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Machine learning spatial modeling is used for mapping the distribution of deep-sea polymetallic nodules (PMN). However, the presence and influence of spatial autocorrelation (SAC) have not been extensively studied. SAC can provide information regarding the variable selection before modeling, and it results in erroneous validation performance when ignored. ML models are also problematic when applied in areas far away from the initial training locations, especially if the (new) area to be predicted covers another feature space. Here, we study the spatial distribution of PMN in a geomorphologically heterogeneous area of the Peru Basin, where SAC of PMN exists. The local Moran’s I analysis showed that there are areas with a significantly higher or lower number of PMN, associated with different backscatter values, aspect orientation, and seafloor geomorphological characteristics. A quantile regression forests (QRF) model is used using three cross-validation (CV) techniques (random-, spatial-, and cluster-blocking). We used the recently proposed “Area of Applicability” method to quantify the geographical areas where feature space extrapolation occurs. The results show that QRF predicts well in morphologically similar areas, with spatial block cross-validation being the least unbiased method. Conversely, random-CV overestimates the prediction performance. Under new conditions, the model transferability is reduced even on local scales, highlighting the need for spatial model-based dissimilarity analysis and transferability assessment in new areas.

Production of natural gas and crude oil in the eastern regions of Russia was accelerated in the past decade, and both the upstream and midstream segments of the oil and gas industry continue to grow at a fast pace. Innovative solutions are needed for engineering and construction surveys aimed to justify options for choosing routes and methods for laying underwater pipeline sections across large rivers and water reservoirs. In our region, positive experience has been gained by employing modern technologies to optimize routing and reduce the costs of detailed surveys. In the project of the Kovykta – Sayansk – Angarsk – Irkutsk gas pipeline construction, an optimal route across the Bratsk water reservoir was chosen based on the results of several stages of investigation, including continuous seismic profiling and side-scan sonar scanning of the reservoir bed. At the first stage, the mosaic maps of side-scan sonograms and a 3D digital model of the reservoir bed bathymetry were constructed and used to develop and propose three options for the gas pipeline design and its route across the reservoir area. At the second stage, detailed underwater and onshore geophysical and drilling operations were carried out along the proposed routes. Based on the transverse profiles, a decision was taken to lay the pipeline section across the reservoir area in a trench along the northern route, which was justified as an economically and technologically optimal solution. In the winter period when the water reservoir surface was covered with thick ice, the northern route was investigated in detail by drilling and seismic survey operations using vertical seismometer cable assemblies and the inverse travel time curve technique. With reference to the velocity law, the travel time sections were processed and converted into depth profiles. A petrophysical model of bottom sediments was constructed, and a scheme was developed to ensure proper processing and interpreting of seismic and acoustic data. Four structural-material complexes were identified: modern silts; underwater eluvial and alluvial deposits; disintegrated and low-strength bedrocks of the Upper Lena Formation; and unaltered bedrock sandstones and siltstones. The continuous seismic profiles and the data from the vertical seismometer cable assemblies were interpreted, and a neotectonic map of bottom sediments was constructed. By analyzing the fault kinematics, it was revealed that normal faults and reverse faults with low-amplitude horizontal shear dominated in the study area; the mapped faults were mainly rootless structures; and displacements along the faults occurred due to a laminar flow of the Cambrian salt layers. An increase in tectonic activity from north to south was explained by the correspondingly degraded strength properties of the bedrocks. Modern neotectonic structures detected from the survey results gave evidence that that the hydrostatic pressure increased after the reservoir had been filled with water, and the phenomenon of reservoir-related seismicity was observed in the study area. Based on the comprehensive geological and geophysical survey data, the geological and engineering conditions of the proposed construction sites were clarified, and the most appropriate route and design of the gas pipeline section across the reservoir area was approved. This study provided the pipeline designers with the qualitative and quantitative information on the phenomena and factors complicating the conditions for laying the gas pipeline in the study area.

High altitude lakes (HALs) of Kashmir Himalaya are the important ecosystems in the mountain ecology of the broader Hindukush Himalayan region. This article provides a comprehensive information about the plankton (phytoplankton and periphyton) assemblages, water quality (WQ), bathymetry, morphometry, and land use land cover (LULC) of some select high altitude mountain lakes of Kashmir Himalaya. LULC analysis revealed that the catchment of the lakes spread over an area of about 16179 ha, is covered by different land cover types dominated by pastures (50.8%), followed by barren rocky (32.6%), snow and glaciers (11.9%), lakes (2.5%), forest (2%), and streams (0.2%). Bathymetric and morphometric analysis revealed that the Gangbal Lake is the deepest (84 m) and largest (162.4 ha) among the investigated lakes. The water quality index revealed that all the HALs have the excellent water quality category. Statistical analysis (Wilk’s λ) depicted that nitrate-nitrogen (NO3−-N), nitrite nitrogen (NO2−-N), ammoniacal nitrogen (NH3-N), total phosphorus (TP), and magnesium hardness (Mg-H) are responsible for major variability between all HALs sites. The cations followed the order of Ca2+> Mg2+> Na+> K+while as anions followed the order as HCO3−> Cl−> SO42−. Algal composition (phytoplankton and periphyton) assessment revealed the presence of 61 taxa belonging to Bacillariophyceae (45), Chlorophyceae (14), Cyanophyceae (1), and Xanthophyceae (1). The higher dominance of Bacillariophyceae indicates oligotrophic nature of the lakes. Canonical correspondence analysis (CCA) highlighted the role of various water quality parameters like pH, EC, and TDS on the composition of phytoplankton and periphyton species among the lakes. The present study therefore generated a baseline database for some of the HALs of Kashmir Himalaya that can act as a precursor for more research on future changes in the lake ecosystems of the region.

