Journal of Earth System Science最新文献

Land use land cover (LULC) changes hugely influence the ecological balance of an ecosystem, which adversely affects the inhabitants, making them more vulnerable to natural calamities. The LULC change studies are therefore carried out to analyze the impact of these changes on the overall ecology of an area and are very helpful in policy framing and proper management of the available natural resources. In this study, changes in the land use and land cover for a three-decade period spanning from 1992 to 2020 have been monitored in the valley of Kashmir using remotely sensed satellite data obtained from USGS/NASA’s Landsat repository. Considerable changes in the LULC patterns were observed with a significant reduction in the area covered by water (18.21%), forest (13.56%), snow/glacial cover (29.32%) and agriculture (22.37%) during the past three decades. Concurrently, expansion in the land covered by urban areas (22.33%), barren land (37.32%), plantation (14.53%) and marshes (13.21%) were noted. The calculated Normalized Difference Water Index (NDWI) confirmed an overall reduction of 51.1% in the water and glacial cover of the study area. Significant changes in the form of forest, water and glacial cover transforming into urban, marshy and barren areas can be largely accredited to increased human interference that may have serious repercussions on the environment.

Heat waves (HWs) are currently one of the most dangerous natural catastrophes both globally and in India, particularly upsurged in urban areas. Bhubaneswar, the capital city of Odisha in India, experiences heatwaves (HWs) each year from the pre-monsoon season to the onset of the summer monsoon. The manifest increase in intensity and frequency of HWs over Bhubaneswar leads to a higher death toll, and increasing vulnerability demands accurate prediction in advance over HWs-prone zones. Numerical weather prediction models are capable of predicting these HWs, subject to the customization of suitable physical parameterization schemes. In this context, the role of five planetary boundary layer (PBL) schemes such as Yonsei University (YSU), Asymmetric Convection Model version 2 (ACM2), Medium Range Forecast (MRF), Mellor–Yamada–Janjic (MYJ), and Bougeault Lacarrere (BouLac) are assessed in predicting six HW events over Bhubaneswar city using a very high-resolution (500 m horizontal resolution) Weather Research and Forecast (WRF) model. The model simulated results are verified against the Indian Monsoon Data Assimilation and Analysis (IMDAA) reanalysis of high-resolution gridded hourly datasets. The performance of the PBL schemes varies with the meteorological parameters that have a physical relationship with HWs. The composite of statistical analysis shows that the ACM2 scheme performs better for the maximum temperature with lesser root mean square error (RMSE) by 1.67°C. The BouLac shows a lesser RMSE of 1.25°C for the early morning temperature. ACM2 and BouLac schemes have replicated the zonal (meridional) wind with an RMSE of 1.47 and 1.79 m/s (2.86 and 2.81 m/s), respectively. Both the BouLac and ACM2 performed well in representing PBL height and relative humidity. The aggregated rank analysis reveals that BouLac and ACM2 are suitable for the prediction of HW over Bhubaneswar city. The city is underwarming during the HW period, and the UHI is about 0.77°C. PBL schemes are overestimating the UHI, and a possible reason might be representations in fluxes and land-atmosphere interactions. The spatial and temporal distribution of energy fluxes simulates the same over built-up areas irrespective of the PBL schemes used in the WRF model.

Abstract

Various models have been proposed to estimate the TBM penetration rate. Generally, the input parameters of these models can be divided into two categories: Machine parameters and geological engineering parameters. The engineering geological parameters will significantly influence the penetration rate if the machine operational parameters are kept within a reasonable near-optimal range. However, while some performance prediction models can be used for many common project settings, they have lower accuracy in certain applications. This study compared the observed penetration rate of a hard rock TBM with those predicted by MCSM, Norwegian University of Science and Technology (NTNU), Farrokh–Rostami, and Ramezanzadeh’s models in the Kerman water tunnel (KWT). Next, joint survey data are collected from the different zones of the KWT. For this purpose, a 3D discrete fracture network (DFN) model code was generated in Mathematica^© version 13. The joint data’s orientation, persistence, and spacing were used to develop a 3D-DFN model for estimating the blockiness rate (BR) index. The BR index is the actual joint intensity in 2D (P₂₁) and 3D (P₃₂). In this study, the BR index is the newest rock mass parameter introduced and used to predict the penetration rate of TBM. This index can serve as a rock mass parameter that provides excellent and realistic results for predicting penetration rate (PR). The corresponding determination coefficient values of the PR with P₃₂ and P₂₁ are R² = 0.96 and R² = 0.98, respectively, and with CIA and UCS, are R² = 0.42 and R² = 0.49, respectively. Furthermore, using the DFN model showed its potential to be an accurate and reliable method for the overall estimation of the in-situ rock mass fragmentation, which highly controls the penetration rate of TBM.

Research Highlights

• The penetration rate of a hard rock TBM was compared with the NTNU, MCSM, Farrokh-Rostami, and Ramezanzadeh predictive models in the Kerman water tunnel (KWT).

