Search Results (101)

Under the continuous impact of global warming, the water cycle has undergone significant changes, causing a series of problems such as water shortage, frequent climate disasters and ecological environment deterioration. Therefore, understanding the evolution of regional historical and future drought and wet conditions is crucial for adapting and mitigating disasters. This paper discusses the evolution of drought and pluvial events in the Henan section of the Yellow River from 1970 to 2014, projects the future evolution of drought and wet conditions, and assesses the performance of various climate models from Coupled Model Intercomparison Project Phase 6 in simulating precipitation and temperature. Subsequently, future drought and wet conditions in the Henan section were projected for the 2015–2100 period across four SSP-RCP scenarios using Standardized Precipitation and Evapotranspiration Index (SPEI) and run theory. The results indicate that the Henan section of the Yellow River exhibited a significant drying trend during the historical period, with a rate of 0.15 per decade. Looking ahead, a wetting tendency is projected under the SSP1-2.6 scenario, with an increasing rate of 0.02 per decade, whereas the other three scenarios consistently show drying trends, with rates of −0.11, −0.15, and −0.23 per decade, respectively. Across all scenarios, drought and wetness variations exhibit pronounced periodicity, particularly at timescales of approximately 20–30 years, suggesting the persistence of multi-decadal hydroclimatic oscillations. Furthermore, drought and wetness events are projected to become more persistent and severe during the mid-to-late 21st century. Compared with the historical baseline, increasing radiative forcing is associated with an expansion in drought-affected areas, accompanied by reduced event frequency but longer duration and greater severity. In terms of risk, the SSP3-7.0 scenario presents the highest overall drought and wetness risk with the widest spatial extent, whereas the SSP2-4.5 scenario shows relatively lower risk levels and a more balanced spatial distribution. Full article

Observed increases in wildfire activity across the contiguous United States (U.S.), together with continued warming and expanding development in fire-prone landscapes, highlight the need to anticipate near-term changes in fire regimes. We apply a Bayesian statistical model that integrates projected population density (SSP2) and downscaled climate simulations under a moderate emissions scenario (RCP 4.5) to estimate future wildfire occurrence, maximum fire size (using the 90th percentile of fire size distribution), and total area burned for large fires (>1000 acres) across all EPA Level III ecoregions for 2020–2060. Relative to 1984–2019, we project nationwide increases of 56% in fire occurrence and 59% in area burned, with larger increases in maximum fire size (63%) in 2020–2060. Spatial patterns vary substantially: fire occurrence increases most strongly in the eastern U.S., including regions where large fires have historically been rare, while western ecoregions experience the largest absolute increases in burned area and extreme fire size. The disproportionate growth in maximum fire size suggests that changes in fire weather will amplify extreme events beyond increases in ignition frequency alone. These projections indicate expanding wildfire risk across diverse U.S. landscapes and underscore the need for regionally tailored fire management and preparedness strategies. Full article

Understanding how land-use dynamics and carbon balance respond to socio-economic development and future climate change is essential. It supports the refinement of ecological management strategies in environmentally fragile regions and the achievement of China’s dual-carbon goals. This study aims to (i) analyze historical land-use evolution in Xinjiang from 2000 to 2020 and simulate its future dynamics from 2021 to 2060 under multiple SSP-RCP scenarios; (ii) quantify land-use carbon emissions and carbon storage using the coupled SD-PLUS-InVEST model; and (iii) evaluate the carbon balance through the carbon emission to storage ratio (CESR). This study coupled the system dynamics (SD) model, Patch-generating Land Use Simulation (PLUS) model, and InVEST model by integrating socio-economic statistics, IPCC climate data, and land-use datasets. The integrated model was used to simulate land-use evolution in Xinjiang from 2000 to 2060 and to quantify the spatiotemporal variation in land-use carbon emissions, carbon storage, and the CESR. Results indicated that carbon emission increased continuously from 2000 to 2020. Carbon emission showed an inverted U-shaped pattern from 2020 to 2060, with the peak occurring in approximately 2030 under the SSP1–2.6 and SSP2–4.5 scenarios, while it continued to rise from 2020 to 2060 under SSP585. Carbon storage exhibited an “initial increase followed by decline” from 2000 to 2020 but increased consistently from 2020 to 2060 under all scenarios. Xinjiang is a carbon-contributing area with the CESR less than 1 from 2000 to 2060. The CESR increased first and then decreased from 2020 to 2060 under SSP126 and SSP245, while it increased significantly under SSP585. The carbon contribution capacity in Xinjiang decreased under SSP585. These findings indicated that Xinjiang is a carbon contribution area, but its contribution function may be weakened by the expansion of energy-related land use and reduction in forest areas. Hence, it is necessity to uphold Xinjiang’s role within the national carbon balance framework by enhancing spatially differentiated land management, promoting the low-carbon transformation of the energy structure, and strengthening ecological restoration efforts to improve regional carbon sink capacity. Full article

