urban migration among other impacts. The study concludes that the factors creating barriers to climate change adaptation are related those contributing to poverty and holding back sustainable local development. Among the key suggestions to enhance the community’s climate change adaptation capacity, the thesis presents an establishment of a government-driven, multi-dimensional and multi-stakeholder intervention mechanism to help local communities manage their vulnerability. / Environmental Sciences / D. Litt. et Phil. (Environmental Management)

Thesis (M. Sc. Agriculture (Agricultural Economics)) -- University of Limpopo, 2020 / Food security is a broad concept especially as far as rural food security in countries is concerned. In essence, it is a phenomenon with the goal of ensuring that all individuals have at all times, an adequate level of food and which they will be able to utilize to meet their increasing consumption demand. Studies have shown that like other countries, South Africa is food secure at the national level but very food insecure at the household level. It is also shown that food insecurity is not fuelled by a lack of food but a lack of food insecurity tackling strategies. The aim of the study is to examine the determinants of food security among rural households in Magong, North West Province, South Africa where the main prevalent economic activity is farming supported with other formal and informal types of employment. A multi-stage sampling technique was used to select the respondents that were interviewed. The first stage involved selecting districts and the second stage was the selection of municipalities. Farm and non-farming households were selected. Structured questionnaire were administered to 108 households. The third stage involved a selection Magong village using purposive sampling based on high concentration of both farming and non-farming activities were selected, which in our case is Magong. The fourth stage involved the selection of respondents based on simple random sampling proportionate to size. The study employed logit model for as data analysis. Of the variables modelled, only income and land size had a significant influence on food security. As far as age is concerned, it was evident that the youth participation in agriculture lacks. This is because most young people are still after white collar jobs. Some were still in the academic world awaiting their certificates which they hope to use a ticket to their first job. The participation in agriculture increases steadily between ages 31 and 50 which could be because the persons in this age brackets were looking for ways to store their wealth as they approach their retirement age. Some of the respondents have inherited the farms from family members and are therefore “forced” to keep the family business running for the sake of sustainability. With regards to the marital status, there is a high number of single/ never married respondents compared to the other groups. This could be people co-habiting and choosing not to marry as a result of the economic conditions making marriage costs unaffordable. Divorce was at its lowest amongst the respondents.v In terms of the gender of the respondents, there was a high participation of women in agriculture. This may be a result of women-based agricultural programmes implemented in the past in the study area. All the variables had a positive relationship with food security. Age had a positive effect of food security, with a positive parameter (β=0.013) which indicated that contrary to what other researchers found, an increase in age when all other factors are held constant, resulted in an increase in food security. The marital status of the household head also positively affected food security. This indicated that compared to their unmarried counterparts, married household heads were food secure (β=0.049). The findings also indicated that married couples and people living with partner had a higher chance of being food secure than those who were single, divorced or widowed. According to the results, male headship of households increases food security by 0.398. It was found that the larger the household size, the more food secure it is. This may be because as the number of members in the household increase, they find more ways of making money and combating food insecurity. A unit increase in household size increases food security by .093 while an increase in land size, increases food security by 0.394. This is expected because as the land size increases, there are chances that the productivity will also increase. From the results of the survey household income had a positive effect on food security. Income is very important as it determines the household’s affordability and its ability to meet its needs

Thesis (M.Sc. (Geography)) --University of Limpopo, 2018 / Soil erosion, which is a critical component of land degradation, is one of the serious global environmental problems often threatening food security, water resources, and biodiversity. A comprehensive assessment and analysis of remote sensing applications in the spatial soil erosion mapping and monitoring over time and space is therefore, important for providing effective management and rehabilitation approaches at local, national and regional scales. The overall aim of the study was to assess the use of multispectral remote sensing sensors in mapping and monitoring the spatio-temporal variations in levels of soil erosion in the former homelands of Sekhukhune district, South Africa. Firstly, the effectiveness of the new and freely available moderate-resolution multispectral remote sensing data (Landsat 8 Operation Land Imager: OLI and Sentinel-2 Multi-Spectral Instrument: MSI) derived spectral bands, vegetation indices, and a combination of spectral bands and vegetation indices in mapping the spatio-temporal variation of soil erosion in the former homelands of Sekhukhune District, South Africa is compared. The study further determines the most optimal individual sensor variables that can accurately map soil erosion. The results showed that the integration of spectral bands and spectral vegetation indices yielded high soil erosion overall classification accuracies for both sensors. Sentinel-2 data produced an OA of 83, 81% whereas Landsat 8 has an OA of 82.86%. The study further established that Sentinel-2 MSI bands located in the NIR (0.785-0.900 μm), red edge (0.698-0.785μm) and SWIR (1.565-2.280 μm) regions were the most optimal for discriminating degraded soils from other land cover types. For Landsat 8 OLI, only the SWIR (1.560-2.300 μm), NIR (0.845-0.885 μm) region were selected as the best regions. Of the eighteen spectral vegetation indices computed, Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) and Global Environmental Monitoring Index (GEMI) were selected as the most suitable for detecting and mapping soil erosion. Secondly, the study assessed soil erosion in the former homelands of Sekhukhune, South Africa by applying a time-series analysis (2002 and 2017), to track changes of areas affected by varying degrees of erosion. Specifically, the study assessed and mapped changes of eroded areas (wet and dry season), using multi-date Landsat products 8 OLI and 7 Enhanced Thematic Mapper (ETM+)). Additionally, the study used extracted eroded areas and overlay analysis was performed together with geology, slope and the Topographic Wetness Index (TWI) of the area under study to assess whether and to what extent the observed erosional trends can be explained. ii Time series analysis indicated that the dry season of 2002, experienced 16.61 % (224733 ha) of erosion whereas in 2017 19.71% was observed. A similar trend was also observed in the wet season. This work also indicates that the dominant geology type Lebowa granite: and Rustenburg layered its lithology strata experienced more erosional disturbances than other geological types. Slopes between 2-5% (Nearly level) experienced more erosion and vice-versa. On the hand, the relationship between TWI and eroded areas showed that much erosion occurred between 3 and 6 TWI values in all the seasons for the two different years, however, the dry season of 2002 had a slightly higher relationship and vice-versa. We, therefore, recommend use and integration of freely and readily available new and free generation broadband sensors, such as Landsat data and environmental variables if soil erosion has to be well documented for purposes of effective soil rehabilitation and conservation. Keywords: Food security Global changes, Land degradation, Land-based ecosystems, Land management practices, Satellite data, Soil conservation, Sustainable Development; Topographic Wetness Index; Time series analysis.