• A 3D-Discrete fracture network (DFN) model code was generated.

• Four different zones of KWT were studied to discriminate rock mass parameters or intact rock parameters that affect the penetration rate of TBM.

• The BR index is the newest rock mass parameter that has been introduced and used to predict the penetration rate of TBM.

• The Blockiness Rate (BR) index as rock mass parameters has verified that it highly influences the penetration rate of TBM.

Abstract

Equatorial longitudinal ionospheric variations are influenced by various physical processes, including the east–west directed electric field (equatorial electrojet, EEJ). However, the specific impact of EEJ variability on the total electron content (TEC) variations in different longitudinal sectors has not been thoroughly explored. Therefore, this study focuses on investigating the longitudinal changes in the EEJ and how they affect the daily patterns of the equatorial ionization anomaly (EIA) on geomagnetic calm time from 2011 to 2013. EEJ was estimated using pairs of magnetometer observations across eight sectors globally, while Global Positioning System (GPS) TEC data were collected from three stations at the southern/northern crests and trough locations within the longitudinal sector. The study presents seasonal variations in EIA TEC during different seasons alongside longitudinal variations of EEJ in both the southern/northern hemispheres. Statistical analysis reveals that the southern/northern equatorial ionospheric anomaly (EIA) crests exhibit positive correlations with the peaks of EEJ in all regions, indicating that the variations in EIA strength align with those of EEJ. The seasonal mean EEJ and EIA crests are most pronounced during equinox seasonal months over the Southeast Asian, Peruvian, and Philippine regions in the investigation period. In these regions, the correlation coefficients for the TEC near the northern crests are relatively higher than those for the southern crests, while the southern crest shows slightly higher values across the Pacific, Indian, Brazilian, and West African regions. Notably, the correlation between an integrated EEJ and the strength of EIA is stronger than that with the day maximum EEJ. The study also presents the seasonal characteristics of EEJ and EIA, with counter electrojets (CEJ) occurrences occurring more observable in Brazil and Africa. However, in most equinoctial seasons, the highest TEC peak close to the EIA crest is observed in these sectors.

Research Highlights

• The northern/southern TEC of EIA crests exhibit variations that correlate with the variations in EEJ.

• TEC of EIA strength variations align with those in EEJ during different seasons.

• The correlation coefficients between EIA and EEJ exhibit high values across all sectors during the moderate year of 2011.

The Mercara Shear Zone (MSZ) is an intensely deformed, curvilinear, mylonitised zone juxtaposed between the Western Dharwar Craton (WDC) and the Coorg Block (CB). In the vicinity of Madikeri town, the MSZ exposes many bands and enclaves of granulite-grade meta-supracrustals and mafic granulites hosted within charnockite or felsic orthogneiss (retrogressed charnockite). Subsequently, the area is intruded by a suite of granitoids along the mid-axis of the shear zone, showing no signature of metamorphism. Views on the origin and timing of the formation of the granulite-grade rocks of the MSZ are not streamlined, and the unmetamorphosed suite of granitoids has not been studied in detail in light of the evolution of the terrain. The field relationship, petrography and bulk rock geochemistry of the suite of unmetamorphosed granitoids from the MSZ were carried out to address this issue. Petrological and geochemical data indicate an I-type affinity of the granitoids. Trace and rare earth element (REE) patterns suggest a magmatic arc setting. The rocks are calc-alkaline, and the REE pattern is fractionated, enriched in Ba, Sr, and depleted in high field strength elements like Nb, Ta, and Ti with almost no significant negative Eu anomaly. These characteristics indicate the dominance of crustal involvement over the mantle in the generation of melt. Studied samples show ‘adakite-like’ geochemical characteristics (high Sr/Y, La/Yb) but are not the product of typical slab melting. The present study indicates that the granitoids were derived from a thick crustal source by partial melting in an oxidized condition (fO₂ between NNO and HM buffer) at 941–985°C and 10–12.5 kbar pressure (corresponding to 30–40 km depth).

Abstract

Organic geochemical and stable isotope records of Oligocene and late Miocene–Pliocene sediments from IODP hole U1501C and Pliocene–Pleistocene sediments from U1499A of South China Sea (SCS) were studied to investigate clock sources of organic matter and carbonates and their spatiotemporal variations with East Asian climatic variability. Geochemical data was constrained using shipboard information. CaCO₃ and total organic carbon contents (wt%) varied between 1.32 to 56.52 and 0.12 to 1.13, respectively. δ¹³C_carb, δ¹⁸O_carb and δ¹³C_org ranged from −4.89 to 1.98‰, −5.54 to 1.96‰, and −24.66 to −28.13‰, respectively. Contributions from mixed sources of carbon were observed in the Oligocene, while the late Miocene–Pleistocene exhibited terrestrial dominance. Early Oligocene carbonate, low and higher TOC are attributed to the opening of SCS, increased terrigenous input, and prevalence of cooler climate. Stable isotopes suggest the expansion of the marine environment and the probable dawning of the East Asian Winter Monsoon (EAWM) during the Oligocene. The late Oligocene marked a transition to a warmer climate. The strengthening of EAWM since the late Miocene is indicated by moderate organic carbon and high carbonates with enriched isotopes. Glacial low sea levels and higher terrestrial inputs increased TOC, while dissolution affected late Plio–early Pleistocene carbonates. Higher carbonates and productivity since the mid-Pleistocene were influenced by alternate weakening and strengthening of EAWM.

