Search Results (460)

As a globally climate-sensitive region and ecological security barrier, the spatiotemporal dynamics of net ecosystem productivity (NEP) on the Qinghai–Tibetan Plateau are of great significance for understanding carbon cycling in alpine ecosystems. However, due to insufficient representation of parameter heterogeneity in models and unclear nonlinear attribution of complex environmental factors, substantial uncertainties remain in the spatiotemporal patterns and driving mechanisms of NEP in this region. Therefore, this study first employed an improved Carnegie–Ames–Stanford Approach (CASA) model to assess NEP on the Qinghai–Tibetan Plateau from 2000 to 2022 and characterize its spatiotemporal evolution, and subsequently applied the optimal multivariate-stratification geographical detector (OMGD) to quantify the independent and synergistic driving effects of hydrothermal conditions, extreme climate events, and human activities on NEP variations. The results indicate that: (1) from 2000 to 2022, vegetation NEP on the Qinghai–Tibetan Plateau exhibited a southeast-to-northwest decreasing spatial heterogeneity pattern, with a multi-year mean value of 219.61 g C·m⁻²; (2) during the study period, NEP showed an overall increasing trend (at a rate of 1.596 g C·m⁻²·yr⁻¹), with 52.5% of the region experiencing significant increases, primarily concentrated in the central–eastern humid regions and alpine meadow areas; and (3) among individual factors, the growing season length was the primary driver of NEP, in addition to temperature and precipitation, while human activities exerted negligible influence; under interaction effects, the hydrothermal synergistic enhancement (0.79 < q < 0.89) exhibited the highest explanatory power. These results show that carbon sequestration in alpine ecosystems is governed by nonlinear hydrothermal interactions and provide a scientific basis for assessing carbon sink resilience in the “Asian Water Tower” under global warming. Full article

Extreme drought events have become increasingly frequent under ongoing climatic change, thereby constraining vegetation growth and altering ecosystem processes. Vegetation recovery time following drought plays a crucial role in ecosystem stability, and extensive studies have been conducted to quantify vegetation recovery. However, most studies estimate vegetation recovery time using a single vegetation index, which does not adequately reflect how vegetation responds to drought conditions, since different vegetation indicators reflect different facets of vegetation dynamics. In this study, multiple vegetation indicators, including Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Leaf Area Index (LAI), Gross Primary Productivity (GPP), and Solar-Induced Chlorophyll Fluorescence (SIF), were applied to investigate post-drought vegetation recovery in the Yangtze River Basin (YRB). The findings reveal that: (1) most vegetation recovered within four months after drought, with one-month recovery being the most prevalent, followed by four-month recovery; (2) the average recovery times derived from EVI, LAI, NDVI, GPP, and SIF were 2.23, 1.62, 2.45, 2.79, and 2.00 months respectively; (3) forests exhibited the fastest recovery rates, whereas shrublands recovered the slowest. This study assesses post-drought vegetation status via the recovery duration, offers theoretical basis for water resource allocation optimization, and provides important reference for coping with future ecological risks. Full article

