Journal of Earth System Science最新文献

Mapping alteration zones, a crucial step for mineral exploration, faces challenges in tropical areas. Dense vegetation hides important geological features, recent clay formation hides deeper alterations, and human activities like farming make it more complicated. However, alteration zones are crucial clues for specific ore deposits. We explore two approaches: one based on knowledge and the other on data. The knowledge-driven method involves experienced geologists analyzing GIS layers, including lineaments, drainage patterns, rock types, and topography. They use this data to identify key signs of ore-forming alterations. Translating this expert knowledge into spatial data helps us map alteration zones effectively. While this approach provides good approximations, it lacks direct evidence. The data-driven method involves advanced remote sensing tools like ASTER imagery. High-resolution data allows us to use image processing techniques to extract alteration information. However, conventional techniques face challenges in the tropics due to dense vegetation and human activity. To overcome this, we use machine learning algorithms trained on carefully selected samples. We found that among selected ASTER-derived products of conventional DIP techniques (reflectance, band ratio, PCA, DPCA), directed PCA alone is capable of demarcating alteration for the study area with a total accuracy of 81.41, 83.92, and 84.42% for LR, ANN, and RF, respectively. Besides, we used contextual geological evidence of alteration presence as another validation method. To validate results, we use the knowledge-driven approach again, employing Relative Alteration Indexes. All alteration indicative field and geological knowledge were weighted with the Analytical Hierarchy Process (AHP) and spatially integrated with three probability classes in the GIS platform. This combined strategy reveals that while Random Forest has the highest accuracy, Logistic Regression yields more geologically significant results. The high value of Relative Alteration Indexes representing highly altered zones indicates their successful mapping from both data and knowledge-driven techniques. This study shows the strengths of both approaches in understanding alteration zones in the tropics. By combining expert knowledge with advanced technology, we can pinpoint areas rich in valuable minerals, even in difficult-to-explore places. Our successful test in the South Purulia region suggests similar discoveries are possible in other unknown areas.

Abstract

Groundwater monitoring has been performed in a well of the Kultuk area on the western shore of Lake Baikal since 2013. Compression and extension of the near-surface crust are defined through measurements of an AR4/8 (²³⁴U/²³⁸U activity ratio) and an A4 (²³⁴U activity) in groundwater from the Kultuk reservoir. Its thermal state is estimated by determining thermophilic macrocomponents Si, Na, and microcomponent Li. The recorded change in the groundwater reservoir and coeval seismogenic processes, which resulted in earthquakes of the central Baikal Rift System, are considered paragenetically related near-surface and deeper processes of the crust, respectively. It is inferred that compression of the Kultuk area, accompanied by the Goloustnoe earthquake in 2015, was changed by its extension during the strong Baikal–Khubsugul seismic reactivation in 2020–2023. Under compression of the crust, groundwater ascended from a shallow part of the reservoir of 0.5–0.9 km episodically heated up to 116°C by friction in a fault plane. Afterward, a deeper hydrogeodynamic center was generated with its final localization at a depth of about 1.2 km in 2019–2020; during the subsequent Baikal–Khubsugul seismic reactivation, groundwater mainly upraised from the hydrogeodynamic center with frictional heating in a fault plane up to 99°C. Episodic penetration of groundwater portions from depth up to 1.6 km accompanied a slight upward enlargement of an active part of the reservoir to 1 km. The further monitoring of chemical hydrogeodynamics of the Kultuk reservoir may provide a forecast of seismic hazards in the central Baikal Rift System.

Research highlights

• 10-year groundwater monitoring in the Kultuk area of the western shore of Lake Baikal shows the temporal change of compression and extension of the near-surface crust through measurements of an AR4/8 (²³⁴U/²³⁸U activity ratio) and an A4 (²³⁴U activity). Compression was accompanied by the moderate Goloustnoe earthquake in 2015. Change to extension results in strong Baikal–Khubsugul seismic reactivation in 2020–2023.