Research highlights

• Organic matter, carbonates, C and O isotopes from Oligocene and late Miocene–Pleistocene sediments, northern SCS.

• Productivity in the South China Sea fluctuated, being low during the Oligocene, with a subsequent increase since the late Miocene.

• δ¹³C_org and δ¹³C_carb indicate cold climatic conditions and probable winter monsoon signatures since the early Oligocene, transitioning to warmer conditions during the late Oligocene.

• During the late Miocene (~8–5.6 Ma), deep-water circulation and intensified winter monsoons led to higher productivity.

• Pliocene sediments (since ~5.6 Ma) showed signs of climatic cooling, sea level fluctuations, and enhanced winter monsoons with carbonate dilution.

• The Plio-Pleistocene period witnessed glacial and interglacial cycles reflecting changing monsoon intensities.

Seismic source characterization is a crucial part of earthquake early warning. With the increasing seismic stations and collected data, some deep learning methods are gradually introduced and perform well in earthquake magnitude evaluation and localization. However, how to handle the sparse and non-European multi-stations is still a problem in earthquake multi-station models. This paper designs a multi-station model based on a graph neural network to accomplish seismic source characterization. The model applies the methods of graph theory to represent earthquake data as graph structure and innovatively adds the earthquake phase picks into the edges of the graph. This method mines the potential information among multi-stations effectively. The proposed methods improve the predicting precision and perform better in real-time performance than the compared models.

North-Eastern (NE), India and its adjoining region is one of the sixth most seismically active regions of the world. In the present investigation, the return period of earthquake and probability of occurrence inferred from Gutenberg–Richter (GR) relation was estimated for NE, India region and its vicinity. When we consider the entire NE, India region and its vicinity, it evidently suggested that the return period of earthquakes of 7 ≤ Mw ≤ 8.6 is short, which ranges from 32.73 to 162.59 years. It was observed that the earthquake occurrence from infinitesimally short interval t~0 for Mw~3.6–4 is embedded with 100% probability. The earthquakes of Mw~4.1–5.3 reach 100% in 10 years. Similarly, Mw~5.4–5.7 reaches to 100% in 20 years. Likewise, Mw~5.8–5.9, 6.0–6.1 and 6.2 reach ~100% in 30, 40 and 50 years, respectively. For large earthquakes of Mw~7.0–8.0, the probability of occurrence reaches >80% in 100 years. This observation strongly indicates that the likelihood of earthquakes occurring in the north-eastern region of India and its surrounding areas tends to increase over time. Further, the region was divided into four zones, namely Block I (26.5–28.5ºN; 89–95ºE), Block II (26.5–28.5ºN; 95–97.5ºE), Block III (23–26.5ºN; 93–97.5ºE) and Block IV (23–26.5ºN; 89–93ºE) based on seismicity and the major tectonic domains of the region. In terms of return period based on GR-relation and stochastic observations, we may conclude that the risk associated with occurrence of earthquake is highest in Block IV, followed by Block III, Block I and Block II respectively. Further, a comparison of the probabilities of earthquake return period considering seismogenic depths along with hypocentral depth data for different blocks was investigated for a comprehensive understanding of seismic occurrences over time. However, overall, the patterns and trends observed remain consistent, emphasizing the seismic activity within each block and its associated return periods. The stochastic observations and findings are elaborately accentuated in the article.

Due to continued continental convergence of Indian–Eurasian plates, the Himalayan region witnessed several high-magnitude earthquakes and is prone to major seismic events in future as well. Most of the countries with seismically active faults examine paleo seismic data in site specific as well as regional seismic hazard analyses. Hence, it is of great concern to find evidence for prehistoric earthquakes following the morphotectonic route and establish the recurrence intervals of potential earthquakes by characterising and dating large prehistoric events. The present study discusses the paleo seismicity and induced deformational features in the Trans-Yamuna region of the outer Northwest Himalaya by interpreting soft sediment deformation and paleo-liquefaction features. We targeted two sites along the Trans-Yamuna active fault system, which are located in the Sirmurital and Bharli villages; both of these locations are close to Doon Valley along the Main Boundary Thrust. Temporal distribution of paleo-liquefaction features evident major seismic events likely to occur during 16th and 19th centuries, which clearly indicates reactivation of faults in this hinterland region that could experience major rupture during the recurrence of large magnitude earthquake and therefore, constructional activities are a matter of great concern to design structures accordingly.