Anthropogenic activities are increasingly altering geomorphic systems, often exceeding the influence of natural processes. Assessing the extent of this Anthropogeomorphic Pressure (AGP) is essential for mitigating its adverse effects on landscapes. This study introduces the Nigam-Kotha Model of Anthropogeomorphic Impact at Ecumene (AGI@E), a novel, holistic approach developed using interdisciplinary variables spanning human and physical geography. The model quantitatively assesses AGP using ten variables, including socioeconomic, demographic, geomorphometric, climatic, and natural hazard factors. It uniquely differentiates between anthropogenic pressure and natural erosion susceptibility, providing a dual-impact profile for ecumene regions. A case study in four sub-districts of coastal South Goa-Marmugao, Salcete, Quepem, and Canacona-was conducted for model validation, covering the period from AD 2000 to 2020. Results revealed markedly higher AGI@E values in Marmugao (338.77 in 2000; 229.44 in 2020) and Salcete (358.34 in 2000; 290.80 in 2020), indicating intensive anthropogenic influence, coinciding with rapid urban and industrial development. In contrast, Quepem and Canacona displayed significantly lower values (Quepem: 85.10 to 103.84; Canacona: 73.40 to 76.29), suggesting relatively stable geomorphic conditions with limited human interference. Extensive field surveys, satellite data, and historical development trends corroborated these outcomes. The AGI@E model effectively identifies and quantifies geomorphic stress in human-dominated landscapes, making it a valuable tool for regional planning and environmental management. However, its applicability is currently limited to ecumene zones, necessitating caution when extrapolating beyond inhabited regions.

This study presents a new database including mineral chemistry, whole rock geochemistry and Sr-Nd isotopic compositions for basalts recovered from the Central Indian Ridge (CIR) with a view to evaluate melt generation processes, source characteristics and tectonic controls on Indian Ocean mantle evolution. The salient geochemical characteristics of the subalkaline, tholeiitic to transitional Central Indian Ridge Basalt (CIRB) are marked by relatively higher abundances of LILE and LREE over HFSE, depletion in HFSE abundances with respect to primitive mantle compositions corroborated by negative Nb, Zr, Hf anomalies and Nb/Nb*<1, Zr/Zr*<1, Hf/Hf*<1; depleted to moderate enrichment of LREE and MREE over HREE and trace element variations reflecting distinct deviation from N-MORB to E-MORB with very low Nb/Y (avg.: 0.08) and Zr/Y (avg.: 3.00) values with respect to OIB (Nb/Y: 1.66, Zr/Y: 9.66). The CIRB samples showing Ba/Nb>6, Rb/Nb>0.6, Nb/U<42 and Ce/Pb<22 conform to the BABB filter thereby preserving past subduction signals and validating the evidence for a subduction-modified source mantle. The Sr-Nd isotopic ratios yielded the following ranges: Sr-87/Sr-86: 0.702810-0.703518 and Nd-143/Nd-144: 0.512831-0.513118 (epsilon(Nd): +3.77 to +9.37), reflecting an enriched heterogeneous mantle end-member source mantle. Isotopic mixing calculations identify major HIMU-EM1 signature with minor EM2 component for CIR basalts attesting to the chemical heterogeneity of the Indian Ocean mid oceanic ridge (MOR) mantle. The major HIMU-EM1 isotopic trend, distinct deviation from DMM-N-MORB with lower Nb/Y, Nb/Yb, Nb/U, Nb/Th and higher Ba/Nb, Ba/Th, Ba/La, Nd/Hf, Ce/Nb for CIRB in comparison with OIB and N-MORB suggest that OIB component or deep mantle plume sources had no influence on the compositional diversity of the mantle source. Instead, these features attribute the fertility of CIRB source mantle to: (i) convection driven recycling of ancient, subducted, metasomatized oceanic crust (HIMU) and (ii) delamination, dispersion and dilution of Gondwanan SCLM, LCC and UCC. This study equates the chemical evolution of the Indian Ocean MOR mantle and its pervasive heterogeneity with polychronous tectonic events involving cyclic amalgamation and disintegration of supercontinents synchronized with ocean basin closure and opening that systematically recycled ancient lithospheric components into the mantle.

