Search Results (448)

To gain a deeper understanding of the lower-atmospheric dynamic characteristics in the transition zone on the northeastern margin of the Tibetan Plateau, high-resolution wind profile data collected by a Doppler wind lidar (DWL) at Yinchuan Hedong International Airport from 2021 to 2023 were used to analyze the vertical structure, seasonal variations, and diurnal characteristics of the low-height wind field and wind shear in this region. The results indicate that (1) the data acquisition rate (DAR) below 1.5 km is generally high, exceeding 90% during most periods, and decreases monotonically with height; the 90% DAR contour height exhibits clear seasonal and diurnal variations, with the largest diurnal amplitude in summer and the smallest in winter. (2) The middle- and low-height wind fields are jointly modulated by topographic forcing and local circulations. Below 0.4–0.7 km, north–northeast and south–southwest winds prevail across all seasons, which is consistent with the blocking and splitting effects of the Helan Mountains. At 42 m, the wind direction shows a marked diurnal transition that may reflect the combined influence of the Helan Mountains’ bypass flow, mountain–plain circulation, and thermal contrasts between the Yellow River and surrounding desert/plain surfaces. (3) Horizontal wind speeds are predominantly concentrated below 6 m s⁻¹, and the development height of this low-wind-speed zone varies seasonally. The vertical velocity statistics show weak positive values in parts of the observed layer, but these signals are interpreted cautiously because vertical-velocity retrieval is subject to additional uncertainty. (4) The low-level wind shear intensity reaches its peak below 100 m and generally exhibits a U-shaped vertical distribution; severe wind shear below 100 m occurs most frequently from nighttime to early morning during May–October, whereas its occurrence frequency is lowest in winter. These findings provide observational evidence for aviation meteorological support and boundary-layer studies in semi-arid regions of Northwest China. Full article

Boundary-layer atmospheric stability, wind-shear variability, and thermodynamic forcing are all important factors for the initiation, intensification, and transport of dust storms. But there is limited knowledge of the quantitative evaluation of bulk-layer atmospheric stability and the relation between wind-driven dust dynamics and atmospheric stability in arid and semi-arid regions. In this research, a hybrid AI–meteorology framework, HyMet-Fusion, is presented that combines visual information derived from satellite observations with physics-based indicators of atmospheric stability to evaluate atmospheric stability during dust storm events over Iraq. The proposed framework is based on the use of deep features extracted from the satellite imagery through a frozen EfficientNetB0 backbone, combined with indicators derived from the ERA5 pressure level data for the atmosphere, such as the Bulk Richardson Number (Bulk Ri), the Wind Shear (WS) and the Dry Air Index (DAI). The two branches were merged using a late fusion (0.75 physics/0.25 image) and each hour was classified into three atmospheric stability conditions: Relatively Stable, Moderately Unstable and Unstable. The overall hourly accuracy using a Leave-One-Event-Out (LOEO) cross-validation scheme, where each dust event was used for independent testing and no dust event was used for training, was 72.4%, with 81.2% accuracy for the dominant stability state and 92.2% correct assessment of the unstable condition time for the severe dust events. Inaccuracies were mainly (66%) in the conservative direction (more instability). Unstable atmospheric conditions were also found to be associated with all severe dust storms and coincided with higher wind shear, lower Bulk Ri values and higher thermodynamic variability. Moderate and light dust events were primarily associated with transitional and relatively stable atmospheric conditions, and differed between the various regions, primarily in Kirkuk and Nasiriyah. Correlation analysis showed that wind shear had the highest correlation with atmospheric instability (r = 0.92), followed by DAI (r = 0.90) and Bulk Ri (r = −0.75). In addition, the wind shear also increased significantly from light to severe dust events at all stations investigated, showing that wind shear is a critical factor for turbulent mixing, vertical momentum exchange and dust uplift processes. The results suggest wind shear is the leading dynamics mechanism for bulk-layer instability in Iraqi dust storms. The findings highlight the complementary benefit of using physics-based atmospheric indicators embedded with deep learning satellite image analysis. The HyMet-Fusion system can be used as a transferable method for observing wind-driven instability of the atmosphere and related dust hazards, which could be employed in boundary-layer meteorology, air-quality forecasting, aviation safety and environmental risk assessment in arid and semi-arid areas. Full article

