Research Articles (Earth Sciences)

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Mapping human fatalities from megafauna to inform coexistence strategies
(Scientific Reports, 2025) Mpakairi, Kudzai Shaun; Kavhu, Blessing; Mutema, Courage
Human fatalities from human–wildlife conflict (HWC) represent a critical dimension of conservation, often triggering retaliatory actions and post-traumatic stress in affected communities. However, most studies focus on the economic implications of HWC, neglecting human fatalities which may have far-reaching long-term implications. This study investigates the spatial and temporal patterns of human fatalities caused by megafaunal species in Zimbabwe, using data collected from 2016 to 2022. Through spatial and statistical analyses based on the Getis-Ord Gi* hotspot analysis and Mann–Kendall trend test, we assess fatalities caused by six megafaunal species: Nile crocodile (Crocodylus niloticus), African elephant (Loxodonta africana), hippopotamus (Hippopotamus amphibius), African buffalo (Syncerus caffer), African lion (Panthera leo) and spotted hyena (Crocuta crocuta). The results of the study showed that crocodiles and elephants account for over 80% of human fatalities in Zimbabwe. These fatalities also significantly increased over the study period (p < 0.03). In contrast, fatalities involving lions, hyenas, hippos, and buffaloes showed no significant increase, indicating more stable but still concerning risks. Fatality hotspots were concentrated in Kariba, Binga and Hwange districts in northern and western Zimbabwe, highlighting areas needing urgent interventions. These insights have broader implications for HWC management across Africa, where megafaunal species frequently interact with human populations. By adopting data-driven, species-specific strategies, other countries facing similar conflicts can foster human–wildlife coexistence and improve conservation outcomes.
Assessing CO2 storage potential in a structurally complex depletedgas reservoir, offshore South Africa
(Elsevier Ltd, 2025) Mhlambi, Sanelisiwe; Agbor, Fritz Ako; van Bever Donker, Jan M
As global efforts to mitigate greenhouse gas emissions intensify, carbon capture and storage (CCS) has emerged as a key strategy for reducing the environmental impact of fossil fuel use. However, geological storage of CO₂ in structurally complex and heterogeneous reservoirs presents a range of issues due to the geological intricacies, with implications for storage capacity estimation, CO₂ injection, migration, and even long-term containment, which pose environmental risks. Therefore, this study assesses the CO₂ storage potential of the depleted F-O Gas Field in the Bredasdorp Basin, offshore South Africa, using a robust modelling approach based on the analysis of a suite of exploration and production datasets from the field. A high degree of structural compartmentalisation with a fault-bounded anticlinal trap characterises the field. The Valanginian-age marine sandstone reservoirs exhibit low to moderate porosity and permeability. In total, a CO₂ storage capacity of 185.3 Mt was determined for the F-O gas field, which reduces to 37.1–74.1 Mt after accounting for reservoir heterogeneity and sweep efficiency. This reduction reflects the impact of the field's complex structural architecture, variable facies distribution, and petrophysical variability, which collectively limit the effective pore volume accessible for CO2 storage. By rigorously integrating the structural architecture of the field, sedimentary processes, facies distribution, and petrophysical variability of the candidate reservoir, this study provides critical insights and strategies into the feasibility of CCS in structurally complex depleted gas fields. Significantly, these findings contribute to ongoing national CCS assessments and support South Africa's long-term decarbonisation agenda.
Estimation of hydrogeological spring catchment area: case of Jinci spring in North China
(Springer Nature, 2025) Xu, Yongxin; Zhang, Zhixiang; Wang, Zhaoliang
Hydrogeological spring catchment area of Jinci spring is the starting point for all hydrogeological analyses and one of the fundamental datasets for karst groundwater modeling. Unfortunately, there is a lack of detailed research on the hydrogeological spring catchment area. To sustainably utilize and protect the karst groundwater resources of Jinci spring, this paper investigates the variation pattern of the spring flow decrease coefficient from 1956 to 1994, estimates the hydrogeological spring catchment area by using the linear regression method and the Turc method. The results show that: (1) The spring flow decrease coefficient generally shows an increasing trend over time, and its variation indicates the time-varying characteristics of the hydrogeological spring catchment area. (2) The hydrogeological spring catchment areas estimated by the linear regression method are 2143, 2084 and 2037 km2, with an average of 2088 km2. (3) The hydrogeological spring catchment area estimated by the Turc method exhibits a series of values, and its time-varying characteristics is the dynamic change with time, resulting from the joint effects of natural and anthropogenic factors. This study provides a theoretical foundation for the protection and management of karst groundwater in the semi-arid region of northern China.