Technological advancement and exponential rise in the human population have led to severe modification of the land surface area. These human‐induced geomorphic modifications are considered as an active geomorphic process that interrupts dynamic equilibrium between landform and anthropogeomorphologic processes. The present study aimed to evaluate the efficiency of Nir's ‘Index of potential anthropic geomorphology’ used to quantify anthropogeomorphic process (AGP) impact. The model was applied in 11 talukas (sub‐districts) of Goa State, India. Goa is a good candidate to understand the impact of anthropogeomorphological process because it has a varied topography with different geomorphological landforms along with rapid increase in urbanisation and mining activities which are anthropocentric. Decadal results show that, during 1991, 2001, and 2011, the tourism hubs of North Goa Bardez (0.32, 0.36, and 0.40) and Tiswadi (0.44, 0.42, and 0.47) required least attention to curb human impact, while the major economic and tourism hubs of South Goa Marmugao (0.55, 0.53, and 0.40) and Salcete (0.40, 0.40, and 0.40) surprisingly showed no increase but instead a decline in the values. In addition, prominent mining talukas Bicholim (0.25, 0.30, and 0.20), Quepem (0.45, 0.39, and 0.15), and Sanguem (0.24, 0.22, and 0.18) also showed declining values, which is indicative of decreased human activities. The index results suggest ‘no requirement of urgent and efficient measures’ in any talukas because none of the values have been found to be above 0.50, which according to the model represents considerable damage to geomorphology. However, Goa is a world‐renowned tourism destination and all these talukas have witnessed massive urban development, high literacy rate, and exponential growth in National State Domestic Product and mining activities, especially since the turn of the millennium, which are contrary to Nir's index results. Therefore, the model has been found to be over‐generalised and ineffective in indicating actual AGP at the meso level.

Climate change poses a significant threat to coastal regions worldwide. This study presents and applies a modified Coastal Vulnerability Index (CVI) to assess coastal vulnerability at the village level, focusing on Canacona, a taluka in South Goa, India. It adapts the existing CVI methodology by incorporating additional variables to better represent the various dimensions of vulnerability, resulting in 21 variables split into a Physical Vulnerability Index (PVI) and a Social Vulnerability Index (SoVI). The results show spatial variability in coastal vulnerability across the studied villages, with Agonda and Nagercem-Chaudi found to be highly vulnerable and Loliem to be the least vulnerable. A hydrological modeling approach is also used to compare the CVI of every village with their susceptibility to inundation due to rising sea levels. The results demonstrate the influence of local factors on vulnerability, challenging previous taluka-level assessments given the scale upon which adaptation typically takes place.

The Laxmi Basin, which is a deep ocean basin situating adjoining to the northwestern continental margin of India, contains a linear seamount chain consisting of the Raman Seamount, Panikkar Seamount and the Wadia Guyot, located over the axial basement high in the Laxmi Basin representing the Panikkar Ridge. The geomorphology of this seamount chain was studied by earlier researchers; however, its characteristic geophysical signatures, possible genesis and age of formation remains to be clearly established. We attempted for a detailed understanding of the morphological characteristics and the geophysical signatures over the spatial extent of these seamounts using a fresh set of multibeam bathymetry data and sea-surface gravity and magnetic anomalies, complemented by the existing seismic reflection sections. Based on the seafloor and basement topography signatures observed together from the multibeam bathymetry data and the seismic reflection sections, we infer that all the three seamounts are associated with the presence of surface/subsurface secondary peaks on their central parts. The free-air gravity anomaly maps show that the seamounts are associated with a very short wavelength gravity high, superimposed on the short wavelength gravity low representing the Panikkar Ridge. The magnetic anomaly maps suggest that all these seamounts are associated with complex magnetic signatures. Based on the presence of morphological features that are generally associated with the volcanic activity and by considering the above complex geophysical signatures and the updated magnetic isochron map of the Laxmi Basin, we support multiphased volcanic origin for the Raman-Panikkar-Wadia seamount chain, emplaced at an age younger to 63.28 Ma.

