Cover crops are increasingly used in citrus production systems to improve soil health, reduce weed pressure and enhance fruit yield and quality. While the benefits of integrating cover crops into orchard management have been widely reported in several countries, information on their use under South African citrus-growing conditions remains limited. Therefore, this study was undertaken to investigate the influence of different cover crop species on soil organic carbon, weed biomass and citrus fruit yield under two cover crop termination practices, namely slashing and non-slashing. The cover crop treatments consisted of vetch, medics, oats and an untreated control without cover crops. The experiment was established as a split-plot arrangement within a randomized complete block design with six replications. Cover crop species constituted the main plot factor, while termination method was assigned to sub-plots. Soil was sampled before planting cover crops and one year after planting cover crops. Cover crop and weed dry weight samples were collected during the termination stage and fruit weight measurements were taken at harvest. Legume cover crops significantly increased Soil Organic Carbon (SOC) in the 0–30 cm soil depth, with vetch recording the highest SOC (0.6–0.8%), representing an increase of approximately 0.14% compared with oats. No significant SOC differences were observed at the 30–60 cm depth. Weed biomass declined markedly over time, from more than 1.4 t ha−1 in 2021/22 to less than 0.6 t ha−1 in 2022/23. Oats provided the greatest weed suppression, reducing weed dry weight to approximately 0.10 t ha−1 in 2022/23, whereas the control treatment consistently recorded the highest weed biomass. Cover crop biomass was highest under oats in 2021/22 (1.50 t ha−1), while excessive rainfall in 2022/23 reduced biomass production across treatments. Termination methods did not significantly influence weed biomass or cover crop biomass. Citrus fruit yield was not significantly affected by either cover crop species or termination method during the short-term study period. The findings indicate that legume cover crops improve SOC, while oats are more effective for weed suppression in lemon orchards. However, longer-term studies are needed to determine whether these soil and weed management benefits translate into increased citrus productivity.

The cultivation of Japanese plums (Prunus salicina Lindl.) in South Africa has increased over the years, yet their water use is unknown. Their cultivation in the Western Cape Province of South Africa is highly dependent on supplementary irrigation, indicating their high water use demand. This study used remote sensing techniques to estimate the actual evapotranspiration (ETc act) of the Japanese plums to assess their water use on a large scale. The accuracy of the procedure had to be validated before getting to tangible conclusions. The eddy covariance was used to measure ETc act in an African Delight plum orchard to validate the FruitLook remote sensing data for the 2023–2024 hydrological year and irrigation season. The seasonal and annual plum crop water requirements measured using the eddy covariance system were 751 and 996 mm, while those estimated by FruitLook were 744 and 948 mm, respectively. Although FruitLook slightly underestimated plum ETc act by a Pbias of −6.15%, it performed well with a Nash–Sutcliffe efficiency (NSE) of 0.91. FruitLook underestimated evapotranspiration mainly during the peak summer season with full vegetation cover when the model may inaccurately represent irrigation impacts, soil moisture availability, and localized advection effects, better captured by the eddy covariance system. Based on the results, FruitLook proved to be sufficiently accurate for large-scale applications to estimate evapotranspiration in Japanese plum orchards in the Western Cape.

The best management practices for cover cropping in citrus orchards, particularly in terms of species selection and termination methods, remain unclear. This study assessed the short-term effects of different cover crop species (vetch, medics and oats) and termination methods (slashed vs. non-slashed) on soil pH and enzyme activities (β-glucosidase, acid phosphatase, and urease) in a citrus orchard with sandy soil. A randomized complete block design with a factorial treatment structure and six replications was used. Soil samples were collected before and one year after cover crop establishment. The results showed that cover cropping increased soil pH from 5.42 to 6.00 after one year. However, no statistically significant differences were observed in soil pH or enzyme activities among cover crop species or termination methods. Marginal increases in enzyme activities were observed under leguminous cover crops, and these changes were insufficient to indicate strong treatment effects. Correlation and principal component analyses revealed that soil enzyme activities were more strongly influenced by soil properties (depth, carbon content and moisture) than by cover crop species or termination methods. These findings suggest that, under sandy soil conditions and within a one-year period, cover cropping has limited immediate effects on soil biological indicators in citrus orchards. Longer-term studies are recommended to assess cumulative impacts.