Investigation of water use and trends in South Africa: a case study for the Mzimvubu to Tsitsikamma Water Management Area 7 (WMA7)
(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Jovanovic, Nebo; Mulangaphuma, Lawrence
This paper investigated sectoral water use and trends in the Mzimvubu to TsitsikammaWater 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 waterrequirement 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.
Petrogenetic characterization of La Vasca alkaline complex and its relationship to the Eastern Mexican Alkaline Province
(Elsevier Ltd, 2025) Frei, Dirk; Martínez-Salinas, Edgar; Weber, Bodo
Peralkaline and agpaitic igneous rocks with local eudialyte mineralization have been reported in the La Vasca alkaline complex (LVAC) but no detailed information on its age and relationship to the Eastern Mexican Alkaline Province (EMAP) has been available. We present petrological, geochemical, isotopic, and geochronological data from the LVAC and the surroundings, located in northwestern Coahuila. The main intrusion is composed of ferroan granitoids that are classified by their alumina saturation index into metaluminous and peralkaline. The metaluminous rocks are monzonite and syenite with post-collisional geochemical affinity. Middle Eocene zircon ages of these rocks range between 47.6 ± 0.3 Ma and 45.4 ± 0.3 Ma and are significantly older than other alkaline rocks from the EMAP. The peralkaline rocks are composed of syenite and eudialyte-bearing foid-syenite with intraplate geochemical affinity that probably coevolved with the metaluminous rocks. Both groups show minimal crustal contamination, with affinity to an Ocean Island Basalt mantle source. The LVAC is explained by a similar formation model than other rocks of the EMAP, suggesting its extension into northwestern Coahuila. Furthermore, the eudialyte foid-syenites represent the first occurrence of agpaitic rocks in Mexico
Integrated flood modelling and risk assessment in urban areas: a review on applications, strengths, limitations and future research directions
(Elsevier B.V., 2025) Pakati, Sibuyisele; Dube, Timothy; Shoko, Cletah
Study region: Global scale. Study focus: The purpose of this study is to provide a comprehensive global assessment of urban flood modelling by: (i) critically reviewing the most widely used flood models in urban settings; (ii) synthesizing their operational mechanisms, including the integration of diverse data types and validation techniques; and (iii) evaluating each model’s strengths and limitations in simulating flood dynamics and assessing urban flood susceptibility. Furthermore, the paper establishes a framework for selecting acceptable modelling methodologies for successful flood risk management in real-world urban scenarios. New hydrological insights for the region: Hydraulic-hydrological models, and cloud-based geospatial platforms have been widely applied in flood modelling and risk and vulnerability assessment. Despite these advancements, accurate flood modelling remains a challenge due to limitations in input data quality. Among earth observation tools, radar satellite data was identified as the most effective due to its reliability under cloudy and rainy conditions. Enhancing model accuracy and validation remains possible through the integration of both optical and radar data with hydraulic and hydrological models. For example, radar backscatter intensity can be used to estimate flood depths. However, key research gaps remain, notably, the integration of high-resolution climate projections and socio-economic factors into flood risk models, and the application of modelling tools in poorly planned urban areas to assess real-time changes in land use following flood events.