The present study focuses on preparing the wetland map using earth observation data and applying a novel ensemble model. Eight advanced machine learning algorithms were applied to determine the probability of the occurrence of wetlands. The random forest (RF), support vector machine (SVM), and multivariate adaptive regression spline (MARS) models outperformed others. So, these models were further used to create a stacking ensemble for improving precision. The RF-SVM-MARS ensemble model was run with seven various parameters. The results show that the integrated parameter has the highest area under the curve (0.960) followed by optical-hydrogeomorphic (0.953), SAR-hydrogeomorphic (0.940), hydrogeomorphic (0.896), SAR-optical (0.892), optical (0.881), and SAR (0.702). The hydrogeomorphic variables exhibited greater influence than the optical and SAR variables. However, the integration of all selected key variables proved to be the most effective approach for probabilistic wetland mapping. The RF-SVM-MARS ensemble model can improve classification accuracy as compared to a single model. An accuracy of 96% was obtained when the ensemble model output was cross-validated with field data. The ground-penetrating radar (GPR) tool was also successfully employed to study the sub-surface strata and water level conditions in wetland and non-wetland areas. The successful application of a new ensemble approach along with the GPR technique for coastal wetland mapping in this study could encourage researchers to choose it as an appropriate methodology. Moreover, the outcomes of the work will help land-use planners and government agencies for better planning, monitoring, and promoting sustainable development of the coastal area.

This book represents a detailed introduction to the geology, structure, and stratigraphic account of Kutch Basin, known for its rich fossilized megafauna.

This is the first systematic high-resolution rock magnetic study complemented by mineralogical and petrological observations conducted on sediment cores representing shallow (active cold seep; SSD-45/Stn-4/GC-01) and deep-seated (NGHP-01–15A) gas hydrate systems in the Bay of Bengal which addresses two key questions: (i) how magnetic minerals respond to the geochemical environment at two different diagenetic settings experiencing variable fluid sequence, and (ii) elucidates the control on the magnetite and greigite authigenesis in sulfidic, methanic, and gas hydrate bearing sediments. Titanomagnetite is the dominant detrital magnetic mineral identified in the studied cores from the Krishna-Godavari (K-G) basin along with diagenetic (pyrite) and authigenic (magnetite, greigite) minerals. Large detrital titanomagnetite and silicate-hosted (fine-grained) magnetic inclusions survived diagenetic dissolution during high sedimentation events. Magnetic proxies (ARM/SIRM and SIRM/χlf) provided useful insights on the diagenetic and authigenic formation and preservation of magnetic particles in the studied cores. Preferential diagenetic dissolution of finer (detrital) magnetic particles in sulfidic and authigenic formation of magnetite in methanic environment is clearly evident in the ARM/SIRM record of cores from both sites. Elevated values of SIRM/χlf in cores SSD-45/Stn-4/GC-01 (sulfidic and hydrate bearing) and NGHP-01–15A (methanic) indicate formation and preservation of ferrimagnetic authigenic (SP) greigite particles. Based on the magnetic proxies, we demonstrated that the formation of authigenic magnetite in the methanic environment of both sites is tightly linked with the microbial iron-reduction process. Multiple occurrences of authigenic carbonate provided evidence on the episodic intensification of anaerobic oxidation of methane (AOM) at active seep and silicate weathering coupled to microbial methanogenesis at deep-seated gas hydrate site respectively.

This work quantifies the impact of pre-, during- and post-lockdown periods of 2020 and 2019 imposed due to COVID-19, with regards to a set of satellite-based environmental parameters (greenness using Normalized Difference Vegetation and water indices, land surface temperature, night-time light, and energy consumption) in five alpha cities (Kuala Lumpur, Mexico, greater Mumbai, Sao Paulo, Toronto). We have inferenced our results with an extensive questionnaire-based survey of expert opinions about the environment-related UN Sustainable Development Goals (SDGs). Results showed considerable variation due to the lockdown on environment-related SDGs. The growth in the urban environmental variables during lockdown phase 2020 relative to a similar period in 2019 varied from 13.92% for Toronto to 13.76% for greater Mumbai to 21.55% for Kuala Lumpur; it dropped to −10.56% for Mexico and −1.23% for Sao Paulo city. The total lockdown was more effective in revitalizing the urban environment than partial lockdown. Our results also indicated that Greater Mumbai and Toronto, which were under a total lockdown, had observed positive influence on cumulative urban environment. While in other cities (Mexico City, Sao Paulo) where partial lockdown was implemented, cumulative lockdown effects were found to be in deficit for a similar period in 2019, mainly due to partial restrictions on transportation and shopping activities. The only exception was Kuala Lumpur which observed surplus growth while having partial lockdown because the restrictions were only partial during the festival of Ramadan. Cumulatively, COVID-19 lockdown has contributed significantly towards actions to reduce degradation of natural habitat (fulfilling SDG-15, target 15.5), increment in available water content in Sao Paulo urban area(SDG-6, target 6.6), reduction in NTL resulting in reducied per capita energy consumption (SDG–13, target 13.3).

