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Masters Degrees (Hydrology)

Permanent URI for this collectionhttps://hdl.handle.net/10413/14581

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Browsing Masters Degrees (Hydrology) by Subject "Cathedral Peak."

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    Detection and attribution of long-term climatic and hydrological trends in the Cathedral Peak catchments.
    (2016) Majozi, Sibusisiwe N.; Toucher, Michele Lynn.
    It has become accepted that global change is a considerable threat to vulnerable environments such as mountains. Various studies highlight the importance of change detection in long term climatic and hydrological data in understanding the catchment responses to various environmental changes. Long term trend detection of rainfall, temperature and streamflow has shown to be of practical importance to water resources management and planning. More especially in mountainous regions which have highly variable microclimates and are vulnerable to climate change impacts. In mountainous regions, the lack of data as a result of sparse observation networks often leads to a poor understanding of the climatic systems and amplifies the degree of uncertainty in trend detection. Given this need, the area of interest to this study was the intensively monitored Cathedral Peak catchments which are representative of the uKhahlamba Drakensberg region where a significant amount of water is generated for the KwaZulu-Natal and Gauteng provinces. In this context, the aim of the study was to detect trends in the historical hydroclimatic data of the Cathedral Peak catchments and gain understanding about the causes of change. To accurately detect and attribute the hydroclimatic trends in rainfall, temperature and streamflow the study was carried out using three methods. The first method investigated the data for historical trends (1948 - 2000), followed by a comparative analysis which investigated the differences between the historical and current records (2012 – 2015). The third method was an attribution study which investigated the influence of rainfall and land use to determine which of the two considered factors contributed as the cause of change. The Mann-Kendall and Sen’s slope estimator non-parametric tests were used to detect trends in the data and determine magnitude of the trends detected while the Mann-Whitney test was used to detect the difference between the historical and current records. The results across all times scales showed a few statistically significant trends in rainfall. However, the majority of the rainfall analyses showed no statistically significant trends with the expectation of a decline autumn rainfall detected in the seasonal analysis. The comparative analysis showed a few significant differences indicating increased rainfall between the historical and current period. The short current record was seen to have restrained the ability to detected definite differences in the rainfall. The significant positive trends detected in the historical temperature records and the comparative analysis provided more evidence of an increase in the temperature between the historical and current period. Furthermore, the positive trends found in the daily maximum and average temperatures were consistent with those from previous studies, which can be used to establish that there has been a general increase in the temperature between 1955 and 2000. Significant negative trends were detected in both the historical streamflow and the comparative analysis which showed evidence of a distinct decline in streamflow between 1949 and 2000. The results from the attribution study indicated that both land use change and rainfall appear to have a noticeable impact on streamflow. The complexity and highly variable nature of rainfall in the Cathedral Peak area as well as the difference in record length largely contributed to the lack of significant trends detected from the historical records and the inconclusive results obtained from the comparative study. However, despite this shortfall detection and attribution studies remain a useful tool in providing valuable information on the effects of global change in sensitive and vulnerable environments such as mountains.