Process domains categorizes sections of streams according to its local dominant processes. These processes often reflect on the local ecology and the streams appearance. But the underlying reason why these different process domains are formed are still not completely certain. In this study the distribution of the process domains: lakes, rapids and slow-flowing reaches in the Bjur River catchment were compared to the geological factors of slope, surficial geology and landforms to see if any connections could be found. The possibility of using GIS (geographic information systems) and remote data to distinguish these stream types and to connect them to the different studied geological factors were also examined. The hypothesis for this study is that the geological factors of slope, surficial geology and landforms all should have an influence over the distribution of the process domains in Bjur River. The analysis was executed through map-studies in ArcGIS and statistical analysis in Excel. All process domains showed statistical significance towards the studied geological factors. The slope was generally steeper in the rapids than in slow-flowing reaches and lakes. The surficial geology displayed more fine-grained sediment (peat) in proximity to lakes and slow-flowing reaches whilst till was more abundant close to rapids. Hilly moraine landscapes were most common around lakes, while rapids displayed a high percentage of glacio-fluvially eroded area. Slow-flowing reaches also showed to have around 44% of its studied points around glacio-fluvially eroded area, and 43% at areas without any major landforms. Even if the statistical analysis and figures display a difference between the different process domains, it is still difficult to say which of these geological factors that plays the most crucial role for their development. However, by using remote data and through studies over slope, adjacent surficial geology and landforms the different process domains can be differentiated from one another.

An accurate fine resolution classification of river systems positively impacts the process of assessment and monitoring of water courses, as stressed by the European Commission’s Water Framework Directive. Being able to attribute classes using remotely obtained data can be advantageous to perform extensive classification of reaches without the use of field work, with some methods also allowing to identify which features best described each of the process domains. In this work, the data from two Swedish sub-catchments above the highest coastline was used to train a Random Forest Classifier, a Machine Learning algorithm. The obtained model provided predictions of classifications and analyses of the most important features. Each study area was studied separately, then combined. In the combined case, the analysis was made with and without lakes in the data, to verify how it would affect the predictions. The results showed that the accuracy of the estimator was reliable, however, due to data complexity and imbalance, rapids were harder to be classify accurately, with an overprediction of the slow-flowing class. Combining the datasets and having the presence of lakes lessened the shortcomings of the data imbalance. Using the feature importance and permutation importance methods, the three most important features identified were the channel slope, the median of the roughness in the 100-m buffer, and the standard deviation of the planform curvature in the 100-m buffer. This finding was supported by previous studies, but other variables expected to have a high participation such as lithology and valley confinement were not relevant, which most likely relates to the coarseness of the available data. The most frequent errors were also placed in maps, showing there was some overlap of error hotspots and areas previously restored in 2010.

The flood of 2000 caused extensive changes within the riparian landscape of the Sabie River, Kruger National Park (KNP). Changes within the riparian landscape and the removal of vegetation resulted in considerable changes in riparian vegetation characteristics. Open patches created by the flood served as a template for the establishment of new species and the regeneration of existing species, which consequently resulted in a patch mosaic. This memorable event encouraged an investigation into the response of the Sabie River ecosystem to the memorable Large Infrequent Disturbance (LID). Riparian ecosystems are driven by varying combinations of environmental factors, such as water availability, disturbance, herbivory, fire and river morphology. This complexity depicts unique vegetation structure and assemblages of associated plant species. The lack of sufficient knowledge on the role of riparian vegetation in the health assessment of surrounding ecosystems along semi-arid rivers prompted the establishment of the Kruger Rivers Post Flood Research Program (KRPFRP). Research conducted through this monitoring program four years after the 2000 flood, revealed no significant changes in the species composition, although the location and density of many common riparian species have been changed. There was a decrease in species density across the macro channel floor (MCF) and an increase in species density across the macro channel bank (MCB). Furthermore, it was reported that the flood altered the distribution of height classes across the macro channel. In general the riparian vegetation was shorter and bushier four years post-flood. These studies furthermore illustrated that the tree to shrub ratio did not change drastically from pre-flood conditions, although a decrease in the number of shrub individuals was reported. The research presented in this dissertation was designed to further explore changes in woody species composition and structure along the Sabie River, KNP at a post flood temporal interval, i.e. between the last survey in 2004 (by the KRPFRP) and 2010. For data compatibility, the sampling and analytical approach of this study conforms to the approach followed by the KRPFRP. Data were sampled within four preselected belt-transects that form part of the larger KRPFRP. All established woody individuals were counted and measured within each contiguous 10 m x 30 m plot within each of the four belt-transects. Log transformed species composition data were analysed through the application of the Bray Curtis dissimilarity index in combination with Ward’s method of clustering. Statistical significant differences between clusters were tested through the application of the Fisher’s exact relationship test. The MIXED Procedure or PROC MIXED model was used to investigate change within the vegetation structural data. Results obtained through the various analytical methods broadly support the findings of the KRPFRP. No significant change in woody species composition could be detected between 2004 and 2010. However, a change in the density (increase and decrease) of certain species across the MCB and MCF was revealed. Species richness and density increased significantly on the MCF oppose to small changes on the MCB. A significant increase in the total number of shrubs on the MCF contributed to an overall increase in woody density for the entire study area between 2004 and 2010. Shrubs therefore remained the most dominant growth form in both sampling years. Trees decreased across the MCB although the total number of established trees remained unchanged between 2004 and 2010. Riparian vegetation structure is directly linked to species assemblages, hence the continued dominance of shrub species along the Sabie River in the KNP The Sabie River riparian landscape is therefore still characterised by short and multi-stemmed woody individuals ten years after the LID. / Thesis (MSc (Environmental Sciences))--North-West University, Potchefstroom Campus, 2013

