The No. 8 Block of Xinjiang represents a typical ultra-low-permeability fractured oilfield in which conventional water-quality evaluation techniques fail to reproduce the water-quality evolution and associated reservoir responses that occur within fractured reservoirs. To address this limitation, a graded water-quality evaluation method and an associated apparatus tailored for water injection in ultra-low-permeability fractured reservoirs were independently developed. Using this method and apparatus, fracture–matrix core water-injection displacement experiments were conducted to quantify water–reservoir compatibility and to characterize permeability evolution in fracture–matrix cores during displacement. An economic evaluation of fracture–matrix core water-injection schemes was subsequently performed. The results indicate that, for fracture–matrix cores with a permeability of 8 mD, suspended particles with a median diameter ≤ 1.5 μm and a concentration ≤ 8 mg/L cause a total permeability impairment of < 20%, demonstrating favorable compatibility and unobstructed migration, with particle retention concentrated primarily within fracture zones. For fractures with a permeability of 20 mD, suspended particles with a median diameter ≤ 3 μm and a concentration ≤ 6 mg/L similarly result in permeability impairment < 20%, indicating good compatibility and successful passage. By integrating reservoir-permeability variations and historical water-injection data, an economic assessment model that accounts for reservoir evolution, oil prices, and injected-water quality was established. The model enables the identification of water-quality standards that both ensure effective reservoir development and maintain economic viability.

Sustainable forest planning in disaster-prone landscapes requires the integration of ecological risk considerations into spatial decision-making frameworks. In this study, a spatial modeling framework was developed to integrate landslide risk into forest land suitability evaluation in Sukabumi, Indonesia, a region that has experienced the highest recorded landslide frequency in West Java over the past decade. Foundational spatial data were derived from forest site typologies and subsequently restructured to isolate environmental variables associated with landslide susceptibility. A spatial multi-criteria evaluation approach was implemented to integrate both qualitative and quantitative criteria within a unified spatial decision-support framework. Criterion prioritization and weighting were determined through the analytical hierarchy process, enabling structured expert judgment to be incorporated into the evaluation process. The resulting spatial suitability map delineated seven optimal forest land-use categories across the study area: pine resin production (19,485.81 ha; 35.03%), teak timber production (8,083.95 ha; 14.45%), agroforestry systems (7,130.91 ha; 12.82%), protection forest zones (2,258.62 ha; 4.06%), biomass cultivation areas (2,117.12 ha; 3.81%), ecotourism development zones (480.28 ha; 0.86%), and biomass processing facility sites (16.90 ha; 0.03%). Spatial prioritization emphasized areas where landslide susceptibility is minimized while maintaining high economic potential for forest-based production systems. The results demonstrate that the systematic incorporation of landslide hazard information can significantly improve the reliability of forest land suitability assessments, providing a more balanced decision-support tool for forest management planning. The approach offers practical value for policymakers and land managers seeking to enhance sustainable forest land-use planning in mountainous and disaster-sensitive regions.

Surface ozone is a major secondary air pollutant carrying significant implications for the stability of the ecosystem, public health, and climate forcing. In Nigeria, rapid urbanization, emission growth, and climatic variability interact to shape ozone dynamics; however, there is little understanding of the specific contribution of meteorological factors. This study investigated the influence of key meteorological variables on surface ozone variability in Nigeria based on a combined Principal Component Analysis (PCA) and Linear Regression (LR) framework. Meteorological parameters include temperature, wind speed, relative humidity, rainfall, cloud cover, short-wave radiation, and atmospheric pressure. PCA results revealed that the first three principal components (PCs) explained approximately 76% of the total variance, suggesting that a limited number of climatic modes, primarily associated with temperature, wind speed, and humidity, dominated ozone variability. LR further quantified the individual contributions of these variables. Cloud cover (-1.015), temperature (-0.975), and wind speed (-0.665) exerted the strongest negative influence on surface ozone concentrations. In contrast, rainfall (0.306) demonstrated a positive association, potentially linked to enhanced post-precipitation soil NO$_x$ emissions. Other variables, including short-wave radiation, atmospheric pressure, and relative humidity, exhibited relatively minor effects. While the model reflected robust predictive performance (Mean Squared Error (MSE) = 0.044), the findings emphasized the significant role of meteorological processes in shaping ozone variability. In drastically urbanizing tropical regions, meteorological dynamics should be incorporated into the forecast of air quality and planning of environmental policies.

