As groundwater demand rises in arid and semi-arid regions, identifying high potential areas is essential for sustainable management. The Kabul aquifer, Afghanistan, is severely stressed by urbanization and over extraction, with groundwater declining at − 0.8 m/year and 33
Understanding vegetation recovery in landslide scars is essential for risk assessment and post‑disaster management. This study investigated how geomorphometric attributes influence vegetation regeneration in 85 mass‑movement scars triggered by an extreme precipitation event in January 2017 in southern Brazil. Annual time series (2018–2026) of four Sentinel‑2 spectral indices were integrated with topographic variables derived from the Copernicus GLO‑30 DEM. Principal component analysis (PCA) and k-means clustering classified scars into high, medium, and low regeneration groups, while linear mixed models evaluated topographic effects on recovery trajectories. Results demonstrated that regeneration follows a non-linear temporal trajectory, characterized by rapid initial recovery followed by progressive leveling off, which is partly tied to optical index saturation limits in maturing canopies. Slope negatively affected vegetation moisture levels, and elevation significantly modulated the bare soil trajectory, with higher altitudes showing faster soil recovery rates. Scar shape, measured by the circularity index, did not exert a significant effect on any spectral index. Curvature and aspect did not significantly influence regeneration trajectories. The high-regeneration class represented 42.3
Understanding long-term rainfall erosivity variability is essential for assessing soil erosion risk and supporting sustainable land and watershed management in tropical monsoon environments. This study presents a century-scale (1901–2020) assessment of rainfall erosivity and erosivity density across Kerala, India, using India Meteorological Department (IMD) gridded rainfall data (0.25° × 0.25° resolution) from 50 grid cells. Rainfall erosivity and erosivity density were estimated from monthly rainfall records using the Arnoldus empirical approach to examine their spatial distribution, temporal variability, elevation relationships, long-term trends, and homogeneous erosivity domains. Trend characteristics were evaluated using the modified Mann–Kendall test and Sen’s slope estimator, while agglomerative hierarchical clustering with Ward’s linkage was employed to identify regions exhibiting similar erosivity characteristics. Mean annual rainfall ranged from 824 to 4,123 mm, with mean annual rainfall erosivity and erosivity density ranging from 1,291 to 29,987 MJ mm ha⁻¹ h⁻¹ y⁻¹ and 1.34–7.38 MJ ha⁻¹ h⁻¹, respectively. The results reveal substantial spatial heterogeneity and pronounced interannual and inter-decadal variability in both rainfall erosivity and erosivity density. Despite episodic periods of elevated erosivity, trend analyses indicate that rainfall, rainfall erosivity, and erosivity density generally declined across most grid cells during the study period, with localized increasing trends restricted to a few eastern highland areas. Elevation exhibited weak inverse relationships with rainfall erosivity and erosivity density, suggesting that erosivity variability is influenced by rainfall characteristics, monsoon dynamics, and topographic setting rather than elevation alone. Hierarchical clustering identified four statistically distinct erosivity domains representing intermediate, high, very high, and extreme erosivity conditions, providing a framework for regional erosion-risk assessment and spatially differentiated soil conservation planning. The observed variability in rainfall erosivity is consistent with differences in rainfall intensity distribution, monsoon variability, and regional topographic influences, highlighting the importance of rainfall characteristics beyond annual precipitation totals. Although the monthly rainfall-based approach may not fully capture short-duration erosive storms, it provides a consistent basis for evaluating century-scale regional erosivity variability. The resulting erosivity database and domain classification offer valuable inputs for RUSLE-based soil erosion modelling, watershed prioritization, and climate-informed land management in tropical monsoon environments.
Saline soils in seasonally frozen regions experience pore–size redistribution under repeated freeze–thaw cycling, which can influence water and solute transport. Here, repacked columns of a saline soil and a non–saline counterpart from Jilin Province, China, were subjected to 1, 3, 5, 10, and 15 freeze–thaw cycles under three initial moisture levels. Pore–size fractions were derived from LF–NMR T2 spectra and evaluated together with the pore–water fractal dimension (Dw), while SEM–based path analysis was used to examine the relative associations between environmental factors and NMR–derived pore–size fractions. Across treatments, pore–size variation generally showed micropore reduction, mesopore expansion, and macropore fluctuation. Moisture content showed the largest relative contribution to pore–size–fraction variation, whereas freeze–thaw cycle number and the salinity indicator showed smaller contributions. Dw further highlighted a moisture–dependent response: Dw remained low under the low–moisture treatments (1.67–1.79) but was higher under the medium– and high–moisture treatments (2.17–2.67). These results suggest that moisture condition, freeze–thaw cycling, and salinity–related soil properties jointly influence NMR–derived pore–size variation in seasonally frozen saline soils.
This study investigates the iron-bearing mineral deposits and contact-metamorphic skarn zones associated with magmatic intrusions in the Keban region (Elazığ, Eastern Türkiye), focusing on the Aşvan (Muratçık), Fatmalı, Üçağaç, and Ulupınar (Birvan) areas. The primary objective is to delineate the spatial extent of Fe-bearing zones using ASTER imagery and to evaluate their multi-stage paragenetic evolution through integrated field verification, mineralogy, petrography, and geochemistry. Advanced image processing techniques specifically ASTER band ratios B2/B1 ferric iron, B5/B4 (iron silicates), and B4/B5 (lateritic zones) were applied using statistical thresholding to map iron anomalies. The spatial distribution of spectral anomalies was quantitatively cross-validated with field samples (MEU series) and reference datasets (MS series) and historical exploration data. Petrographic, mineralogical, and geochemical analyses demonstrate a distinct chemical variation across the skarn system, with total iron contents shifting sharply from dioritic/gabbroic endoskarn contacts (1–15
