Search Results (1,611)

As a key tectonic zone formed by the India–Eurasia collision, the eastern Tibetan Plateau has complex crustal structures and intense tectonic activity. Its crustal stability is closely linked to regional geohazards and the safety of major engineering projects. This study assessed crustal stability using nine multi-source datasets, including terrestrial gravity, Bouguer gravity anomalies, seismic data, active faults, terrain indicators, and annual precipitation. A hybrid weighting framework coupling the Analytic Hierarchy Process (AHP) and CRITIC method was established, and factor analysis was further adopted to cross-verify the rationality of index weights. Moderately unstable and unstable zones appear as alternating bands with distinct linear extensions. These unstable areas are mainly distributed around Jiuquan–Zhangye–Wuwei, Xining–Haidong, Yushu–Garzê, Mianyang, and Chengdu. Statistically, stable, moderately stable, moderately unstable, and unstable zones account for 20.74%, 35.47%, 28.78%, and 15.01%, respectively. The results provide a scientific reference for regional planning and infrastructure site selection in tectonically active regions. Full article

Drought is a natural hazard characterized by gradual onset and prolonged precipitation deficit. With climate change intensifying precipitation variability, accurate drought assessment is critical for effective water resource management and mitigation. Focusing on Maryland in the Mid-Atlantic region of the United States, this study computes and analyzes drought indices to assess both near (2021–2060) and late (2061–2100) drought conditions, in the context of climate variability. We employed three distinct objectives to enhance drought assessment and monitoring capabilities under projected climate scenarios: (1) calculation of the Standardized Precipitation Index (SPI) reflecting meteorological conditions using precipitation data from seven GCMs across three SSPs for two future periods (2021–2060 and 2061–2100); (2) integration of both precipitation and temperature projections in the Palmer Drought Severity Index (PDSI) (implemented here as a simplified PDSI based on a standardized Z-index) to reflect combined hydrological and thermal influences (i.e., Hydrological indices); and (3) a Low Precipitation Duration–Frequency Analysis (LPDF) as indicator of both meteorological and hydrological conditions to quantify and compare the frequency and severity of low precipitation events across different SSPs. These objectives were achieved by fitting a gamma distribution for SPI and an Extreme Value Type I distribution for LPDF, and applying Z-index (i.e., long-term moisture abnormalities) and weighting factors representing the ratio of precipitation to evapotranspiration. Results reveal notable variability in SPI values, with a general trend toward increased extreme wet conditions, especially under high emission scenarios (i.e., SSP585) in the latter half of the century (2061–2100). Meanwhile, PDSI analysis indicated a subtle shift toward drier conditions despite increases in precipitation, particularly under SSP126 and SSP245, suggesting that temperature rises may offset precipitation gains. In addition, LPDF values indicated a reduced frequency of prolonged low-precipitation events under SSP585 compared to SSP126 and SSP245; this reflects higher total precipitation and should not be interpreted as resilience to drought, since the concurrent rise in temperature-driven evaporative demand can still intensify hydrological and agricultural drought stress. These results highlight the importance of incorporating climatic variables in drought assessments to understand future meteorological and hydrological scenarios under climate change projections. The study can help water resource managers and illustrates how such integrations can enhance our understanding of future drought scenarios under different climate change projections. 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

Urban parks provide recreation, cultural ecosystem services, microclimate regulation, and benefits for well-being, but their realized value may vary with air pollution and heat. This exploratory study linked 2947 Google Maps reviews posted in 2024–2025 to daily PM2.5, temperature, humidity, and precipitation and assessed a BERT-based workflow for classifying star-linked sentiment and dominant emotion text labels. Star-linked sentiment classifications were highly favorable (mean score of 4.86/5; 88.39% very positive). Independent weighting of the rounded air-quality and heat-stress subgroup summaries yielded consistent approximate overall shares for provisional joy (28.9%) and anger (32.5%), but the full seven-class distribution could not be reconstructed from the archive. All emotion-label analyses remain provisional. All 25 tested environmental correlations were negligible (absolute Spearman ρ ≤ 0.049), and none met the Bonferroni-corrected significance threshold (α = 0.002). Posting dates classified as heat-stress days showed descriptive differences in provisional anger and joy labels, but posting date is an uncertain proxy for the visit date. The findings do not establish individual-level exposure associations. They instead illustrate the methodological safeguards needed before user-generated park feedback and environmental monitoring can support climate-responsive management. Full article

