Luvuvhu River Catchment Research Articles

Impact of weirs in altering benthic macroinvertebrate assemblages and composition structure in the Luvuvhu River Catchment, South Africa

Stream flow weirs disrupt river flow regimes, physical conditions, and biological composition of rivers, posing significant threat to the river’s functionality, integrity, and sustainability. Home to diverse aquatic organisms, there is a lack of impact assessment of weirs on the stream of the Luvuvhu River Catchment (LRC). The aim of this study was to examine the impact of six weirs on aquatic macroinvertebrate assemblages and composition across five streams. A total of six sampling surveys on macroinvertebrates and physico-chemical parameters were conducted upstream and downstream of six weirs in 12 months between June 2021 and June 2022. The South African Scoring System score (SASS score) and Average Score per Taxon (ASPT) indices were used to compare organisms’ response between upstream and downstream of weirs. Generalized linear mixed models (GLMM) were used to determine the effect of physico-chemical variables on macroinvertebrate assemblage, while the CCA was employed to assess similarities between downstream and upstream sampling points across various sites. A total of 18,914 macroinvertebrate individuals were observed from 65 families during the survey. In upstream sections, the SASS score was driven by habitat integrity, electrical conductivity, and water depth, while ASPT responded significantly to habitat integrity, pH, dissolved oxygen and electrical conductivity. In the downstream sections, the SASS score increased with an increasing habitat integrity score and river width, while decreasing with elevation and pH levels. ASPT increased with increasing habitat integrity and elevation in the downstream sections, while decreasing with increasing river width and water temperature. This study’s findings suggest habitat integrity is largely driving aquatic abundance and assemblage in the LRC, and it is therefore important to maintain the ecological integrity of rivers.

Relationships between reference site quality and baetid mayfly assemblages in mountainous streams of the Luvuvhu catchment, South Africa

With water quality deteriorating rapidly at a global scale, river sections suited to serve as reference sites are being increasingly lost. It thus becomes critical to develop rapid methods to confirm that previously monitored sites continue meet the requirements of reliable reference sites. In the absence of pristine sites, 9 near-natural sites, as defined by the Kleynhans (1996) classification, were used as reference sites for the Luvuvhu River catchment to compare the quality of physico-chemical factors against a biological metric. Baetid mayfly community structure at a site was chosen as an index of water quality, since this family is common in all types of freshwaters, highly diverse and adapted to unpolluted running water. Baetid larvae were sampled monthly from stones-in-current biotopes across 9 sites for over 1 year, between December 2016 and January 2018. A Spearman’s correlation test was used to evaluate the relationship between physico-chemical factors and identify redundant variables. Water quality standards were measured against the national water quality guidelines for aquatic ecosystems. We used a generalized linear model to determine the effect of physico-chemical variables on baetid species, and canonical correspondence analysis to show the relationships between baetid species, sites, and physico-chemical variables. A total of 3 039 individuals belonging to 12 mayfly species were recorded. Our findings indicated that while the physico-chemical factors were highly variable, they were within favourable ranges to reflect reference site conditions. While water temperature was the most important driver of baetid community structure in general, as it negatively affected their abundances, a subset of species (Pseudoponnota sp., Pseudocloeon sp., Acanthiops varius and Demoulinia crassi) showed clear responses to changes in TDS and stream width. We conclude that specific baetid species show good potential as biological indicators of reference sites and chronic water temperature stress, making assessment of reference sites easier.

Prioritising climate coping and adaptation strategies for smallholder farmers in Luvuvhu River Catchment, South Africa

