Statistical analysis of rainfall and groundwater trends and their spatial variations in the Mopani District, South Africa

Master of Earth Science in Hydrology and Water Resources

Department of Earth Sciences

This study analysed rainfall and groundwater level trends and variations in the Mopani District, Limpopo of South Africa to guide sustainable water resource strategies, improve decision- making, drought assessments, and climate adaptation strategies. The methodology involved a two-phase approach, starting with data collection through desktop research and fieldwork in the Mopani District. Historical groundwater level and rainfall data were analysed using techniques like the double mass curve, Mann-Kendall test, Sen’s slope estimator, quantile regression, and geospatial analysis with QGIS software to identify trends and correlations. Rigorous quality control measures ensured data integrity, which was confirmed through double-mass curve analysis showing a strong correlation between monitoring stations (R² = 0.9995). The Thiessen polygon method was utilized to select rainfall stations based on their proximity to groundwater monitoring points, emphasizing the hydrological connectivity of the area. The study found that several boreholes, such as Bordeaux Julesburg, Rubbervale, State Land Vuheli, and Nghalume, Skwinyani, Caledone Ndengeza, Nkoankoa, Doorhoek, and Worcester, with Sen’s slope values ranging from -0.049 to -0.547 m/year, showed significant decreases in groundwater levels, indicating potential depletion or over-extraction. Monitoring borehole stations in Namakgale, Paardedood, and Doornhoek with slope values ranging from 0.0743 to 0.1255 m/year also showed non-significant decreasing trends. However, boreholes like Mica and Silwane Nyakalane with slopes of 1.63 m/year and 1.69 m/year exhibited significant increases, likely due to improved recharge conditions influenced by factors such as rainfall, agricultural activities, or other climatic factors. The increasing trend in Haenersburg was not statistically significant (p = 0.960), suggesting random variation rather than a reliable upward trend. The trend analysis of annual rainfall data from 2006 to 2020 at Giyani, Tzaneen Westfalia Estate, and Hoedspruit stations revealed decreasing trends, with negative Sen’s slope values of -13.504, -8.626, and -18.452, respectively. However, these reductions were not statistically significant, suggesting that these reductions may be due to natural variability rather than long-term climate changes. Quantile regression analysis of annual groundwater levels across 16 monitoring borehole stations indicated variability in trends, with negative slope coefficients reflecting decreasing groundwater levels for stations like Bordeaux Julesburg and Rubbervale Station. Overall, 75% (12 out of 16) of boreholes exhibited statistically significant decreasing trends influenced by factors such as over extraction rates and recharge variability. In Hoedspruit, the trends at quantiles 0.1 (p-value = 0.010) and 0.2 (p-value = 0.031) were significant, indicating a noteworthy decline in lower rainfall values. This study reveals significant trends in rainfall and groundwater levels across various monitoring stations, aligning with previous research in Mopani District, Limpopo Province, and South Africa. It emphasizes the need for ongoing monitoring to understand water resource management implications and address challenges related to climate variability and water availability in the region.