Search Results (6,218)

Building on the success of its predecessors, the 9th International Electronic Conference on Water Sciences (ECWS-9) has been hosted entirely online. The conference aims to explore pivotal advancements in water sciences amidst environmental change. Researchers and practitioners are invited to contribute across a spectrum of critical topics, from hydrological processes, water resources management, and ecohydrology to urban water systems, agricultural water use, wastewater reuse, and the application of remote sensing and artificial intelligence. Special attention will be given to extreme hydro-meteorological events, water policy, and the impacts of climate change. Full article

Net primary productivity (NPP) and its response to global climate change are one of the hot topics in global change research. Based on Net primary productivity remote sensing data and meteorological data, this study analyzed the spatiotemporal variation in vegetation NPP in Maowusu sandy land by using Sen trend analysis, Mann–Kendall significance test, coefficient of variation stability analysis, partial correlation and complex correlation analysis, and quantitatively analyzed the response of vegetation NPP to climate factors. The results showed that from 2001 to 2023, the overall vegetation NPP showed a significant upward trend, and the annual average increased from 124.28 g·(m⁻²·a)⁻¹ to 221.41 g·(m⁻²·a)⁻¹. The Theil–Sen median slope of NPP was +3.87 g·(m⁻²·a)⁻¹ with a coefficient of variation (CV) of 0.19, suggesting a robust but spatially variable greening trend. In total, 98.53% of the area showed an upward trend, with a very significant and significant increase area. The overall stability of vegetation NPP was strong, with an average coefficient of variation (CV) of 0.19 and a CV< of 0.30 in 97.96% of the regions, but the local area from southwest to east was highly volatile and there was a risk of secondary desertification. The influence of climate factors on vegetation NPP had significant spatial heterogeneity: precipitation was the key driving factor, and most areas were positively correlated. Potential evapotranspiration was positively correlated in the central and northern regions, and negatively correlated in some southern areas. The overall temperature has a negative effect, and only the local area has a weak promoting effect. Multi-correlation analysis shows that vegetation NPP is the result of the synergy of multiple climatic factors, and the hydrothermal coupling mechanism plays a decisive role in its spatial pattern. This study can provide a scientific basis for the restoration of vegetation ecosystems, environmental protection policy formulation, ecological protection and high-quality development of the Yellow River Basin in Maowusu Sandy Land. Full article

The shift to renewable energy sources is widely seen as a promising way to reduce carbon emissions and mitigate the impacts of climate change. The abundance of renewable energy resources in Africa has enormous potential to reduce greenhouse gas emissions and promote climate resilience. This study conducted a bibliometric analysis of research trends in the adoption of renewable energy systems for climate change mitigation in Africa from 1993 to the first quarter of 2025. The results showed a steady growth in publications during the 2000s, with a growing annual rate of approximately 12.7%, reaching a peak in 2024, indicating increasing research interest in Africa. The thematic analysis highlights key but underdeveloped and emerging themes, including climate change mitigation, renewable energy sources, greenhouse gas assessment, climate change, energy policy, economic growth, carbon emissions, energy consumption, rural electrification, and energy transformation for further investigation. These findings also revealed regional disparities, highlighting the need to strengthen institutional capacity, develop clear long-term policies, and develop innovative financing mechanisms to expedite the deployment of renewable energy. Additionally, results from network analysis and emerging keyword detection revealed that enhanced regional and international cooperation, grid modernization, and technological innovation, such as energy storage and digital solutions, are vital in the developmental efforts to enhance optimized resource utilization and ensure energy access and security. The study thus provides insights into existing research gaps and future research directions, which will benefit policymakers, academics, and related stakeholders in their efforts to utilize Africa’s renewable energy potential to mitigate climate change, enable sustainable development, and achieve energy security throughout the continent. Full article