Urban coastal cities face compounded flood hazards driven by sea-level rise, intense precipitation, and dense impervious surfaces. This study develops and demonstrates a cloud-native Python 3.12 GIS framework for flood susceptibility screening and critical facility exposure analysis in Miami, Florida, one of the most flood-exposed coastal cities in the United States. Defined here as a geospatial workflow that retrieves data dynamically from cloud-hosted APIs and executes entirely within a hosted computing environment, the framework integrates three open-source spatial indicators: terrain elevation from the USGS 3D Elevation Programme via py3dep; Euclidean distance to water bodies from OpenStreetMap via OSMnx; and building footprint density as an impervious surface proxy, also from OpenStreetMap. Indicators were standardised and combined using literature-informed MCDA weights (water proximity: 0.40; elevation: 0.35; building density: 0.25) into a continuous flood susceptibility index, classified at the 33rd- and 66th-percentile thresholds. In this proof-of-concept application, high-susceptibility zones cover 48.66 km² (34.0%) of the city, concentrated along coastal waterfronts and inland canal corridors. Overlaying critical facility locations on the classified surface indicates that 9 of 16 hospitals (56.2%), 61 of 244 schools (25.0%), and 5 of 17 fire stations (29.4%) fall within high-susceptibility zones; because this overlay uses centroid-based facility points that have not been cross-checked against official municipal or state facility registries, these counts should be read as indicative rather than definitive. Exact binomial testing shows that the school exposure deficit is statistically significant (p = 0.00), while elevated hospital exposure, although substantively notable, does not reach significance at the current sample size (p = 0.07). The susceptibility surface itself has not been quantitatively validated against external benchmarks such as FEMA flood maps or historical inundation records, the MCDA weights have not been sensitivity-tested, and spatial autocorrelation in the index has not been assessed; concrete protocols for each of these steps are specified as subsequent calibration work rather than as prerequisites for the architecture demonstrated here. The contribution of this paper is the reproducible, cloud-native workflow architecture and its proof-of-concept application, not a validated operational assessment tool; we present it explicitly as a methodological protocol and workflow demonstration, not as an evaluation of flood risk. The framework is fully reproducible, low-cost, and transferable to other US coastal cities. Full article

An integrated hydrometallurgical process for the recovery of vanadium from spent petrochemical catalysts and the production of high-purity ammonium metavanadate (AMV) was developed and experimentally validated. Alkaline leaching of roasted vanadium-bearing catalysts resulted in vanadium extraction of 90%–95%, producing a solution containing 37.0 g/L V₂O₅ together with phosphorus, sulfur, silicon, and molybdenum impurities. Two purification approaches, ion-exchange sorption and magnesium oxide treatment, were evaluated for impurity removal. Sorption using the macro porous anion-exchange resin Biolite 200U provided effective silicon removal but resulted in significant vanadium losses (up to 19.6%) due to co-sorption of vanadium and phosphorus. In contrast, magnesium oxide treatment at 70–80 °C reduced the phosphorus concentration from 0.39 to 0.04 g/L (approximately 90% removal) and completely removed silicon while limiting vanadium losses to less than 2.5%. Following purification, ammonium metavanadate was precipitated using ammonium chloride at a V₂O₅:NH₄Cl molar ratio of 1:2 and pH 8.8–9.0, achieving approximately 99% vanadium recovery. X-ray diffraction analysis confirmed the formation of single-phase NH₄VO₃ after solution purification, whereas precipitation from untreated solutions resulted in contamination by alumina-bearing phases. The proposed process provides an effective route for producing purified ammonium metavanadate suitable for subsequent conversion into metallurgical-grade V₂O₅. The ultimate goal of the proposed technology is the production of metallurgical-grade ferrovanadium (FeV80). Because AMV is thermally converted to V₂O₅ with a weight loss of approximately 24%–25%, phosphorus and sulfur concentrations in AMV must be maintained below approximately 0.04 wt.% to ensure compliance with the impurity requirements of FeV80 according to GOST 27130-94. Full article