Smallholder farmers are highly vulnerable to climate change and require prioritised strategies to minimise the impacts. Challenges faced by smallholder farmers hinder the implementation of coping and adaptation strategies, limiting sustainable agriculture. This study prioritised climate change coping and adaptation strategies and developed a plan to promote implementation by smallholder farmers. Linear additive model of multicriteria decision analysis within CLIMACT Prio tool Excel Spreadsheet was used to prioritise 16 strategies, in consultation with 23 stakeholders. Stakeholders included smallholder farmers, academics, municipal and government officials. Sensitivity analysis was used to determine the effect of changing weights on final ranking of the strategies. Reducing production space to maximise irrigation had the highest score of 1 and rank of 1 while reducing sand mining had the lowest score of 0.82 and rank of 7. Adjusting fertilisers, food preservation, reducing sand mining along river banks, planting high-yielding crop varieties and reducing soil erosion had an equal score of 0.95 and rank of 2. Varying the weight of each criterion did not affect ranking of the strategies. The study found that most strategies had short implementation time frames and were classified as coping strategies. Identified benefits of the prioritised strategies support national, regional and global development goals. The study provided information required for decision support which is an integral part of climate services. It also promotes improvement of relevant stakeholders’ policies and programs to support smallholder farmers.

Using Geospatial Techniques and Analytic Hierarchy Process to Map Groundwater Potential Zones.

This study is conducted in Luvuvhu River Catchment (LRC) of South Africa, which has numerous major agricultural farms that are located in the upper catchment, especially in Levubu Valley. The significant irrigation developments in upper catchment have resulted in a decrease in the yield of surface water resources to such an extent that these resources struggle to meet domestic and industrial demand. The aim of this study is to delineate groundwater potential zones (GWPZ) as a way of establishing alternative water resources to relieve the overly stressed surface water resources. Various datasets are processed to extract groundwater controlling factors. Map layers of controlling factors are assigned weights according to their relative importance to groundwater occurrence using analytic hierarchy process and then integrated based on weighted sum analysis to generate GWPZ map. Rainfall infiltration breakthrough (RIB) and area under curve (AUC) are used to validate the GWPZ map. GWPZ map shows that lower catchment has very high groundwater potential covering about 409 km2 . Nonetheless, about 50% of LRC spatially falls within high groundwater potential zone. Groundwater recharge, based on RIB for three boreholes, that is, A9N0007, A9N0008, and A9N0018 around Levubu Valley is estimated at 8.3, 15.4, and 16.2%, respectively. Boreholes A9N0018 and A9N0018 correspond to moderate to high groundwater potential zone, whereas A9N007 coincides with low to moderate zone. Considering the groundwater recharge estimates and associated potential zones, RIB results correspond well with GWPZ map. Also, an AUC, based on 26 boreholes, of 70.9% is achieved; thus, indicating a reliable model.

Baetid abundances are a rapid indicator of thermal stress and riparian zone intactness.

Riparian zone vegetation plays an integral role in freshwater ecology, notably by buffering water temperatures, and in providing habitat for the adult stages of many aquatic species. We measured the contribution that riparian vegetation makes to temperature buffering, and how this affects the freshwater fauna, specifically using changes in abundances of baetid may flies for the Luvuvhu River catchment in South Africa. Water temperatures were compared for shaded versus un-shaded sites, and thermal stress between seasons was estimated using a cumulative probability model for the most widespread mayfly species, Dabulamanzia media. It is concluded that thermal stress due to losses in riparian shading could be detected using mayfly abundances in a regular monitoring programme.

Rainy season characteristics for the Luvuvhu River catchment, South Africa

Maize is a staple crop in South Africa and is mainly grown under rain-fed conditions. Rain-fed agricultural production is heavily reliant on rainfall during the planting season. Information on rainy season characteristics is of utmost importance as it guides farmers in preparing for the upcoming season. The study investigated rainy season characteristics for the Luvuvhu River Catchment with reference to rain-fed maize production. Historical daily rainfall data were obtained from 12 weather stations for the period 1923–2015. Instant+ statistical software was used to compute onset, false onset, cessation and length of the rainy season. The trends in rainy season characteristics were analysed using the Spearman rank correlation test. Onset of the rainy season can be expected from the first week of October to the third week of January, while cessation can be expected from the first week of February to the first week of May. The length of the rainy season ranged from 67 to 203 days. Seasonal rainfall ranged from 182 to 1 535 mm. Phafuri, Sigonde, Phunda Maria and Folovhodwe had a higher probability of false onset. No significant changes in rainy season characteristics at a 5% level of significance were observed. There was a strong correlation between onset and length of the rainy season. Based on rainfall patterns only, Phafuri, Sigonde and Folovhodwe might not be suitable for maize production under the current climate. The most favourable sites for maize production within the catchment are Entabeni, Levubu, Lwamondo, Thathe, Tshiombo and Vreemedeling. The findings of this study have implications on agricultural activities and food security as maize is a staple crop in the Luvuvhu River catchment area. Information on rainy season characteristics may therefore help in strengthening food security.

