LONG TERM CHANGES AND VARIABILITY IN RAINFALL AND STREAMFLOW IN THE LUVUVHU RIVER CATCHMENT, SOUTH AFRICA

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1 LONG TERM CHANGES AND VARIABILITY IN RAINFALL AND STREAMFLOW IN THE LUVUVHU RIVER CATCHMENT, SOUTH AFRICA J.O. Odiyo, R. Makungo and T.R. Nkuna University of Venda, Thohoyandou, South Africa ABSTRACT A study has been conducted to investigate the long term changes and variability in daily rainfall and streamflow in the Luvuvhu River Catchment. The changes and variability in daily rainfall and streamflow, impact on available water resources and their allocation. Daily rainfall data for rainfall stations for the period 9/-/ and daily streamflow data for stations for the period 9/-/ were obtained from South African Weather Services and the Department of Water Affairs, respectively. The data was grouped into cycles of and years and the daily mean rainfall and streamflow, and their standard deviations for each cycle were computed. The standard deviation was used to define the rainfall and streamflow variability. Linear regression was used to compute the trends in and year mean rainfall and streamflow, and their standard deviations. The rainfall stations show decreasing trend in and year mean rainfall except for Zwartranjes station which shows an increasing trend due to its location in a remote mountainous area with a different hydrologic behaviour. Ten year mean daily rainfall show decadal rainfall fluctuations. Streamflow stations showed contrasting trends in and years mean streamflow showing that other factors such as anthropogenic activities and impoundments could be impacting on streamflow. The impact of anthropogenic activities on long term streamflow changes and trends in the study area requires further investigations. The study generally showed increased variability of rainfall and streamflow. Keywords: Long term changes, rainfall, streamflow, variability

2 INTRODUCTION The observed global warming, the human induced increase in concentrations of greenhouse gases in the atmosphere, and the development of numerical climate models, have led to an increased concern for the detection of long term changes in climate characteristics (Fauchereau et al., ). High vulnerability to weather and climate hazards, associated with the growing population, and the resulting increased pressure on natural water systems and artificial water storage capabilities, make southern Africa one of the regions where potential changes in the hydrological cycle due to global warming could lead to extreme negative impacts on societies (Schulze et al., ). This has made studies on long term changes in rainfall and streamflow of great interest in South African (SA). According to Ampitiyawatta and Guo (9) precipitation is a good indication of long-term changes which pose impacts on water resources. Furthermore, changes in precipitation patterns are very important for water resources managers who deal with water resources planning and management. There are a number of studies on rainfall changes that have been done in SA, including Limpopo Province, where Luvuvhu River Catchment is located. Tyson et al. (97) noted quasi oscillations of between and years and between and years based on analyses of rainfall data for 7 stations across SA for the period between and 97. Dyer and Tyson (977) observed a year oscillation of rainfall for the northeastern parts of SA over the period 9 to 97. Dyer and Gosnell (97) noted significant long-term oscillations with a mean wavelength of 9. years from of the longest and most reliable rainfall stations from SA sugar industry. Nicholson (9, 99) and Hulme (99) did not identify any trends in the mean annual rainfalls over southern Africa between the periods 9-97, 9-9 and 9-99, respectively. Lumsden et al. (9) performed qualitative analysis of potential changes in hydrologically relevant rainfall statistics focused on determining where convergence exists amongst the different global climate models (GCMs) with respect to changes in rainfall in SA. Hydrologically relevant statistics identified include annual means and variances of the rainfall scenarios, as well as the distribution of daily rainfall amounts. The results in the GCMs evaluated in the study showed more rainfall was projected for the east of the region while less rainfall was projected along the west coast and the adjacent interior, with the possibility of a slight increase in inter-annual variability (Lumsden et al., 9). Kruger () provides more examples of studies on historical trends in precipitation over southern Africa. Kruger () reported significant decreases in annual precipitation in northern Limpopo, northeastern Free State, western KwaZulu-Natal and the southeastern regions of the Eastern Cape, and significant precipitation increases during the wet season in the northern Northwest Province and an area over Northern Cape Province, Western Cape Province and Eastern Cape Province. Lynch et al. () reported gradual increase in annual rainfall in the Potchefstroom area from 9 to 99. Median annual rainfall decrease over the latter half of the th century was reported in Limpopo Province by Warburton and Schulze (). Dollar and Rowntree (99) did not detect any long term change in rainfall pattern of the Bell River Catchment in the Eastern Drakensberg of South Africa. The study, however, found annual, seasonal rainfall cycles with variance peaks every -9 years. There are limited studies on long term changes and variability in streamflow. Fanta et al. () investigated the variability of river flow for river flow gauging stations in nine countries of the southern African region including SA, with a view to document the spatial variability of the river flow regimes. The study showed evidence of declining runoff in parts of Zambia, Angola, Mozambique and the High Veld in SA. Grenfell and Ellery (9) investigated the seasonal and interannual variations in streamflow in the Mfolozi River, SA using the median, mean and coefficient of variation. Research on southern Africa rainfall trends has focused on annual data series with little information on seasonal or daily data (Dollar and Rowntree, 99). Thus, long-term daily average changes and variability has not been covered extensively. The same applies to long term daily streamflow changes and variability. Such a study has not yet been done in the Luvuvhu River Catchment. The current study aimed at investigating long term changes and variability in rainfall and streamflow in the Luvuvhu River Catchment will provide additional information on long term changes and variability in daily rainfall and streamflow on a local scale.