Marine geophysical surveys were carried out at the underwater site in the south-western sector of the Eastern Harbor of Alexandria, opposite to the Egyptian Sea Scout Club. Survey works aimed to detect and study the surface and subsurface geomorphological changes caused by historic sea-level rise and natural hazards, by integrating the results of high-resolution geophysical mapping for the seafloor textures and the subsurface layers with previously published core data and sea-level records, the survey works employed echo-sounder, side scan sonar, and sub-bottom profiler. Acoustic data were ground-truthed using an ROV camera and sediment grab sampler. Results of bathymetric mapping and sonar imaging outlined two breakwaters and quay corresponding to a submerged ancient port; also, sediment types were classified according to variation in the magnitude of the backscattered intensities. Interpretation of sub-bottom profiles illustrated the depositional sequence of the topmost sedimentary layers where the sediment thicknesses were thickened by rates that perfectly matched with the recorded sea-level rise rate during the last two millennia, as indicated by isopach maps. Anthropogenic activities were noticed in particular outcropping areas on the sub-bottom profiles. The results explained the role of natural hazards and sea-level rise in changing the geomorphology of the coastline and seabed features.

Data on spatial distribution and habitat conditions are presented for walleye pollock Theragra chalcogramma at southern Kuril Islands in spawning season (spring 2015) and feeding season (summer 2016). In spring, walleye pollock are distributed over the entire shelf and continental slope down to 900 m depth and occupy the upper layer on the shelf and intermediate layer at the slope with water temperature 0.1–1.5 o C. In summer, they aggregate at the depth of 200–270 m beyond the shelf in the intermediate water at the Pacific slope of Iturup Island, under the temperature of 1.3–2.9 o C. Both spatial and bathymetric migrations of pollock are minimal at the Pacific side of Iturup, but they migrate for spawning westward and southwestward to the Okhotsk Sea and slope of Small Kuril Ridge where concentrate at the benthic front between the tidal mixing zone and the Intermediate water. Seasonal redistribution of walleye pollock is accompanied with changes of size-age structure in the main aggregations.

In 2006, the BGR signed a contract with the International Seabed Authority (ISA) for the exploration of polymetallic nodules in the Clarion-Clipperton Zone of the northeast Pacific. During nine expeditions, in particular, “Area E1”, the eastern part of the contract area, with a size of ~60,000 km2, was explored in detail. Here, we outline BGR’s exploration methods and provide resource estimates for Area E1 and three sub-areas. The resource assessment is predominantly based on statistical analyses of data obtained by 12-kHz multibeam bathymetry and backscatter mapping, box core sampling and geochemical analysis of nodules. The main parameter for the assessment is the nodule abundance (kg/m2), as its coefficient of variation (CoV) over the entire eastern contract area is relatively high at 36%. In contrast, the metal contents of nodules show only minor variation, with a CoV of 8% for manganese and 8% for the sum of copper, nickel and cobalt. To estimate mineral resources for the entire Area E1, we used an artificial neural network approach with a multivariate statistical correlation between nodule abundance derived from box cores and hydro-acoustic data. The total estimated resources are 540 ± 189 million tonnes (Mt) of dry nodules, and the total estimated metal contents are 168 Mt of manganese, 7.5 Mt of nickel, 6.3 Mt of copper, 0.9 Mt of cobalt, 0.4 Mt of rare-earth elements and 0.3 Mt of molybdenum. A geostatistical resource estimate of three economically prospective areas with a total size of 4498 km2, intensively sampled by box cores, was carried out using ordinary kriging of nodule abundance and metal grades. Within these three nodule fields, 7.14 Mt of dry nodules are classified as measured mineral resources covering an area of 489 km2. Indicated mineral resources amount to 11.2 Mt, covering an area of 825 km2, and inferred mineral resources of 35.5 Mt of dry nodules were estimated for an area of 3184 km2. In total, the metal contents of the three prospective areas amount to 16.8 Mt of manganese, 0.74 Mt of nickel, 0.63 Mt of copper and 0.09 Mt of cobalt.

Lake evolution and its changes over time are an evident and easily measurable signal of human activities and climate change impacts in mountain regions. This study presents bathymetric modeling of permanent lakes (Begnas and Rara Lakes) located in two different geographic settings of Nepal. Moreover, temporal changes in land cover and soil erosion of the lake watersheds, as well as climatic trends around these lakes, are assessed. This study supports establishing reference sites for exploring scientific evidence on the impacts of anthropogenic and climate change on lake hydrological systems. Second-order polynomial models best represent the relationship between lake depth and volume. Rara Lake had a maximum depth of 169 m with an area of 10.52 km2 and a volume of 1013.305 million cubic meters (Mm3), whereas Begnas Lake had a maximum depth of 12.5 m with an area of 2.98 ± 0.10 km2 and a water volume of 13.539 Mm3 in the year 2019. Both lake regions are experiencing changes in temperature and rainfall. The area and volume of Rara Lake and its watershed have been relatively stable even with minimal land-cover change during the recent decades. Begnas Lake and its watershed have experienced significant changes in the last few decades. This study concludes that human activities in the Begnas Lake watersheds are the primary source of lake area variation rather than climate change.