Large river basins require spatial evidence showing where tourism-support conditions and ecological constraints coincide. Using the Yellow River Basin, we built a reproducible workflow that combines Google Earth Engine preprocessing with local spatial analysis to map tourism development suitability (TDSI), ecological sensitivity (ESI), and conflict intensity on a 1 km equal-area grid in 2013, 2018, and 2023. Annual hotspot shares remained near one-fifth of valid cells, and 153,958 cells (19.80%) entered the hotspot set in at least two benchmark years. Spatially matched reference checks were mixed: official tourism cells showed a positive high-suitability contrast against 50 km block-matched cells (0.778 versus 0.563; empirical p = 0.043), whereas OSM POIs, the named-attraction subset, and GBIF cells showed no clear geography-adjusted enrichment. Aggregation from 1 km to 2 km preserved broad structure, but weighting and ecological-constraint choices changed local membership materially. The full XGBoost–SHAP model identified precipitation variability, land-surface thermal change, protected-area proximity, relief, and road-network intensity as leading internal correlates; a strict two-covariate model achieved AUC = 0.680 and F1 = 0.538, limiting external mechanism claims. The products support uncertainty-aware regional screening. Site-specific approval and long-term persistence claims require finer regulatory, field, and temporal evidence. Full article

Borna disease virus 1 (BoDV-1) is a noncytolytic, neurotrophic virus that causes neurological disorders, where astrocytes contribute to neuropathology. Cellular prion protein (PrP^C) is involved in pro-survival signaling and antioxidative defense. Using rat astroglial C6 cells as an in vitro model, we investigated whether persistent BoDV-1 infection alters N-glycan maturation of PrP^C. Western blotting showed that PrP^C shifted toward lower-molecular-weight glycoforms as cell density increased. This tendency was more evident in BoDV-1-infected C6 cells without detectable changes in total surface PrP^C expression. Two-dimensional polyacrylamide gel electrophoresis showed a shift of PrP^C toward lower molecular weight and more basic isoelectric points. Conventional RT-PCR detected reduced signals of MGAT5, which encodes N-acetylglucosaminyltransferase V (GnTV), whereas MGAT1–4 signals were not markedly altered. In addition, GnTV overexpression induced a higher-molecular-weight shift of PrP^C. PHA-L4 precipitation followed by anti-PrP immunoblotting showed reduced β1-6-branched complex N-glycan signals associated with PrP^C. BoDV-1 infection also decreased the RT-PCR signal of E26 transformation-specific 1 (ETS1) as well as reduced ETS-dependent promoter activity and superoxide dismutase activity. These findings suggest that persistent BoDV-1 infection may impair PrP^CN-glycan maturation through suppression of the ETS1–MGAT5/GnTV pathway activity, thereby potentially affecting astroglial antioxidative capacity. Full article

This study systematically optimized the extraction processes of two bioactive constituents, total flavonoids and crude polysaccharides, from the dried underground tubers of Nephrolepis cordifolia (L.) C. Presl, and further comprehensively characterized their in vitro antioxidant activities. For total flavonoid extraction, an ethanol–ammonium sulfate aqueous two-phase system (ATPS) was integrated with ultrasonic-assisted aqueous two-phase extraction (UATPE), and the process parameters were optimized via Box–Behnken design-based response surface methodology (RSM) using total flavonoid content (TFC) as the primary response indicator. The validated optimal conditions were determined as follows: extraction time of 40.67 min, solid-to-liquid ratio of 1:30.71 (g/mL), ammonium sulfate mass fraction of 24.03%, and ethanol concentration of 35% (v/v). Under these optimized conditions, the TFC reached (54.83 $\pm 1.58)$ mg rutin equivalents per gram dry weight (mg RE/g DW), which was significantly higher than the values obtained from conventional ATPS [(49.05 $\pm 0.41)$ (mg RE/g DW)] and traditional ethanol extraction [(28.68 $\pm 1.54)$ (mg RE/g DW)] (p < 0.05). For crude polysaccharide production, an ultrasonic-assisted water extraction followed by ethanol precipitation protocol was adopted, and parameters were screened through an L₉ (3³) orthogonal experimental design. The obtained optimal extraction parameters were an extraction time of 10 min, three extraction cycles, and solid-to-liquid ratio of 1:15 (g/mL). A maximum crude polysaccharide yield of (14.89 $\pm 0.18)$ % was achieved under these conditions, with a relative standard deviation of 1.21% (n = 3) across parallel validation tests. Subsequent antioxidant assays demonstrated that the total flavonoid fraction from Nephrolepis cordifolia exhibited potent scavenging capacities against both 1,1-Diphenyl-2-picrylhydrazyl radical (DPPH•) and 2,2′-Azinobis-(3-ethylbenzthiazoline-6-sulphonate) radical cation (ABTS•⁺) radicals. Within the tested concentration range of 0.1–0.5 m g/mL, the crude polysaccharide presented a significant positive concentration-dependent enhancement of activity in four classical in vitro antioxidant systems, including DPPH radical scavenging, ABTS cation radical scavenging, hydroxyl radical scavenging, and total reducing power. Collectively, these findings confirm that the introduced ultrasonic-assisted extraction strategy remarkably improves the recovery efficiency of target bioactive components from Nephrolepis cordifolia. Both total flavonoids and crude polysaccharides display excellent in vitro free radical scavenging potential. This work provides a solid methodological basis for the efficient preparation of the two bioactive compounds, and highlights that Nephrolepis cordifolia is a promising candidate for further exploration as a natural antioxidant source. Full article