3 STUDY AREA The Luvuvhu River Catchment is located in the Luvuvhu/Letaba Water Management Area in Limpopo Province of South Africa. The Luvuvhu River Catchment (LRC) is located between the longitudes 9 9'.''E and '.''E and latitudes 7'.7''S and 7'7.''S (Fig. ). The mean annual rainfall is mm while the mean annual runoff is x m. Topography varies from - m (Fig. ) and it greatly influences rainfall and runoff distribution in the catchment. Highest rainfall occurs in the upper reaches where the Soutpansberg Mountains are found with little rainfall in the lower reaches around the Kruger National Park. Figure : Location of the study area Figure : Topography of the study area

4 METHODOLOGY Daily rainfall data for rainfall stations for the period 9/-/ was obtained from South African Weather Services while daily streamflow data for stations for the period 9/-/ was obtained from the Department of Water Affairs. The long term mean and standard deviation for rainfall and streamflow were computed as follows: Each rainfall and streamflow data set was broken into year window periods (pentad). The mean and standard deviation were computed for each and every pentad for all the stations. Each rainfall and streamflow data set was broken into year window periods. The mean and standard deviation were computed for each and every decade for all the stations. The mean and standard deviation were computed in order to show the long-term changes and variability respectively. Linear regression method was used to estimate the trends in the daily mean rainfall and streamflow over the study period for both the and year cycles. This method fits a regression line to the series and the slope describes whether the trend is strong or not. The null hypothesis is that the slope of the line is zero. The standard deviation is one of the most common statistical parameters to measure overall dispersion (variation) of data (An et al., ), and has been widely used to study rainfall and/or streamflow variability (examples include, studies such as Sing and Mulye (99), Baeza and García del Jalón (). Linear regression has been used in a number of trend analyses studies including Suppiah and Hennessy (99), Schmidli and Frei () and Cheung et al. (), amongst others. RESULTS The ranges of the and year means and standard deviations for rainfall and streamflow data for all stations are provided in Tables and. All the results were analyzed in terms of the hydrological year. For example the period of the years refers to the hydrological years in the range 9/- 9/.The and year rainfall means and standard deviations ranges for each station are comparable. The and year means for streamflow are mostly not comparable though the standard deviations are comparable. The streamflow differences in the ranges of and year means may be due to floods which occurred in the pentads, and 9- and the decades and 9-. The major flood events occurred in the hydrological years 97/77, 99/9 and 999/. The flood events occurred in the first half of the decade followed by dry cycles or in the second half of the decade and these led to the increase of streamflow either in the or years cycles, respectively. The standard deviations ranges are generally higher than the means for both rainfall and streamflow data which show high rainfall and streamflow variability in the study area. Fauchereau et al. () reported that southern Africa s geographic location, steep topography, contrasted oceanic surroundings and atmospheric dynamics are conducive to great interannual variability of the hydrological cycle. Reason and Rouault () reported the connection of ENSO-like decadal variability with South African rainfall.