The Breede Gouritz Water Management Area is critical for the agricultural and forestry industries, tourism, and property development. It is imperative to understand climate and related variable trends, groundwater depth and land cover trends, especially the interworking of these variables, which was the aim of this study. The catchment was divided into different climate and land cover subregions. A change detection analysis was utilized for four selected subregions, and the best models, according to the evaluation metrics, were used to forecast each variable into the near future. Relationships between variables were statistically correlated and compared to land cover trends. Results show that more arid/semi-arid areas expect temperature increases, evapotranspiration decreases, and precipitation decreases, rendering groundwater resources vulnerable. The temperate subregions to the West show mixed temperature trends and no trends in precipitation. Evapotranspiration is expected to increase. A rise in groundwater depth is expected in the near future, where increased precipitation is also expected. The impact of development in the entire subregion is already visible, with the possibility that urbanization and agricultural expansion could lead to diminishing wetlands and forests. Careful planning and consideration regarding groundwater resource management must be made, especially for vulnerable areas north and Northeast of the study area.

This paper investigated sectoral water use and trends in the Mzimvubu to Tsitsikamma Water Management Area 7 (WMA7). The investigation considered the Water Authorisation and Registration Management System (WARMS) database and field surveys as a source of water use information. The study was able to successfully make use of time series statistical analysis to show water use trends for identified priority sectors over a 5-year period by sourcing historical water use data of the study area. Further, the groundwater stress index and streamflow impact were applied to assess water use impacts on the surface and groundwater. The WARMS database and field survey results identified major sectoral water users such as agriculture (irrigation), municipal water services, dam storage, afforestation, power generation, recreation, mining, and industries. Study findings revealed that the agricultural sector is a major water user, with an estimated 60% of the total water requirement over a 5-year period (2018 to 2022). The application of the groundwater stress index revealed that the majority of the Quaternary catchments have surplus groundwater available. The application of streamflow impact revealed that the majority of catchments have low flow or no flow. The rise of water use clearly indicates a lack of water use compliance and enforcement. An increase in total water use could put water resources under stress, including an impact on the aquatic ecosystem, reduced water quality, and economic and social consequences. Therefore, the study recommends that a follow-up on compliance of surface water and groundwater use licenses be regularly conducted.

The current paper determined water resource classes and Resource Quality Objectives (RQOs) for significant water resources in the Mzimvubu to Tsitsikamma Water Management Area 7 (WMA7) to facilitate sustainable use of the water resources while maintaining ecological integrity. A novel stepwise quantitative and qualitative method was developed to ensure water resource protection in the study area. The methodological approach is proposed as a model framework that could be adopted as guideline and transferable to other catchments in the implementation of Resource Directed Measures (RDMs). The method used water quality and quality components of water resources to determine the classes and RQOs. The study's major findings were that nineteen Integrated Units of Analysis (IUAs) were delineated, and ninety-five Resource Units were identified and prioritized for both surface and groundwater. Driving water quality variables (nutrients, electrical conductivity, and Escherichia coli) were observed and primary water users (irrigation, settlements, and wastewater treatment works) were identified per Integrated Units of Analysis. Five water resource scenarios were developed and evaluated to capture a likely water resource condition for the present and future. The scenario analysis showed impact is expected under any of the operational scenarios assessed at selected reaches. The water resource classes were determined, with eleven IUAs classified as Class lll, seven IUAs as Class ll, and one IUA as Class l. Water quality and quantity RQOs were set to ensure that both river and groundwater resources are compliant and protected. Therefore, the study recommends that this methodological framework, where classes and RQOs were determined, needs to be implemented and tested.

