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Masters Degrees (Environmental Science)

Permanent URI for this collectionhttps://hdl.handle.net/10413/7408

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Browsing Masters Degrees (Environmental Science) by Subject "Acacia mearnsii--KwaZulu-Natal."

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    Investigating the potential of a classification algorithm to identify black wattle (Acacia mearnsii De Wild.) tress using imaging spectroscopy.
    (2012) Agjee, Na'eem Hoosen.; Pillay, A.; Ahmed, Fethi B.
    In South Africa, invasive black wattle trees (Acacia mearnsii D. Wild) are a major threat to ecosystem functionality causing widespread social, economic and environmental degradation. It is important that environmental managers are provided with rapid, regular and accurate information on the location of invasive black wattle trees to coordinate removal efforts. This study investigated the potential of an automated image classification algorithm to accurately identify black wattle (A. mearnsii De Wild.) trees using imaging spectroscopy. Hyperspectral data acquired by the EO-1 Hyperion sensor was used to identify black wattle trees in two study areas near Greytown, KwaZulu-Natal, South Africa. Image classifications were performed by the classification algorithm to identify black wattle trees using general and age specific spectral signatures (three to five years, seven to nine years, eleven to thirteen years). Results showed that using the general spectral signature an overall accuracy of 86.25% (user’s accuracy: 72.50%) and 84.50% (user’s accuracy: 69%) was achieved for study area one and study area two respectively. Using age specific spectral signatures, black wattle trees between three to five years of age were mapped with an overall accuracy of 62% (user’s accuracy: 24%) and 74.50% (user’s accuracy: 49%) for study area one and study area two respectively. The low user’s accuracies for the age specific classifications could be attributed to the use of relatively low resolution satellite imagery and not the efficacy of the classification algorithm. It was concluded that the classification algorithm could be used to identify black wattle trees using imaging spectroscopy with a high degree of accuracy.
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    The use of environmental isotopes, soil water measurements and soil water modelling to understand tree water use of an Acacia mearnsii (Black wattle) stand in KwaZulu-Natal.
    (2015) Watson, Andrew.; Everson, Colin Stuart.; Clulow, Alistair David.; Bulcock, Hartley Hugh.
    In Southern Africa commercial afforestation is an important agricultural activity and accounts for a large portion of the gross agricultural production, However, there are concerns regarding its possible detrimental impact on the hydrological system. Previous research in the Two Streams catchment by Clulow et al. (2011) showed that a commercial forestry species (Acacia mearnsii) was using more water than available through precipitation over a 30-month period (total evaporation was greater than rainfall) and they concluded that the trees were drawing water from another source. In this study, field measurements of stable isotopes of rainfall, soil water, stream water and groundwater were collected and analysed in order to understand the deficit in the water balance identified by Clulow et al. (2011). Experimental apparatus was used to extract isotopes from soil water. Automated rainfall and streamflow samples were used to sample rainfall and stream water (evaporation seals were designed to prevent fractionation). A specific set of criteria was used to program the automated rainfall sampler to better differentiate between event samples. HYDRUS 1-D model outputs of simulated total evaporation and soil water fluxes were verified from total evaporation and soil water measurements at the site. Rainfall varied in isotope signature throughout the year ranging from -150 to -15 permil (δ2H) and -20 to 2 permil (δ18O), these values were largely dependent on rainfall volume. Groundwater isotope composition signature changed only slightly throughout the year ranging from -12 to -5 permil (δ2H) and -4 to -1.5 permil (δ18O), with seasonality being the driving variable. The results from the isotope signatures showed that the main contributor to streamflow (-15 to -1.5 permil (δ2H) and -4.5 to -1.5 permil (δ18O)) was groundwater. Soil isotope signatures varied with depth and season, ranging from -25 to -8 permil (δ2H) and - 1.5 to 4 permil (δ18O). Groundwater signatures were evident on three occasions within the soil horizon (2.0 m and 2.4 m on 23/08/2013 and 1.6 m on 13/0/2013), where water was moved by hydraulic lift or capillary rise and made available for uptake by rooting systems. This was confirmed by Watermark and TDR-100 measurements, where there were upward fluxes of deep soil water during the dry season. HYDRUS-1D results suggested that simulated total evaporation (1052 mm) was similar to measured actual evaporation (1095 mm) during the wet season and dry season. The results conclude that the Acacia mearnsii trees extracted soil water or deep groundwater during the dry season, which allows for continuous growth throughout the year. This supports the conclusion of Clulow et al. 2011 and confirms that commercial forestry could have significant long-term impacts on catchment hydrology, particularly in dry season low flows.