5 Table : and year means and standard deviations for rainfall data year year year year Station Mean Mean Stdev Stdev Goedehoop Hanglip Tshakhuma Zwartranjes Elim Table : and year means and standard deviations for streamflow data Station year Mean year Mean year Stdev year Stdev A9H A9H A9H A9H Figure shows the linear regression for and year rainfall means for Elim, Goedehoop, Hanglip, Tshakhuma and Zwartranjes rainfall stations. The rainfall stations show decreasing trend in and year means except for Zwartranjes station. Zwartranjes is located in a remote area in the Soutpansberg Mountains as compared to the other rainfall stations and may be characterized by different rainfall behaviour which may result in different trends. Trends in rainfall characteristics are likely to be associated with changes in atmospheric circulation patterns (Suppiah and Hennessy, 99). Other works have also attributed changes in African rainfall to Indian Ocean processes and atmospheric features such as the intertropical convergence zone and anticyclones (Cheung et al., ). Shongwe et al. (9) projected drying rainfall trends in the southern African region, though decade-to-decade rainfall fluctuations were also noted. The year mean daily rainfall show decadal rainfall fluctuations which is in agreement to that noted in Shongwe et al. (9). Droughts that have become more intense and widespread in South Africa (Fauchereau et al., ) confirm decreasing trends obtained in this study. Warburton and Schulze () also reported decrease in median annual rainfall over the later half of the th century in the Limpopo Province while Kruger () noted significant decrease in annual precipitation in northern Limpopo Province. These results are in agreement with the results of the current study despite the fact that the current trends are based on mean daily rainfall. The and year streamflow means for A9H, A9H, A9H and A9H are provided in Fig.. A9H and A9H show decreasing trends in and year means. These are associated with the decreasing trends in rainfall. A9H shows increasing trend in and year means while A9H shows increasing trend in year mean and almost no trend in year mean (Fig. ). These stations show contrasting trends in and year mean streamflows showing that other factors such as anthropogenic activities and impoundments could be impacting on the streamflow. Chunzhen (9) noted that detection and attribution of a trend in a hydrological time series are much more difficult because changes in runoff are affected not only by climate factors, but also by non-climate factors, such as increases in water use and water consumption resulting from population growth, economic development, and changes in land use and land cover. These might be the reasons for contrasting trends in streamflow in the study area since the anthropogenic activities including agriculture, afforestation, settlements, amongst others, occur in the quaternary catchments where each streamflow gauge is located and may affect the observed runoff. Griscom et al. () reported considerable land cover changes associated with human population growth and land use activities such as agriculture, grazing and fuel wood cutting in the Luvuvhu River Catchment. The study reported % increase in bare land

6 between 97 and which might have resulted in increased streamflow in parts of the catchment. The impact of anthropogenic activities on long term streamflow changes and trends in the study area requires further investigations. Odiyo et al. (submitted) showed increase in streamflows and percentages of time flows of specific magnitudes stay in the Luvuvhu River due to removal of alien vegetation. This could also have partially contributed particularly to increased flow trends post 99 when the removal of alien vegetation was initiated. The year mean daily streamflow also show decadal fluctuations similar to those of mean daily rainfall. Elim, Goedehoop, Tshakhuma and Zwartranjes show increase in and year standard deviations except for Hanglip station for which the standard deviation show no change (Fig. ). All streamflow stations show increasing trend of and year standard deviations, except for station A9H which show slightly decreasing trend for the year standard deviation (Figure ). Thus the results indicate increased variability of rainfall and streamflow. Figures - show year cyclic increase and decrease in mean and standard deviation for all rainfall and streamflow stations. Fauchereau et al. () has confirmed that great interannual variability of rainfall in South Africa was found to exist from the 9s onwards.