As wildfires intensify globally due to climate change, accurate wildfire danger forecasting systems have become essential for effective disaster management and early warning. Fuel Moisture Content (FMC), defined as the ratio of water mass to dry fuel mass, plays a critical role in determining ignition probability and fire spread dynamics. This study conducts a comparative analysis of five major national wildfire danger rating systems: the National Fire Danger Rating System (NFDRS, USA), Canadian Forest Fire Danger Rating System (CFFDRS), European Forest Fire Information System (EFFIS), Australian Fire Danger Rating System (AFDRS), and the Korean Forest Fire Danger Rating System (KFDRS). Using a multi-criteria comparative framework, the systems were evaluated based on fuel classification structure, input variables, modeling approach, and spatiotemporal prediction resolution. The results reveal substantial disparities in spatial resolution (100 m to district-level), temporal resolution (hourly vs. daily), and fuel moisture modeling approaches (physics-based, index-based, and hybrid systems). Specifically, NFDRS and AFDRS provide high-frequency forecasting with hourly temporal resolution, operating at spatial resolutions of 1 km and 100 m, respectively, and incorporating dynamic fuel moisture modeling. In contrast, CFFDRS and KFDRS primarily rely on daily index-based predictions. Furthermore, while many global systems increasingly leverage remote sensing and machine learning for real-time FMC estimation, South Korea’s KFDRS remains predominantly empirical and weather-driven. The analysis identifies critical limitations in the KFDRS, including coarse spatial resolution (district-level), limited integration of Live Fuel Moisture Content (LFMC) modeling, and the lack of AI-augmented hybrid approaches. Accordingly, this study proposes a phased three-stage policy roadmap (2026–2035), emphasizing sensor-network expansion, AI–physics fusion modeling, and high-resolution (10 m) FMC mapping to enhance forecasting accuracy in complex terrains. These findings provide strategic insights for improving wildfire risk management and supporting the transition from reactive response to predictive wildfire forecasting under increasing climate variability. Full article

Soybean is a vital crop supporting global food, feed, and biofuel production. Soybean yields have surged, with record yields reaching 14,678 kg/ha⁻¹, though average farm yields remain stagnant at 2770–2790 kg ha⁻¹. The persistent yield gaps leave 44% of potential production unrealized due to climate change, threatening food security. To meet future caloric demands, which are projected to rise by 46.8% by 2050, soybean breeding must prioritize climate-resilient, high-yielding varieties with minimal ecological footprints. In this comprehensive and in-depth review, we synthesized existing literature and Google Patents and reviewed the multifaceted impacts of climate-change driven eCO₂ and stresses (heat, drought, flooding, salinity, and pathogens), revealing non-linear interactions where eCO₂ may not compensate yield losses under combined stresses. We then highlight key strategies for soybean breeding under climate-change scenario. To this regard, we provide a detailed trait-by-trait breeding roadmap covering seed number, seed size, seed weight, protein-oil balance and their metabolic trade-offs, above and below ground plant architecture, nitrogen fixation and nodulation dynamics, root system architecture, water use efficiency, canopy architecture, flowering time regulation, early maturity etc., in light of specific genes and validated strategies. We explicitly discuss the novel strategies including deeper understanding of traits, abiotic stress physiology, changing pathogen dynamics, phenomics, (multi-)omics, machine learning, and modern biotechnological techniques for developing future soybean varieties. We provide a future roadmap prioritizing specific actions, including engineering climate-resilient ideotypes through gene stacking, optimizing nitrogen fixation and nutrition under stresses leveraging omics data, pan-genome, wild soybean, speeding breeding hubs, and participatory farmer-network validation, while redefining the future soybean breeder would be a hybrid orchestrator of data and dirt. This review establishes a foundational framework for translating climate-adaptive morphological, biochemical, physiological, omics, agronomic, phenomics, and biotechnological insights into actionable breeding strategies, thereby guiding policy-driven investment in soybean improvement programs targeting 2050 and beyond. Full article

To address climate change, reducing food loss along the production and supply chain is a global priority. Addressing this challenge requires a shift in agrifood systems toward greater sustainability, in which new technologies and novel foods appear as promising strategies. Among emerging novel foods, 3D-printed foods are an interesting new food technology for food loss reduction, resource optimization, and by-product valorization. However, to reach market success, it needs consumer acceptance, a topic far unexplored, particularly in the Italian context. To fill the literature gap, this article investigates Italian consumers’ intention toward 3D-printed savory snacks using an extended Theory of Planned Behavior, based upon the relevant literature. Survey data were collected, and partial least squares structural equation modeling was performed to test research hypotheses. Results show that attitude and subjective norms are the strongest predictors of purchase intention. In addition, perceived usefulness is shown to be a powerful construct, positively impacting attitude and subjective norms, while self-identity as a green consumer reinforces perceptions of the benefits of 3D-printed foods. Sensory appeal impacts consumer attitude. These insights have practical policy and micro-level applications, suggesting tailored strategies, educational campaigns, and supportive policies and marketing campaigns for fostering acceptance of 3D printing in the agrifood sector. Full article