Rising greenhouse gas concentrations have exacerbated global warming, elevating the importance of land use and land cover (LULC) changes in achieving carbon neutrality. This is especially true in coastal areas, which face dual pressures from rapid urbanization and the need to protect carbon sinks. This study developed an SD-MCCA coupling framework to predict the dynamic changes in LULC in four SSP scenarios (SSP126, SSP245, SSP370, SSP585) in the coastal zone of Zhejiang Province from 2020 to 2100. Among them, the carbon storage was estimated by the InVEST model, and the dual-target optimization was carried out using the NSGA-II algorithm. Results indicated that construction land expanded significantly across all scenarios (50.3–110.2%), leading to a decline in carbon storage. However, outcomes were highly scenario-dependent; by 2100, carbon storage under the SSP126 pathway (1032.94 Mt) was notably higher than under the SSP585 pathway (1012.90 Mt). Coastal wetlands and forests emerged as major contributors to carbon storage, exhibiting high positive contribution scores, while construction land sites show significant negative correlations. Dual-target optimization achieved collaborative improvement: the optimized SSP126 scenario increased carbon storage by 1.16%, while economic benefits increased by 9.05%. The policy proposal emphasizes the priority of the SSP126 scenario, restricts the expansion of construction land, and enforces the ecological red line of wetlands and forests, guided by the phased Pareto optimal strategy. Full article

The Land Use and Land Cover (LULC) of many regional landscapes are changing due to natural effects and anthropogenic activities, impacting biodiversity and ecosystem services. LULC dynamics reflect the altered flow of energy, water, and greenhouse gases, influencing the pillars of sustainability: society, environment, and economy. Thus, assessing LULC changes is vital for understanding the relationship between nature and society. This study used multi-temporal remotely sensed imagery to examine LULC change between 1990 and 2019 in the context of Forest Transition Theory (FTT) across the Greater Shawnee National Forest (GSNF) area of southern Illinois, USA, using a random forest algorithm, and projecting change to 2050 with a Land Change Model integrated with IPCC temperature and precipitation scenarios. From 1990 to 2019, LULC analysis showed increases in deciduous forest (1.35%), mixed forest (26.40%), agriculture (2.15%), and built-up areas (6.70%), while hay/grass/pasture declined (16.0%). LULC change intensity was highest from 1990 to 2001 (2.35% annually), slowing to 0.23% (2001–2010) and 0.18% (2010–2019). The overall accuracy (OA) of LULC classification ranged from 0.9 to 0.95 at a 95% confidence interval (CI). Projections to 2050 showed consistent increases in built-up areas (17.12–42.61%), water (28.75–39.70%), and hay/grass/pasture (6.23–38.38%), while overall forest cover declined in all scenarios. Deciduous forests decreased by 3.11–19.87% and were replaced by mixed forests in some scenarios (12.45–23.63%), while evergreen forests showed mixed responses, ranging from a decline of up to 17.13% to an increase of 2.90%. The OA of projected LULC ranged from 0.71 to 0.83 (95% CI) across SSP-RCP-based temperature and precipitation scenarios. The results showed that the GSNF broadly follows the FTT framework: forest recovery since 2001 coincided with rural depopulation, slow agricultural expansion, and rising incomes. However, climate change is expected to disrupt this recovery, pushing transitions toward mixed and evergreen forests. Findings demonstrate the importance of integrating remote sensing-based LULC with socio-economic trends and climate adaptation strategies to sustain forests and ecosystem services under future environmental pressures. Full article