Groundwater resources are changing under the current climate change trajectory. Mitigation and adaptation measures include understanding the inter-working relationships among all climate variables and water resources, specifically groundwater, since it has less direct impacts than surface waters due to its nature. The Breede Gouritz Water Management Area provides an interesting platform to assess these interdependencies, since they have not been assessed before. To assess any underlying dependencies, a multivariate analysis of independent variables including monthly average temperature, summative precipitation, and average evapotranspiration, and a dependent monthly variable, i.e., average groundwater depth, from 14 boreholes was conducted. Moreover, a groundwater depth near-future prediction for each relevant borehole was made. The Multiple Linear Regression model was chosen as the appropriate one since it is cost- and time-effective, entry-level, easy to interpret, and provides a simple and basic understanding of the relationship dependencies. The Kruskal-Wallis test was also performed to elaborate on findings from the Multiple Linear Regression models. Simple linear models incorporating independent and dependent variables can only account for up to 41.7% of the variation in groundwater depth. Groundwater depth is mainly influenced by temperature and evapotranspiration and is expected to be lower for ten dependent variables. The more arid regions in the study area can expect groundwater depth to lower soon and need to use alternative water resources. The temperate west of the study area could expect more favorable outcomes regarding groundwater depth in the near future. Incorporating more variables and using a multi-modal approach to combat non-linear relationships is recommended in future.

South Africa is considered one of the driest countries, and its water insecurity challenges are exacerbated by climate change and variability, depletion, and degradation, among other factors. The challenges of water insecurity are exacerbated by some of the introduced crops, like the Japanese plums (Prunus salicina Lindl.) grown in South Africa, as they consume a lot of water. The Japanese plums are grown under irrigation to supplement low and erratic rainfall in the country. There is little information on the water requirements of Japanese plums (particularly in water-scarce regions), a gap addressed by this study. Therefore, the study aims to quantify and compare the seasonal water use of high-performing, full-bearing Japanese plum orchards under drip and micro-sprinkler irrigation in the Western Cape Province, using readily available satellite data from the FruitLook platform. The seasonal water use volumes of selected plum orchards were compared at provincial and farm scales. At a provincial scale, micro-sprinkler-irrigated orchards consumed significantly more water (up to 19%) than drip-irrigated orchards, whilst drip-irrigated orchards experienced an average 38% greater water deficit. Results were more variable at the farm scale, which was attributed to the influence of site-specific soil, climate, and crop conditions on the performance of the irrigation methods. Therefore, a blanket approach cannot be used when selecting an irrigation method and design. Instead, a case-by-case approach is recommended, which takes into account the root distribution, soil texture, and planting density, among other factors. The generated knowledge facilitates allocating and licensing water resources, developing accurate irrigation scheduling, and promoting improved water use efficiency.

Japanese plums have relatively high water requirements, which depend on supplementing rainfall volumes with accurately quantified irrigation water. There is a lack of knowledge on the seasonal water requirements of plum orchards. This gap in the literature poses an imminent threat to the long-term sustainability of the South African plum industry, which is particularly plagued by climate change and diminishing water resources. The systematic literature review conducted in this study aimed to provide a foundation for supporting water management in irrigated Japanese plum [Prunus salicina Lindl.] orchards. Seventeen peer-reviewed articles obtained from the literature were analyzed. Approximately 66% of the cultivars were cultivated under different regulated deficit irrigation regimes for water-saving purposes and to increase fruit quality. This review of our knowledge provided benchmark figures on the annual water requirements of Japanese plums. The full-year plum crop water requirements obtained from the literature ranged between 921 and 1211 mm a−1. Canopy growth, pruning and growing season length were the most common causes of differences in the water requirement estimates. Further research is required to measure the water requirement of plums from planting to full-bearing age and the response of plum trees to water stress, especially in the South African context.

This paper assessed and evaluated the river and groundwater quality of five major catchments in the Mzimvubu to Tsitsikamma Water Management Area (WMA7). The river assessment and evaluation considered the present state maximum, minimum and mean seasonal values of physiochemical parameters (EC, NO3 + NO2, Cl, pH, NH4-N, PO4-P and Mg). The study was able to successfully make use of statistical analysis and a water quality index in order to explain seven-year trends and the present state of all five catchments within the study area. The statistical analysis results showed that water quality parameters such as PO4, NH4 and NO3 + NO2 were not complying with the South African Water Quality Guidelines (SAWQG) limits, suggesting that the study area was impacted by anthropogenic activities such as agriculture, sewage works, etc. The application of WQI showed that the Gamtoos catchment was in a good water quality state (49.71) while the other four catchments were in a poor to very poor state, according to the WQI classification. Based on the groundwater quality assessment, the physicochemical parameters (NH4, EC, Ca, NO3 + NO2, pH, Na, Cl, Mg, F, K, SO4 and CaCO3) were selected and the main parameters of concern were EC (salinity), NO3 + NO2 and SO4. However, groundwater assessment revealed that groundwater quality was chemically suitable for drinking purposes in most parts of the study area. Therefore, the study recommended resource-directed measures to improve surface and groundwater resource protection, especially in areas where surface and groundwater quality for other uses remains a challenge. Further, strong water resource compliance monitoring and enforcement to control water resource pollution sources is critical.