Development and application of a hybrid terrain–multispectral image model of floodplain hydroperiod
(Springer Science and Business Media B.V., 2025) Grenfell, Michael; Munch, Zahn; Grenfell, Suzanne
Surface water mapping is a crucial aspect of studying river and wetland hydrological, geomorphological, and ecological processes. However, deriving inundation frequency solely from a normalised difference water index does not account for geomorphologically induced flooding dynamics, which reduces model accuracy. This study evaluated spatiotemporal inundation dynamics using a novel approach that combines geomorphologically relevant descriptors from a high-resolution LiDAR-derived digital elevation model with spectral outputs from Sentinel-2 imagery. The hydroperiod for the Nuwejaars River Floodplain was determined by: (1) mapping macro-scale geomorphic features and floodplain topography using a DEM and height above nearest drainage; (2) calculating the percentage of images (127 images with clouds < 20%), in which a particular pixel was flooded using Sentinel-2 imagery (2018 to 2023); (3) applying an unsupervised learning algorithm and thresholding in Google Earth Engine to assign water frequency values to each pixel; and (4) deriving a hydroperiod that integrates geomorphic data and Sentinel-2 imagery to classify inundation patterns (F1 = 0.67, n = 60). Accuracy assessment of the model, incorporating various spectral indices, was performed using a confusion matrix and validated against field data. The terrain-informed hydroperiod model achieved improved accuracy (75.9%), precision (66.7%), and recall (66.7%) statistics. Analysis revealed substantial spatial variation in inundation frequency closely related to floodplain geomorphology, with largest inundation frequencies occurring downstream of a partial avulsion and limited inundation in distal, abandoned channels. The study highlights the importance of integrating hydroperiod mapping with geomorphological insights. This approach is essential for understanding how historical and future changes in hydroperiod affect floodplain ecological processes and ecosystem service provision
Earth observation-based analysis of flood extent and impacts on land use and cover in the Cape Town Metropolitan Region, South Africa
(Elsevier Ltd, 2025) Pakati, Sibuyisele S.; Dube, Timothy; Shoko, Cletah
This work leverages multi-source data spatial approach in mapping floods extents and their effect on key land use land cover in the Cape Town Metropolitan Region, for the 2023 period. Using the Google Earth Engine cloud computing platform, the study mapped flood extent through Sentinel-1 Synthetic Aperture Radar (SAR), and Sentinel 2- Multispectral Instrument (MSI) for landcover classification before and after a flood event. Landcover classification for the period before and after the flood occurrence were performed using the Random Forest (RF) algorithm. To assess the flood-affected categories, the pre-flood image was overlaid on the flood extent spatial layer. The research findings showed that the central and low-lying areas of the Metropolitan area were significantly affected by the floods. A total land area of about 2074 ha(ha) (84.30 %) was affected. Further results showed that floods mostly affected bare areas (32.64 % equivalent to 803.05 ha) and built-up (46.84 % equivalent to 1152.33 ha) areas. The affected built-up areas were mainly located in low-lying regions, near floodplains, and near water bodies. Overall, the findings of the study underscore the importance of spatially explicit techniques in flood mapping and informing early warning systems for disaster preparedness.
Optimally integrating a reservoirs group and a flood detention basin for improving their flood control performance
(Elsevier B.V., 2025) Liu, Dedi; Mu, Zhenyu; Wang, Zhenyu
Jingjiang flood detention basin and Three gorges (TG), Shuibuya (SBY) and Geheyan (GHY) reservoirs are located in the midstream and downstream of Changjiang River Basin. These reservoirs as a group and the flood detention basin are crucial to mitigate the extreme magnitude flood events in the midstream and downstream of Changjiang River Basin. This study proposed an optimal model to integrate the operation of a reservoirs group and flood detention basin rather than the current separately operations for improving their flood control performance. The operation schemes of an FDB sluices are enumerated for exploring the potential start time and end time of operating an FDB. The regulation of a reservoirs group is integrated with the operation of the sluices of an FDB. The impacts of the optimal FDB and reservoirs group flood control schemes on the flood control performance are quantified to gain insights on the difference between the FDB and reservoirs group flood control. The results and discussion indicate that synchronizing the operation of an FDB sluice-gate for the flood peak is better than the traditional rule for reducing the over flood volume. And the more flexible FDB flood control scheme can significantly improve the flood control performance. Therefore, our study will not only propose an optimal model to integrate an FDB and a reservoirs group, but also help to comprehend the mechanism of the reservoirs group and FDB flood control. [Display omitted]. A model to integrate a flood detention basin (FDB) and reservoirs is proposed for improving flood control performance. The impacts of FDB on flood control are quantified to understand the difference between FDB and reservoir flood control. The ways of operating FDB affect flood control performance are explored.