Carbon storage (CS) is a critical ecosystem service for climate mitigation. CS in urbanizing areas is being squeezed by climate-driven capacity decline and human-induced stock loss. Focusing on the Yangtze River Delta Urban Agglomeration (YRDUA), we integrated the InVEST CS module with climate projections under SSP-RCP scenarios to quantify CS dynamics during 2000–2020 and project trajectories for 2030–2070, while attributing CS changes to land use change (LUC). The findings indicated that: (1) From 2000 to 2020, the share of cropland decreased from 54.72% to 49.60%, while the share of construction land increased from 6.05% to 12.55%. (2) Regional CS ranged from 2829.46 to 2941.96 Tg C and exhibited a persistent spatial gradient, decreasing from south to north. (3) CS is projected to increase under SSP5-8.5, to rise and then decline under SSP1-1.9, and to decrease overall under SSP2-4.5. (4) From 2000 to 2010, the conversion of cropland to forest made the largest positive contribution to CS changes, while the conversion of water to cropland dominated from 2010 to 2020. Conversely, cropland expansion into construction land was the primary driver of negative CS changes throughout the 2000–2020 period. For the future period (2030–2070), under all scenarios, the conversion of grassland to forest is expected to be the dominant driver of positive CS gains, whereas the conversion of grassland to cropland will consistently lead to the largest CS losses. These findings highlight the need for scenario-specific and spatially differentiated land-management strategies to sustain regional carbon sinks and enhance long-term climate resilience in agglomerations. Full article

The combined effects of climate change and socio-economic development have intensified the risk of water supply–demand imbalance in China. To project future trends, this study develops a multi-scenario coupled prediction framework integrating climate, socio-economic, and human activity drivers, combining data-driven and physically based modeling approaches to assess terrestrial water storage imbalance in nine major river basins under six representative SSP–RCP scenarios through the end of the 21st century. Using ISIMIP multi-model runoff outputs along with GDP and population projections, agricultural, industrial, and domestic water demands were estimated. A Water Conflict Index was proposed by integrating the Water Supply–Demand Stress Index and the Standardized Hydrological Runoff Index to identify high-risk basins. Results show that under high-emission scenarios, the WCI in the Yellow River, Hai River, and Northwest Rivers remains high, peaking during 2040–2069, while low-emission scenarios significantly alleviate stress in most basins. Water allocation inequity is mainly driven by insufficient supply in arid northern regions and limited redistribution capacity in resource-rich southern basins. Targeted strategies are recommended for different risk types, including inter-basin water transfer, optimization of water use structure and pricing policies, and the development of resilient management systems, providing scenario-based quantitative support for future water security and policy-making in China. Full article

The cover-management factor (C-factor) plays a pivotal role in soil erosion control and is the most easily influenced by policymakers. Despite the availability of numerous C-factor estimation methods, systematic comparisons of their applicability and associated uncertainties remain limited, particularly for future projections under climate change scenarios. This study systematically evaluates multiple widely used C-factor estimation models and projects potential C-factor changes under future scenarios up to 2070, using 2015 as a baseline. Results reveal substantial spatial variability among models, with the land use/land cover-based model (CLu) showing the strongest correlation with the reference model (r = 0.960) and the lowest error (RMSE = 0.048). Using the CLu model, global average C-factor values are projected to increase across all Shared Socioeconomic Pathways–Representative Concentration Pathways (SSP-RCP) scenarios, rising from 0.077 to 0.079–0.082 by 2070. Statistically significant trends were observed in 28.0% (SSP1-RCP2.6) and 26.6% (SSP5-RCP8.5) of global land areas, identified as hotspot regions (HRs). In these HRs, mean C-factor values are expected to increase by 16.1% and 33.4%, respectively, relative to the 2015 baseline. Economic development analysis revealed distinct trajectories across income categories. Low-income countries (LICs, World Bank classification) exhibited a pronounced dependency on development pathways, with C-factor values decreasing by −50.3% under SSP1-RCP2.6 but increasing by +95.8% under SSP5-RCP8.5 compared to 2015. In contrast, lower-middle-income, upper-middle-income, and high-income countries exhibited consistent C-factor increases across all scenarios. These variations were closely linked to cropland dynamics, with cropland areas in LICs decreasing by 64.6% under SSP1-RCP2.6 but expanding under other scenarios and income categories between 2015 and 2070. These findings highlight the critical importance of sustainable land-use policies, particularly in LICs, which demonstrate the highest magnitude of both improvement and degradation under varying scenarios. This research provides a scientific foundation basis for optimizing soil conservation strategies and land-use planning under future climate and socioeconomic scenarios. Full article