Non-perennial rivers (NPRs) have three hydrological states; each state has its importance, function and implication for water resource management. The dynamics of these states have been inadequately assessed and understood. Hence, this study sought to determine the spatiotemporal variations in the hydrological conditions of NPRs, focusing on the Touws River–Karoo drylands and Molototsi River within the semi-arid region of the Limpopo Province of South Africa. Additionally, the study aimed to delineate and characterize the primary areas contributing to runoff in these two river systems. Sentinel-1 and Sentinel-2 satellite data sources were employed in this study. Specifically, the modified normalized difference water index (MNDWI) derived from Sentinel-2 was utilized to delineate water surface areas along the two rivers. Subsequently, these derived datasets were utilized to assess the hydrological states over a 32-month period (2019–2022). Based on the presence of water, the river's state was classified as flowing, pooled, or dry. The results showed that remote sensing can be used to determine the hydrological state of the two river systems with ~90% overall accuracy. However, there is about a 30% chance that a flow event can be missed using Sentinel-2 due to clouds and temporal resolution. Some of these gaps can be filled using synthetic aperture radar (SAR) data (Sentinel-1), as demonstrated with the Molototsi River. In the Molototsi catchment, the upper catchment contributes the majority of flows. For the Touws River, the southwestern part of the catchment was determined as the major contributing area for the observed flows. This suggests that the chosen observation site might not be representative of upper catchment dynamics; therefore, a monitoring site in the upper catchment is required. This study provided hydrological information and an approach that can be used to monitor the hydrological states for better understanding and management of NPRs and catchments.

Cover crops are used in sustainable agricultural practices to improve soil quality and minimise the effect of climate change, water restrictions and drought. The South African citrus industry produces and exports a diverse range of citrus fruits; however, knowledge of cover crops in citrus orchards in South Africa is limited. This review focuses mostly on evaluating cover crop selection, effects on the soil microbial community, weed control, citrus yield and fruit quality. In terms of cover crop selection, legumes seem to be preferred over non-legume cover crops. The reviewed literature reported that legume cover crops increased nitrogen by 67 to 209 kg N ha-1 through the nitrogen fixation process. Additionally, the cultivation of legume cover crops substantially improved the cost savings of nitrogen fertiliser. The fruit yield improved by 7.6 to 64%, while fruit quality improved by 2.3 to 12.4% fruit weight and 2.4 to 5.8% Bx. This demonstrates that the benefits of cover crops to South African citrus growers include improved soil quality and fruit yields and decreased costs.

Japanese plum (Prunus salicina) farming in the Western Cape (South Africa) is an important industry for the export market and job creation and is a large water user; however, adequate information on water requirements of this crop is not available in this semi-arid area. The objective of this study was to determine seasonal plum water requirements for the purpose of water use planning and allocation. The study made use of experimental data from four fully bearing, high-yielding plum orchards (cv African Delight and Fortune) in two major plum production regions (Robertson and Wellington). Crop water requirements and the soil water balance were modelled with the physically based HYDRUS-2D model. Seasonal crop water requirements were estimated to be between 524 mm (cv Fortune in Wellington) and 864 mm (cv African Delight in Robertson). Initial basal crop coefficients (Kcb) ranged between 0.98 and 1.01, whilst Kcb for the mid-stage averaged between 1.11 (cv African Delight in Robertson) and 1.18 (cv Fortune in Wellington). Modelling scenarios indicated that soil water redistribution beyond the root zone continues at reduced rates after the soil dries to levels below field capacity. Irrigation management needs to be balanced with other farming practices to reduce leaching and impacts on water resource quality, as well as with the economics of the farm.

