Preliminary monitoring of faecal indicator organisms of surface water: A case study of Mvudi River, South Africa

Faecal contamination of water bodies is a known cause of high morbidity in developing countries. This study was carried out to assess the level of faecal contamination in Mvudi River used as a source of domestic water for people who live around it. Certified multimeters were used to measure pH, conductivity and turbidity while membrane filtration technique was employed to test for E. coli and total Enterococci in 18 water samples collected during sampling from January to March, 2014. The pH and conductivity values obtained varied between 7.30-7.88 and 10.47-15.94 mS/m respectively. Turbidity values were in the range of 17.57 and 429 NTU. E. colicounts were in the range of 950-11,533 cfu/100 mL while total Enterococci varied between 1,650-4,767 cfu/100 mL. The pH and EC data determined complied with the guideline values of the Department of Water Affairs and Forestry of South Africa (DWAF) and the World Health Organization (WHO) for domestic water use, but turbidity, E. coli and total Enterococci levels exceeded these guideline values. Mvudi River is microbiologically unfit and should not be used for drinking, domestic and recreational purposes without proper treatment. Keywords: Contamination, faecal indicator, organisms, surface, domestic water 

Impact of land use change on surface runoff and stream discharges in Luvuvhu River Catchment

Luvuvhu River catchment in Limpopo Province of South Africa experiences floods resulting from heavy rainfall of intensities exceeding 15 mm per hour associated with the Intertropical Convergence Zone. The generation of runoff is triggered by the rainfall intensity and soil moisture status. Runoff was calculated as a product of the net precipitation and a curve number coefficient. It was then routed using the Muskingum-Cunge method through the basin along flow paths determined by the topography using a diffusive wave transfer model that enabled the calculation of response functions between start and end point, depending upon slope, flow velocity and dissipation characteristics along the flow lines. Results showed that the simulated discharges closely compared with the measured discharges without the need for model optimization. It was concluded that simulation techniques had the potential to determine the influence of changes in land use to the hydrologic response of the catchment.NR

Yield-reliability analysis and operating rules for run-of-river abstractions for typical rural water supply: Siloam Village case study

The study focused on yield-reliability analysis and operating rules for optimum scheduling of run-of-river (ROR) abstractions for typical rural water supply schemes using Siloam Village, Limpopo Province, South Africa, as a case study. Efficient operation of water supply systems requires operating rules as decision support tools. System operation methods have hardly been developed or applied to water supply to rural communities that depend on ROR abstractions. Simulated runoff was used to derive unregulated river yield at different levels of assurance of supply (LAS) for Nzhelele River at Siloam Village using 1-day flow duration curves. Yield-reliability analysis results were used to derive operating rules. The results show that Nzhelele River can meet domestic and low-flow requirements at 50–80% (1:2-1:5) LAS. The low-flow and domestic water requirements can be partially met at 90% (1:10) LAS. The generic operating rules for ROR abstractions were consequently derived from the procedure used in developing operating rules for Nzhelele River. This enables generation of operating rules for ROR abstractions in any typical rural water supply system

Effect of hysteresis on water flow in the vadose zone under natural boundary conditions, Siloam Village case study, South Africa

A one-dimensional vadose zone model was used to simulate flow under natural boundary conditions. The effects of hysteresis and temporal variability of meteorological conditions were evaluated. Simulations were performed in HYDRUS-1D code for the period April 2013–January 2014 (6601 hours) at three different locations in a delineated portion of the sub-quaternary catchment A80A of Nzhelele with different soil textures. Soil hydraulic characteristics were estimated in a Rosetta library dynamically linked to the HYDRUS-1D model which is based on the numerical solution of a one-dimensional Richard’s equation. Analysis of the simulation results suggests that ignoring hysteresis for soils of similar textural class does not lead to any significant deviation of the model predicted soil moisture, unlike for soils with different textural classesResearch and Publications Committee (RPC) which is under the Directorate of Research and Innovation of the University of Venda, South Afric

An evaluation of the effects of climate change on flood frequency in the Luvuvhu River Catchment, Limpopo Province, South Africa

