Journal of Water and Climate Change (Nov 2021)
Trend analysis of selected hydro-meteorological variables for the Rietspruit sub-basin, South Africa
Abstract
Identifying hydro-meteorological trends is critical for assessing climate change and variability both at a basin and regional level. This study examined the long- and short-term trends from stream discharge, temperature, and rainfall data around the Rietspruit sub-basin in South Africa. The data were subjected to homogeneity testing before performing the trend tests. Inhomogeneity was widely detected in discharge data, hence no further analyses were performed on such data. Temperature and rainfall trends and their magnitudes at yearly, seasonal, and monthly time steps were identified after applying the non-parametric Mann-Kendall and Sen's slope estimator. The possible starting point of a trend was determined by performing the sequential Mann-Kendall test. This study revealed a combination of upward and downward trends in both temperature and rainfall data for the time steps under observation. For rainfall on an annual basis, there were no statistically significant monotonic trends detected, although non-significant downward trends were dominant. However, significant decreasing rainfall trends were observed in dry and low rainfall months, which were April, August, September, and November. In contrast, significant upward temperature trends were detected at the Vereeniging climate station at an annual scale and in October, November, spring, and winter. The findings are critical for climate risk management and reduction decisions for both near- and long-term timescales. HIGHLIGHTS The need to perform homogeneity tests to avoid erroneous conclusions is emphasised.; The study cautions the direct use of stream discharge data for climate analyses in urban areas.; Long-term data show no significant changes in rainfall while temperature is rising.; Findings will improve the understanding of hydro-meteorological trends specific to the Rietspruit sub-basin mainly due to temperature spatial variability.;
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