• The thermal state in the Kultuk water reservoir is estimated by determining thermophilic macrocomponents Si, Na, and microcomponent Li. Under compression of the crust, groundwater ascended from a shallow part of the reservoir of 0.5–0.9 km episodically heated up to 116°C by friction in a fault plane. During the Baikal–Khubsugul seismic reactivation, groundwater mainly upraised from the hydrogeodynamic center with frictional heating in a fault plane up to 99°C.

• The further monitoring of chemical hydrogeodynamics of the Kultuk reservoir may provide a forecast of seismic hazards in the central Baikal Rift System.

Abstract

The Mesoproterozoic rocks of the Krishna Province in the Eastern Ghats Mobile Belt are situated at the edge of the Indian interior cratons and the mobile belts along the edge. We use newly acquired high-resolution gravity and magnetic along with the regional geophysical data to delineate the faults, lineaments, and subsurface boundaries between the various domains of the Krishna Province. We use this data to forward model the crustal architecture below these terranes. Our analysis shows that the Ongole domain rocks are continuing further southwards up to the Nellore and below the K–G Basin on the north side at subsurface levels. The Vinjamur and Udayagiri domains of the Krishna Province are merged into a single narrow belt known as the Nellore–Khammam Schist Belt. The joint 2D modelling of the gravity and magnetic data across these domains reveals two easterly dipping parallel thrusts separating the Dharwar–Nellore–Khammam Schist Belt and Nellore–Khammam Schist Belt–Eastern Ghats Mobile Belt, respectively. The interpreted suture between the Nellore–Khammam Schist Belt and Ongole domain of EGMB is characterized by the ophiolite and alkaline complexes of Mesoproterozoic ages. We propose that the collision between the Krishna Province and Indian Cratons occurred during the Nuna amalgamation.

Research highlights

• The detailed crustal structure across the Dharwar Craton and EGMB was analyzed using geophysical data.

• Redefined the boundaries between the various domains of the Krishna Province.

• A paleo suture was identified between the Eastern Ghats Mobile Belt and the Nellore–Khammam Schist Belt.

Urban sprawl usually expands in regularized and natural forms, and the character of an urban sprawl is found complex and unclear. Therefore, it becomes necessary to distinguish the character of an urban sprawl for sustainability in all aspects. In this paper, we have identified the proximity factors by which we could distinguish between both forms, i.e., regularized and natural expansion. We performed buffer analysis to calculate the areas covered by each land-use land-cover class in each buffer separately. Then, Shannon’s entropy index was calculated for each buffer zone and dataset. Geomatics tools were used to analyze the historical datasets, which included land-use land-cover maps, population density maps, and proximity maps.

Mangrove forests, being high-yielding ecosystems, often dominate the intertidal sites along equatorial and subtropical coasts. Despite the known significance of mangroves to the coastal ecology, especially fisheries, deforestation remains a severe danger due to coercion for forest products, ground transformation for aquaculture, and seaside urban growth. Remote sensing is integral in mapping and analysing changes in mangrove forests’ areal extent and spatial patterns due to natural disasters and anthropogenic causes over the last three decades. This work depicts remote sensing analysis for change detection in mangrove forest land use land cover from 2014 to 2019. Indian Remote-Sensing Satellite Resourcesat-2 LISS-IV datasets have been used for analysis. A comparison with the Sentinel-2A dataset and two machine learning models: Random Forest and Classification and Regression Tree, has been performed with 2019 data. This work identifies CART as a suitable choice for supervised landform classification utilising remotely sensed geophysical data that is used to decipher spatial changes concurred over time. An overall growth in the mangrove cover was observed from 2014 to 2019, from 86.26 to 89.63 ({hbox {km}^{2}}), along the Mumbai coastline. Spatial comparison over the years shows the growth and loss of land-use cover areas. The performance metrics such as overall accuracy, producer accuracy, Kappa coefficient, and Matthews correlation coefficient are computed. The experiments were conducted using the Google Earth Engine, a powerful cloud computing platform.

