Institute for Soil, Climate and Water

Chemical methods are reliable for soil testing, but they can be both time-consuming and expensive. This reason makes them unsuitable for quick analysis, especially for many soil samples. Infrared spectroscopy is a cutting-edge technique that offers promising alternative methods that are fast, cheaper, and environmentally friendly. Research findings show contradicting accuracy levels for the infrared protocol when predicting phosphorus (P) and potassium (K). For this reason, the study employed meta-analysis to investigate the effect of selected factors on the prediction accuracy of P and K. Studies that tested P and K in the laboratory using the protocol were selected. The results showed that concentration and soil sample size can significantly (p < 0.001) affect the prediction accuracy of these plant-available nutrients. A positive correlation was observed between the coefficient of determination (r2), sample size (r2 = 0.75 P, r2 = 0.68 K), and concentration (r2 = 0.62 P, r2 = 0.64 K). The variation observed in the dependent variable (r2) was explained mostly by sample size and concentration. This could be the source of the overall low prediction accuracy observed from the studies [r2 = 0.46, RPD = 1.44 (P) and r2 = 0.55, RPD = 1.55 (K)].

Opencast coal mining has devastated the grassland biomes in the Mpumalanga Province of South Africa. A rain-fed rehabilitation trial on mechanically reconstructed soil, following strip coal mining, was conducted to demonstrate that the post-mining landscape can be returned to sustainable land use. Information is lacking on the interactive effects of rainfall, soil and vegetation properties as a function of rehabilitation procedures. Hence, various rehabilitation treatments and topsoils were evaluated over three seasons, using a grass mixture comprising of annual and perennial species. Trial measurements included soil properties, as well as the growth and chemical composition of the grass stand. Statistical significance was observed for most measurements as a result of the treatments. A large variation in grass nutrient properties was observed as a result of treatment effects. A decreasing trend in canopy nutrient content over time was found. This study of soil-plant nutrient relationships revealed that low canopy nutrient contents were a consequence of insufficient soil nutrient levels. The monitoring of soil fertility and plant properties should be a prerequisite in any rehabilitation study, and soil fertility should be maintained to support sustainable plant growth. Trials on different soils and in different rainfall regions, with increased topsoil thickness, should be considered.

The purpose of this study was to monitor and compare the growth and productivity of maize/beans sole and inter-cropping systems under conventional (CON) and in-field rainwater harvesting (IRWH) tillage practices. During the typical drought conditions of the 2018/19 growing season, seven homestead gardens of smallholder farmers (four in Paradys and three in Morago villages) in the Thaba Nchu rural communities of South Africa were selected for on-farm demonstration trials. Two tillage systems CON and IRWH as the main plot and three cropping systems as sub-treatment (sole maize and beans and intercropping) were used to measure crop growth and productivity parameters. The results showed that IRWH tillage had significantly higher above-ground dry matter for both sole maize (29%) and intercropped maize (27%) compared to CON treatments. The grain yield under both tillage systems showed that IRWH-Sole >> IRWH-Ic >> CON-Sole >> CON-Ic, with values ranging from 878.2 kg ha−1 to 618 kg ha−1 (p ≤ 0.05). The low harvest index values (0.21–0.38) could have been due to the effect of the drought during the growing season. The results of precipitation use efficiency (PUE) showed that the IRWH tillage was more effective at converting rainwater into maize biomass and grain yield compared to CON tillage. However, the different cropping systems did not show a consistent trend in PUE. During the growing season, the PUE for AGDM varied for different tillage and cropping system treatments in Morago and Paradys. For maize, it ranged between 10.01–6.07 and 9.93–7.67 kg ha−1, while for beans, it ranged between 7.36–3.95 and 7.07–3.89 kg ha−1 mm−1. The PUE for grain yield showed similar trends with the significantly highest values of PUE under IRWH tillage systems for the Morago sites, but there were no significant differences at the Paradys site in both tillage and cropping systems. There is a critical need, therefore, to devise alternative techniques to promote an increase in smallholders’ productivity based on an improved ability to capture and use resources more efficiently.