The novel coronavirus which is also known as (SARS-CoV-2) was first detected in Wuhan, China in late December 2019. It is a highly contagious and mutable disease that has become a pandemic. The majority of nations had opted for partial to total lockdown restrictions as a measure to contain the spread of COVID-19. India announced a 68-day nationwide lockdown on March 25, 2020 which was subsequently extended and succeeded by different phases (with relaxation in restriction rules) till May 31, 2020. The lockdown has dramatically impacted the economy of the country. However, it has come as the breathing space for the environment as its anthropogenic exploitation came to standstill. Drastic reduction in pollution level and increment in environment-friendly variables have been observed around the world. The present study assessed the trends of particulate matter (PM10), sulphur dioxide (SO2), and the Oxides of Nitrogen (NOx) during the pre-lockdown, lockdown, and post-lockdown periods and similar period of 2019 for Guwahati city situated in northeast India. The meta-analysis of continuous data was performed using descriptive statistics on air pollutant data was acquired from the Central Pollution Control Board and Assam Pollution Control Board. The result revealed that as much as 63.02%, 80.28%, and 84.25% reduction in the mean concentration of PM10, SO2, and NOx pollutants, respectively, and the fluctuation from the mean values were also drastically reduced by 93% for PM10, 96.11% for SO2 and 89.47% for NOx in comparison to a similar period of 2019. The significance of the study is to show how the different sets of restrictions (in phases) imposed upon a city can significantly reduce pollutant concentrations. The study suggests that after modifications (to minimize the economic damages) the lockdown can also be one of the important measures to arrest high pollution levels in the urban and industrialized areas.

Study of the sedimentary structures helps to interpret the depositional process of siliciclastic sediments. Sedimentary structures are classified based on the morphology, formation process, sediment rheology, deformation mechanism and relative timing of sedimentation. In this study, the structures are categorized as Primary depositional, Diagenetic, Soft Sediment Deformation Structures (SSDS) and Deformational Structures. Laminations, dropstone, graded beddings, and cross-bedding are primary structures formed during sedimentation and among the diagenetic structures, liesegang rings were identified. The other structures such as convolute, flame and load, ball and pillow (pseudonodules), slump fold and syn-sedimentary fault are classified as SSDS and are reported for the first time. The dykes and shear zone are the intrusive and deformational structures, respectively. In our study, the regional geology and structural data suggest a deltaic environment with a turbiditic condition of deposition for the formation of the SSDS. In a deltaic environment the SSDS were formed due to rapid deposition of sediments by suspension, their disruption due to liquefaction, and movement of sediment in a water-logged state. The processes were controlled by slope of the basin, gravity controlled density currents and differential compaction. In this environment of high sediment supply, fluctuating water level, slope instability and sediment density there resulted an in situ deformations of the sediments and formation of the SSDS. We have correlated the typical Bouma sequence with the various structures including the SSDS that are associated with the metagreywacke-argillite strata in the study area. The strata with 4 units (A–D) reveal a typical Bouma sequence which was influenced the low-density turbidity currents. With time, the deep basin sediment depositional environment progressively changed to a shallow environment.