Climate change is increasing the frequency and intensity of extreme rainfall events, profoundly affecting vegetation–atmosphere–soil interactions and ecosystem stability. Northeast China (NEC), a major ecological region, is highly sensitive to precipitation variability. However, the annual mechanisms underlying vegetation responses to rainfall extremes, the mediating roles of soil moisture (SM) and vapor pressure deficit (VPD), and the ecosystem-specific differences remain insufficiently understood. This study investigates these processes during 2000–2022 by integrating precipitation extremes, normalized difference vegetation index (NDVI), SM, VPD, and land cover data. Ten rainfall extreme indices were evaluated using the Mann–Kendall (MK) test and Sen’s slope estimator, while NDVI responses were examined through correlation analysis, mixed-effects models, and structural equation modeling (SEM). Results show strong spatial heterogeneity in precipitation extremes, with intensified heavy rainfall in southern NEC and prolonged drought conditions in northern areas. Vegetation exhibited significant greening trends (NDVI slope = 0.0026 yr⁻¹, R² = 0.718, p < 0.001), accompanied by increasing SM (slope = 0.0478 yr⁻¹, p = 0.003) and mild warming (slope = 0.0005 yr⁻¹, p = 0.045). NDVI showed a strong correlation with SM (ρ = 0.65, p < 0.01) but a weak relationship with temperature (ρ = 0.04, p > 0.05), highlighting SM as the dominant driver of regional greening. Grasslands and cultivated lands were more sensitive to rainfall fluctuations, whereas forests showed greater resilience. SEM results indicate that extreme rainfall affects NDVI mainly through indirect pathways mediated by SM and VPD, with mediation effects exceeding 97%. These findings improve understanding of nonlinear vegetation–atmosphere–land interactions and provide scientific insights for climate adaptation, ecosystem management, and ecological restoration under future climate change. Full article

Brazil presents a distinctive convergence of continental-scale climatic diversity, extensive urbanization, large-scale biomass burning, rapid land-use change, persistent air-quality monitoring gaps, and deep social inequalities, producing highly heterogeneous and compound environmental health risks. In this context, treating air pollution and climate change as parallel environmental crises obscures their structural interconnections through shared emission sources, mutually reinforcing exposure pathways, and overlapping health and social consequences. In this narrative review, we critically synthesize scientific and institutional lines of evidence and argue that air pollution and climate risks can be more effectively addressed in Brazil through a single strategic agenda for science, public health, and governance. We first discuss why these challenges cannot be managed in isolation, emphasizing the effects of heat, drought, stagnation events, biomass burning, and extreme weather on pollutant formation, dispersion, and health burden. We then examine Brazil as a critical case where recent regulatory advances coexist with structural limitations in monitoring, data integration, and territorial coverage. Based on this diagnosis, we propose an integrated national agenda organized around five mutually reinforcing priorities: monitoring through hybrid networks; predictive science through climate-informed modeling and early warning; public health through the convergence of epidemiology, toxicology, and mechanistic research; equity-oriented research and action through the explicit incorporation of vulnerability, inequality, and climate justice; and policy appraisal through the assessment of disease burden, economic costs, mitigation co-benefits, and trade-offs. We further discuss the governance mechanisms needed to connect these priorities and translate evidence into coordinated action and adaptive public policies. We also argue that the Amazon should be approached not as an isolated ecological exception but as a central component of a broader Brazilian and Global South discussion on environmental health, land-use change, and climate justice. In this scenario, Brazil has the scientific capacity and regulatory momentum to become a reference in the integrated management of air pollution and climate risks, but this will depend on replacing fragmented approaches with a coordinated framework capable of linking exposure, mechanism, burden, inequality, and action. Full article

Against the backdrop of global climate change, drought–flood abrupt alternation (DFAA) has become a major compound climate extreme threatening ecosystem stability and sustainable watershed management. This study investigated the spatiotemporal characteristics and ecological responses of DFAA in the Jialing River Basin, China, using meteorological and hydrological observations from 1971 to 2020. DFAA events were identified using the Standardized Weighted Average Precipitation Index (SWAP) and run theory, and their spatiotemporal heterogeneity was characterized using spatial autocorrelation analysis. The Long-duration DFAA Index (LDFAI) was derived using the WEP-L distributed hydrological model. Ecological responses during 2000–2020 were evaluated by integrating the Remote Sensing Ecological Index (RSEI), grey relational analysis, and a Copula-based conditional probability model. The results showed that drought-to-flood events exhibited stronger spatial clustering than flood-to-drought events. Ecosystem responses showed significant lag effects, averaging 6.9 months for spring–summer events and 5 months for summer–autumn events, with greater sensitivity during the summer–autumn period. Under DTF events, the probability of maintaining relatively high ecological quality was significantly higher than under FTD events, whereas FTD events were associated with a higher probability of ecological degradation. Under compound scenarios, consecutive same-type events were more conducive to ecosystem stability, while alternating sequences of different event types significantly amplified negative ecological stress and represented high-risk scenarios for ecological degradation. These findings provide scientific support for adaptive watershed management, ecological restoration, and climate change adaptation in drought–flood-prone regions. Full article