Evaluating the relationship between hydrological extremes and groundwater in Luvuvhu River Catchment, South Africa

Extreme hydrological events have been reported to be on an increase in terms of magnitude and frequency in southern Africa. Groundwater in this area plays a significant role in domestic water supply and agriculture. The aim of this study is to evaluate the relationship between groundwater levels and hydrological extremes in north-eastern South Africa. An index-based approach was used to determine the drought and flood events over the study period while the Water Table Fluctuation approach was used to determine groundwater recharge. Flow duration curves were further employed to determine the exceedance period of high and low flows in the study area. Mann-Kendall and Sequential Mann-Kendall were used to detect trends and the point of change. Both floods and drought were found to have occurred in the study area at different magnitudes, however both the Standardized Precipitation Index (SPI) and Standardized Streamflow Index (SSI) found that majority of these were not categorized as mild to near normal conditions. Specific yield determined using the simple linear regression method ranged between 0.04 and 0.06. Groundwater recharge estimates ranged between 1.1 and 11.5 % of mean annual rainfall ranging between 167–1000 mm/a. About 60 % of the stations (i.e. rainfall, streamflow, and groundwater) show significantly decreasing trend. This therefore indicates that there is a decreasing trend in groundwater levels, streamflow, and rainfall over the study area. Based on the trend analysis findings, it suggests that extreme events in the catchment influences groundwater resources.

Can Famine Be Averted? A Spatiotemporal Assessment of The Impact of Climate Change on Food Security in The Luvuvhu River Catchment of South Africa

Climate change has proved to be a threat to food security the world over. Using temperature and precipitation data, this paper examines the differential effects climate change has on different land uses in the Luvuvhu river catchment in South Africa. The paper uses the Normalised Difference Vegetation Index (NDVI) and Vegetation Condition Index (VCI), which were calculated from Landsat images, and the Standardised Precipitation Index (SPI) for a sample of years between 1980 and 2016 to assess how drought and flood frequency have affected the agricultural environment. The results indicate that the lowest SPI values were recorded in 1996/1997, 2001/2002 and 2014/2015, suggesting the occurrence of drought during these years, while the highest SPI values were recorded in 1997/1998, 2002/2003 and 2004/2005. The relationship between three-month SPI (SPI_3) and VCI was strongest in grassland, and subsistence farming areas with the correlation coefficients of 0.8166 (p = 0.0022) and −0.6172 (p = 0.0431), respectively, indicating that rainfall variability had a high negative impact on vegetation health in those land uses with shallow-rooted plants. The findings of this study are relevant to disaster management planning in South Africa, as well as development of farming response strategies for coping with climate hazards in the country.

Assessing the frequency of drought/flood severity in the Luvuvhu River catchment, Limpopo Province, South Africa

The Luvuvhu River catchment experiences rainfall variability with a high frequency of extremely dry and wet conditions. Understanding the frequency of drought and floods in this catchment area is important to the agriculture sector for managing the negative impacts of these natural hazards. This study was undertaken to investigate the frequency and severity of drought/floods and linkages with the El Niño Southern Oscillation (ENSO) phenomenon. Poor and resource-limited small-scale farmers in the Luvuvhu River catchment area struggle to adjust due to decreasing crop yields and livestock mortality caused by drought and floods. Monthly rainfall data from 15 grid points (0.5° × 0.5°) was used to compute the Standardised Precipitation Index (SPI) for the period between 1979 and 2016. The 3-month SPI was calculated for the December–January–February (DJF) period. The second half of the agricultural season was selected because the influence of ENSO is high during the late summer season (DJF) in the catchment. The SPI results indicate that the agricultural seasons 1982/83, 1991/92 and 2015/16 were characterised by extreme drought. Conversely, the SPI values also show that the wettest seasons were recorded in 1998/99 and 1999/00. The catchment experiences a high frequency of moderate to severe drought in the north and north-eastern parts. Spatially, the occurrence of moderate to severe dry conditions covers large areas in the north and south-western parts. Severe to extreme wet conditions cover large areas in the north and south-eastern parts of the catchment. The SST index (Niño 3.4) shows a strong influence on rainfall variability in the catchment, resulting in either dry or wet conditions. Therefore, this study recommends further research focusing on more climatic modes that influence rainfall variability, as well as further development of drought and flood forecasting to improve farmers’ adaptations options and reliability of weather forecasts used as a tool to manage crop production.