The present study sets out to elucidate how magnetic minerals derived from wide array of source regions respond to shelfal sedimentary processes in a complex shelf system. Bulk sediment magnetic mineralogy comprised of detrital magnetic (magnetite, titanomagnetite, titanohematite) particles with variable concentrations and grain sizes. A prominent change in magnetic mineral contribution from mafic to felsic dominated sediment province is clearly evident through a trend of decline in magnetite content manifested by fining of magnetic crystal size. Elevated magnetite content followed by the presence of fine and coarse-grained magnetic particles, and mere variations interms of mineralogy can be attributed with the enhanced magnetic contribution from the Deccan basalt (DcB) in the shelf sediments off Narmada, Tapti, Mahi, and Sabarmati (NTMS) River system, Arabian Sea. A distinct shift in magnetite content accompanied by abrupt fluctuations in clastic grain size in the sediment core off Ganga-Brahmaputra (G-B) shelf, Bay of Bengal indicate the major change in detrital sedimentation. A major change in the magnetic mineralogy linked with enhanced supply of titanomagnetite particles marks the onset of mafic sourced material in the sediments off Pennar - Swarnamukhi (P-S) shelf, Bay of Bengal. Magneto-granulometry data revealed that magnetic crystal size is independent of physical grain size above >40 mu m in NTMS and G-B, and >20 mu m in P-S samples. Decoupling is largely due to polycrystalline nature, where fine-grained magnetic particles occurred as inclusions within silt and sand fractions. We demonstrate that multi -proxy approach presented in this study can be effectively used to assess the influence of the contrasting prov-enance and oceanographic conditions on the shelfal sediment dynamics.

This chapter covers the details on the stratotype-sections of the litho-stratigraphic units of Kutch Basin with the unit-by unit description of the lithology displayed in respective tables useful for correlation and understanding the depositional history of the Basin. This is very useful for the post-graduate and research students interested in taking up dissertation/thesis apart from general understanding of the Mesozoic to Recent sedimentation history.

Land-use change is a dynamic and multidimensional process that links nature with human activities. It directly influences soil, water and atmosphere and hence is directly related to many global environmental issues. Understanding the hydrologic response of watersheds to physical (land use) and climatic (rainfall and air temperature) change is a critical element of water resource planning and management. Land-use changes can significantly affect surface water runoff, flood frequency, baseflow and annual mean river discharge. Hence, the specific objective of this study was to understand the land-use change that has occurred over the years in five river watershed areas in Goa, India, from the hydrological modeling perspective. The watershed areas of five rivers across the state of Goa were selected for this study. These rivers are the Kalna, Sal, Talpona, Galjibag, and Khandepar. Satellite images for five years from 1977 to 2018 were used. The remote sensing data (from LISS III, Landsat 1–5, and Landsat 8) were geo-referenced and merged. The image classification for change analysis and the various spatial analyses were performed using software, such as ArcGIS 10.3, TerrSet 18.31 and Microsoft Office 2010. The most recent data (2009 to 2018) show that there has been a decrease in the forest cover in all the five watershed areas, except in the Galjibag watershed. This decrease was greatest for the Sal watershed (5.75%). The Kalna and Galjibag watersheds showed the greatest increase in the built-up area. The results indicate that the Sal watershed is witnessing rapid urbanization and the Khandepar watershed is experiencing the least. These results can provide useful insights for generating future land-use scenarios to carry out hydrological modeling exercises in these five watersheds and to facilitate prediction of water flows.