Drought remains one of the most damaging natural hazards to agricultural production and is projected to continue posing substantial risks to food security in the future, particularly in major rice-growing regions. Based on the RCP4.5 and RCP8.5 scenarios under CMIP5, this study used a process-based crop growth model to simulate the growth of rice in China in different future periods (short-term (2031–2050), medium-term (2051–2070), and long-term (2071–2090)). We fitted rice vulnerability curves to evaluate the rice drought risk quantitatively according to the simulated water stress (WS) and yield. The results showed that the drought hazard in major rice-growing areas in China (MRAC) were low in the middle and high in the north and south. The areas without rice yield loss will decline in the future, while the areas with a high yield loss will increase, especially in southwestern China and the middle and lower Yangtze Plain (MLYP). Owing to the markedly increased evaporative demand and the reduced moisture transport caused by a weakening East Asian summer monsoon, northeastern China will be a high-risk area in the future, with the expected yield loss rates in scenarios RCP4.5 and RCP8.5 being 39.75% and 45.5%, respectively. In addition, under the RCP8.5 scenario, the yield loss rate of different return periods in south China will exceed 80%. A significant gap between rice supply and demand affected by drought is expected in the short-term future. The gaps will be 67,770 kt and 78,110 kt under the RCP4.5-SSP2 and RCP8.5-SSP3 scenarios, respectively. The methodology developed in this paper can support the quantitative assessment of drought loss risk in different scenarios using crop growth models. In the context of the future expansion of Chinese grain demand, this study can serve as a reference to improve the capacity for regional drought risk prevention and ensure regional food security. Full article

Accurate prediction of land use and land cover (LULC) change is essential for sustainable development and climate change adaptation planning. This study projects LULC changes across 17 administrative regions of South Korea from 2020 to 2050 using the Future Land Use Simulation (FLUS) model under four integrated SSP-RCP scenarios: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. The model was calibrated with land cover data for 2000–2010 and validated against observations for 2010–2020 using socioeconomic variables together with CMIP6 climate projections. In practical terms, FLUS produces scenario-based maps of future land patterns that inform land regulation, infrastructure planning, and climate adaptation. Across all scenarios, urban areas expanded by 488,000–585,000 ha, mainly through the conversion of agricultural land, which accounted for 10–24% of transitions in high-growth regions. Agricultural land decreased by 124,000–174,000 ha, and forests declined by 473,000–572,000 ha. Transformation intensity peaked around 2030 and then slowed in later decades. Urban expansion was greatest under SSP5-8.5, followed by SSP3-7.0, SSP1-2.6, and SSP2-4.5. Gyeonggi Province exhibited the most pronounced spatial change, whereas Seoul showed limited additional growth consistent with its already saturated urban structure. Validation results indicated an overall accuracy range of 57–83% with metropolitan areas generally outperforming provincial regions. These findings reveal spatial and temporal hotspots of land cover change and provide region-specific information that can guide urban development, land and ecosystem management, climate adaptation policy, and progress toward carbon neutrality. Full article

Heatwaves are intensifying across China under global warming. Although previous SSP-RCP studies project more frequent and intense events, systematic evaluations of exposure mechanisms among the elderly in China remain limited. The purpose of the paper is to reveal the spatiotemporal dynamics and inequality of heatwave exposure among China’s urban elderly and to disentangle the driving influences of climate change, ageing, and urbanization. Historical and future heatwaves across China are identified and analyzed, exposure inequality is evaluated using the Gini coefficient, and the relative contributions of key drivers are quantified through factor separation. Results showed that heatwave frequency and duration increased from 2000 to 2019, with high-risk provinces clustering in the Yangtze River Basin, North China Plain, and Sichuan Basin. Future projections indicate substantial growth in elderly exposure to heatwaves, while under the SSP3-70 scenario, inter-provincial inequality in exposure tends to alleviate rather than intensify. Climate change was identified as the dominant driver, while ageing amplified risks and urbanization partly mitigated growth. These findings highlighted the urgent need for place-based adaptation and health protection strategies, aligned with climate mitigation, demographic transition, and sustainable urban planning. Full article

Understanding the evolutionary dynamics of land use and habitat quality (HQ) under climate change scenarios is pivotal for formulating science-based biodiversity conservation policies and promoting climate-resilient urban development in arid regions. By integrating the SD–PLUS–InVEST framework with SPEI-driven drought scenarios, this study introduces a novel coupling mechanism that links climate variability, land-use transitions, and HQ evolution in the Northern Slope of the Tianshan Mountains (UANSTM) under SSP–RCPs scenarios. The HQ assessment was validated using the Remote Sensing Ecological Index (RSEI). Simultaneously, the Optimal Multivariate-Stratification Geographical Detector (OMGD) was applied to identify scale-optimized drivers of HQ changes. The results indicated the following: (1) From 2000 to 2020, cultivated and construction land in the UANSTM expanded, while forest and water areas declined, with unused land remaining dominant from 2000 to 2020. (2) HQ decreased from 0.36 to 0.33 (2000–2020), significantly correlating with RSEI (Pearson r = 0.329, Spearman ρ = 0.446, p < 0.001), with climatic, vegetation, and coupled natural-social factors remaining the dominant drivers. (3) From 2020 to 2050, under all climate scenarios, the areas of farmland, grassland, and construction land are expected to grow, while HQ is projected to improve through the conversion of low-quality areas into moderate- and high-quality habitats (greatest under SSP119, least under SSP585). The framework advances predictive insights for arid-region ecological planning, supporting practical applications in habitat management and sustainable land-use planning, while providing a methodological paradigm for dryland habitat resilience assessment. Full article

