Geological Survey of Pakistan

This paper presents a deep ensemble learning approach for enhancing mineral prospectivity mapping (MPM) for porphyry copper deposits in the western Chagai belt, southwestern Pakistan, by integrating geophysical, geochemical, remote sensing, and geological datasets. The approach utilizes a spectral–spatial convolutional neural network (SSCNN), theoretically motivated by the coupled spectral–spatial nature of mineralization-related geospatial patterns, to extract high-dimensional features from multi-source geodata. In addition, a mineralization-based data augmentation strategy, incorporating geologically constrained spectral–spatial replacement to generate synthetic samples reflecting mineralization-favorable conditions, is employed to alleviate data imbalance and limited sample size. The ensemble of four SSCNN models achieved robust and consistent performance across four independent train–test splits, using a limited subset of known deposits for training, with F1-scores exceeding 0.94 and peaking above 0.98. The model-predicted prospectivity exhibits strong spatial correspondence with known deposits and exploration targets delineated using knowledge-driven approaches in the previous studies, particularly highlighting high-potential zones in the southeastern Reko Diq area. Field validation through rock outcrop surveys and handheld X-ray fluorescence confirmed copper and iron mineralization at eight newly identified locations. The SSCNN architecture effectively captures high-dimensional spatial and spectral features while mitigating overfitting, and the mineralization-based augmentation technique further improves model sensitivity to small-scale mineralized zones. This ensemble strategy addresses key challenges in MPM, such as limited sample size, class imbalance, data noise, and uncertainty in sample selection, while also significantly improving model generalization and robustness. Feature importance analysis revealed strong concordance between model-driven predictions and established geological knowledge, underscoring the interpretability and reliability of the method. Overall, this approach offers a powerful, data-driven framework for guiding mineral exploration in complex geological terrains and demonstrates its potential for broader application in mineralized belts globally.

Microplastics are ubiquitous pollutants in aquatic habitats that provide serious threats to human health and the environment. This paper thoroughly investigates the microplastics distribution, environmental behavior of microplastics in surface and groundwater systems and their effects on aquatic systems and humans. It looks at how microplastics enters surface water bodies and then infiltrate into groundwater systems. The modes of transportation, their function as carriers of contaminants and current status in surface and ground water is also investigated. Furthermore, the effects of microplastic pollution on the environment and human health are assessed, with a focus on bioaccumulation and possible threats to aquatic organisms. Microplastic characteristics including size and morphology critically influence their absorption, translocation and potential adverse effects in humans. This study emphasizes on introducing standardized analytical procedures for groundwater microplastics study. In order to provide the groundwork for multidisciplinary research and sustainable water management, this paper aims to clarify the threats that microplastics pose to the environment and to people. This paper also discussed the current challenges and potential approaches for reducing microplastic contamination.

Active faults play a critical role in controlling landslide hazards, particularly in orogenic belts such as the western Himalayas, where landslides pose a persistent threat to lives and infrastructure. This hazard became evident during and after the 2005 Kashmir earthquake, which ruptured along the Bagh-Balakot Fault (BBF). This study investigates the spatiotemporal influence of the BBF on landslide distribution from 2006 to 2024 using multi-temporal landslide susceptibility mapping and spatial analysis. Two comprehensive landslide inventories were developed for the pre- and post-decadal periods, LSI-2013 (2006–2013) and LSI-2024 (2014–2024), using high-resolution remote sensing and field validation. Landslide susceptibility was assessed using Logistic Regression (LR) and Random Forest (RF) models, incorporating eleven conditioning factors screened for multicollinearity using Pearson correlation and VIF analyses based on a 70/30 split of landslide and non-landslide points into training and testing datasets. The results indicate that the RF model consistently outperformed LR, achieving higher predictive accuracies with area under the curve (AUC) values of 0.91 (LSI-2013) and 0.90 (LSI-2024). Maximum landslide densities of 4.0 and 2.2 landslides/km2 were recorded within the 0–250 m and 250–500 m buffers of the BBF, respectively. This pronounced localized clustering remains significantly higher within 1 km along the BBF across both temporal inventories, underscoring the long-term geomorphic influence of fault activity, particularly along its northern segment. In contrast, areas distal to the fault exhibit an overall temporal decline in landslide susceptibility from 2013 to 2024, reflecting progressive post-seismic slope stabilization following the 2005 earthquake. The multi-temporal landslide susceptibility maps clearly demonstrate the persistent fault-controlled susceptibility patterns and evolving nature of landslide hazard in this region. Ultimately, this study provides comprehensive site-specific spatial guidance for landslide hazard assessment and offers insights for informed land-use planning and risk mitigation in tectonically active regions of the western Himalayas.