Land use and land cover changes in sub-catchments of Zimbabwe and their implications on wetland and catchment soil water conditions
(Elsevier Ltd, 2025) Dube Timothy; Mupepi Oshneck; Marambanyika Thomas
This study evaluated land use and land cover changes in the Shashe and Tugwi and Zibagwe sub-catchments from 2017 to 2023, with a focus on their impacts on dry season wetland extent and condition. Utilizing the Google Earth Engine Cloud Computing platform, Sentinel-2 Level 1C data were processed using Support Vector Machine (SVM) classification algorithm to analyse these changes. The Soil Moisture Active Passive level 4 (SMAP L4) soil moisture and the Normalised Difference Vegetation Index (NDVI) were computed to determine the influence of catchment level land cover change on soil moisture conditions. This study considered the influence of land cover on wetland conditions and catchment level soil moisture levels which got minimum attention in previous wetland studies. The study highlights that bare land in Tugwi and Zibagwe increased more rapidly (601.1 %) than in the drier Shashe sub-catchment. However, the wetland area decreased more in Shashe, indicating greater wetland degradation despite the slight difference (0.4 %). The analysis revealed that wetlands experienced an overall 11.8 % loss in Shashe and 11.4 % loss in Tugwi-Zibagwe. Results indicate that 5.2 %, 3.4 % and 2.3 % of the wetland area was replaced by grassland, shrubland and bare land respectively in Tugwi and Zibagwe combined whilst 4.8 %, 3.6 % and 2.32 % of the wetland area were replaced by bare land, grassland and shrubland respectively in Shashe. Statistically significant weak positive correlations were confirmed between soil moisture and NDVI in Tugwi and Zibagwe combined (r = 0.28; p = 0.04) and Shashe (r = 0.43; p = 0.02). Rainfall had stronger correlation with soil moisture in Tugwi and Zibagwe (r = 0.43; p = 0.19) and Shashe (r = 0.62; p = 0.38) which were not statistically significant indicating more influence of land cover on soil moisture than rainfall. The findings accentuate the critical need for sustainable land use practices to mitigate the adverse effects on natural land cover and wetland ecosystems. The rapid expansion of bare land and reduction in wetlands underscore the pressing challenges posed by land cover changes, particularly in regions experiencing increasing aridity. •Land use and cover changes in the three sub-catchments are assessed.•The influence of land cover change on wetland extent and soil moisture conditions are analysed.•The relationship between root zone soil moisture and rainfall and land cover change is analysed.
A multi-source data approach to carbon stock prediction using bayesian hierarchical geostatistical models in plantation forest ecosystems
(Taylor and Francis Ltd., 2024) Dube, Timothy; Chinembiri, Tsikai Solomon; Mutanga, Onisimo
Modeling of environmental phenomena is usually confounded by the influence of multiple factors existing at different time and spatial scales. Bayesian modeling is presumed to be the best approach for modeling such complex systems. Using a Bayesian hierarchical inferential framework, we employed a multi-source data approach (i.e. remote sensing derived anthropogenic, climatic and topographic set of variables) to model Carbon (C) stock in a managed plantation forest ecosystem in Zimbabwe’s Eastern Highlands. We therefore investigated how two related multi-data sources of new generation remote sensing derived ancillary information influence C stock prediction required for building sustainable capacity in C monitoring and reporting. Two mainstream models constructed from Landsat-8 and Sentinel-2 derived vegetation indices coupled with climatic and topographic covariates were used to predict C stocks using forest inventory data collected using spatial coverage sampling. A multi-source data driven approach to C stock prediction yielded slightly lower predictions for both the Landsat-8 ((Formula presented.) and the Sentinel-2 ((Formula presented.) -based C stock models than C stock predictions published in related studies. Distance to settlements ((Formula presented.)) and (Formula presented.) are significant predictors of C stock with the Sentinel-2-based C stock model outperforming its Landsat-8 model variant in terms of prediction accuracy. The Sentinel-2-based C stock model resulted in a 1.17 MgCha−1 Root Mean Square Error (RMSE) with a ((Formula presented.) 95% credible interval whilst the Landsat-8-based C stock counterpart gave a 2.16 MgCha−1 RMSE with a ((Formula presented.) associated 95% credible interval. Despite a multi-source data prediction approach to the modeling of C stock in a managed plantation forest ecosystem set-up, the issues of scale still play a major role in modeling spatial variability of natural resource variables. Both climatic and topographic derived ancillary data are not significant predictors of C stock under the present modeling conditions. Accurate and precise accounting of C stock for climate change mitigation and action can best be done at landscape scales rather than local scale as the scale of variation for climate-change-related variables vary at larger spatial scales than the ones utilized in the present study.