An analytical non-Hermitian bilayer composed of coupled right-handed and left-handed $LC$ lattices is investigated. The uncoupled lattices exhibit exact dual dispersions characterized by complementary direct and inverse excitation spectra. When the layers are coupled through a purely imaginary interlayer coupling, the resulting non-Hermitian Hamiltonian undergoes exceptional-point transitions that separate regions with purely real eigenenergies from regions with complex eigenenergies. It is shown that the spectral splitting is progressively transferred from the real-energy sector to the imaginary-energy sector, giving rise to hybridized modes with finite lifetimes. The corresponding relaxation time, which is directly related to the mobility of the excitations, is governed by the imaginary-energy splitting and diverges at the exceptional-point boundary. These findings establish a direct connection between electromagnetic duality, non-Hermitian spectral properties, and transport phenomena in mesoscopic networks. Possible extensions of the present approach may be relevant for artificial circuit platforms, including Josephson-junction arrays. Full article

Mineral-scale deposition remains a persistent flow-assurance and asset-integrity constraint in oil and gas production. Calcium carbonate, calcium sulfate, barium sulfate, iron sulfide, and mixed inorganic scale deposits reduce tubing internal diameter. They also impair near-wellbore permeability, block safety-critical valves, reduce heat-transfer efficiency, and intensify under-deposit corrosion. Conventional management relies on prediction, chemical inhibition, squeeze treatments, acid dissolution, chelation, mechanical scraping, milling, jetting, and operational water management. These methods are indispensable, but each has a restricted operating envelope. Key limitations include mineral selectivity, corrosion risk, environmental discharge, intervention cost, debris generation, and poor effectiveness against chemically resistant sulfate scales, particularly BaSO₄. Ultrasound has therefore attracted interest as a non-chemical technology. Acoustic cavitation, microstreaming, pressure oscillation, mechanical vibration, and micro jetting may suppress nucleation, disturb boundary layers, weaken adhesion, and fragment brittle deposits. This review critically evaluates ultrasound-assisted scale prevention and removal, with emphasis on production tubing and oilfield relevance. Existing studies show credible mechanistic plausibility and promising laboratory performance for CaCO₃, CaSO₄/gypsum, KCl, NaCl, and membrane or heat-transfer fouling systems. It also compares performance metrics, field cases, and technology-readiness barriers. The evidence is less mature for long steel tubulars operating under high-pressure, high-temperature, multiphase production conditions. Current evidence positions ultrasound at technology-readiness level (TRL) 3–4 for CaCO₃ and CaSO₄ systems, where laboratory and bench-scale validation is established, and at TRL 2–3 for BaSO₄, where mechanistic plausibility exists but controlled experimental validation remains absent. The technology is not yet at the pilot–production transition for downhole tubing applications, but it is approaching that threshold for surface process equipment. Its most credible near-term role is as an intensifier paired with low-dose chemical inhibitors, where acoustic boundary-layer disruption can reduce the minimum inhibitory concentration threshold of inhibitors, and with mild chelating agents for early-stage BaSO₄ management, where ultrasound-enhanced mass transfer may accelerate chelant penetration into deposit microstructure. Advancing ultrasound from its current TRL toward field qualification requires targeted BaSO₄ scale validation in steel tubing systems, acoustic field mapping under HPHT multiphase conditions, mass-removal metrics, and a structured pilot programme. Full article