Agricultural drought threatens rainfed agriculture in northeast Thailand, where variable monsoon rainfall, limited irrigation access, and extensive cropland increase vulnerability. This study developed a Google Earth Engine-based Agricultural Drought Risk Index (ADRI) for the Chi River Basin using six benchmark years (2000, 2005, 2010, 2015, 2020, and 2025). CHIRPS precipitation, MODIS-derived vegetation health, ERA5-Land soil moisture, irrigation accessibility, and agricultural land exposure were normalized and integrated by weighted linear combination. The analysis quantified risk-class areas, irrigated–rainfed contrasts, persistent hotspots, weight sensitivity, and spatial agreement with the official Land Development Department recurring-drought map. Moderate risk dominated most years, but high-risk area expanded to 60.7% in 2015, coincident with severe rainfall deficits during the 2015–2016 El Niño event. Conditions improved in 2020 and 2025 as rainfall, vegetation health, and soil moisture recovered. Rainfed areas consistently had higher ADRI values than irrigated areas, and persistent hotspots were concentrated in southeastern and downstream agricultural zones. The principal spatial and temporal patterns remained stable under ±10% weight perturbations. External validation identified ADRI > 2.90 as the optimal threshold, with raster-level precision, recall, and F1 of 0.779, 0.884, and 0.828, respectively; the 998-point sample produced an F1 of 0.832. ADRI therefore provides a practical basin-scale screening framework for drought monitoring, adaptation prioritization, and agricultural water-management planning. Full article

Alternaria leaf spot caused by Alternaria alternata affects Ocimum basilicum L. worldwide, yet its occurrence and impact in Serbia have remained unknown. This study identified the causal agent of leaf spot on O. basilicum cv. Genovese using molecular, morphological, and pathogenic analyses, and assessed the effects of disease and meteorological conditions on herb yield and morphometric traits. From 109 sampled plants in the preliminary survey (2021 and 2022) and field experiment (2023–2025), 59 isolates were obtained from symptomatic leaves, stems, branches, and seeds. Isolates were preliminarily identified based on the ITS rDNA region. Pathogenicity tests were done on detached leaves, stems, and seedlings. For selected A. alternata isolates, identification was confirmed based on additional regions (Alt a1, ATP, and CAL) and morphology (PDA, PCA, and V8 media), while pathogenicity was confirmed on whole plants. Disease incidence varied from 0% (2023) to 34.87% (2024) under warm and favourable moisture conditions. Significant reductions in plant height, plant weight, number of branches, and leaf size indicated the combined effects of disease and unfavourable meteorological conditions, while dry herb yield was reduced by up to 59.8%. Temperature and precipitation between harvests played a key role in disease development and yield loss. This study provides the first comprehensive molecular, morphological, and pathogenic characterization of A. alternata causing basil leaf spot in Serbia and demonstrates the importance of climate–disease interactions for basil production. These findings provide a basis for targeted disease monitoring, early detection, and climate-informed disease management strategies. Future studies should validate these findings in additional basil cultivars and production environments. Full article