Climate change increasingly threatens Mediterranean ornamental horticulture and green infrastructure through elevated temperatures, prolonged drought conditions, soil salinity, and more frequent extreme weather events. As a result, plant growth, phenology and landscape sustainability are significantly affected. This systematic review aimed to identify and qualitatively synthesize the available evidence on the responses of ornamental plants and their production and end use systems to climate-related stress, with emphasis on Mediterranean native species and their potential contribution to climate-resilient landscaping. The review was conducted and reported in accordance with PRISMA 2020. An adapted Population–Exposure–Outcome framework was used to operationalize the overarching review question and guide eligibility assessment. Scopus and the Web of Science Core Collection were systematically searched for peer-reviewed English-language articles published between 1 January 2001 and 31 May 2026. Eligible publications examined ornamental plants, floricultural species, or native and endemic taxa with potential ornamental or landscape use and addressed climate-related stressors, plant resilience, adaptation strategies, cultivation or propagation practices, green-infrastructure applications, or related ecological trade-offs in Mediterranean-relevant contexts. Two reviewers independently assessed titles, abstracts, and full texts using predefined eligibility criteria. The review used a structured qualitative narrative synthesis organized into thematic domains to systematically identify, select, and synthesize the available evidence. Meta-analysis was not undertaken because of substantial heterogeneity in plant material, environmental stressors, study designs, and reported outcomes. A total of ninety studies were included and organized into five domains: climate stress and plant responses (n = 14), native Mediterranean ornamental species (n = 21), adaptation and resilience strategies (n = 16), urban landscaping and green infrastructure (n = 25), and ecological risks and invasive species (n = 14). The review revealed that several native Mediterranean plants possess morphological, physiological, or ecological characteristics associated with tolerance to drought, salinity, and other climate-related stresses, supporting their potential use in sustainable ornamental horticulture. Water-efficient irrigation, alternative water sources and substrates, nursery preconditioning, non-microbial biostimulants, and genotype or physiological screening showed adaptation potential, but their effectiveness depended on species, genotype, intervention intensity, and application context. Evidence remained limited for compound stresses, combined interventions, nursery-to-landscape transfer, long-term field performance, commercial scalability, and environmental trade-offs. Overall, climate-resilient ornamental horticulture requires the integration of plant selection, propagation, production, controlled stress screening, landscape validation, and ecological-risk assessment. This review proposes an evidence-to-application framework to support research, nursery production, landscape planning, and the responsible deployment of climate-adapted ornamental plants. Full article