South Korea faces escalating climate change threats that increase the risk of large-scale outages of long duration. However, efforts to expand the grid are often limited by low consumer acceptance of higher tariffs. This study employs a nationally representative contingent valuation survey of 1000 households to quantify residential consumers’ willingness to pay (WTP) for grid expansion to avoid a hypothetical 24 h nationwide blackout caused by extreme weather. The findings reveal an average monthly WTP of KRW 2226 (USD 1.54), equivalent to about KRW 0.60 trillion (USD 0.4 billion) annually—approximately 12% of planned grid investment needs. Among the socioeconomic variables, the negative coefficient on generation suggests younger cohorts exhibit higher WTP, consistent with—though not conclusive evidence of—their expectation of greater exposure to future climate risks. Similarly, the presence of children is positively associated with WTP, indicating family protection motives that encompass both immediate household needs and intergenerational considerations related to the distribution of climate-related burdens. These findings provide policy-relevant insights for designing equitable and acceptable tariff schemes that support critical investments to strengthen sustainable grid resilience amidst escalating climate risks. Full article

In the context of accelerating climate change and increasing pressure on natural resources, agriculture needs to rethink its operating models to ensure both sustainability and long-term stability. The circular economy (CE) is increasingly invoked as a possible solution, but its concrete contribution to the climate resilience of agricultural systems remains insufficiently integrated and often assessed in a fragmented manner. This study aims to analyze the role of circular strategies in strengthening the climate resilience of agriculture, through a systemic approach based on multiple indicators. The methodology is based on a structured and comparative analysis of recent scientific literature, complemented by a bibliometric and co-occurrence analysis of keywords, in order to identify the main research directions and evaluation methods used. The analyzed indicators cover dimensions related to soil, water, crop performance, energy and socio-economic resilience of farms. The results suggest that circular economy strategies may contribute to climate resilience through cumulative, and context-dependent effects, including improvements in soil quality, resource-use efficiency, and reduced dependence on external inputs. However, evidence regarding direct impacts on production stability and adaptive capacity remains heterogeneous and often indirect. The study contributes by proposing an integrated conceptual framework that highlights the systemic nature of climate resilience and its links to decarbonization pathways, providing a basis for future empirical research and policy development. Full article

Climate change poses a significant threat to the livelihoods of smallholder farmers in South Africa, particularly in rural areas where dependence on rain-fed agriculture and limited institutional support heighten vulnerability. This study investigates how different forms of social capital (bonding, bridging, and linking) influence climate change adaptation strategies among smallholder farmers in Bergville, KwaZulu-Natal. A mixed-methods design was employed, combining a household survey (n = 150), focus group discussions, and key informant interviews. Households engaged in smallholder farming were purposively identified and randomly selected within the study ward. To accommodate varying literacy levels, structured questionnaires were administered through interviewer-led surveys. Quantitative data were analysed using descriptive statistics, chi-square tests, and a probit regression model, while qualitative data were thematically analysed to contextualise adaptation decisions and social dynamics. The findings show that trust in peer information, farmer group membership, collective action, and access to extension services significantly increase the likelihood of adopting climate adaptation practices (p < 0.05). While bonding social capital supports short-term coping, limited bridging and linking social capital constrain access to institutional resources and climate information. By explicitly operationalising and empirically distinguishing these dimensions of social capital, the study provides context-specific evidence on how uneven social networks shape adaptation outcomes. Strengthening inclusive institutional linkages and extension services is essential for promoting long-term climate resilience among smallholder farmers in rural South Africa. This study contributes to the international literature by providing empirical evidence on the differentiated roles of social capital dimensions in shaping adaptation outcomes in resource-constrained rural contexts. The findings highlight the need for policy interventions that strengthen institutional linkages, improve extension service delivery, and promote inclusive access to adaptation resources to enhance long-term climate resilience. Full article