Rural areas in Limpopo Province (South Africa) are in urgent need of interventions for safe and secure water supply to adapt to climatic changes and the increased frequency of droughts. A feasibility study was conducted for the adoption of solar-powered groundwater pumping systems and Multiple Water Use Services (MUS) in Greater Giyani Municipality (Limpopo). Stakeholder engagement, geotechnical data and socio-economic information were used in the feasibility study. The Solar Powered Irrigation Systems (SPIS) tool (GIZ and FAO, 2021) was used to design solar-powered shallow groundwater pumping systems at nine case study sites: four villages (water supply for domestic use) and five small-scale farms. Given the technical design configurations, peak water requirements ranged from 28.8 to 58.9 m(3)/d, peak power requirements from 1.2 to 3.4 kWp and required solar panel surface areas from 8.0 to 22.3 m(2). Viable financial mechanisms for the operation and maintenance of MUS are leasing, cooperatives, informal saving groups and pay-per-use. The adoption of the technology appears to be financially and technically viable to augment the water supply. However, groundwater levels will have to be monitored and water purification plants for drinking water will have to be established to ensure long-term sustainability.

Japanese plums form part of a multi-billion rand deciduous fruit industry in South Africa. Despite this, there is a paucity of knowledge on the seasonal water requirements of plum orchards. In a time of changing climatic conditions and diminishing water resources, this gap in literature poses an imminent threat to the long-term sustainability and global competitiveness of the South African plum industry. Therefore, this paper aimed to provide a review of the available literature on the crop water requirements of full-bearing well-irrigated Japanese plum orchards for improved agricultural water management. Full-year water requirements for well-watered full-bearing Japanese orchards ranged between 921 and 1 211 mm a-1 with a mean value of 1 084 ±140 mm a-1. Canopy growth and pruning appeared to be the most common causes of differences in water requirement estimates. Growing season length also plays a role with late-season maturing orchards having higher water requirements than their early and mid-maturing counterparts. The knowledge review provided benchmark figures for the annual water requirements of Japanese plums. However further research is required to determine the water requirement of plums from planting to full-bearing age and the response of plum trees to water stress, in a South African context.

Inaccurate crop coefficients are major contributing sources of uncertainty that lead to inefficient use of limited available water resources. Understanding the need to improve water use efficiency in South Africa’s fruit industry, this study evaluated the method of deriving crop coefficients developed by Allen and Pereira (2009) over a variety of irrigated fruit tree crops. Detailed data of transpiration, evapotranspiration and weather variables measured using the heat ratio method, eddy covariance method and automatic weather stations, were collected from a water research funding body established by the South African government. This study adjusted the stomatal sensitivity function (Fr) in the model by replacing the ratio of the leaf resistance (rl) to the standard leaf resistance of a reference crop (100 sm−1) with rl/α where α is a resistance parameter for the specific crop. The resistance parameter was solved accordingly for each fruit type. Respective unique α values were obtained as: macadamia nuts (200 sm−1), citrus (50 s m−1), peaches (20 s m−1) and pecans (20 s m−1). These unique values were used to simulate basal and single crop coefficients that produced satisfactory results when compared to the actual measured values. Overly, no unique standard α value exists for most tree crops although a value close to 20 sm−1 may give reasonable estimates for pome and stone fruit. Crop coefficients derived using locally measured data were standardised and tabulated in a format that facilitates their transferability between sites. However, there is still a need to acquire crop specific information to parameterize α and improve accuracies.

Climate and land use change (CLUC) impact studies on water and groundwater resources have evolved in recent years. To determine whether all research gaps have been or are being addressed through the current intellectual structure, a bibliometric analysis, as well as a record review, was enacted to determine the intellectual structure of CLUC impacts on water resources, with a particular focus on the implications for groundwater resources research in the Breede Gouritz Water Management Area (BGWMA) in South Africa. Methods applied included publication-related trends and science mapping. This study found that CLUC impact research being published has increased by 600% between 2014 and 2021, localised research is being done in 95 countries, and land use change (LUC), specifically urbanisation, is being considered more often as a variable. However, a few gaps in the research remain, including smaller spatiotemporal scales in more locations, a stronger focus on LUC in all its forms, LUC versus climate change (CC) impact studies, and multi-modal approaches to related research. CLUC impacts on water and groundwater resources research have made significant progress over the years, but more research is necessary to make this a robust area of research.