Terrestrial water storage (TWS) is a key parameter for understanding regional water cycles and climate change. To address the low spatial resolution and temporal gaps of Gravity Recovery and Climate Experiment (GRACE) and its successor satellites (GRACE Follow-On) data, as well as the uneven spatial distribution of Global Navigation Satellite System (GNSS) stations, this study integrates GNSS vertical deformation with GRACE/GFO Mascon data to jointly invert and conduct an in-depth analysis of TWS changes and hydrological drought characteristics in three central Chinese provinces (Hubei, Hunan, and Jiangxi) from January 2011 to June 2023. For missing parts of GRACE and GNSS data, different methods were effectively employed to fill the gaps. The optimal weighting factors were then determined using the Akaike Bayesian Information Criterion (ABIC), leading to the inversion of TWS variations. Combined with hydrometeorological data (precipitation, evapotranspiration, and runoff), drought monitoring was further conducted. The results indicate that joint inversion effectively integrates the high-frequency spatial signals of GNSS with the large-scale smoothing features of GRACE. The spatial distribution of the annual TWS amplitude obtained from different methods (GRACE, GNSS-Green, GNSS-Slepian, and Joint) showed high consistency, generally exhibiting a pattern of lower values in the northwest and higher values in the southeast. Using the TWS derived from joint inversion, a drought index (Joint-DSI) was constructed, successfully identifying and tracking seven major drought events in the study area. Among these, the drought from April 2017 to November 2018 lasted the longest (20 months), while the event from August 2022 to June 2023 was the most severe, with a peak deficit of 142.303 km³. This study demonstrates that the joint inversion method can effectively overcome the spatiotemporal limitations of single observation techniques, providing a high-precision, high-resolution, and reliable geodetic approach for regional water resource management and extreme drought monitoring. Full article

The use of post-consumer scrap (PCS) in aluminium structural components is a challenging but important strategy for reducing carbon footprint in the automotive industry. However, introducing PCS increases uncertainty and compositional variation, which complicates property assurance in serial production. This paper evaluates a parallel hybrid modeling framework that combines a physics-based Kampmann–Wagner precipitation model (NaMo) with a machine learning (ML) model, using a distance-based, adaptive weighting coefficient pre-trained on earlier non-PCS observations. The hybrid is tested on a separate dataset from alloys that emulate plausible compositional deviations introduced by PCS. To probe robustness, training is repeated with randomized initialization to evaluate distributions of RMSE and $R^2$ for yield strength ($R_{p0.2}$) and ultimate tensile strength ($R_m$). The results show that the hybrid improves average performance relative to both constituent models and also reduces variation in accuracy compared to the ML model. The results support the role of adaptive weighting as a pragmatic safeguard against machine learning extrapolation under domain shift, while also exposing limitations related to coefficient calibration and feature choice in the distance metric. The findings are discussed in the context of decision support tools for recycling-oriented manufacturing and gradual onboarding of PCS chemistries into data-driven property models. Full article

Reversible solid oxide cells (ReSOCs) represent one of the most promising electrochemical technologies for sustainable energy conversion and storage, yet their large-scale deployment remains constrained by electrode materials capable of sustaining stable performance under alternating oxidizing and reducing conditions. Reversible solid oxide cells require electrode materials that combine phase stability, chemical compatibility, redox tolerance and a microstructure suitable for gas transport and surface reactions. However, the relationships among cation composition, thermal processing, phase formation and local chemical homogeneity remain insufficiently understood, particularly for compositionally complex perovskite-related oxides. In this work, this problem was addressed through a comparative physicochemical screening of three candidate electrode materials synthesized by a simple co-precipitation route: two co-doped lanthanum ferrites, (La_0.8Sr_1.2) (Fe_0.9Co_0.1)O_6+δ (LSFC) and (La_0.8Ca_1.2) (Fe_0.9Co_0.1)O_6+δ (LCFC), and one high-entropy praseodymium nickelate, Pr(Ba_0.8Ca_0.2)(Fe_0.2Co_0.2Ni_0.2Cu_0.2Zn_0.2)₂O_6+δ (PBC-HEO). DTA–TG analysis was used to determine the thermal decomposition and crystallization ranges of the precipitated precursors. Phase evolution as a function of calcination temperature was investigated by X-ray diffraction, while Raman and FTIR spectroscopy were employed to examine the local metal–oxygen environment and structural disorder. Raman spectroscopy confirmed the formation of perovskite-type metal–oxygen frameworks in all samples and revealed distinct redistributions of spectral weight between apical/equatorial (or symmetry-related) BO₆ stretching sub-modes and bending/tilting modes, reflecting different local defect-chemical mechanisms associated with A-site doping (Sr vs. Ca) in the Ruddlesden–Popper ferrites and B-site multi-cation occupancy in the double-perovskite PBC-HEO. Bulk and local elemental compositions were assessed by ICP-MS and SEM-EDS, respectively, and SEM was used to compare particle morphology and porosity. SEM-EDS analysis showed that PBC-HEO developed the most open and interconnected microstructure among the investigated powders, although accompanied by residual compositional heterogeneity. This morphology may favor gas accessibility; however, its effective impact on electrocatalytic performance requires dedicated surface area, porosimetry, electrical, and electrochemical measurements. LSFC formed a single major Ruddlesden–Popper phase only after high-temperature calcination, whereas LCFC retained calcium-containing secondary phases. PBC-HEO developed a major perovskite-related phase at 700 °C, accompanied by minor Zn-rich segregation. Under the selected processing conditions, PBC-HEO retained the finest and most interconnected porous microstructure, although it also displayed the highest local compositional heterogeneity. These results demonstrate that cation selection and thermal history jointly control phase stability, local disorder and microstructure, providing a basis for the subsequent electrochemical evaluation and optimization of perovskite-related ReSOC electrode materials. Full article