Flood risk assessment in Luvuvhu river, Limpopo province, South Africa

Floods are the most destructive and affect a larger population as compared to any other weather related disasters. Luvuvhu River Catchment is one of the areas in South Africa that has been subjected to extensive flood damage. A major flood hazard which claimed lives and left thousands homeless occurred in the year 1999/2000. The main aim of the study was to analyse flood frequency and assess flood risk in Luvuvhu River Catchment. Four flow gauging stations covering the catchment were used for flood frequency analysis and only a segment was assessed for flood risk.The Anderson-Darling (AD), Kolmogorov-Smirnov (KS), and Chi-Squared (x2) goodness of fit tests revealed Log Normal, Log Pearson 3 and Generalized Extreme Value as the best fitting distribution to the annual maximum discharge data. The computed peak discharges were 206.61 m3/s, 351.63 m3/s, 498.46 m3/s and 685.41 m3/s for 20, 50, 100 and 200 year return period for A9H001 station.HEC-RAS was used with ArcGIS for floodplain mapping. Flood risk maps provided an indication of areas that are at risk of being inundated during floods with 20, 50, 100 and 200 years return period which were 462,407 m2, 539,198 m2, 594,735 m2 and 65,925 m2 respectively. These areas will be submerged in depth of water ranging from 0.1 m along the floodplains to 9 m in the main channel. They also revealed that settlements and cultivated areas will be the most vulnerable land uses in all flood events except 200 year flood, where natural resources will be more exposed.

Short-Term and Medium-Term Drought Forecasting Using Generalized Additive Models

Forecasting extreme hydrological events is critical for drought risk and efficient water resource management in semi-arid environments that are prone to natural hazards. This study aimed at forecasting drought conditions in a semi-arid region in north-eastern South Africa. The Standardized Precipitation Evaporation Index (SPEI) was used as a drought-quantifying parameter. Data for SPEI formulation for eight weather stations were obtained from South Africa Weather Services. Forecasting of the SPEI was achieved by using Generalized Additive Models (GAMs) at 1, 6, and 12 month timescales. Time series decomposition was done to reduce time series complexities, and variable selection was done using Lasso. Mild drought conditions were found to be more prevalent in the study area compared to other drought categories. Four models were developed to forecast drought in the Luvuvhu River Catchment (i.e., GAM, Ensemble Empirical Mode Decomposition (EEMD)-GAM, EEMD-Autoregressive Integrated Moving Average (ARIMA)-GAM, and Forecast Quantile Regression Averaging (fQRA)). At the first two timescales, fQRA forecasted the test data better than the other models, while GAMs were best at the 12 month timescale. Root Mean Square Error values of 0.0599, 0.2609, and 0.1809 were shown by fQRA and GAM at the 1, 6, and 12 month timescales, respectively. The study findings demonstrated the strength of GAMs in short- and medium-term drought forecasting.

The use of Water Requirement Satisfaction Index for assessing agricultural drought on rain-fed maize, in the Luvuvhu River catchment, South Africa