In this study, we conducted a comprehensive investigation of rock magnetic, mineralogical, and sedimentological records of sediment cores supplemented by a high resolution seismic data to elucidate the controls of structural and diagenetic ( early vs. late ) processes on the sediment magnetism in active and relict cold seep sites in the Bay of Bengal. Two distinct sediment magnetic zones (Z-I and Z-II) are defined based on the down-core variations in rock magnetic properties. The sediment magnetism is carried by complex magnetic mineral assemblages of detrital (titanomagnetite, titanohematite) and authigenic (fine-grained greigite) minerals. Overall, the magnetic susceptibility varies over one order of magnitude with highest values found in relict core. Uppermost sediment magnetic zone (Z-I) is characterized by higher concentration of magnetite as seen through elevated values of magnetic susceptibility (χ lf ) and saturation isothermal remanent magnetization (SIRM). A systematic gradual decrease of χ lf and IRM 1T in Z-I is attributed to the progressive diagenetic dissolution of iron oxides and subsequent precipitation of iron sulfides. Magnetic grain size diagnostic (ARM/IRM 1T ) parameter decreases initially due to the preferential dissolution of fine-grained magnetite in the sulfidic zone (Z-I), and increases later in response to the authigenic formation of magnetite and greigite in methanic zone (Z-II). Distinct low S-ratio and χ lf values in methanic zone of relict core is due to increased relative contribution from highly preserved coercive magnetic (titanohematite) grains of detrital origin which survived in the diagenetic processes. A strong linkage between occurrence of authigenic carbonates and greigite formation is observed. Two plausible mechanisms are proposed to explain the formation and preservation of greigite in Z-I and Z-II: 1) decline in methane flux due to massive hydrate accumulation within the active fault system and formation of authigenic carbonate crust in the sub-surface sediments hindered the supply of upward migrating fluid/gas; thereby limiting the sulfide production which preferentially enhanced greigite formation in Z-I and 2) restricted supply of downward diffusing sulfide by the carbonate layers in the uppermost sediments created a sulfide deficient zone which inhibited the pyritization and favoured the formation of greigite in the methanic zone (Z-II).

The rapid transformation of land cover/land use (LCLU) is a strong indication of global environmental change. In order to monitor LCLU through maps, a significant dataset and robust technique are necessary. Thus, the primary objective of the current research is to evaluate and compare the efficiency of several notable satellite sensors including Landsat-8 (L-8), Sentinel-2 (S-2), Sentinel-1 (S-1), combined Sentinel-1 and Sentinel-2 (S-1-2), LISS III (L-3), and LISS IV (L-4) for LCLU mapping applying random forest (RF), logit boost (LB), stochastic gradient boosting (SGB), artificial neural network (ANN), and K-nearest neighbor (KNN) models. For this purpose, 300 samples for each of the six LCLU classes have been selected based on field survey and high resolution Cartosat-3 images. The classification accuracy namely producer accuracy (PA), user accuracy (UA), overall accuracy (OA) and kappa coefficient have been calculated from the confusion matrix of the applied models. This results show the highest accuracy has been derived from the integration of S-1-2 datasets followed by S-2, L-8, L-3, L-4, and S1. On the other hand, LB model is the most consistent and efficient in comparison with other models for all the datasets. Regarding importance of variable, SWIR band is repeatedly the most crucial factor while blue band is the least significant variable. From this comparative assessment of sensors, it has been found that high spatial and spectral resolutions along with combination of satellite datasets are required to get better accuracy rather than only high spatial resolution in regional scale mapping. The present study strongly advocates the use of combined S-1-2 data together with the application of LB model for LCLU classification.

The research aims to propose the new ensemble models by combining the machine learning techniques, such as rotation forest (RF), nearest shrunken centroids (NSC), k-nearest neighbour (KNN), boosted regression tree (BRT), and logitboost (LB) with the base classifier adabag (AB) for flood susceptibility mapping (FSM). The proposed models were implemented in the central west coast of India, which is vulnerable to flood events. For flood inventory mapping, a total of 210 flood localities were identified. Twelve effective factors were selected using the boruta algorithm for FSM. The area under the receiver operating characteristics (AUROC) curve and other statistical measures (sensitivity, specificity, accuracy, kappa, root mean square error (RMSE), and mean absolute error (MAE)) were employed to estimate and compare the success rate of the approaches. The validation results of the individual models in terms of AUC value were AB (92.74%) >RF (91.50%) >BRT (90.75%) >LB (89.07%) >NSC (88.97%) >KNN (83.88%), whereas the ensemble models showed that the AB-RF (94%) was of the highest prediction efficiency followed by, AB-KNN (93.33%), AB-NSC (93.02%), AB-LB (92.83%), and AB-BRT (92.64%). The outcomes of the ensemble models established that the AB is more appropriate to increase the accuracy of different single models. Therefore, this study can be useful for proper planning and management of the study area and flood hazard mapping in alike geographic environment.

This chapter deals with a general introduction to Kachchh Basin with reference to Geology, Stratigraphy, Structure, Igneous Activity, and basin evolution. This is intended to provide the geological background to the geo-tourists.