Radar-based Quantitative Precipitation Estimation (QPE) in semi-arid Mediterranean climates is critically challenged by systematic underestimation of shallow precipitation, yet gauge–radar merging frameworks tailored to such environments remain poorly evaluated. This study develops and assesses a merging pipeline for Cyprus, combining X-band polarimetric observations from the Paphos and Larnaca operational radar network with accumulations from a 50-station rain gauge network across 11 rainfall events spanning the 2024 wet season (January and November–December 2024). Four approaches were evaluated: raw radar mosaic, global mean field bias (MFB) correction, spatially varying local inverse distance weighting (IDW) bias correction assessed through leave-one-out cross-validation (LOOCV), and a Random Forest (RF) machine-learning retrieval trained on polarimetric, geometric, and orographic predictors and evaluated through leave-one-event-out cross-validation (LOEO-CV). Raw radar exhibited severe and highly variable underestimation, with station-level bias factors ranging from 1.4 to 200×. Global MFB correction removed systematic offset but, as a single spatially uniform scalar, could not improve spatial correspondence; it was beneficial only where the bias field was spatially coherent. Local IDW correction provided cross-validated reduction in RMSE for most events (commonly 40–53%), but this improvement reflected removal of mean bias rather than recovery of spatial pattern: only 17 January 2024 combined RMSE reduction (24.07 mm to 11.31 mm) with genuine spatial skill (leave-one-out r = 0.850, bias-field coherence r = 0.742), while several events improved in RMSE yet retained near-zero spatial correlation, and 30 and 31 January degraded outright. These results characterise the limits of distance-weighted (IDW) interpolation specifically; whether geostatistical estimators incorporating topographic external drift can restore spatial skill where the present gauge network constrains the bias field remains to be tested. When re-evaluated on the same rainy matched-pair set (N = 2378), the Random Forest reduced 10 min RMSE by only 2.6% relative to the best classical Z-R estimator (from 10.38 mm to 10.10 mm) and reduced the systematic bias from −5.06 mm to −4.25 mm, but did not improve point-to-point spatial correspondence (r ≈ 0), indicating that this mean-regression Random Forest provides effective bias-correction skill without spatial-correspondence skill, leaving the fundamental representativeness gap between CAPPI sampling and gauge point measurements unresolved. Three pre-conditions for local bias correction skill are identified as empirical diagnostics under the sample conditions of this study: a minimum of approximately 40 contributing gauges, a spatially coherent bias field, and a moderate bias range. A formal bootstrap or resampling-based uncertainty estimate for these indicators was not attempted, because eleven events constitute too small a sample for stable resampling statistics; the per-event relationships between the number of contributing gauges, the bias-factor range, the bias-field spatial autocorrelation, and the LOOCV error are therefore presented as the empirical basis for these diagnostic indicators, which should be refined and tested for statistical robustness as longer event records become available. These findings demonstrate that the suitability of spatial merging can be diagnosed from network and bias field properties prior to correction, and that machine-learning retrieval offers complementary value through systematic bias removal where spatial interpolation fails. Probabilistic merging frameworks, denser gauge networks, and ML approaches that explicitly target spatial correspondence are identified as priority developments for eastern Mediterranean QPE. Full article