Analysis of drought on rain-fed maize production in the Luvuvhu River Catchment was measured using the Water Requirement Satisfaction Index (WRSI). Computation of WRSI was performed using a crop water balance model in Instat+ software for a 120-day maturing maize crop using nine different planting dekads from October to December. This study made use of seven weather stations, which adequately represent climatic and geographical environments of the catchment, containing historical rainfall and temperature data from 1974 to 2015. The non-parametric Spearman’s Rank Correlation test was conducted to determine drought trends. Thereafter, probabilities and extreme widespread dry and wet agricultural seasons were analysed using STATISTICA software. Results revealed that since the 1980s, the catchment had been subjected to frequent drought conditions, with an average frequency of once every two to three seasons. Extreme drought episodes (WRSI <50) were commonly identified in the northern drier parts of the catchment as compared to the high rainfall region, whereby 50-93% of the analysed seasons were subjected to extreme drought conditions. Furthermore, there were no drought trends (ρ values close to 0) during the analysed climate period. Water Requirements Satisfaction Index (WRSI) values corresponding to more intense drought conditions were reflected during the December planting date for all stations. Moreover, at the low rainfall region, it was seen that extreme droughts occurred once in five seasons, regardless of the planting date. Thus, the study led to a recommendation of using October-November as the optimum planting date in the catchment. Furthermore, farmers located areas with high probabilities of drought during critical stages can be advised to supplement rain-fed farming with irrigation should they be located nearby to rivers.

Challenges to Implementing an Environmental Flow Regime in the Luvuvhu River Catchment, South Africa.

Rivers are now facing increasing pressure and demand to provide water directly for drinking, farming and supporting industries as a result of rapidly growing global human population. Globally, the most common practice for catchment managers is to limit water abstraction and changes to stream flow by setting environmental flow standards that guard and maintain the natural ecosystem characteristics. Since the development of the environmental flow concept and methods in South Africa, very few studies have assessed the institutional constraints towards environmental flow implementation. This study determined stream flow trends over time by fitting simple linear regression model to mean daily stream flow data at three selected stations in the Luvuvhu River Catchment (LRC). We also conducted a literature search to review, firstly the response of aquatic organisms (fish and macroinvertebrate) to changes in habitat conditions and secondly on local challenges affecting the sustainable implementation of environmental flow regime and related water resources management strategies. All the three stream flow stations show decreasing stream flow volume of 1 and 2 orders of magnitude faster in some stations with the possibility that flow will cease in the near future. Qualitative analyses from both local and international literature search found that the main challenges facing the implementation of sustainable flow strategies and management are absence of catchment management agency, lack of understanding of environmental flow benefits, limited financial budget, lack of capacity and conflict of interest. Rivers with changing stream flows tend to lose sensitive species. The development of scientifically credible catchment-wide environmental flow and abstraction thresholds for rivers within the LRC would make a major contribution in minimizing the declining stream flow volumes. Monitoring and reporting should be prioritized to give regular accounts of the state of our rivers.

Spectroscopic Determination of Water Salinity in Brackish Surface Water in Nandoni Dam, at Vhembe District, Limpopo Province, South Africa

The problem of limited water supply in the Vhembe District (Limpopo Province, South Africa) is exacerbated by a preponderance of dissolved salts, which cause disagreeable taste and odour in the water as reported by the communities using this water for drinking. The water treatment plant that supplies the treated water to the communities in the District sources this raw water from the Nandoni Dam at the Luvuvhu river catchment. There are no scientific studies that have been reported in the literature that focused on determining the levels of water salinity from various water sources in the municipalities of the District. Water samples from various sites across the Nandoni Dam, a primary source of domestic water supply in the region, were collected through each season over a period of twelve months in order to ascertain the concentrations of dissolved salts in the dam. Onsite analyses of the water samples were conducted using the YSI ProDSS multimeter, while the laboratory water analyses were conducted using the spectroquant and atomic absorption spectrometers. Although salinity tests seem to indicate that the water sampled across most of the Nandoni Dam is brackish during all seasons of the year with the highest being 750 mg/L, water samples from the dam mid-outlet and the treatment plant are slightly below the World Health Organization (WHO) brackish water bracket of 500 mg/L with unfavourable taste for drinking. Results from this study indicate that the water sourced from the Nandoni Dam is not suitable for human consumption and therefore requires integrated water resource management, as well as robust and cost-effective water desalination treatment.