Himalayan glaciers are sensitive indicators of climate variability and change and constitute an important component of regional water resources. In this study, glacier changes between 2010 and 2025 were quantified in the glacierized headwaters of the Kosi Basin, with particular emphasis on the Arun and Tamor sub-basins, using multi-temporal Landsat imagery and Geographic Information System (GIS)-based spatial analysis. Glacier boundaries were delineated from Landsat 5 and Landsat 8/9 imagery, and changes in glacier number and area were quantified through spatial comparison of the resulting glacier inventories. Glacier ice volume was estimated using an area–volume scaling relationship. The total mapped glacier area decreased from 962.15 km$^2$ in 2010 to 923.89 km$^2$ in 2025, representing an overall decline of 3.98%. Estimated glacier ice volume decreased from 85.584 km$^3$ to 81.885 km$^3$. In contrast, the number of mapped glacier units increased slightly from 295 to 297. When considered together with the observed changes in glacier geometry, this increase is consistent with the fragmentation of some larger glacier bodies into smaller, spatially disconnected units. Spatial analysis further revealed changes in glacier margins and overall geometry across the study area, indicating continued reconfiguration of the glacierized landscape. These changes are broadly consistent with the ongoing response of Himalayan glaciers to climatic forcing, particularly atmospheric warming and changes in precipitation regimes. The observed reductions in glacier area and estimated ice storage indicate continuing cryospheric change that could alter the magnitude and seasonality of glacier-derived runoff within the Kosi River system. These findings demonstrate the utility of multi-temporal satellite remote sensing and GIS-based analysis for quantifying glacier change in data-sparse high-mountain environments and provide an updated baseline for evaluating future cryospheric and hydrological changes in the eastern Himalaya.

Relief morphometry fundamentally influences the spatial organization of physical gradients, surface processes, and geoenvironmental conditions, yet these relationships have rarely been integrated into a unified quantitative framework linking terrain structure to biosphere conditions. This study systematically evaluated relationships among key morphometric parameters—including slope, elevation, curvature, aspect, and terrain roughness—and physical gradients, geoenvironmental conditions, and biosphere conditions through a quantitative-dialectical synthesis of the literature. Fifty-nine studies published between 1993 and 2025 were selected using Population–Exposure–Outcome (PEO) criteria and screened following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. Evidence, primarily derived from digital elevation models (DEMs) with spatial resolutions of 30 m or finer, was synthesized using standardized morphometric metrics. Across the reviewed studies, moderate-to-strong associations ($r$ = 0.58–0.84) were reported between relief morphometry and major physical and geoenvironmental variables. Slope was consistently associated with erosion and drainage dynamics, elevation with climatic gradients and ecological zonation, and curvature and terrain roughness with water redistribution, infiltration, and ecosystem resilience.The evidence supports an integrated functional pathway whereby relief morphometry structures physical gradients that regulate hydrological and gravitational surface processes, thereby shaping geoenvironmental and, ultimately, biosphere conditions. On this basis, an integrative $M \rightarrow \Phi \rightarrow P \rightarrow C \rightarrow B$ framework was proposed, where $M$ denotes relief morphometry, $\Phi$ physical gradients, $P$ surface processes, $C$ geoenvironmental conditions, and $B$ biosphere conditions. Climate, lithology, and land use were incorporated as contextual modulators.The framework provides a systematic basis for geomorphological zoning, erosion-susceptibility assessment, preliminary landslide-susceptibility screening, watershed characterization, and terrain-based environmental assessment. Although a coherent conceptual and quantitative synthesis is established, the proposed framework should not be interpreted as a universally validated causal model; its transferability, parameterization, and predictive performance remain to be tested across contrasting geological, climatic, ecological, and geomorphological settings.