The study of the statistical trends on rainfall and temperature is much more efficient for hydrological design and planning for scarce water availability zones. In the present study, the sequential Mann–Kendall test (SqMKT) on the Mat-Lab platform is used to study the pattern of rainfall series and temperature series data of the Tikamgarh area of India, surrounded by five stations (nearby) from 2000 to 2020. The SqMKT is mainly used to perform non-linear trends on the rainfall and temperature series. In the SqMKT analysis on rainfall series projects, there was no significant trend in all months, except in the month of June. These months have intersecting points, and each point has Z values in the range of –0.5 < Z < 1.5. The SqMKT analysis on the temperature series shows a significant trend in the months of April, June, July and December, respectively, whereas the remaining months do not have any pattern or trend, similar to the rainfall series and temperature series have u values in the range of –0.5 < u < 1.5. The global climatic pattern is somewhat directly or indirectly connected to the Indian climate pattern, which results in variations in rainfall and temperature patterns from year to year. The indefinite variation in rainfall and temperature results in a direct impact on crop yield and crop water demand or total water availability.

A 40-cm core of lake-bottom silt from Yercaud Lake (Eastern Ghats, south India) dates from 2500 years ago to the present, as confirmed by AMS radiocarbon dating. The average deposition rate varied from 0.024 to 0.008 cm/yr. Sediment particle size distribution, stable isotopes (δ¹³C and δ¹⁵N), C/N, and total organic carbon (TOC) were investigated as indicators of environmental change. In the top 10 cm are the coarsest sediments, which range from silt to silty sand and have a TOC of up to 5%. Algal lacustrine organic matter is combined with terrestrial or wetland organic matter from vascular plants to form organic matter (OM) with a C/N ratio of 12–18. High C/N levels are associated with low ¹³C and high TOC contents, indicating periods of drier climate between 0–500 and 800–2000 years BP. Grain-size characteristics, which fluctuate independently of OM qualities, are likely to have changed because of intensive human use of the lake basin in the past 600 years. Climate changes observed in OM do not correspond to changes observed in other south Indian lakes where precipitation is primarily from the southwest monsoon.

b-value analysis obtained using earthquake catalogues has been associated with stress accumulation for a very long time. In this study, the spatial and temporal distribution of the b-value, also known as the frequency magnitude distribution factor, was calculated and examined before and after the February 6, 2023, Kahramanmaraş earthquakes (Mw 7.7 and Mw 7.6). For this, all earthquakes that occurred between 1900 and the earthquakes of February 6, 2023, and all aftershocks that occurred until September 1, 2023, were used. A circular area with a radius of 300 km, including nearby active faults from the center of the first earthquake to the center of the second earthquake, was divided into grids of equal size. The b-value was calculated for each grid using the maximum likelihood method. Very low b values were detected in the area where the first earthquake occurred, and it was observed that the b-value decreased relatively in the area where the second earthquake occurred. From the change in b-value over time, it was determined that the b-value has decreased significantly in recent years. This situation is associated with stress accumulation in the area where both earthquakes occurred, especially the low b values of the region where the first earthquake occurred. The fact that b values obtained using aftershocks are still low suggests that stress in the region is not completely released, has not been completely relieved and aftershocks will continue for a long time.

We assess the water budget of the Mahadayi river, an inter-state basin on India’s west coast with a long-running dispute. We seek to answer the following question: What is the discharge at any given location along the Mahadayi river or its tributaries on any given day? After presenting the dispute and the decisions of the tribunal, we describe the modelling framework, which is able to simulate the high rainfall gradients in the neighbourhood of the ridge associated with the Sahyadris, the high discharge during the summer monsoon, the much weaker discharge following the monsoon, and the high abstraction during monsoon onset. The model is not designed to simulate the negligible dry-season discharge. The simulation yields the daily time series of discharge at any location along the Mahadayi or its tributaries. For the Kalasa nala, there is a significant impact of the permitted diversion in the northern part of the Mhadei Wildlife Sanctuary, but the impact on the Mahadayi discharge or the Mandovi estuary is less than the natural variability. The Bhandura diversion has a minor impact on the discharge at the Goa–Karnataka border. Based on the simulated water budget, we suggest possible solutions to resolve the dispute.