Kozarnika Cave revealed a lengthy archaeological sequence covering the Lower, Middle, and Upper Paleolithic periods. The site is a significant milestone in understanding the various stages of early human colonization and migration into Europe. The available paleomagnetic data indicate that the lower boundary of the deposits corresponds to the Brunhes–Matuyama reversal. During the archaeological excavations, an exceptionally rich assemblage of small mammal remains was recovered. Based on small mammals, two biozones have been delineated—lower (Biozone B) and upper (Biozone A)—which correspond to the Late Biharian and Toringian, respectively. In the present study, a total of 75 species of terrestrial small mammals (Eulipotyphla, Lagomorpha, Rodentia) are analyzed in detail. One new species, Nannospalax sirakovi sp. n., is described. Based on geometric analysis of the mass material of voles (Microtina and Lagurus), the controversial taxonomic positions of some species have been clarified. It has been proven that Microtus arvalinus is a distinct species. Rapid evolution within the species Lagurus transylvanicus towards the modern species L. lagurus has been demonstrated. In all layers of Biozone B, two important guide fossils, Mimomys savini and M. blanci, occur. They are indicative of the second stage of the Early Biharian, which is considered earlier than the Brunhes/Matuyama reversal. Besides this, multiple species characteristic of the Early Pleistocene (Villanyian and the Early Biharian) have been identified (Borsodia newtoni, B. arankoides, Prolagurus pannonicus, Ungaromys nanus, Villanyia cf. exilis, Allophaiomys deucalion, A. cf. pliocaenicus, A. cf. burgondiae, Mimomys pitymyoides, M. cf. tornensis, Lagurus arankae). Although very scarce, they occur regularly in the stratigraphic assemblages of Biozone B, which is dominated by typical Late Biharian species, such as Allophaiomys gregaloides, Microtus arvalidens, M. nivalinus, M. nivaloides, and L. transylvanicus. The occurrence of Mesocricetus newtoni and Spermophilus citellus in Biozone B marks the earliest known occurrence of these species. The faunal turnover within the lower part of the deposits has been analyzed in detail. A reorganization of the fauna has resulted from the gradual disappearance of the Early Pleistocene species. Paleoecological reconstructions based on stratigraphic assemblages of small mammals suggest that the faunal turnover recorded in Biozone B is associated with paleoclimatic changes during the MIS19–MIS17 interval and reflects a reorganization of the biota related to the mid-Pleistocene transition. This period was marked by significant changes in Earth’s climate, shifting from low-amplitude 41,000-year obliquity-driven cycles to high-amplitude, roughly 100,000-year fluctuations that define the later Pleistocene and Holocene. Full article

Extreme spatial intensification in affordable housing exposes the structural limitations of conventional room-based zoning, yet existing generative design methods often fail to deeply couple spatial automation with volatile occupant behavioral logic. This study proposes a generalizable Structure–Behavior–Function (SBF)-based generative framework to realize the transition from top-down rigid zoning to bottom-up behavioral adaptation. The framework deconstructs traditional rooms into three coupled layers: minimal ergonomic action domains (structural), 3D Design Structure Matrix-based activity correlation quantification (behavioral), and multi-objective optimization metrics encoding (functional). A discrete grid-based evolutionary approach with a hard–soft dual-constraint mechanism is introduced, combining geometric collision detection for physical feasibility and behavioral correlation rules for spatial zoning reward–punishment. Layout performance is validated via pedestrian circulation simulations. Using a representative megacity affordable housing standard as a case study, controlled computational experiments reveal an empirical power-law scaling boundary between minimum viable area and occupancy size. We establish an Adaptability Surcharge Index (ASI) to quantify the 3.0–7.2% spatial efficiency degradation from rigid structural constraints. The framework achieves 30.3–45.7% floor area reduction versus traditional benchmarks while maintaining comparable circulation efficiency. Validation using an existing residential case further confirms the practical applicability of the proposed framework. This work provides a scalable computational methodology for hyper-dense spatial optimization and a quantitative foundation for future residential space standard formulations. Full article

Vehicle-to-grid (V2G) integration in commercial building microgrids (CBMGs) offers a promising path for grid support, economic arbitrage, and resilience enhancement. However, practical implementation is hindered by the optimization–execution gap, where high-level aggregated commands fail to match low-level physical charger capacities and individual battery boundaries, as well as by the lack of sociotechnical coupling under extreme weather events, where vehicle owner range anxiety dominates. To address these challenges, a closed-loop multi-timescale energy management system for V2G-enabled CBMGs under exogenous meteorological conditions is proposed. The framework features an integrated four-layer cyber–physical control architecture connecting macroscopic day-ahead scheduling, receding-horizon model predictive control (MPC), discrete real-time parking slot allocation with hardware safety boundary constraints, and equipment-level power flow execution. To handle extreme events, an exogenous meteorological stress index is formulated to quantify ambient structural hazards and temperature deviations, which are then mapped to owner range anxiety and loss-aversion behaviors using prospect theory. Rather than relying on heuristic rule-switching, the optimizer executes a smooth and continuous transition from normal economic peak-shaving to active pre-disaster energy reservation and load demand survival. The cyber–physical system is validated using high-fidelity simulations under typical summer and winter blizzard scenarios. The results demonstrate that the proposed hierarchical architecture successfully eliminates optimization–execution mismatches and guarantees zero load shedding. Furthermore, sensitivity analyses establish the optimal system configuration with the critical defense tolerance of 0.6 and the baseline anxiety ratio of 4, which successfully resolves the trade-off between premature defensive actions and insufficient energy reserves while considering human behavioral uncertainty. Full article

