>Magister Scientiae - MSc / The Kars has a well-defined channel along the 62 km stretch from its sources in the Bredasdorp Mountains. After entering the Agulhas plain which has a very low gradient, this river changes into a triangular shaped wetland. This wetland is 7 km in length with no defined channel running through it. The wetland then discharges into another 7 km long channel that joins the Heuningnes River with its mouth at the Indian Ocean. The presence of the wetland causes frequent flooding which affects cultivated lands and a major highway linking towns on the coastal Cape Agulhas area with the rest of the country. Before this study, there was no monitoring of flows along the Kars River including water levels within the wetland. Consequently, the conditions leading to flooding of the wetlands were unknown. This study is aimed at understanding how the combination of local rainfall, Kars River inflow into the wetland, soil characteristics, and the morphology of the wetland influence flooding/inundation. The study monitored river inflows into and outflows from the wetland. A soil survey was conducted within the wetland using the augering method and an infiltrometer to determine soil type and infiltration rates. This was done to assess the hydrological characteristics of the wetland. Using the collected climate data and river flow data, a conceptual model was developed for predicting downstream outflows and possible flood events on a daily timescale. The results indicated that the Kars wetland comprises soil with high silt and clay content, and low infiltration capacity. The wetland causes flood attenuation and diffuse surface flows. Low infiltration rates result in ponding of local rainfall which can contribute to flooding.

South Africa has a few unique and understudied areas of interest regarding wetlands, of which the Maputaland Coastal Plain (MCP) is one. This is regarded as a large gap in scientific knowledge, especially since firstly, the MCP is regarded as a unique area in terms of biodiversity, geology, social history, and ecosystem variety; and secondly, wetlands are a vulnerable, and yet a greatly important ecosystem type in South Africa. Additionally the wetlands on the aeolian derived sandy soils associated with the MCP are problematic to delineate. Although the wetland delineation guideline of DWAF (2005) gives a list of criteria to aid the delineation process on sandy coastal aquifers, this has never been scientifically reviewed. The aim of this study was to investigate how vegetation and soil properties vary down the topographical slope in various wetland types on the MCP. This was done in order to contribute to the knowledge base and understanding of wetlands in this area, as well as to determine whether differences between zones are significant enough to be used as indicators of wetland boundaries. Soil colour was investigated as a possible new delineation indicator. A section is also devoted to commentary on the current wetland delineation procedure on the MCP. This study shows that wetland types on the MCP are very distinct from each other, and therefore broad statements about the soil and vegetation characteristics of wetlands are discouraged. Three substrate types namely high organic-, duplex-, and sandy substrates dominate wetlands on the MCP. These play a major influential role in the general characteristics and function of the wetland types. Contrary to popular belief, redoximorphic accumulation and -depletions do occur on the MCP, but are often inconsistent in their presence. Chemical soil properties were found not to be good indicators of wetland boundaries on the MCP, although certain patterns can be discerned and applied to determine wetland conditions. The main drivers of wetland vegetation are the wetness- and productivity gradients. A few prominent indicator species can be used for the identification of wetland and non-wetland sites specifically on the MCP. Additionally, a relatively underutilised vegetation assessment procedure called Weighted Averaging was investigated, and can in most cases effectively discern between wetland and non-wetland conditions. This is a useful tool to apply in delineation practices in addition to other indicators. Soil colour can be used to successfully indicate wetland boundaries, and therefore be used as an additional wetland indicator. However, the method requires further testing and refinement for different wetland types. In general the vegetation and soil indicators do not correlate perfectly, and therefore delineation by means of one indicator only is greatly discouraged. An investigation of recommended delineation procedures for the MCP shows that new information on the understanding of wetlands in sandy coastal aquifers urgently needs to be disseminated. Approaches such as that of the USDA-NRCS where regionally specific guidelines are designed to be adapted regularly as new information becomes available, as well as the development of sets of hydric indicators specific to problematic areas, are recommended / College of Agriculture and Environmental Sciences / D. Phil. (Environmental Science)

No description available.

No description available.

The Maputaland Coastal Plain in Kwa Zulu-Natal is covered by aeolian sands . According to the national wetland delineation manual delineating wetlands in this area is complex due to problematic wetland soils. The aim of this study was to classify and describe the vegetation of the different zones of the wetland systems to determine the main drivers of the plant communities. The understanding of these complex ecosystems could assist in wetland delineation. Twenty wetlands from five wetland systems were surveyed. The vegetation zones of each wetland were sampled and basic environmental data were collected. The results from this study indicate that different plant species assemblages are characteristic for the wetland zones. However, zone delineation using vegetation composition varies between the different wetland systems, and should be evaluated according to the system in question. The major determinants of the vegetation communities in wetlands on the MCP are the substrate type and hydrological regime / Environmental Sciences / M.Sc. (Environmental Management)

Thesis (M. En.)--Miami University, Institute of Environmental Sciences, 2006. / Title from first page of PDF document. Includes bibliographical references (p. 35 [1st set of paginations]).

The Maputaland Coastal Plain in Kwa Zulu-Natal is covered by aeolian sands . According to the national wetland delineation manual delineating wetlands in this area is complex due to problematic wetland soils. The aim of this study was to classify and describe the vegetation of the different zones of the wetland systems to determine the main drivers of the plant communities. The understanding of these complex ecosystems could assist in wetland delineation. Twenty wetlands from five wetland systems were surveyed. The vegetation zones of each wetland were sampled and basic environmental data were collected. The results from this study indicate that different plant species assemblages are characteristic for the wetland zones. However, zone delineation using vegetation composition varies between the different wetland systems, and should be evaluated according to the system in question. The major determinants of the vegetation communities in wetlands on the MCP are the substrate type and hydrological regime / Environmental Sciences / M.Sc. (Environmental Management)

No description available.