Olive cultivation represents a key pillar of rural economies and cultural heritage in Mediterranean regions, including western Greece. Despite its socio-economic importance, the sector faces increasing pressures from climate change, market volatility, and technological transformation, while progress toward environmentally sustainable production remains uneven. This study investigates how olive farmers’ perceptions of carbon footprint and climate risks are influenced by their demographic characteristics. Primary data were collected through 402 structured questionnaires distributed to olive producers in the Aetolia–Acarnania region. The sample was designed to represent farmers directly engaged in olive production, ensuring the relevance and reliability of the collected data. The findings, based on descriptive statistics, reveal significant heterogeneity in producers’ perceptions of climate risks and their capacity to respond through sustainable practices. Demographic characteristics appear to play an important role in shaping awareness of carbon footprint and the potential adoption of environmentally responsible farming strategies. These results suggest that sustainability transitions in perennial cropping systems depend not only on technological availability but also on social, informational, and institutional capacities. Strengthening agricultural advisory services, farmer training, and climate adaptation strategies may therefore support the adoption of climate-smart practices in olive cultivation. Furthermore, cooperation and value-chain integration are identified as potentially important mechanisms for facilitating knowledge transfer and supporting the adoption of sustainable practices (e.g., efficient irrigation and optimized input use). However, their contribution to environmental performance and greenhouse gas mitigation cannot be directly inferred from the present perception-based analysis and should be examined in future research using appropriate quantitative or environmental assessment frameworks. Full article

Climate change disproportionately threatens low- and middle-income countries, yet integrated assessments combining socio-economic fragility with physical hazards remain limited. This study quantifies multi-dimensional climate vulnerability and derives optimized adaptation policies for six representative nations (Bangladesh, Colombia, Kenya, Morocco, Pakistan, Vietnam) by fusing socio-economic indicators with climate risk data (2000–2024). A computational framework integrating unsupervised learning, dimensionality reduction, and predictive modeling was employed. Principal Component Analysis synthesized eight indicators into a Compound Vulnerability Score (CVS), while K-Means and DBSCAN identified distinct vulnerability regimes. XGBoost quantified driver importance, and Graph Neural Networks captured systemic interconnections. XGBoost identified projected drought risk (31.2%), precipitation change (18.1%), and poverty headcount (14.3%) as primary drivers. Graph networks demonstrated significant risk amplification in African nations (Morocco SRS: 0.728–0.874; Kenya SRS: 0.504–0.641) versus damping in Asian countries. A Reinforcement Learning (RL) agent was trained using Deep Q-Networks with experience replay to optimize intervention portfolios under budget constraints. The RL policy achieved a 23% reduction in systemic risk compared to uniform allocation baselines, generating context-specific priorities: drought management for Morocco (score 50) and Pakistan (40); poverty alleviation for Kenya (40); coastal protection for Bangladesh (40); agricultural resilience for Vietnam (35); and institutional capacity building for Colombia (50). In conclusion, socio-economic fragility non-linearly amplifies climate hazards, with poverty and drought risk constituting critical vulnerability multipliers. The AI-driven framework demonstrates that targeted interventions in high-sensitivity systems maximize systemic risk reduction. This integrated approach provides a replicable, evidence-based foundation for strategic adaptation finance allocation in an increasingly uncertain climate future. Full article

Dynamic economic growth and climate change increase pressure on water resources, posing a challenge to achieving sustainable development goals, especially in regions with diverse hydrological conditions and development trajectories. This study aims to quantitatively assess the dynamic asymmetry between water management efficiency and the level of sustainable development in the European Union and the Three Seas Initiative (3SI) countries, with particular emphasis on cumulative mechanisms, regional divergence, and the potential low equilibrium trap. The values of the analysed indicators were calculated for 2015, 2021, and 2022, and subsequently their changes were determined for 2021/2015 and 2022/2021. This study was conducted using Eurostat data, applying the CRITIC method for objective weight determination, the TOPSIS technique for constructing synthetic measures, the Kruskal–Wallis and Mann–Whitney tests to assess inter-group differences, and linear regression to identify dependencies. Countries were grouped according to the dynamics of changes in the synthetic water management index. The results indicate a clear asymmetry: the water sector is characterised by a cumulative mechanism and strong divergence (particularly evident in the short period), whereas sustainable development remains significantly more stable, homogeneous, and weakly linearly correlated with previous water achievements. In 3SI countries, a higher rate of improvement in water indicators was observed compared to the rest of the EU; however, no significant synergy with progress in sustainable development was found. The negative impact of the Water Exploitation Index on sustainable development is statistically noticeable but does not confirm the existence of a clear “low equilibrium trap” across the entire 3SI region. This study highlights the need for regionally differentiated, asymmetrical water policies and the integration of water management with broader ecological transformation strategies. Full article

