Geosystems and Geoenvironment最新文献

Studying the origin of rivers, the development of drainage through geological time, and the multiple processes that affect the composition of the sediment is a fascinating scientific adventure. This article probes into modern sedimentary processes in the Orange River catchment, which covers much of South Africa, and monitors changes in petrographic, mineralogical, geochemical, and geochronological signatures along the ∼4000 km-long fluvial and coastal conveyor belt that transferred pyroxene-rich and diamond-bearing sand from Lesotho to Angola.

The Orange River, established as early as the Early Jurassic as a classic example of dome-flank drainage, is perhaps the oldest river on our planet. A quarter of Orange sand is supplied by the erosion of Lesotho basaltic highlands, reaching 3482 m a.s.l. and representing a remnant of one of the most extensive magmatic effusions of Phanerozoic history, the Lower Jurassic Karoo lavas. Basaltic lavas, dolerite sills and dykes shed rock fragments and clinopyroxenes that constitute the unique fingerprint of Orange River sand. Only a tenth of the sediment is supplied by the Vaal River, the longest Orange tributary that drains siliciclastic and volcanic units ranging in age from Neoarchean in the Transvaal to early Mesozoic in the Karoo Basin. In the arid middle and lower reaches, the Orange River carves its course into the Namaqua Belt and receives the Molopo River flowing only episodically across the vast Kalahari Desert and the Fish River draining sedimentary rocks of the Nama Group and Karoo Supergroup. Fragile sedimentary rock fragments do not survive high-energy wave transport, but basaltic rock fragments and pyroxenes do, allowing us to trace sand transport for ∼1800 km all along the Atlantic coast of Namibia to as far as southern Angola. Understanding sediment mass transfer has scientific as well as practical interest, being a prerequisite for effective fluvial and coastal management, with particular economic significance in the special case of diamond-bearing Orange sand.

The impact of urban and industrial effluents in the tropical Indian estuaries (Ariankuppam backwater and Chunnambar River), east coast of India have been investigated in the present study by determining the degree of heavy metals contamination of the estuarine sediments. A total of 30 surface sediment samples were collected from both estuaries and were analyzed for trace metals, grain size and organic matter. The granulometric analysis reveals that both the estuaries are predominated by silty sand to sandy silt. The significant amount of organic matter (OM) in the Ariankuppam estuary sediment is due to natural (mangroves) and anthropogenic (pollution) organic input. Pearson correlation analysis reveals that there was a strong negative correlation of sand fraction with other sediment variables (silt, clay, and organic matter) and heavy metals, whereas a positive correlation was observed between silt+clay, organic matter, and heavy metals. The significant positive correlation of Fe with Ni, Cu, Pb and Zn presents Fe-Mn oxyhydroxides are the main controlling factor of heavy metals in both estuarine sediments. Cluster analysis and PCA helped to discriminate the station groups along both estuaries according to their sediment components and heavy metals. This study also revealed that sediment grain size is a key factor influencing organic matter and heavy metal accumulation in surface sediments. The calculated pollution indices such as Contamination factor (CF), Geoaccumulation Index (Igeo) and Pollution Load Index (PLI) values indicate that both estuaries are moderate to highly contaminated by Co and low to moderately contaminated by Pb and Zn. Based on the factor analysis, it is presumed that river runoff and industrial and untreated domestic wastes from lands are responsible for increased heavy metal concentration in both estuaries. Increased levels of metal contamination along the Union Territory of Puducherry coastline may increase the risk of human exposure to metals through the consumption of seafood, making the need for tougher regulations on the discharge of metals into the environment even more important.

This research explores flood prediction in the Lower Damodar River Basin (LDRB) using a hybrid ensemble of a Naïve Bayes Tree (NBT) and five bivariate statistical models such as Evidential Belief Function (EBF), Index of Entropy (IOE), Frequency Ratio (FR), Statistical Index (SI), and Modified Information Value (MIV). A total of 348 flood locations and 15 conditioning factors including hydrological, topographical and land cover were considered for this analysis. To ensure the precision of model predictions, a multicollinearity assessment was executed. Receiver operating characteristic (ROC) curve, area under curve (AUC), mean absolute error (MAE), mean squared error (MSE), and root mean squared error (RMSE) were performed to compare and asses each of the models all. The results reveal that all models performed well in creating flood hazard maps with AUC >0.8 and RMSE <0.4. FR and EBF models demonstrated the highest predictive accuracy (AUC=0.85), followed by the IOE, SI, and MIV models. The ensemble of NBT with bivariate models shows promising results, showcasing reduced error metrics and improved accuracy for the IOE, SI, and MIV models. This study highlights the potential of ensemble models in flood hazard prediction, offering valuable insights for global flood risk management. The successful application of these data-driven models showcases their importance in forecasting flood risks, aiding decision-makers and planners in developing more effective flood mitigation strategies.

The Sahinkalesi, a volcanic dome located NNE of Hasandağ, Türkiye exhibits anomalous heat flow value, geothermal gradient and the Curie point depth is located at very shallow depth in this region. Our investigation indicates presence of super-critical thermal regime (378°C) at about 4 km depth and the MT analysis indicate shallow magma chamber at about 5 km depth. The crust is relatively thin below this region with the low-velocity region located at depth of about 36 km. Thermo-Hydro-mechanical model investigation has been carried out using finite element discretization technique. For faulted zone reservoir models, 30 years of geothermal energy exploitation does not cause thermal breakthrough for mass flow rates up to 500 kg/s, however, the mean stress developed in the reservoir becomes much larger and may be unsustainable for the reservoir stability. To ensure the success of a fractured reservoir model, the use of multiple wellbores is recommended. In the case of a closed-loop geothermal system, the primary concern is the control of thermoelastic stress. This can be achieved either by increasing the wellbore depth while reducing the injection mass flow rate, or by extending the wellbore's horizontal component. The outlet temperature in both the cases maintained at 275°C. This is the first time a superhot EGS site has been identified in Türkiye.