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Changing rainfall patterns on vulnerable hill slopes are a significant factor in increasing landslide frequency and resulting damages. In the Nilgiris district of the Western Ghats, India, recent shifts in rainfall patterns, including increased overall precipitation and more erratic downpours, have raised concerns about landslide occurrences. This study examines the correlation between the altering rainfall patterns and the occurrence of landslides in a quantitative manner. A thorough analysis of rainfall data from 1992 to 2022 using R (hydroTSM) is conducted to evaluate its impact on landslides. Using the Analytical Hierarchy Process (AHP), a comprehensive Landslide Susceptibility Map (LSM) is generated by incorporating twelve significant landslide causative factors. The results indicate that 1% of the study area is in the very high susceptibility zone and 18% in the high susceptibility zone. These findings are crucial for developing targeted mitigation strategies, effective land use planning, and ensuring the safety of the region's inhabitants and infrastructure.

Abstract Background The areas prone to geological hazards such as liquefaction need special attention with respect to social vulnerability. Though liquefaction by itself may not result in damage, it may trigger a series of ground failures such as ground oscillation, lateral spread, loss of bearing strength, etc., which cause heavy damage. Globally, during the past few decades liquefaction hazard analysis has become one of the important criteria in seismic risk analysis and mitigation management, especially for urban areas. Greater Chennai is one of the million-plus population cities in India. The city also felt earthquakes/tremors in the past history. Method The present study aims to assess the social vulnerability of the population density of the Greater Chennai area due to liquefaction susceptibility using GIS technology. The liquefaction susceptibility map (hazard) for the Greater Chennai was prepared by integration of geological and geomorphological parameters and analyzed over socioeconomic parameters (exposure) using an integration of GIS and AHP. Results The result showed that around 53% of Greater Chennai’s households and population are very much exposed to liquefaction hazard. Conclusions This study can be used as a base level study for decision-making during land use planning as well as disaster mitigation planning.

Among all the natural hazards, earthquake prediction is an arduous task. Although many studies have been published on earthquake hazard assessment (EHA), very few have been published on the use of artificial intelligence (AI) in spatial probability assessment (SPA). There is a great deal of complexity observed in the SPA modeling process due to the involvement of seismological to geophysical factors. Recent studies have shown that the insertion of certain integrated factors such as ground shaking, seismic gap, and tectonic contacts in the AI model improves accuracy to a great extent. Because of the black-box nature of AI models, this paper explores the use of an explainable artificial intelligence (XAI) model in SPA. This study aims to develop a hybrid Inception v3-ensemble extreme gradient boosting (XGBoost) model and shapely additive explanations (SHAP). The model would efficiently interpret and recognize factors’ behavior and their weighted contribution. The work explains the specific factors responsible for and their importance in SPA. The earthquake inventory data were collected from the US Geological Survey (USGS) for the past 22 years ranging the magnitudes from 5 Mw and above. Landsat-8 satellite imagery and digital elevation model (DEM) data were also incorporated in the analysis. Results revealed that the SHAP outputs align with the hybrid Inception v3-XGBoost model (87.9% accuracy) explanations, thus indicating the necessity to add new factors such as seismic gaps and tectonic contacts, where the absence of these factors makes the prediction model performs poorly. According to SHAP interpretations, peak ground accelerations (PGA), magnitude variation, seismic gap, and epicenter density are the most critical factors for SPA. The recent Turkey earthquakes (Mw 7.8, 7.5, and 6.7) due to the active east Anatolian fault validate the obtained AI-based earthquake SPA results. The conclusions drawn from the explainable algorithm depicted the importance of relevant, irrelevant, and new futuristic factors in AI-based SPA modeling.

Achankovil shear zone is a North West-South East (NW-SE) oriented Precambrian structure of South India. Present work identified evidences of two faults (trending NW-SE) in the southern most end of this shear zone. They are Thenmala fault and Thenmala south Fault. This study is an attempt to understand the structural control of these NW-SE structures over the drainage development of the study area, based on geomorphological evidences and field data. Morphometric analysis of the drainage basins clearly indicate that basins located near NW-SE structures shows more anomalies. This anomalies in the vicinity of lineaments and faults indicate their influence over the drainage development. Observed brittle faults evidences with numerous slip planes from the south eastern end of the study area also support this argument. Morphometric evidences in association with brittle fault observations suggest that Achankovil shear zone may be week and reacting to the current stress regime.

Abstract Landslide Hazard Zonation (LSH) maps play a key role in landuse planning particularly in landslide prone areas. LSH mapping is globally accepted one for analyzing the area for landslide susceptibility. Different approaches were followed by many researchers in India to prepare landslide hazard zonation mapping depending upon their need and requirement. The Nilgiris district in Western Ghats of India is one of the severe to high landslide hazard prone areas of India. Many agencies have carried out research on LSH mapping for the Nilgiris district with different scales. A systematic study of inventory and zonation was 122carried out in 1980’s by government agencies. However there is no proper updation or documentation on landslides after 1980’s in the district The purpose of this paper is to review the existing landslide-related studies in the district of The Nilgiris and review the district’s existing landslide hazard map with updated information. Landslide hazard maps in The Nilgiris were compiled in the GIS platform from various authenticated sources. Data on landslides from 1824 to 2014 were collected and a spatial database on landslides was created. A detailed inventory was analyzed and used for revision of the district’s landslide hazard impact on the 2009 landslides.. Based on the landslide inventory and densely populated areas and repeated landslides at the same locations, the most landslide hazard areas were identified.

The tannery industry is characterized by the consumption of a large quantity of water, around 30–40 m3 for processing 1000 kg of hide or skin. This amount becomes wastewater, containing about 300 kg of different chemicals, mainly refractory organic compounds, with high chemical oxygen demand (COD), total dissolved salts (TDS), chromium, and evolution of toxic gases, such as ammonia and sulfides, etc. The remaining tanning chemicals are released as effluent having high resistance against biological degradation, becoming a serious environmental issue. Usually, end-of-pipe treatment is not sufficient to meet the concerns of environmental issues. In terms of cleaner production options, the redesigning of the existing effluent treatment procedures with alternate or additional treatment techniques, which “supports resource recovery with no added chemicals”, is expected to give a sustainable solution for the management of toxic effluent. The Zero Liquid Discharge (ZLD) system serves to ensure zero water emission, as well as treatment facilities by recycling, recovery, and reuse of the treated wastewater using advanced cleanup technology. The international scenario shows the implementation of ZLD thanks to pressure from regulatory agencies. The ZLD system consists of a pre-treatment system with conventional physicochemical treatment, tertiary treatment, softening of the treated effluent, reverse osmosis (RO) treatment for desalination, and thermal evaporation of the saline reject from RO to separate the salts. By adopting this system, water consumption is reduced. Moreover, ZLD also becomes effective in disaster mitigation in areas where the tannery industry is a strong economic actor. With this review, we aim to give an outlook of the current framework.