Climate change poses a great risk to natural resources and agriculture in the Luvuvhu River Catchment. The catchment has experienced floods resulting from higher than normal rainfall associated with the Intertropical Convergence Zone and cyclones, which have caused enormous damage to property and impacted negatively on fauna and flora and human livelihoods. In order to understand the dynamics involved in the effects of climate change in the catchment, annual maximum flow data was used to evaluate flood frequencies. The distribution models used in the study included the Generalized Extreme Value distributions, the Gumbel Extreme Value type I distribution, the Log-normal distribution and the Log Pearson type III distribution. The extreme value analysis showed that the Log-normal and Log-Pearson type III distributions provided the best fit, which could be used to derive the probability of occurrence of flood events. The results showed a general increase in the frequency of extreme events, accompanied by floods of higher magnitude.NRFhttp://www.witpress.co

Determinants of solid fuel use and emission risks among households : insights from Limpopo, South Africa

Emissions from residential solid fuels reduce ambient air quality and cause indoor air pollution resulting in adverse human health. The traditional solid fuels used for cooking include coal, straws, dung, and wood, with the latter identified as the prevalent energy source in developing countries. Emissions from such fuel sources appear to be significant hazards and risk factors for asthma and other respiratory diseases. This study aimed at reporting factors influencing the choice of dominant solid fuel for cooking and determine the emission risk from such solid fuel in three villages of Phalaborwa, Limpopo province, South Africa. The study used descriptive analysis to show the relationship between the socio-economic variables and the choice of cooking fuel at the household level. Multiple correspondence analysis (MCA) was used further to detect and represent underlying structures in the choice of dominant fuels. MCA shows the diversity and existing relationship of how variables are related analytically and graphically. Generalised linear logistic weight estimation procedure (WLS) was also used to investigate the factors influencing choice of fuel used and the inherent emission risks. In the three villages, wood was the prevalent cooking fuel with 76.8% of participant households using it during the summer and winter seasons. Variables such as low monthly income, level of education, and system of burning are revealed as strong predictors of wood fuel usage. Moreover, income, water heating energy, types of wood, and number of cooking hours are significant (p ≤ 0.05) in influencing emission from wood fuel in the community. A notable conclusion is that variables such as income, education status and system of burning are determinants of wood fuel usage in the three villages, while income, water heating energy, types of wood and number of hours influence vulnerability to household emission and possible health risks in the use of solid energy sources

Flood Frequency Analysis of Annual Maximum Stream Flows for Luvuvhu River Catchment, Limpopo Province, South Africa

Luvuvhu River Catchment (LRC) is one of the regions in South Africa where floods have caused enormous damage and impacted negatively on fauna and flora. Over the years, the catchment has experienced floods resulting from heavy rainfall associated with the ITCZ. Annual maximum flow data from 8 stations with 50 years hydrological data were used to analyze flood frequencies in the catchment. To derive the probability of occurrence of flood events, the frequency distributions which could best describe the past characteristics and magnitudes of such floods were tested. This involved the determination of the best flood frequency models, which could be fitted to the available historical recorded data. The distribution models used included the Generalized Extreme Value, Gumbel or Extreme Value type 1, Log-Normal and the Log Pearson type III distributions. The extreme value analysis showed that the Gumbel and Log Pearson type III distributions provided the best fit.NR

WormBase: A data management and information system for forecasting Spodoptera exempta (Lepidoptera: Noctuidae) in Eastern Africa

Forecasting and information services on nutgrass armyworm, Spodoptera exempta (Walker), have been in operation in East Africa since 1969. Using current season and historical data from moth traps, together with outbreak and meteorological data, the probability of outbreaks in administrative areas can be predicted for the following week. WormBase, a database and information system, was developed to provide improvements in access to the data, data interpretation and synthesis, presentation of forecasts and information, forecast evaluation, and training of forecasters. The development and function of WormBase, written in dBASE IV for the use on IBM-compatible, PCs, is described. The database management section of the system provides facilities for entering, browsing, plotting and printing data. The forecasting tools section provides a range of programs that assist with specific tasks routinely undertaken by forecasters, including production and verification. WormBase is currently in use in Kenya and Tanzania