Developing integrated climate change adaptation strategies using the water-energy-food nexus approach: a case study of the Buffalo River catchment, South Africa.
Bibliographic record
Abstract
South Africa’s climate has high spatial and temporal variability. Literature on historical rainfall patterns shows substantial declines in rainfall across the country, except in south-western South Africa, which displays increasing trends. Under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 scenarios, statistically downscaled rainfall projections show different patterns across South Africa throughout the 21st century. Literature indicates that this uncertainty will majorly impact South Africa’s surface water availability as its main input variable is rainfall; hence, all possible outcomes need to be planned for. Planning should include the energy and food production sectors as they primarily depend on the water sector. The Buffalo River catchment, situated in the northern parts of KwaZulu-Natal, South Africa, is a high rainfall receiving area, with a mean annual precipitation of 802 mm. Despite its abundant rainfall, the catchment has had its fair share of droughts, significantly impacting livelihoods and socio-economic activities. Recent reports indicate that the Buffalo River catchment’s surface water storage facilities are insufficient to meet the population’s demands by 2050. A detailed water resources assessment is required to confirm and quantify the possible alterations that climate change could cause to the catchment’s hydrology before any actions can be taken, especially regarding increasing the water storage capacity of the catchment. As such, this study aims to investigate and assess the impacts of climate change on the Buffalo River catchment’s surface water availability and reliability of water resources in meeting projected water demands, with a specific focus on agricultural and energy generation water demands. Furthermore, the study aims to develop integrated water resources adaptation strategies to increase water, energy and food security within the catchment. Due to its transdisciplinary nature, the Water-Energy-Food (WEF) nexus methodology was used as an analytical tool to carry out the research’s objectives. The study was based on the null hypotheses of climate change not varying surface water availability and reliability, and that the optimized CC water management strategies will not yield any improvements in merging potential gaps between water supply and demands. Study findings indicate that the Buffalo River catchment is anticipated to receive increases in precipitation magnitude and fluctuations throughout the 21st century. However, the increases in surface water availability that result from the anticipated rainfall increases are insufficient and unreliable to meet the rise in demands for water within the catchment, more so the irrigation demands. Through investigating the catchment’s already-existing proposed climate change policy interventions for water resources management, the study found that they were centred around boosting domestic water provisions whilst only meeting <3% of projected demands by the energy and agricultural sector. As such, by optimizing these policy plans using the WEF nexus’ Climate, Land-Use and Water Strategies (CLEWS) framework’s analytical tools, integrated climate change adaptation strategies were formulated, which were modelled to significantly improve the water storage capacity of the catchment, as well as water allocations and distribution among water users. The study concluded that the Buffalo River catchment’s surface water availability is expected to increase under climate change, however, current water storage capacity is not reliable to meet water demands throughout the 21st century. Lastly, the study also concluded that the catchment does possess immense potential for improved surface water availability to merge the gap between its water supplies and demands. Thus, the null hypotheses stipulated in this research are rejected. For discussions, policymaking and general research related to these improvements in water resources management in the Buffalo River catchment, the climate change adaptation strategies established in this research are recommended. Also, based on model evaluation statistics, the WEF nexus was successful in examining the interrelations among WEF resources, and is recommended for future studies to examine long-term integrated demand-supply strategies for WEF sectors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".