7 9 7 Elim Hanglip year mean year mean Goedehoop year mean. Tshakhuma year mean.... Zwartranjes Goedehoop Hanglip year mean year mean year mean..... Elim Zwartranjes year mean 9- - Tshakhuma year mean year mean Figure : and year mean rainfall

8 Figure : and year mean streamflow.... A9H A9H year mean (m /s) 9- year mean (m /s) A9H year mean (m /s)... A9H year mean (m /s) A9H year mean (m /s) A9H year mean (m /s) A9H 9- year mean (m /s) A9H year mean (m /s)

9 Elim year Stdev 9- Goodehoop Hanglip year Stdev year Stdev Tshakhuma 9 7 Zwartranjes year Stdev year Stdev 9- Elim Goedehoop 9- - Figure : and year rainfall standard deviations 9 7 Hanglip year Stdev Tshakhuma year Stdev year Stdev - year Stdev 9 7 Zwartranjes year Stdev

10 Figure : and year streamflow standard deviations A9H Year year Stdev A9H.. year Stdev Year A9H year Stdev A9H year Stdev Year A9H A9H year Stdev year Stdev A9H year Stdev..... A9H 9- year Stdev

11 CONCLUSION The study investigated long term changes and variability in rainfall and streamflow in the Luvuvhu River Catchment. The and year long term mean and standard deviation, and linear regression were used to show the long-term changes and variability, respectively. The rainfall stations show decreasing trend in and year mean rainfall except for Zwartranjes station which shows an increasing trend. Ten year mean daily rainfall show decadal rainfall fluctuations. This is in agreement with other studies done in Limpopo Province. Zwartranjes is located in a remote area in the Soutpansberg Mountains which may be characterized by different rainfall behavoiur, thus explaining the difference in its rainfall trends from those of the other stations. Streamflow stations showed contrasting trends in and years mean streamflow showing that other factors such as anthropogenic activities and impoundments could be impacting on streamflow. The impact of anthropogenic activities on long term streamflow changes and trends in the study area requires further investigations. Chunzhen (9) noted that it is important to separate the natural climate variability from anthropogenic one in historical data of hydrometeorological observations for a long term period. Such a study should be carried out in the current study area. All rainfall and streamflow stations show increasing trend for and year standard deviations, except for streamflow station A9H which shows nearly constant trend for the year standard deviations. The results of the study, thus, generally show increased variability of rainfall and streamflow. This increases the variability of the available water resources. ACKNOWLEDGEMENTS South African Weather Services and Department of Water Affairs are acknowledged for providing data used in this study. REFERENCES Ampitiyawatta, A.D. and Guo, S. (9) Precipitation trends in the Kalu Ganga Basin in Sri Lanka, The Journal of Agricultural Science, (), -. An, H., Eheart, J. W. & Braatz, R. D. (), Stability-oriented programs for regulating water withdrawals in riparian regions, Water Resour. Res.,, W, doi:.9/wr9. Baeza, D. & García del Jalón, D. () The natural variability approach, application to five rivers in the Ebro Basin, Spain, In: García de Jalón D. & Vizcaino P. (Eds) Proceedings of th Int. Symp. on Ecohydraulics Aquatic Habitats: Analysis & Restoration, Madrid. Cheung, W.H., Senay, G. B. & Singh, A. () Trends and spatial variation of seasonal and annual rainfall in Ethopia, Int, J, Climatology., 7 7. Chunzhen, L. (9) Research advances in impacts of natural climate variability and anthropogenic climate change on streamflow, Adv. Clim. Change Res. (Suppl.), 7J Dollar, E. S. J. & Rowntree, K. M. (99) Hydroclimatic trends, sediment sources, geomorphic resources in the bell river catchment in Eastern Cape Drakensburg South Africa, South African Geographical Journal. 77(): -. Dyer, T. G. J. & Gosnell, J. M. (97) Long term rainfall trends in the South African Sugar Industry, Proceedings of the South African Sugar Technologists' Association, -. Dyer, T.G.J. & Tyson, P.D. (977) Estimating above and below normal rainfall period over South Africa, 97-, Journal of Applied Meteorology., -7.

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