The mechanistic understanding of biogeochemical dynamics in the Gulf of Guinea (GoG) has historically been hindered by persistent cloud cover and reliance on static geographic boundaries. In this study, we analysed a 20-year (2003–2022) satellite-derived chlorophyll-a (Chl-a) dataset to overcome these observational limitations through a three-part spatial and machine-learning framework. First, the Data Interpolating Empirical Orthogonal Functions (DINEOF) algorithm reconstructed a gap-free climatology, demonstrating robustness under extreme simulated cloud cover (R² = 0.884). Second, a Fuzzy C-Means (FCM) clustering algorithm objectively partitioned the basin into three dynamic, physically driven bioregions: an oligotrophic gyre, river plumes, and an upwelling mega-cluster. Third, we applied an explainable Random Forest framework, supported by SHapley Additive exPlanations (SHAP), to identify the main physical and biogeochemical predictors associated with coastal Chl-a variability using hindcast nutrients and a strict chronological split (training: 2003–2018; test: 2019–2022). The models produced conservative but meaningful independent test-period performance across coastal zones, with R²_log values from 0.437 to 0.595. Rather than revealing a new ecological paradox, the framework provides a basin-specific interpretation of a globally documented pattern: offshore oligotrophication alongside localized coastal enrichment. The open ocean and transition/upwelling sectors show negative Chl-a tendencies consistent with sea surface warming, enhanced stratification, and reduced upward nutrient supply. Conversely, coastal ecosystems are structured by local hydrological and wind-driven forcings that modulate the regional climate signal. In the Congo plume, Chl-a variability is primarily structured by haline plume dynamics and secondary nutrient constraints, whereas the Niger plume reflects coupled mixed-layer and terrigenous nutrient controls. These findings establish a spatially objective typology of the GoG, providing a regional reference framework for future high-resolution missions, monitoring, and coupled physical–biogeochemical modelling. Full article

Tracking capacity fade and predicting the lifespan of Lithium Iron Phosphate (LiFePO₄) batteries under calendar aging are crucial for the reliability of Battery Energy Storage Systems (BESSs) in tropical regions. Conventional empirical models often rely on static environmental averages and neglect coupled thermal–hygroscopic dynamics. To address these limitations, this paper introduces a multi-physics coupled state-space-based continuous integral model for battery degradation under dynamic tropical boundary conditions. The primary novelty of this research lies in the development of a continuous-time multi-physics state-space degradation model that explicitly captures the interconnected interactions between temperature, humidity, and State of Charge (SoC) under dynamically varying tropical microclimates. Calendar aging tests were conducted for 180 days inside an environmental test chamber under tropical microclimate conditions (average of 29.91 °C, RH of 77.26%), with reference performance tests executed at a low C-rate of C/20 to extract static electrochemical capacity. Parameter identification using an Ordinary Least Squares (OLS) solver demonstrates high model fitting, with R-squared values ranging from 0.8229 to 0.9429. Extrapolation results provide realistic end-of-life projections between 8.9 and 59.8 years and successfully identify the critical physical transition points P1 and P2 at the Solid Electrolyte Interphase (SEI) layer. Overall, this research provides a prognostic instrument for optimizing the operational management of utility-scale BESS in tropical climates. Full article