The aim of the study is to analyze the impact of climate change on modern low-energy construction. The authors attempted to answer the question whether an existing single-family building that meets the current requirements for a low-energy facility can be called such in terms of ongoing long-term climate changes. Therefore, on the model of the building in question, the ESP-r program analyzed the impact of climate change on energy consumption for both heating and cooling purposes. The SSP2-4.5 scenario (RCP 4.5 according to the IPCC 5th Assessment Report) was adopted, generating future climate parameters for 2050 and 2080, using the HadCM3 model. In order to validate the model, the actual energy consumption values were compared with the values obtained from numerical modeling in the ESP-r program. The final task was to analyze the impact of ongoing climate changes on energy parameters and comfort of use of the facility. Based on the results obtained, the authors concluded that the effect of the changes that take place is the need to introduce an air conditioning system into it in the summer, because the currently existing solution, using a mechanical ventilation system to maintain thermal comfort, is unable to provide the required parameters in the rooms. We are dealing with the phenomenon of excessive temperature increase in the building in the summer. Therefore, the facility currently designed as a low-energy building will require the installation of additional installation systems in the coming years, primarily cooling rooms, which will involve increased energy consumption. Full article

Amid China’s dual-carbon goals and widening regional disparities, land-use/cover change (LUCC)-induced volatility in carbon storage (CS) has emerged as a binding constraint on emission reduction and the low-carbon transition in resource-based regions. Yet integrated historical-scenario assessments and rigorous evidence on spatial-heterogeneity mechanisms remain limited, which hampers targeted spatial governance. Using Shanxi Province, a resource-based province, as the study area, this study develops a coupled PLUS-InVEST framework under SSP-RCP scenarios. It integrates spatial autocorrelation, geographically weighted regression (GWR), and structural equation modeling (SEM) to characterize spatiotemporal responses of CS to LUCC and to identify underlying drivers. The results indicate that: (1) Regional CS follows an inverted U-shaped trajectory, initially increasing due to ecological restoration projects and subsequently declining owing to industrial development and urban expansion; (2) By 2030, forestland expansion under SSP126 is projected to enhance CS, whereas accelerated urbanization under SSP585 is expected to intensify CS losses; (3) Significant spatial clustering of CS remains consistent from historical periods to future projections, underscoring its sensitivity to topography, vegetation patterns, and human activities; and (4) CS is jointly shaped by natural and anthropogenic drivers, with DEM and slope providing stable protection, while population density and transport-network configuration cause ongoing disturbances. The study provides an integrated historical-scenario assessment and reveals the underlying mechanisms for resource-based regions, offering quantitative evidence to support optimization of the Ecological Conservation Redline, managing urban growth boundaries, and implementing zoned ecological restoration. Full article

Ecosystem service value (ESV) is a critical indicator of regional ecological well-being. Assessing and forecasting ESV are essential for achieving the coordinated development of environmental and economic systems. This study employs the SD-PLUS model, integrating Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs) to assess the spatiotemporal dynamics of land use and land cover change (LUCC), as well as ESV in Zhengzhou from 2030 to 2040. It analyses the impact of various driving factors on ESV and examines the spatial correlations among ecosystem services across different regions. The results indicate that the total ESV is expected to decrease by 73.53 × 10⁷ yuan, primarily due to significant reductions in cropland and water areas. By 2040, ESV is projected to increase by 14.51 × 10⁷ yuan under the SSP126 scenario, decrease by 73.18 × 10⁷ yuan under the SSP585 scenario, and show a moderate decline under the SSP245 scenario. Climate factors, transportation location, and topographical features have a significantly positive impact on ESV, while environmental and socioeconomic factors exert a negative influence. The analysis of interrelationships among ecosystem services shows that synergies dominate, especially between supporting and cultural services, with only localised trade-offs observed. These findings contribute valuable insights for the development of scientifically sound, well-reasoned, and efficient strategies for ecological conservation and sustainable development. Full article