Available satellite data for monitoring small and seasonally flooded wetlands in semi-arid environments of Southern Africa
(John Wiley and Sons Ltd, 2024) Gxokwe, Siyamthanda; Dube, Timothy; Mazvimavi, Dominic
Time-series monitoring of wetland eco-hydrological dynamics using remote sensing continues to be an attractive and practical tool, mainly due to its ability to overcome challenges related to in situ data availability. However, acquiring seamless and cloud-free data for accurate and routine wetlands monitoring remains a persistent challenge. In this study, we aimed to evaluate the availability of satellite scenes in the google earth engine (GEE) catalogue that could facilitate the monitoring of eco-hydrological dynamics in small and seasonally flooded wetlands within the semi-arid environments of southern Africa. The study covered a 20-year period from 2000 to 2020, with a specific focus on the Nylsvley floodplain as a case study. The study conducted a comprehensive assessment of available products on the GEE platform, including Landsat thematic mapper (TM), enhanced thematic mapper plus (ETM+), operational land imager (OLI), sentinel-1 and sentinel-2. The identified images underwent rigorous filtering and screening based on varying cloud-cover percentages (0%, 1%–10%, 11%–25% and 26%–50%). The results revealed a considerable number of satellite products (1376) available for the study period. Specifically, there were 492 landsat images, 394 sentinel-1 images and 490 sentinel-2 images. Amongst these, sentinel-2 and landsat-7 had the highest number of images (69% and 76%, respectively) with cloud-cover percentages ranging from 0% to 20%. However, images with cloud cover exceeding 26% were excluded from the analysis. Further analysis indicated that using satellite images with 0% cloud cover resulted in an overall accuracy (OA) ranging between 69% and 72%, while 1%–10% cloud cover had an OA ranging between 68% and 70%, and 11%–25% cloud cover had an OA ranging between 69% and 80.55% for both the dry and wet seasons. Overall, the classification results demonstrated satisfactory OAs (68%–82%) for all scenes, with some inaccuracies observed for certain classes, notably bare surface and long grass. These inaccuracies were particularly evident when using landsat-7 scenes, attributable to the spatial resolution of the data. The findings emphasised the availability of a substantial amount of archival satellite data, capable of monitoring small and seasonally flooded wetlands, providing valuable insights into the eco-hydrological dynamics of these ecosystems. Moreover, the study highlighted the benefits of cloud-computing platforms like GEE in addressing challenges associated with big data filtering, processing and analytics, thereby enhancing environmental monitoring and assessments, which may have been limited by the unavailability of advanced processing tools and seamless cloud-free data.
Assessment of the spatiotemporal dynamics of the hydrological state of non-perennial river systems and identification of flow-contributing areas
(South African Water Research Commission, 2024) Maswanganye, Sagwati E; Dube, Timothy; Jovanovic, Nebo; Kapangaziwiri, Evison; Mazvimavi, Dominic
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
Assessment of Huixian Karst wetland for local water augmentation in Guilin, China
(Multidisciplinary Digital Publishing Institute (MDPI), 2024) Qi, Jihong; Xu, Yongxin; Kanyerere, Thokozani
Due to the rapid exploitation of water resources in the Huixian karst wetland in the southwest of China in the past decades, the wetland has suffered from shrinkage in size and serious degradation of ecological functioning. To assess how much water within the wetland could still be taken out for local supply purposes while the wetland can still be kept in its normal ecological functioning. Through the use of multi-methods, including field surveys by a multi-disciplinary team, water balance, Remote sensing, GIS and numerical simulation, this paper characterizes the wetland regime of the study area and finally determines scenarios of water resource utilization for local water supply within acceptable parameters of wetland ecological health. Through the analysis of the methods, it was found that the hydrological characteristics of the study area were conditioned by not only the karst water but also the regional precipitation fluctuations. A zone of mobile watersheds for lake Mudong was established as opposed to a conventional single watershed. If the wetland ecosystem is kept at the current status of class III, a scenario of withdrawal of up to 20% of lake inflows could be accommodated. The results and their approaches would provide much-needed information for the protection of the wetland and its sustainable water utilization per se. It would offer a basic reference for similar problems in karst areas of southwest China and other areas alike.