The flood of 2000 caused extensive changes within the riparian landscape of the Sabie River, Kruger National Park (KNP). Changes within the riparian landscape and the removal of vegetation resulted in considerable changes in riparian vegetation characteristics. Open patches created by the flood served as a template for the establishment of new species and the regeneration of existing species, which consequently resulted in a patch mosaic. This memorable event encouraged an investigation into the response of the Sabie River ecosystem to the memorable Large Infrequent Disturbance (LID). Riparian ecosystems are driven by varying combinations of environmental factors, such as water availability, disturbance, herbivory, fire and river morphology. This complexity depicts unique vegetation structure and assemblages of associated plant species. The lack of sufficient knowledge on the role of riparian vegetation in the health assessment of surrounding ecosystems along semi-arid rivers prompted the establishment of the Kruger Rivers Post Flood Research Program (KRPFRP). Research conducted through this monitoring program four years after the 2000 flood, revealed no significant changes in the species composition, although the location and density of many common riparian species have been changed. There was a decrease in species density across the macro channel floor (MCF) and an increase in species density across the macro channel bank (MCB). Furthermore, it was reported that the flood altered the distribution of height classes across the macro channel. In general the riparian vegetation was shorter and bushier four years post-flood. These studies furthermore illustrated that the tree to shrub ratio did not change drastically from pre-flood conditions, although a decrease in the number of shrub individuals was reported. The research presented in this dissertation was designed to further explore changes in woody species composition and structure along the Sabie River, KNP at a post flood temporal interval, i.e. between the last survey in 2004 (by the KRPFRP) and 2010. For data compatibility, the sampling and analytical approach of this study conforms to the approach followed by the KRPFRP. Data were sampled within four preselected belt-transects that form part of the larger KRPFRP. All established woody individuals were counted and measured within each contiguous 10 m x 30 m plot within each of the four belt-transects. Log transformed species composition data were analysed through the application of the Bray Curtis dissimilarity index in combination with Ward’s method of clustering. Statistical significant differences between clusters were tested through the application of the Fisher’s exact relationship test. The MIXED Procedure or PROC MIXED model was used to investigate change within the vegetation structural data. Results obtained through the various analytical methods broadly support the findings of the KRPFRP. No significant change in woody species composition could be detected between 2004 and 2010. However, a change in the density (increase and decrease) of certain species across the MCB and MCF was revealed. Species richness and density increased significantly on the MCF oppose to small changes on the MCB. A significant increase in the total number of shrubs on the MCF contributed to an overall increase in woody density for the entire study area between 2004 and 2010. Shrubs therefore remained the most dominant growth form in both sampling years. Trees decreased across the MCB although the total number of established trees remained unchanged between 2004 and 2010. Riparian vegetation structure is directly linked to species assemblages, hence the continued dominance of shrub species along the Sabie River in the KNP The Sabie River riparian landscape is therefore still characterised by short and multi-stemmed woody individuals ten years after the LID. / Thesis (MSc (Environmental Sciences))--North-West University, Potchefstroom Campus, 2013