In a world under the constant impact of global warming, wetlands are decreasing in size all across the globe. As the wetlands are a vital part of preventing global warming, the ability to prevent their shrinkage through restorative measures is critical. Continuously orbiting the Earth are satellites that can be used to monitor the wetlands by collecting images of them over time. In order to determine the size of a wetland, and to register if it is shrinking or not, deep learning models can be used. Especially useful for this task is convolutional neural networks (CNNs). This project uses one type of CNN, a U-Net, to segment vegetated water in satellite data. However, this task requires labeled data, which is expensive to generate and difficult to acquire. The model used therefore needs to be able to generate reliable results even on small data sets. Therefore, pre-training of the network is used with a large-scale natural image segmentation data set called Common Objects in Context (COCO). To transfer the satellite data into RGB images to use as input for the pre-trained network, three different methods are tried. Firstly, the commonly used linear transformation method which simply moves the value of radar data into the RGB feature space. Secondly, two convolutional layers are placed before the U-Net which gradually changes the number of channels of the input data, with weights trained through backpropagation during the fine-tuning of the segmentation model. Lastly, a convolutional auto-encoder is trained in the same way as the convolutional layers. The results show that the autoencoder does not perform very well, but that the linear transformation and convolutional layers methods each can outperform the other depending on the data set. No statistical significance can be shown however between the performance of the two latter. Experimenting with including different amounts of polarizations from Sentinel-1 and bands from Sentinel-2 showed that only using radar data gave the best results. It remains to be determined whether one or both of the polarizations should be included to achieve the best result. / I en värld som ständigt påverkas av den globala uppvärmningen, minskar våtmarkerna i storlek över hela världen. Eftersom våtmarkerna är en viktig del i att förhindra global uppvärmning, är förmågan att förhindra att de krymper genom återställande åtgärder kritisk. Kontinuerligt kretsande runt jorden finns satelliter som kan användas för att övervaka våtmarkerna genom att samla in bilder av dem över tid. För att bestämma storleken på en våtmark, i syfte att registrera om den krymper eller inte, kan djupinlärningsmodeller användas. Speciellt användbar för denna uppgift är konvolutionella neurala nätverk (CNN). Detta projekt använder en typ av CNN, ett U-Net, för att segmentera vegeterat vatten i satellitdata. Denna uppgift kräver dock märkt data, vilket är dyrt att generera och svårt att få tag på. Modellen som används behöver därför kunna generera pålitliga resultat även med små datauppsättning. Därför används förträning av nätverket med en storskalig naturlig bildsegmenteringsdatauppsättning som kallas Common Objects in Context (COCO). För att överföra satellitdata till RGB-bilder som ska användas som indata för det förtränade nätverket prövas tre olika metoder. För det första, den vanliga linjära transformationsmetoden som helt enkelt flyttar värdet av radardatan till RGB-funktionsutrymmet. För det andra två konvolutionella lager placerade före U-Net:et som gradvis ändrar mängden kanaler i indatan, med vikter tränade genom bakåtpropagering under finjusteringen av segmenteringsmodellen. Slutligen tränade en konvolutionell auto encoder på samma sätt som de konvolutionella lagren. Resultaten visar att auto encodern inte fungerar särskilt bra, men att metoderna för linjär transformation och konvolutionella lager var och en kan överträffa den andra beroende på datauppsättningen. Ingen statistisk signifikans kan dock visas mellan prestationen för de två senare. Experiment med att inkludera olika mängder av polariseringar från Sentinell-1 och band från Sentinell-2 visade att endast användning av radardata gav de bästa resultaten. Om att inkludera båda polariseringarna eller bara en är den mest lämpliga återstår fortfarande att fastställa.

The study focused on the role of the local community in the management of wetland. The study was triggered by the lack of participation of the local community in the management of the wetland. It is important to note that wetlands perform a number of ecosystem services, some of which are well recognised, others less so, and are internationally recognised as being one of the most important ecosystems for the conservation of biodiversity. South Africa is a signatory to the international obligations, which makes it a legal responsibility to make sure that wetlands are managed appropriately. It is therefore important for these natural resources to be managed appropriately. Information for generating data was obtained through the assessment of the wetland health and from the investigation of the management of the local community. In order to achieve the objectives of the study, qualitative method was used to gather the necessary data. The findings indicate that the current state of the wetland is severely modified, which means large loss of natural habitat, biota and basic ecosystem functions has occurred. The results also indicate that the community is ill-equipped to manage the resource appropriately. The findings therefore imply that immediate management interventions must be developed to improve the health of the wetland. In improving the state of the wetland, the study recommends, amongst others, that mitigation measures aimed at improving the wetland health and participation of wetland users be promoted. An establishment of a community-driven and multi-stakeholder intervention mechanism to help the community manage and utilise the wetland properly is also recommended. The study concludes by indicating that the community must comply with the environmental legislation and takes a lead in the management of the wetland, for the aim of restoring the functionality and integrity of the wetland. / Environmental Sciences / M. Sc. (Environmental Management)