This study investigates the hydrocarbon generation potential of the Eocene (Ypresian) Nammal Formation throughout the Potwar Basin, Pakistan. Lithostratigraphic, organic geochemical and palynofacies analyses, along with isochore and isopach mapping of five wells (Dakhni-11, Toot-20, Garhi-X1, Fimkasar-04 and Rajian-08) and one outcrop section, were used in the current study. The Nammal Formation comprises shallow-marine to lagoonal shales interbedded with limestone and occasional marls. It is distributed throughout the Potwar Basin, showing a variable thickness that ranges from 3 m in the eastern Rajian-08 well to 66 m in the western Dakhni-11 well. The depth isochore map for the Garhi-X1 well shows that the formation is present at a depth of 4886 m, compared to southern parts where it is exposed at the surface along the Salt Range Thrust. Organic geochemical and palynofacies analyses indicate that the formation is dominated by Type II kerogen with minor Type III kerogen. Data show that the formation gets more mature towards the northwestern part of the Potwar Basin, demonstrating fair total organic content (TOC) values (>1%) that suggest it is a potential source rock. Palynofacies assemblages are consistent with the organic geochemical analysis, which suggest suboxic to anoxic conditions during deposition of the Nammal Formation. The thermal alteration index and T max values show that the formation is more mature towards the north.

The Paleocene-Eocene Thermal Maximum (PETM) was the most prominent climatic perturbation of the Cenozoic. Rapid climate warming and ocean acidification resulted in biotic changes including the largest deep-sea extinction event of the last 90 Ma and a marked turnover in larger benthic foraminifera (LBF). While heavily studied as a potential analogue for future climate change, important spatial gaps remain in our understanding of the environmental and biotic impacts of the PETM. Particularly, the expression of the PETM in the shallow marine settings of central Eastern Tethys remains poorly documented because of the scarcity of well-preserved PETM sections in the region. Here, we identify the PETM and its biotic impact in shallow marine carbonate ramp deposits of the late Paleocene and early Eocene Dungan Formation from the Lower Indus Basin (Eastern Tethys; present day Pakistan). A ∼ 2.5‰ carbon isotope excursion (CIE) identifies the stratigraphic position of the PETM, which coincides with the boundary of shallow benthic zones (SBZ) 4 and 5. The CIE is associated with a major turnover of LBF, including the first appearances of Alveolina ellipsoidalis, Glomalveolina minutula, Assilina dandotica and Ranikothalia sidensis, and the disappearances of Glomalveolina levis, Miscellanea juliettae, Azzarolina daviesi, Karsella hottingeri, Kathina pernavuti and Kathina selveri. Microfacies and biofacies analysis suggest shallow marine carbonate environments, ranging from inner to mid-ramp settings, demonstrating that the CIE and LBF turnover are associated with the PETM event and not just a result of local sea level change. We conclude that the stratigraphic correspondence between the LBF turnover and the onset of the PETM in the Lower Indus Basin resembles that observed in carbonate settings of Western Tethys. This is distinct from other records from the Eastern Tethys, where the LBF turnover is reported to have occurred well after the onset of the PETM. Our observations confirm that the PETM had an impact on shallow marine benthic foraminifera in the western side of central Eastern Tethys.