Main memory carries data outside the processor’s trust boundary, so commodity systems-on-chip (SoCs) increasingly encrypt it; yet, in-line memory encryption engine itself becomes a differential power analysis (DPA) target whose key, if recovered, unlocks all of dynamic random-access memory (DRAM). We present PACE, a page-adaptive, cache-anchored memory encryption engine for RISC-V that makes nth-order DPA resistance practical and keeps cryptographic latency off the cache eviction critical path. PACE inserts a TileLink adapter between the last-level cache and the memory port and applies, per physical page, one of four policies (plaintext/confidentiality/confidentiality+integrity/+masking-order-d) selected from RISC-V page table bits through a memory-mapped control plane. Confidentiality uses counter mode whose per-line keystream is precomputed during cache residency; integrity is tree-free at the embedded operating point via on-chip counters and tags, with a live split counter block-MAC Bonsai Merkle tree for scale-out. DPA resistance is layered: ISAP-style fresh re-keying caps the data complexity per key at $q\approx 1$, and domain-oriented masking (DOM, d + 1 shares) protects the sole key processing block to order d. We implement PACE in Chisel on a Rocket SoC (Chipyard) and evaluate it with open-source tooling. A deterministic TileLink-level harness proves ciphertext-in-memory and detects tamper/replay/splice, and the live Tier-B engine (DRAM counters and per-line message authentication codes (MACs) plus an on-chip-rooted block-MAC tree) is validated from end to end on full Rocket and BOOM SoCs and on the FPGA; the masked Ascon-p S-box is proven order-d secure (d = 1, 2) under a glitch- and transition-aware model by three independent formal tools (COCO, PROLEAD, and SILVER, the last also deciding the full composability lattice and confirming exact glitch-robust order-2 probing security), with COCO extending the exact verdict to the highest synthesized order d = 3 (secure at probing orders 1–3); a simulated trace correlation power analysis (CPA) recovers the full key from an unprotected core and is defeated by masking, with a mutual information analysis confirming the $N\propto {\sigma }^{2(d+1)}$ trace amplification law. We further realize PACE on field-programmable gate array (FPGA) silicon: the engine plus an on-chip ring oscillator power sensor is placed, routed, timing-closed at 100 MHz, and programmed on a Xilinx XC7Z020, and we drive a fixed-vs-random Test Vector Leakage Assessment (TVLA) campaign read back entirely over a JTAG (Joint Test Action Group). A multi-core configuration and a Linux control-plane driver are likewise validated. Across synthetic access patterns and named application kernels (AES, SHA-256, matrix multiplication, pointer chasing) on both in-order Rocket and out-of-order BOOM, application-level overhead is within measurement noise of plaintext for cache resident workloads (masking, in particular, is cycle-identical to plain confidentiality), and we characterize the cost of each policy, masking order, and re-keying interval, demonstrating side-channel-hardened memory encryption on open RISC-V hardware. Full article

Dynamic Positioning systems are crucial for modern marine vessels to maintain positions or track trajectories under environmental disturbances. Traditional model-based and neural network control schemes often suffer from heavy computational burdens, low-velocity nonlinearities, and chattering near decision boundaries during waypoint transitions, which can trigger actuator saturation. To address these challenges, this paper proposes an enhancing robust adaptive control algorithm. Specifically, a model-free control framework is developed by employing an asynchronous deep Actor–Critic neural network with multi-layer perceptron for high-precision policy approximation in continuous spaces. To accelerate convergence, an online meta-driven radial basis function network is proposed for adaptive reward shaping, optimized by the Adam scheme. Furthermore, at the guidance level, a hysteresis state machine and an adaptive damping reference model are designed to decouple wave-induced high-frequency chattering and eliminate thrust saturation. By applying dynamic surface control, the proposed scheme avoids complex thrust allocation calculations. The proposed method enhances system autonomy and ensures smooth transient behavior while maintaining compatibility with standard marine hardware. Full article

This paper reviews numerical modeling approaches for Dielectric Barrier Discharge (DBD) plasma actuators in aircraft active flow control. While extensive experimental studies exist, a dedicated review of computational methodologies—covering macroscopic, microscopic, and empirical models—has been absent. This work systematically evaluates major models (Shyy, Suzen–Huang, Dorr–Kloker, Roth, Orlov–Corke, Massines), discussing their formulations, assumptions, computational cost, and applicability. It synthesizes simulation studies in aerodynamic applications such as separation control, drag reduction, transition delay, film cooling, and compressor stability. Key findings show that macroscopic models offer a practical balance between accuracy and cost for design-oriented studies, whereas microscopic models provide deeper physical insight at higher expense. The review highlights the effectiveness of DBD actuators in modifying boundary layers, delaying stall, and improving aerodynamic efficiency. Finally, persistent challenges are identified—including energy efficiency, scalability, and model calibration and future directions are suggested, such as hybrid modeling, multi-actuator arrays, and real-time control integration. Full article