SWAT model uncertainty analysis, calibration and validation for runoff simulation in the Luvuvhu River catchment, South Africa

The soil and water assessment tool (SWAT) was calibrated for the Luvuvhu River catchment, South Africa in order to simulate runoff. The model was executed through QSWAT which is an interface between SWAT and QGIS. Data from four weather stations and four weir stations evenly distributed over the catchment were used. The model was run for a 33-year period of 1983–2015. Sensitivity analysis, calibration and validation were conducted using the sequential uncertainty fitting (SUFI-2) algorithm through its interface with SWAT calibration and uncertainty procedure (SWAT-CUP). The calibration process was conducted for the period 1986 to 2005 while the validation process was from 2006 to 2015. Six model efficiency measures were used, namely: coefficient of determination (R2), Nash–Sutcliffe efficiency (NSE) index, root mean square error (RMSE)-observations standard deviation ratio (RSR), percent bias (PBIAS), probability (P)-factor and correlation coefficient (R)-factor were used. Initial results indicated an over-estimation of low flows with regression slope of less than 0.7. Twelve model parameters were applied for sensitivity analysis with four (ALPHA_BF, CN2, GW_DELAY and SOL_K) found to be more distinguishable and sensitive to streamflow (p < 0.05). The SUFI-2 algorithm through the interface with the SWAT-CUP was capable of capturing the model's behaviour, with calibration results showing an R2 of 0.63, NSE index of 0.66, RSR of 0.56 and a positive PBIAS of 16.3 while validation results revealed an R2 of 0.52, NSE of 0.48, RSR of 0.72 and PBIAS of 19.90. The model produced P-factor of 0.67 and R-factor of 0.68 during calibration and during validation, 0.69 and 0.53 respectively. Although performance indicators yielded fair and acceptable results, the P-factor was still below the recommended model performance of 70%. Apart from the unacceptable P-factor values, the results obtained in this study demonstrate acceptable model performance during calibration while validation results were still inconclusive. It can be concluded that calibration of the SWAT model yielded acceptable results with exception to validation results. Having said this, the model can be a useful tool for general water resources assessment and not for analysing hydrological extremes in the Luvuvhu River catchment.

Analysis of potential future droughts limiting maize production, in the Luvuvhu River catchment area, South Africa

Recurring droughts associated with global warming have raised major concern for the agricultural sector, particularly vulnerable small-scale farmers who rely on rain-fed farming such as in the Luvuvhu River catchment. The Standardized Precipitation Evapotranspiration Index (SPEI) and Water Requirement Satisfaction Index (WRSI) were calculated to assess drought on a 120-day maturing maize crop based on outputs of the CSIRO-Mk3.6.0 under RCP 4.5 emission scenario, for the period 1980/81–2089/90. Results by SPEI show that 40–54% of the agricultural seasons during the base period experienced mild drought conditions (SPEI 0 to −0.99), equivalent to a recurrence of once in two seasons. However, WRSI results clearly indicated that stations in the drier regions (annual rainfall <600 mm) of the catchment experienced mild drought (WRSI 70 - 79) corresponding to satisfactory crop performance every season. Results further showed overall mild to moderate droughts in the beginning of the near-future climate period (2020/21–2036/37) with SPEI values not decreasing below −1.5. These conditions are then expected to change during the far-future climate period (2055/56–2089/90), whereby results on the expected crop performance predicted significantly drier conditions (p < 0.05). This study provided information on how farmers in the area can prepare for future agricultural seasons, while there is sufficient time to implement strategies to reduce drought risk potential. Thus, integrated interventions could provide best options for improving livelihoods and building the capability of farmers to manage climate change-related stresses.

Use of standardized precipitation evapotranspiration index to investigate drought relative to maize, in the Luvuvhu River catchment area, South Africa

Drought frequency and severity analysis during the growing period of maize was carried out by means of the Standardized Precipitation Evapotranspiration Index (SPEI) based on climatic data from seven weather stations (1975–2014). The index was aggregated at different time scales following three consecutive planting dates (October, November and December), relative to the average start of the rainy season in the area. Temporal analysis of droughts was conducted and trends were evaluated using the non-parametric Spearman's Rank Correlation test. The relative frequency distributions of the different drought categories were plotted for each growth stage of maize, with respect to the three planting dates. Results revealed an average drought occurrence of once every two seasons. The 1991/92 drought was identified as the most extreme drought during the analysis period; and generally there were no significant trends across the catchment, except for weak increasing SPEI at Levubu, Lwamondo and Thohoyandou with Spearman's ρ values of 0.4. This implies that the severity of drought decreased over time in these regions following the respective planting dates. The study further revealed that planting a 120-day maturing maize crop in December would pose a high risk of frequent severe-extreme droughts (SPEI -1.5 to ≤ −2) during the flowering to grain-filling stage at the high and moderate rainfall regions, while results at the low rainfall region indicated this risk following planting in October.