Against the backdrop of climate change and compounded by human activities, increasing water scarcity has triggered a series of drought disasters, which have already severely impacted both ecological environments and socioeconomic production. The SWAT model, recognized for its strong portability and superior spatial heterogeneity, has gained widespread acceptance in fields such as hydrology and environmental science, and is extensively applied in hydrological simulation studies across large-scale river basins. Hydrological models of the study area can be constructed in the SWAT model to simulate changes in hydrological variables by conducting spatial discretization, parameter specification, and boundary condition definition. Standardized drought index can effectively reflect the spatiotemporal variations in drought disasters, holding significant importance for clarifying and predicting drought characteristics. This study took the Luanhe River Basin as the research area, constructed a watershed hydrological model based on SWAT, and projected changes in the basin’s hydrological processes for the period 2030–2060. Based on the model’s projected data, we calculated drought indices and extracted drought events for the basin. The results indicate the following: (1) During the simulation period, only 30% of the years in the Luanhe River basin had annual runoff above the long-term average, with a range of 228.18 mm. The range of mean annual runoff across sub-basins was 173.32 mm. Drought and uneven water resource allocation over both spatial and temporal scales coexisted, and this issue is expected to intensify under future climate warming and drying. (2) The mid-reaches of the Luanhe River are more prone to drought compared to the upper reaches for its higher water demand. However, due to a stronger capacity for ecological restoration, droughts there are mostly of low intensity in the mid-reaches. In contrast, the upper reaches experience more periods classified as severe or extreme drought, and the drought events encountered are generally more intense than those in the mid-reaches. (3) The method proposed in this study can screen extreme drought events based on outliers in the characteristic values of drought events. Taking the simulation from this study as an illustration, anomalies in drought event characteristic values suggest a potential basin-scale, prolonged extreme drought event in the Luanhe River Basin from June 2038 to July 2042. Proactive drought prevention policies should be formulated for this period. The findings of this study provide guiding significance and practical value for drought assessment, risk management, and policy application in the Luanhe River Basin. This study methodologically combines hydrological model predictions with drought event responses, providing a novel method for predicting basin-scale drought conditions and issuing early warnings for extreme drought events. Full article

The increasing frequency and severity of wildfires pose growing challenges to ecological security in remote forest regions. In road-sparse primeval forests, wildfire prevention and ground emergency response are constrained not only by fire-prone environmental conditions, but also by limited tactical access routes. Existing wildfire susceptibility studies can identify areas with higher fire occurrence potential, whereas route planning studies often optimize access without explicitly considering where fires are more likely to occur. This study developed a GIS-based decision-support framework linking wildfire susceptibility modelling with firefighting access route planning in the northern primeval forest region of the Greater Khingan Mountains, China, to improve the efficiency of wildfire prevention and response in areas with sparse road networks. Using 887 historical fire points and nine environmental and anthropogenic predictors, Logistic Regression (LR), Random Forest (RF), and Extreme Gradient Boosting (XGBoost) models were compared to identify relatively wildfire-prone areas. High-susceptibility locations were grouped into operational management zones using K-means clustering. A generalized forest traversal cost surface was constructed by integrating terrain, vegetation, land cover, water constraints, and existing-road accessibility, and a hybrid simulated annealing and 2-opt algorithm was used to design candidate access corridors. Results show that the RF model achieved the best internal-validation performance (AUC = 0.948; overall accuracy = 0.873), and feature-importance comparison showed that land surface temperature, proximity to roads, and NDVI were the most influential predictors. In total, 386 target points extracted from the high- and extreme-susceptibility classes were grouped into 12 spatial clusters. The optimized network identified 1008.46 km of candidate corridors and reduced the mean nearest-access distance for 13 historical wildfire events by 53.7% after the planned network was incorporated. After incorporating the planned corridors into the existing road system, the road-network density increased from 0.96 to 2.015 m/hm². These findings demonstrate that susceptibility-driven route planning can translate predicted fire-prone areas into prioritized management units and candidate access corridors, thereby reducing spatial accessibility gaps and supporting phased patrol deployment and emergency-resource allocation in road-sparse primeval forests. Full article

Wildlife-vehicle collisions (WVCs) represent an important ecological and road-safety problem, yet the influence of short-term meteorological variability on their occurrence remains insufficiently understood. This study investigated the associations between temperature extremes, abrupt temperature changes, and broader hydro-meteorological conditions and reported WVC frequency in Serbia over a 10-year period (2016–2025). A municipality-day dataset comprising 6281 police-reported WVCs was analyzed using an event-based methodology. Exploratory analyses were complemented by Poisson regression models to evaluate prolonged temperature episodes, abrupt temperature shocks, and broader hydro-meteorological conditions, while additional regional analyses examined the consistency of the observed associations across Serbia. The results demonstrated pronounced seasonal variation, with the highest reported WVC frequencies occurring during spring and late autumn. At the national level, prolonged cold episodes were associated with significantly lower reported WVC frequencies during their onset and middle phases, whereas heat episodes showed no significant associations. Abrupt cool-down shocks were associated with a short-term increase in reported WVC frequency on the day of the temperature decrease, while warm-up shocks showed no significant effects. Moderate and heavy precipitation, snow-day conditions, and prolonged dry spells were associated with reduced reported WVC frequency, whereas daily mean temperature and atmospheric pressure were not independently associated with reported WVC frequency. Regional analyses generally supported the national findings, although no regional associations remained statistically significant after false discovery rate correction. These findings demonstrate that short-term meteorological variability is associated with reported WVC frequency in a temporally dependent manner and highlight the importance of considering both environmental events and regional variability when investigating wildlife-vehicle collisions. Full article