Remote sensing crop water productivity and water use for sustainable agriculture during extreme weather events in South Africa
(Elsevier B.V., 2024) Mpakairi, Kudzai Shaun; Dube, Timothy; Sibanda, Mbulisi
The impact of climate variability and extreme weather events on agricultural productivity in arid environments has become a focal point in contemporary research. Monitoring crop water productivity (CWP) is critical and urgently required especially in the arid regions where agriculture consumes an above-average portion of the available fresh water resources. In this context, this study aimed to demonstrate the utility of remotely sensed data in assessing CWP and water use dynamics across diverse crop types in South Africa during the El Niño (2018/19) and non-El Niño (2021/22) events. In addressing the objective, the study also assessed the intra- and inter-annual variations in crop water productivity for diverse crop types including, grains, grapes, citrus fruits, teas, planted pastures, and oil seeds. The study used potential evapotranspiration and biomass derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite to estimate CWP from 2017 to 2021. This period included El Niño (2018/19) and non-El Niño (2021/22) years. The results showed that potential evapotranspiration (PET) derived from MODIS was related to the PET estimated from weather stations (R2 > 0.6; RMSE < 21.90; p-value < 0.001). In terms of water use, planted pastures had the highest water use 114 mm/month), while teas and citrus fruits had the lowest water use (6 mm/month). Citrus fruits, grapes and teas consistently had the lowest annual mean crop water productivity (<0.02 kg/m3/annually), while oil seeds had the highest annual mean crop water productivity (>0.1 kg/m3/annually). Lastly, there were no significant differences (p-value > 0.05) between the CWP for all the crops observed between El Niño (2018/19) and non-El Niño (2021/22) periods, suggesting the effectiveness of adaptation measures and interventions during this period. These results provide a simple, spatially explicit framework, relevant to understanding crop-water use, laying the groundwork for informed decision-making and sustainable agricultural practices. Integrating these findings into policy frameworks and agricultural strategies is paramount for ensuring food security and resilience in a changing climate. © 2024
The influence of physicochemical variables on plant species richness and distribution in the coastal salt marshes of the Berg River Estuary, South Africa
(Elsevier, 2024) Mngomezulu, Nomcebo T; Rajkaran, Anusha; Veldkornet, Dimitri A
The continuous distribution of coastal salt marsh habitats along an elevation gradient can be disrupted by tidal creeks running through them. Tidal creeks wind through salt marshes and create different environmental con ditions for adjacent habitats. While studies have emphasized the importance of tidal creeks as links facilitating interactions in salt marshes, few have studied plant communities and physiochemical conditions associated with tidal creeks. This study determined the influence of creek physicochemical variables on the diversity and dis tribution of coastal salt marsh plants. Six transects in the lower reaches of the Berg River Estuary, South Africa were sampled over two seasons at sites with either the presence or absence of creeks. Species composition and abundance were analysed by replicate quadrats and paired with physicochemical variables (groundwater and sediment). The k-means of 20 species in 334 quadrats revealed four distinct clusters of salt marsh habitats, creeks, intertidal salt marsh, supratidal salt marsh and reeds. Species richness was higher along transects with creeks (16) compared to those with no creeks (5). The physiochemical variables, groundwater temperature, pH, dissolved oxygen, conductivity, and sediment variables (redox potential, organic content, percentage silt and percentage sand), significantly influenced the abundance of creek species. This study highlights the importance of tidal creeks in forming unique vegetation communities in salt marshes, where they act as refugia for intertidal species. It is suggested that tidal creek communities should be included in salt marsh vegetation descriptions and monitored in association with physicochemical variables in response to climate change.
Seasonal variations in water use of japanese plum orchards under micro-sprinkler and drip irrigation methods using fruitlook data
(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Mashabatu, Munashe; Motsei, Nonofo; Jovanovic, Nebojsa
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.