Promoting the construction of National Forest Cities to enhance urban ecological environmental quality and foster green and sustainable development has become an important policy pathway in China’s ecological civilization agenda. This study employs panel data for 214 Chinese cities over the period 2003–2023 and adopts a difference-in-differences (DID) approach to empirically examine the impact of National Forest City construction—a policy implemented in China since 2004—on urban ecological environments and its underlying mechanisms. The results indicate that National Forest City construction significantly improves urban ecological environmental quality. The findings remain robust after a series of robustness checks. Mechanism analysis shows that National Forest City construction primarily promotes urban environmental improvement by enhancing urban green innovation and optimizing adjustments to the urban industrial structure. Further heterogeneity analysis reveals that the environmental effects of the policy are more pronounced in non-resource-based cities, non-central cities, large cities, and cities with stronger governance capacity and higher levels of environmental concern. The conclusions provide policy implications and mechanistic insights from China’s experience for other cities around the world seeking to jointly address environmental pollution and climate change through comprehensive ecological interventions and to advance green and sustainable development. Full article

Understanding why national decarbonization pathways diverge is essential for designing effective climate and energy policy. Using harmonized data for 1970–2022 from Our World in Data and the Maddison Project Database, this study examines long-run emission trends and electricity-mix transitions in four countries representing distinct energy regimes: Japan, Australia, India, and South Africa. We combine per-capita and total CO₂ trajectories with a Kaya–LMDI decomposition aligned with updated methodological guidelines. Results reveal persistent and deepening transition divergence. Japan experienced partial decoupling before a nuclear vulnerability shock in 2011 reversed progress and temporarily increased fossil dependence. Australia shows a recent erosion of long-standing coal lock-in, driven by policy reform and falling renewable costs. India and South Africa remain highly coal-dependent, with population and income growth overwhelming improvements in energy intensity. Across countries, efficiency gains contributed to emission mitigation, but only structural changes in fuel mix produced sustained reductions in carbon intensity. Taken together, these findings suggest that divergent institutional and infrastructural lock-in conditions—rather than income levels alone—shape the pace, direction, and resilience of decarbonization. The study also speaks to recent international policy debates emphasized by the IPCC and the IEA, as well as to justice-oriented discussions in the energy transition literature. The results highlight major implications for climate policy, energy-system resilience, and just transition strategies. Full article

Urban floods have become a major systemic risk to sustainable urban development under climate change and increasingly frequent extreme hydro-meteorological events. Yet evidence on the long-term evolution of urban flood resilience (UFR) and its structural constraints at the provincial scale remains limited. This study develops a PSR-based framework to assess UFR and diagnose its dominant obstacles using data for 21 prefecture-level cities in Sichuan Province from 2011 to 2023, including meteorological, geomorphological, socioeconomic, infrastructure, environmental, and public service indicators. A combined AHP–EWM is used to integrate subjective and objective information, TOPSIS is applied to derive a composite UFR index and subsystem scores, and an obstacle degree model is employed to identify key constraints and their temporal evolution. Results show that: (1) UFR in Sichuan Province fluctuated but increased overall during 2011–2023, reaching its highest level in 2023; (2) resilience improvement was driven mainly by the response subsystem, while the pressure subsystem showed the greatest interannual variability; and (3) the annual top five obstacles were highly persistent and insufficient response capacity was the dominant long-term constraint on resilience enhancement. These findings underscore that improving the adequacy, institutional robustness, and operational stability of response systems is central to enhancing UFR. This study provides empirical support for the assessment of provincial-scale resilience and policy-oriented flood risk governance. Full article