Extreme droughts can rapidly reshape surface-water patterns in river-connected floodplain wetlands, yet the fine-scale responses of individual dish-shaped sub-lakes remain insufficiently resolved. This study focused on the 2022 extreme drought in Poyang Lake, China’s largest freshwater lake and a globally important floodplain wetland system. The objectives were to quantify wetland landscape changes during the 2022 extreme drought event and to compare the heterogeneous responses of dish-shaped sub-lakes under contrasting surface-water linkage and management-context settings. We developed a high-resolution wetland monitoring framework on the Google Earth Engine platform by integrating Sentinel-2 multispectral imagery, Sentinel-1 synthetic-aperture radar, and the Dynamic World land-cover product. This multi-source approach was designed to reduce spectral confusion among turbid water, saturated mudflats, and exposed lakebeds during extreme low-water stages. Monthly wetland maps were generated for the Poyang Lake National Nature Reserve and compared with a five-year historical baseline from 2017 to 2021. The framework achieved an overall accuracy of 87.44%, with a Kappa coefficient of 0.80. The results revealed a rapid wet-to-dry transition in 2022. The water area contracted by 78.1% from July to September and remained 73.6–74.7% below the historical baseline from September to November. This contraction was accompanied by extensive observable surface-water fragmentation, apparent loss of visible surface-water linkage among sub-lakes, and substantial wetland habitat contraction. Sub-lakes exhibited clearly differentiated drought responses. Sub-lakes with stronger visible surface-water linkage to the main lake generally experienced more rapid water loss during recession, whereas reserve-managed or facility-present sub-lakes retained residual water to varying degrees and may have provided important refugial habitats for waterbirds and aquatic species. These findings suggest that surface-water linkage condition, local topographic setting, and 2022 management context were jointly associated with the heterogeneous drought responses of sub-lakes. The proposed framework provides a tool for monitoring wetland landscape changes associated with extreme drought events, assessing ecological vulnerability, and supporting adaptive water-level management under intensifying climate extremes. Full article

Although metal-modified biochar demonstrates high efficacy for phosphorus (P) removal in aqueous systems, its soil-scale mechanisms and ecological consequences under extreme rainfall remain largely unknown. In this study, we investigated how iron-modified biochar (BC+Fe) regulates P leaching and soil microbial communities in acidic soils using adsorption assays and column leaching experiments under simulated prolonged heavy rainfall. Mechanistically, BC+Fe exhibited adsorption kinetics that were better described by the pseudo-second-order model, consistent with a chemisorption-dominated P retention mechanism. Across six consecutive leaching events, BC+Fe significantly increased soil pH from 4.1 to 4.5 and reduced cumulative P loss by 37.7% compared to unmodified biochar (BC), with the most pronounced mitigation occurring during the initial leaching events when P losses were greatest. After leaching, soil total and available P concentrations under BC+Fe were approximately 3.4- and 3.7-fold higher, respectively, than under BC. Crucially, while both biochar types shifted bacterial community composition, BC+Fe maintained bacterial Shannon diversity and network complexity at levels comparable to the unamended soil and significantly higher than those under BC. Further analysis revealed that P leaching loss and soil pH were the primary environmental drivers shaping these microbial responses, and specifically, severe P loss was directly associated with simplified network complexity and intensified microbial competition (reflected by increased negative cohesion). Functional profiles inferred using Tax4Fun2 further showed that BC+Fe supported higher predicted microbial functional redundancy than both BC and the unamended control. Collectively, these findings demonstrate that iron-modified biochar mitigates P leaching through robust chemisorption and pH stabilization, while concurrently safeguarding microbial network complexity and functional redundancy. This dual benefit highlights the potential of iron-modified biochar as a sustainable amendment for maintaining soil ecosystem buffering capacity against severe hydrological stress. Full article