Machine learning and deep learning have demonstrated usefulness in modelling various groundwater phenomena. However, these techniques require large amounts of data to develop reliable models. In the Southern African Development Community, groundwater datasets are generally poorly developed. Hence, the question arises as to whether machine learning can be a reliable tool to support groundwater management in the data-scarce environments of Southern Africa. This study tests two machine learning algorithms, a gradient-boosted decision tree (GBDT) and a long short-term memory neural network (LSTM-NN), to model groundwater level (GWL) changes in the Shire Valley Alluvial Aquifer. Using data from two boreholes, Ngabu (sample size = 96) and Nsanje (sample size = 45), we model two predictive scenarios: (I) predicting the change in the current month’s groundwater level, and (II) predicting the change in the following month’s groundwater level. For the Ngabu borehole, GBDT achieved R2 scores of 0.19 and 0.14, while LSTM achieved R2 scores of 0.30 and 0.30, in experiments I and II, respectively. For the Nsanje borehole, GBDT achieved R2 of −0.04 and −0.21, while LSTM achieved R2 scores of 0.03 and −0.15, in experiments I and II, respectively. The results illustrate that LSTM performs better than the GBDT model, especially regarding slightly greater time series and extreme GWL changes. However, closer inspection reveals that where datasets are relatively small (e.g., Nsanje), the GBDT model may be more efficient, considering the cost required to tune, train, and test the LSTM model. Assessing the full spectrum of results, we concluded that these small sample sizes might not be sufficient to develop generalised and reliable machine learning models.

Water is a fundamental requirement for human, animal, and plant survival. Despite its importance, quality water is not always fit for drinking, domestic and/or industrial use. Numerous factors such as industrialization, mining, pollution, and natural occurrences impact the quality of water, as they introduce or alter various parameters present therein, thus, affecting its suitability for human consumption or general use. The World Health Organization has guidelines which stipulate the threshold levels of various parameters present in water samples intended for consumption or irrigation. The Water Quality Index (WQI) and Irrigation WQI (IWQI) are metrics used to express the level of these parameters to determine the overall water quality. Collecting water samples from different sources, measuring the various parameters present, and bench-marking these measurements against pre-set standards, while adhering to various guidelines during transportation and measurement can be extremely daunting. To this end this study proposes a network architecture to collect data on water parameters in real-time and use Machine Learning (ML) tools to automatically determine suitability of water samples for drinking and irrigation purposes. The developed monitoring network is based on LoRa and takes the land topology into consideration. Results of simulations done in Radio Mobile revealed a partial mesh network topology as the most adequate. Due to the absence of large and open datasets on drinking and irrigation water, datasets usable for training ML models were developed. Three ML models - Random Forest (RF), Logistic Regression (LR) and Support Vector Machine (SVM) were considered for the water classification process and results obtained showed that LR performed best for drinking water, while SVM was better suited for irrigation water. Recursive feature elimination was then combined with the three ML models to reveal which of the water parameters had the greatest influence on the classification accuracies of the respective model.

Study region: The Touws River in the Klein Karoo region of South Africa Study focus: This study sought to improve the understanding of pool dynamics along non-perennial rivers (NPRs) by utilising the water balance approach to assess the water fluxes that influence pool dynamics in the Touws River. The water balance model made use of various in-situ and satellite-derived data.New hydrological insights: The analysis of the water losses from the pool showed that most of the water was lost through evaporation. The interaction between the pool and groundwater is dependent on the water levels, as the pool loses water to the subsurface up to a certain depth then it starts gaining. When the Wolverfontein 2 pool is full, it can retained water for approximately 258 days without having a surface water inflow. A water balance model was established, and it simulated the water levels with a high correlation of 0.9. This model was also evaluated in the neighbouring pools, and while it simulated the water levels of the upstream pool well, this was not the case for the downstream pool. When remote sensing-derived rainfall and evaporation data were used in the model, the simulated water levels had a slightly lower correlation of 0.7 with the observed water levels. Overall, the remotely sensing-based monthly fluxes estimates could not provide the detailed pool information that was required for the water balance. Errors may have arisen, or they may have been inherited, from any of the three remotely-sensed parameters, namely, the surface area, the rainfall or the evaporation. Although remote sensing did not provide detailed information, it is worth noting that it provides baseline information on the pool dy-namics. Overall, this work underscores the relevance of multisource data and the water balance, it helps to better understand the pool dynamics and it will help with the better management of NPRs.