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15 April 2025Enhancing Streamflow Forecasting in Major West African Rivers by Utilizing Meta-Heuristic Algorithms and Climate Data Time Lag Analysis
Accurate streamflow prediction is essential for irrigation planning, water allocation, and flood risk management, particularly in water-scarce regions like the Niger River Basin. However, the complexity of hydrological processes and data limitations make reliable predictions challenging. This study optimizes Support Vector Machine (SVM) hyperparameters for daily streamflow prediction using time-lagged climate data and four metaheuristic algorithms—Binary Slime Mould Algorithm (BSMA), African Vulture Optimisation Algorithm (AVOA), Archery Algorithm (AA), and Intelligent Ice Fishing Algorithm (IIFA). Model performance was assessed using eight evaluation metrics, with results showing that AA and IIFA consistently outperform the others, achieving Nash-Sutcliffe Efficiency (NSE) values between 0.986–0.999 and 0.893–0.999, respectively. AVOA and BSMA show less consistent performance, with NSE ranges of 0.524–0.999 and 0.863–0.965, respectively. The study highlights the novel integration of multiple metaheuristic algorithms for optimizing machine learning models, offering insights into their effectiveness for hydrological prediction. By demonstrating the superior performance of AA and IIFA, this research provides a robust framework for enhancing long-term streamflow forecasting. These findings support improved water resource management in West Africa, helping policymakers address climate variability, water scarcity, and hydrological uncertainty.
Open Access
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28 May 2025A Framework for Watershed Flood Resilience in the Context of Climate Change: Concept, Assessment, and Application
Extreme flooding events are increasing in frequency and severity due to climate change, challenging the effectiveness of traditional, infrastructure-centric flood management strategies. A key gap remains in the lack of spatially explicit and process-based frameworks for assessing and enhancing flood resilience at the watershed scale, which hinders the development of integrated and adaptive management solutions. This study proposes a conceptual framework for evaluating watershed flood resilience (WFR) by integrating resilience theory with the “source-flow-sink” paradigm from landscape ecology. It applies it to the post-disaster reconstruction of the Sishui River Basin following the 2021 Zhengzhou flood in China. The framework quantifies WFR through pre-event resistance capacity and intra-event adaptive capacity using hydrological modeling and loss curves. It systematically analyzes the effects of targeted interventions across source, flow, and sink areas. The results demonstrate that the proposed approach significantly improves WFR in the Sishui River Basin, with source interventions generally outperforming flow and sink interventions in the simulated cases, and compensatory effects observed among different intervention types. The findings confirm the operational feasibility and effectiveness of the proposed framework, including nature-based solutions and spatial planning in watershed management, which could provide support for future holistic and adaptive flood resilience strategies addressing climate change.
Open Access
Article
26 June 2025Analysis of Rainfall Trend in Australia
Australia is renowned for its highly variable rainfall patterns, which make it a continent marked by both droughts and flooding rains. With global warming driving atmospheric warming and altering weather systems, this variability is projected to intensify. Despite this, the specific trends and extent of rainfall changes across the country remain uncertain. Within this context, in this study, the temporal variability of rainfall in Australia was examined at annual, seasonal, and monthly scales using rainfall data spanning 1920 to 2020. Specifically, non-parametric tests were employed to assess the magnitude and significance of rainfall trends across 505 rainfall series within the Australian region. Results showed a widespread increase in rainfall in summer and spring throughout the study area. By contrast, autumn and winter showed a marked decrease in rainfall, with the greatest evidence along the Queensland coast and in southern Western Australia. If these trends are confirmed in the coming years, these deficits could limit water resources, affecting agricultural areas, the conservation of natural areas, and national parks. In addition, these changes in rainfall could increase the risk of droughts and wildfires, which could also have socio-economic impacts.