Against the global backdrop of carbon peaking and carbon neutrality goals, renewable energy subsidy policies worldwide are shifting from universal, tariff-based schemes toward targeted, market-oriented mechanisms. However, existing research remains divided on the incentive effects of subsidies on firm investment and the risk of resource misallocation, and few studies have established a clear micro-macro linkage between firm-level subsidy receipts and regional employment and growth outcomes. Taking China’s 2016 renewable energy subsidy reform—characterized by competitive project bidding and green certificate trading—as a quasi-natural experiment, this study constructs a two-layer panel dataset covering 286 A-share listed renewable energy firms (2010–2023, 2412 firm-year observations) and 30 provincial-level regions in China (2010–2023, 420 region-year observations). Employing difference-in-differences (DID), triple difference-in-differences (DDD), mediation effect models, and threshold regression, combined with instrumental variables and placebo tests to address endogeneity, we empirically examine how subsidy policies transmit from firm behavior to regional employment and economic growth. The results indicate that the 2016 reform significantly boosted regional employment (elasticity = 0.035, p < 0.01) and economic growth (elasticity = 0.031, p < 0.05) in treated provinces. At the firm level, subsidy intensity exhibits an inverted U-shaped relationship with investment efficiency, with an estimated inflection point at 8.3% of operating revenue within the sample. Mechanism analysis shows that easing financing constraints, stimulating technological innovation, and reducing operational risk serve as core transmission channels, with the strongest contribution from financing constraint alleviation. Heterogeneity analysis further finds larger effects for private firms, high-tech enterprises, and coastal regions. This study develops a nonlinear analytical framework of “subsidy intensity–firm behavior–regional outcomes”, identifies context-specific boundaries of subsidy effectiveness, and provides integrated micro-macro empirical evidence for optimizing subsidy policies and advancing the global energy transition. Full article

The height of a water-conducting fractured zone (WCFZ) is directly related to the design of water-preserved coal mining and water-hazard risk assessment in ecologically fragile mining areas in western China. Existing empirical formulas have limited regional adaptability, and individual machine learning models may show insufficient stability under small-sample and nonlinear data conditions. To address this issue, a heterogeneous Stacking ensemble prediction framework was constructed based on measured data from the Yushen mining area. Mining thickness, working face length, mining method, burial depth, coal seam dip angle, and hard strata proportion coefficient were selected as input variables. The base layer consisted of support vector regression (SVR), classification and regression tree (CART), random forest (RF), extreme gradient boosting (XGBoost), and back-propagation neural network (BPNN), while Ridge regression was used as the meta-learner. Under the current data split, the test set R², RMSE, MAE, and MAPE of the Stacking model were 0.953, 10.99 m, 8.79 m, and 9.847%, respectively, indicating overall superiority over individual models and other ensemble configurations. The field validation results showed that the relative errors of the model for boreholes LD-1 and LD-2 in the fully mined area were 1.99% and 1.28%, respectively; however, an overestimation of 52.70% occurred for LD-3 in the coal-pillar-adjacent area. This indicates that the model is more suitable for the regional-scale screening of the maximum fractured-zone height and should not be directly used for fine-scale prediction in local boundary-affected zones. SHAP analysis showed that mining thickness, working face length, and hard strata proportion coefficient were the main influencing variables, and their response trends were generally consistent with key-strata control and the transition toward full-mining conditions. This study provides a reference for the rapid prediction of WCFZ height and preliminary evaluation of water-preserved coal mining in weakly cemented mining areas in western China. Full article

The Dongting Lake Region is a major river-connected lacustrine ecosystem and ecological security barrier in the middle Yangtze River Basin, where land use change has important implications for ecosystem service provision. However, how land use transition pathways and spatial clustering jointly shape land-cover-based ecosystem service value (ESV) estimates remains insufficiently understood, particularly under a coefficient-based valuation framework. This study used land-use data for 2005, 2010, 2015, 2020, and 2025 (with the 2025 layer being not fully observation-based but derived from remote-sensing interpretation and model-assisted updating rather than direct field observations). The analytical framework integrated land-use transition analysis, land-use dynamic degree analysis, equivalent-factor-based ESV estimation, spatial autocorrelation analysis, one-way parametric sensitivity analysis with a ±50% variation, and stage-specific comparisons aligned with policy implementation timelines. These methods were applied to investigate the spatiotemporal dynamics of estimated ESV in the Dongting Lake Region. Cropland, forestland, and water bodies remained the dominant land use types, while built-up land expanded through the conversion of agricultural and ecological land. Estimated total ESV declined during the study period, although the annual rate of decline was lower during 2015–2025 than during 2005–2015. Under the adopted equivalent-factor framework, water-body-related transitions contributed most to estimated ESV change, reflecting both the ecological importance of water-related systems and the high coefficients assigned to water bodies, especially for hydrological regulation. Estimated ESV showed persistent positive spatial autocorrelation, with High–High clusters concentrated around East Dongting Lake, South Dongting Lake, and West Dongting Lake. These findings provide land-cover-based evidence for territorial spatial optimization and SDG-related ecosystem management. However, the identified clusters should be interpreted as candidate lake-centered high-value ecological spaces for further assessment, rather than as definitive conservation priorities or ecological zoning boundaries. Full article