Extreme climate events can disturb vegetation dynamics and alter ecosystem stability. This study investigated the evolution of extreme climatic conditions and vegetation greenness across the Yangtze River Basin during 1982–2022 by integrating CN05.1 daily meteorological records with the PKU-GIMMS NDVI V1.2 dataset. Using the index framework of the ETCCDI, fifteen extreme weather-related climate indices were calculated. Trend magnitudes were quantified using Sen’s slope estimation, while the Mann–Kendall trend test was used to determine the direction and significance of long-term changes. Both standard correlation and lagged cumulative correlation were used to assess NDVI–climate relationships; the latter tested ten predefined windows formed from climate conditions between the current month and three months before each NDVI observation, with the largest absolute correlation defining the optimal window. The basin experienced a distinct warming signal in temperature extremes during 1982–2022, characterized by reduced occurrences of TN10p and TX10p, together with more frequent TN90p and TX90p events. Precipitation extremes showed an overall intensification, with R95p and R99p increasing by 9.2 mm per decade and 5.6 mm per decade. NDVI also increased throughout the analysis period, with a basin-wide rate of 0.0038 per decade and the fastest greening in the middle reaches at 0.0069 per decade. Vegetation NDVI was generally positively associated with warm-related temperature indices and negatively associated with cold-related indices. The lagged cumulative analysis identified the strongest NDVI–climate associations within windows combining current and antecedent climate conditions, with marked differences among subregions and vegetation types. Because the analyses are correlation-based and did not quantify non-climatic drivers such as land-use change or ecological restoration, the results should be interpreted as statistical associations rather than causal attribution. Overall, these findings characterize how vegetation greenness covaries with extreme climate indices across the Yangtze River Basin. Full article

The Southern Jiangsu hills region is located within the Yangtze River Delta Ecological Barrier. Soil erosion poses a threat to the development of commercial forests and the water quality of Lake Taihu, making it urgent to quantify the mechanisms by which vegetation and rainfall regulate slope erosion. This study established five standard runoff plots in Zhangzhu, Yixing, and continuously monitored runoff and soil loss from 2022 to 2023. By combining Random Forest modeling, partial least squares structural equation modeling (PLS-SEM), and moderation effect analysis, the study assessed the contributions of various driving factors under different rainfall types. The results indicate that the peach orchard (PEA + GRA) is an optimal ecological model, achieving runoff and sediment reduction rates of over 54.09% and 70.19%, respectively. Rainfall is the dominant factor driving runoff (r = 0.75), while the maximum 30 min rainfall intensity (I₃₀) is the dominant factor driving soil loss (r = 0.82). Furthermore, during low- to moderate-intensity rainfall events, vegetation attributes primarily govern hydrological responses; however, during extreme Type III rainstorms (24 h rainfall exceeding 50 mm), rainfall volume becomes the decisive factor. Moderation analysis further reveals that vegetation height and cover exert significant moderating effects on the initial transition phase from rainfall to runoff. These findings provide evidence-based guidance for optimal soil and water conservation strategy selection in subtropical hilly landscapes. Full article