Extensive netting in Albasini and Nandoni dams: a potential threat to fish as a sustainable food source in the Vhembe District, South Africa

Fish populations in Albasini and Nandoni dams are negatively affected by extensive netting practices. This observation was made by the authors following a number of fish health assessment surveys related to aquatic pollution in the Luvuvhu River catchment. A comparison between the number and size of fish collected over a period of ten years indicated decreases in the average size and a consistent low number of fish, despite similar extensive sampling efforts. Unregulated netting is a common practice in both dams. This may become a serious problem as fish from these two dams are an important source of protein for the local communities. The purpose of this note is to report that gillnets are illegally used in the system and on the effect this could have on the fish population. The authors suggest educational and awareness initiatives to inform local communities about the importance of utilising fish in a sustainable manner to ensure the livelihood of generations to come.

Dry spells assessment with reference to the maize crop in the Luvuvhu River catchment of South Africa

Agricultural productivity in South Africa is negatively affected by drought as a result of frequent periodic dry spells and increasing crop water demands resulting in poor crop development and low yields. Thus, we embarked on this study which aims at investigating dry spell occurrences in relation to growing season of maize in the Luvuvhu River Catchment. Daily rainfall data (1945–2014) from 12 stations which represent the catchment fairly well was utilized in this study. Three consecutive planting dates were staggered based on three consecutive onsets of the rainy season. Dry spells were categorized into three groups: short, medium and long dry spells. The data was then subjected to theoretical distribution fitting using the Anderson–Darling goodness-of-fit test; and probabilities of occurrence were computed using a probabilistic model that best fits the data. Trend analysis was performed on the frequency of dry spells per growing period using the non-parametric Spearman's rank correlation test. Out results indicated high probabilities (≥80%) of short dry spells at all the stations irrespective of the timing of planting. Further analysis revealed that a risk of yield reduction with planting following the first onset of rains was higher than that with planting following the second and third onsets. In order to minimize this risk, farmers can be advised to plant between mid-November to mid-December. Trend analysis indicated no trend for all the various dry spell lengths except for Thohoyandou with a decreasing trend and Sigonde with a weak increasing trend in long dry spells. Such findings can be used to describe drought conditions for improvement of agricultural productivity and food security, in a given area.

Long-term changes and variability in rainfall and streamflow in Luvuvhu River Catchment, South Africa

We investigated long-term changes and variability in daily rainfall and streamflow in the Luvuvhu River Catchment, South Africa. Changes and variability in rainfall and streamflow impact on available water resources and the allocation of these resources. Daily rainfall data for six stations and daily streamflow data for four stations for the period 1920/1921–2005/2006 were grouped into cycles of 5 and 10 years. Daily means and standard deviations were computed for each cycle. Standard deviation was used to define the rainfall and streamflow variability. Linear regression was used to compute trends in 5- and 10-year average rainfall and streamflow and their standard deviations. Paired two-tailed t-tests (significance level of 0.05) were carried out to verify the spatial variability of rainfall and streamflow in the study area. Mann–Kendall and linear regression were used to determine trend analyses based on long-term annual rainfall and streamflow data. All but two rainfall stations showed decreasing trends in 5- and 10-year mean rainfall; 10-year mean daily rainfall showed decadal rainfall fluctuations. Contrasting trends were observed in 5- and 10-year mean streamflow, indicating that other factors such as anthropogenic activities and impoundments could be impacting on streamflow. Trend directions identified from Mann–Kendall and linear regression analyses of long-term annual rainfall and streamflow were similar to those identified by linear regression of 5- and 10-year mean daily rainfall. Results of paired two-tailed t-tests verified the spatial variability of rainfall and streamflow in the study area. We have shown that the variability of rainfall and streamflow has increased in the Luvuvhu River Catchment over the 86-year study period.