Seasonal and spatial dynamics of surface water resources in the tropical semi-arid area of the Letaba catchment: Insights from google earth engine, landscape metrics, and sentinel-2 imagery
(Multidisciplinary Digital Publishing Institute (MDPI), 2024) Dube, Timothy; Mashala, Makgabo Johanna; Ayisi, Kingsley Kwabena
Understanding the spatial and seasonal dynamics of surface water bodies is imperative for addressing water security challenges in water-scarce regions. This study aimed to evaluate the efficacy of multi-date Sentinel-2-derived spectral indices, specifically the normalized difference water index (NDWI), modified normalized difference water index (MNDWI), and Sentinel 2 Water Index (SWI), in conjunction with landscape metrics for mapping spatial and seasonal fluctuations in surface water bodies. Google Earth Engine (GEE) was employed for this assessment. The research achieved impressive overall accuracies, ranging from 96 to 100% for both dry and wet seasons, highlighting the robustness of the methodology. The study revealed significant differences in water bodies in terms of size and coverage between the dry and wet seasons. Surprisingly, the dry season exhibited a higher prevalence of water bodies when compared to the wet season, indicating unexpected patterns of water availability in the region and the substantial heterogeneity of water bodies. Meanwhile, the wet season was characterized by extensive coverage. These findings challenge conventional assumptions about water resource availability during different seasons. Based on the findings, the study recommends that water resource management strategies in semi-arid regions consider the observed seasonal variability in water bodies. Policymakers and stakeholders should adopt adaptive management approaches to address the unique challenges posed by differing water body dynamics in dry and wet seasons. Future research endeavors should explore the underlying factors driving these seasonal fluctuations and assess the potential long-term impacts on water availability. This can help to develop more resilient and sustainable water security strategies to cope with changing climate conditions in semi-arid tropical environments.
Local perspectives, regional consequences: the socio-environmental impacts of sand harvesting in southern Africa
(Elsevier Ltd, 2025) Jovanovic,Nebojsa; Smigaj,Magdalena; Walker,David
After water, sand is the most exploited resource on Earth, with extraction rates often exceeding the sustainable supply, impacting ecosystems and local communities. Still, there is very little information on the situation in southern Africa, despite the rapid economic growth in the region and associated increase in sand demand. This study aimed to address this gap by identifying the implications of sand extraction on local communities and the ecosystem, drawing upon the perspectives of local stakeholders. Qualitative data collected in Botswana, South Africa and Mozambique through stakeholder interviews, revealed a suite of environmental and social issues surrounding both licensed and unlicensed operations. The experienced negative impacts and benefits were occasionally contradictory in nature, strongly depending on characteristics relating to geography, and the type of sand harvesting activity. We subsequently explored links between experienced benefits, impacts and current regulatory frameworks through development of a Driver-Pressure-State-Impact-Response (DPSIR) framework, which highlighted that careful mining site selection and adherence to regulations could minimise socio-environmental impacts whilst achieving benefits. The findings of the study provided insights on the main obstacles for alleviating sand harvesting-related impacts and existing knowledge gaps that need to be first addressed to inform the development of more sustainable sand harvesting practices.
Bush encroachment with climate change in protected and communal areas: a species distribution modelling approach
(Elsevier B.V., 2025) Maphanga, Thabang; Dube, Timothy; Sibanda, Mbulisi
Savanna rangelands have experienced widespread degradation due to bush encroachment, raising significant concerns among conservationists and rural communities. In the context of climate change, these ecosystem shifts are likely to intensify, especially in South Africa's semi-arid regions. Understanding the impacts of climate variability and change on species distribution within these rangelands is crucial for mitigating further ecosystem disruption. Environmental factors, along with climatic variables, can accelerate the process of bush encroachment, threatening both biodiversity and land use. Early identification of areas vulnerable to invasion is key to developing effective and cost-efficient management strategies. This study aims to model the distribution of invasive species across protected and communal landscapes under long-term climate change projections. A Random Forest (RF) model produced the highest accuracy metrics for Area under the curve (AUC) = 0.99 and True Skill Statistic (TSS)=0.97, while a MaxEnt model recorded the second highest AUC (0.98) and TSS (0.97). The results show a clear difference between the current and future scenarios of the spatial distribution in all the models. Applying a species distribution model (SDM) using both MaxEnt and RF produced a higher degree of prediction accuracy because RF is susceptible to overfitting training data while MaxEnt can produce predictable and complex results. Moreover, the overall predictions using the ensemble model demonstrated an increase in areas suitable for encroachment under RCP 8.5 but a decrease in the bush encroachment rate under RCP 2.6. These findings underscore the critical need for proactive management strategies to mitigate bush encroachment, particularly under high-emission scenarios, ensuring the sustainability of semi-arid savanna rangelands in the face of climate change.

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