The ICARIA Horizon Europe risk-assessment framework and web-based Decision Support System (DSS) were applied in the Southern Aegean Region (Greece) to quantify single- and multi-hazard climate risks (wildfire, heatwave, extreme wind) and to assess adaptation under historical and future climates (SSP1-2.6, SSP5-8.5). The study integrates high-resolution hazard layers (5 km Fire Weather Index, downscaled temperature extremes), satellite-derived land surface temperature (30 m LST for building exposure), asset-level exposure and vulnerability, and probabilistic event-tree-based multi-hazard modelling, and was tested with stakeholders in Rhodes and Syros. Results show increases in wildfire and ecological multi-hazard risk: ecological high-risk (categories 4–5) areas expand by ~10–15%, and economic high-risk zones by ~5–8%. On Rhodes, very high fire-weather days (FWI > 70) rise under SSP5–8.5, and the central mountains shift into the highest ecological risk (category 5). A multi-hazard indicator (FWI > 80, Tmax > 30 °C, wind > 10.8 m/s) identifies persistent future hotspots. The 2023 Rhodes wildfire (~17,600 acres burned; ~€1.29 M electricity, ~€400 k water damage, ~2500 livestock and ~60,000 olive trees lost; ~19,000 evacuees) supports model projections. Adaptation substantially reduces risk. Vegetation substitution (e.g., Ceratonia siliqua, low-flammability stands) cuts category-5 ecological areas by ~30–32% and high-risk economic areas by ~20% (single hazard) and ~28–34% (multi-hazard). On Syros, retrofitting 1980–2010 buildings reduces top-risk classes (4–5) by ~25–35% and lowers thermal-stress exposure. Stakeholder trials found the DSS user-friendly and useful for comparing business-as-usual versus adaptation scenarios and for strategic planning, while highlighting needs for broader hazard coverage and continued support. Full article

River networks influenced by tides represent dynamic, hydrologically complex systems where fluvial inflows interact with oceanic tidal forcing. Conventional flow-based indica-tors of hydrologic alteration (IHA) inadequately capture tidal-driven dynamics, including diurnal water level fluctuations, flow reversals, and tidal asymmetry. This study develops an augmented IHA (AIHA) framework comprising 96 indicators derived from hourly-resolution hydrodynamic simulations (1960–2019) in the Pearl River Delta (PRD), China. The AIHA extracts four daily series—ebb-peak flow and residual, highest, and lowest water levels—supplemented by tidal characteristic metrics. A moving t-test identified 1991 as the significant regime shift, enabling comparison of reference (1960–1991) and altered (1992–2019) periods. Three-dimensional alteration was assessed as follows: deviation from the range of variability (RVA), shift in central tendency (RCM), and change in dispersion (RCD). Indicator importance was integrated via CRITIC weighting and multi-site Borda scoring. Results show that range shifts and central-tendency shifts were generally dominated by low-intensity alteration, accounting for 58.3–71.9% and more than 85% of the indicators, respectively, whereas dispersion shifts were more pronounced, with medium- and high-alteration indicators accounting for an average of 42.4%. Water level indicators exhibited substantially greater alteration sensitivity than flow indicators, particularly in estuarine zones where the alteration degrees of some indicators exceeded 90%. Among hydrological elements, ebb-peak flow indicators responded more strongly in range shifts, with an average comprehensive alteration degree of 29.6%, while water level indicators showed more pronounced changes in central tendency and dispersion; the lowest water level indicators were especially sensitive, with average comprehensive alteration degrees of 19.6% and 77.3%, respectively. Spatially, center-of-distribution shifts (RCM) diverged: positive in western/northern tributaries (increased flows) versus negative in the eastern PRD (decreased flows). Integrated Borda scoring identified low-flow extremes during dry seasons, event timing, and tidal modulation as the most sensitive responses to hydrological stress. The AIHA framework demonstrates that tidal river alteration is characterized by intensified low-flow volatility and amplified tidal influence, with water level metrics providing a superior detection capacity than achieved by discharge alone. This process-integrated approach offers robust quantitative support for ecological flow management and estuarine restoration in tidal environments globally. Full article