The utilisation of water hyacinth for production of biogas is considered to be a solution to both its control and the global renewable energy challenge. In this instance, an investigation was conducted to evaluate the potential of water hyacinth inoculum to enhance methane production during anaerobic digestion (AD). Chopped whole water hyacinth (10% (w/v)) was digested to prepare an inoculum consisting mainly of water hyacinth indigenous microbes. The inoculum was incorporated in the AD of freshly chopped whole water hyacinth to set up different ratios of water hyacinth inoculum and water hyacinth mixture with appropriate controls. The results of batch tests with water hyacinth inoculum showed a maximal cumulative volume of 211.67 ml of methane after 29 days of AD as opposed to 88.6 ml of methane generated from the control treatment without inoculum. In addition to improving methane production, inclusion of water hyacinth inoculum reduced the electrical conductivity (EC) values of the resultant digestate, and, amplification of nifH and phoD genes in the digestate accentuates it as a potential soil ameliorant. This study provides an insight into the potential of water hyacinth inoculum to enhance methane production and contribute to the feasibility of the digestate as a soil fertility enhancer.

Ecological restoration efforts at scale have been shown to play an important role in reducing human impact on the environment, improving climate change adaptation and halting extinctions globally. Upscaling restoration efforts requires funding, and therefore evidence of the benefits of restoration is needed. This study aims to contribute towards addressing these gaps by: (1) bolstering the evidence base of the water-related impacts of investment into ecological restoration by improving the methods of predicting the streamflow impacts of alien tree clearing; and (2) exploring the potential size of the variability in catchment responses at a fine-scale (60x60m) in one particular region by comparing four different neighbouring catchments. We model the impacts on streamflow in four strategic water providing catchments using the fully-distributed MIKE-SHE modelling tool. We find that the benefits of clearing mature infestations of alien trees, such as pines, from naturally tree-less ecosystems can increase available surface water resources by 15.1 to 29.5%. Clearing riparian invasions is predicted to have a 1.7 times greater impact compared to terrestrial (non-riparian) invasions. The largest modelled impact of restoration on streamflow is on the mid to low flows, and this impact is greater in dry years relative to wet years. The findings are novel in that they shed light on the types of spatial uncertainties that can be expected in modelled gains, with implications for generalisation. These findings are important for leveraging investment to upscale restoration efforts in water scarce regions, as they suggest improved water security during the dry season and droughts. Upscaling efforts is essential if the degradation of ecosystems globally is to be prevented, halted and reversed, as proposed by the United Nations Decade on Ecosystem Restoration.

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.

In arid environments of the world, particularly in sub-Saharan Africa and Asia, floodplain wetlands are a valuable agricultural resource. However, the water reticulation role by wetlands and crop production can negatively impact wetland plants. Knowledge on the foliar biochemical elements of wetland plants enhances understanding of the impacts of agricultural practices in wetlands. This study thus used Sentinel-2 multispectral data to predict seasonal variations in the concentrations of nine foliar biochemical elements in plant leaves of key floodplain wetland vegetation types and crops in the uMfolozi floodplain system (UFS). Nutrient concentrations in different floodplain plant species were estimated using Sentinel-2 multispectral data derived vegetation indices in concert with the random forest regression. The results showed a mean R2 of 0.87 and 0.86 for the dry winter and wet summer seasons, respectively. However, copper, sulphur, and magnesium were poorly correlated (R2 ≤ 0.5) with vegetation indices during the summer season. The average % relative root mean square errors (RMSE’s) for seasonal nutrient estimation accuracies for crops and wetland vegetation were 15.2 % and 26.8%, respectively. There was a significant difference in nutrient concentrations between the two plant types, (R2 = 0.94 (crops), R2 = 0.84 (vegetation). The red-edge position 1 (REP1) and the normalised difference vegetation index (NDVI) were the best nutrient predictors. These results demonstrate the usefulness of Sentinel-2 imagery and random forests regression in predicting seasonal, nutrient concentrations as well as the accumulation of chemicals in wetland vegetation and crops.