Landslide is a part of natural natural disasters that causes fatalities to humans, destroys property and overwhelms the regional economy. Various landslide evaluation attempts have been utilized to determine the landslide susceptibility values. Machine learning (ML) has been used in numerous research areas including geotechnical disciplines to produce an effective model to resolve the geotechnical challenge. The ML model has been adopted to produce a landslide susceptibility map (LSM) in many studies with various types and algorithms. This review paper discusses the ML approach used to develop LSM with specific approaches: Support Vector Machine (SVM). The basic principle of ML in producing the LSM is determined and discussed. The study also provides information on the types of validation and performance of the model in developing LSM. SVM and its hybrid model were found to yield good performance in producing LSM in most of the studies with SVM outperforming most of the other ML approaches. This research contributes to the landslide mapping field by providing a readily available, State-of-the-Art reference for researchers, practitioners and local authorities in producing efficient and reliable LSM based on the SVM principle.

Coastal aquifers suffer from saltwater intrusion due to several natural and anthropogenic activities and they pose a severe problem in many coastal regions of India. Anthropogenic activities like saltwater aquaculture activities and salt pans are one of the major causes for saltwater intrusion into freshwater aquifers in coastal regions. Along with these activities, over-exploitation of fresh groundwater for domestic and agriculture purpose also leads to infiltration of saltwater into shallow freshwater aquifers. To address this effect, it is necessary to understand the spatial distribution and extent of the saltwater intrusion in coastal areas. In the present study, SEAWAT model is used to delineate the saltwater intrusion effect and predict the extent of saltwater intrusion resulting from anthropogenic activities in the Nizampatnam coastal area, Andhra Pradesh. The simulation was carried out for the period 2016 to 2018 revealing a change in the extent of the saltwater intrusion up to 2 km into the inland areas from the coast as well as in the vicinity of fishponds. Based on the hydrological conditions observed during the study period and leveraging the calibrated model, saltwater intrusion prediction was carried out for the next two decades. The results show that anthropogenic activities will lead to saltwater intrusion into freshwater aquifers up to 6 km into inland areas from coast at a rate of 200 m/year. Therefore, the sustainable management plans are essential for protecting the freshwater aquifers from the saltwater intrusion in the Nizampatnam coastal area.

This study contains research information on how to counter adverse results (over break, dilution and reduced safety) when conducting blasting operations using Mimosa mine in Zvishavane as a case study. Two perimeter blasting techniques were incorporated into the original blasting pattern used at the mine in order to analyse their effect on blasting operations as compared to the original pattern. To achieve this, a trial blast of each blasting pattern was carried out and the resulting mining heights, dilution and number of bolts replaced to improve safety were recorded and analysed. These results indicated that using perimeter blasting as a method of controlling a blast was capable of minimizing or possibly eliminating some of the negative effects of blasting in poor ground conditions. Further analysis was carried out between the two perimeter blasting techniques and it was concluded that smooth wall blasting was the best method to use in blasting in poor ground conditions. This was as a result of its low drilling times as well as cheaper drilling cost as compared to line drilling.

A watershed is the result of several geomorphic processes such as weathering, erosion, degradation and aggradation which are influenced by several factors viz. tectonics, lithology, climate, landslides and mass wasting processes etc. In a tropical climate, watersheds contribute a significant amount of eroded material which is reflecting the impact of lithology, precipitation, tectonics, relief and anthropogenic activities. In the Himalayan region besides significant heterogeneity in lithology, stratigraphy, structure and tectonics, it is observed that variability is exhibited in climatic conditions over a small region. These factors contribute to the development of geomorphic landforms and are best studied in watersheds or river basins. In the present study, Giri Watershed (GW) is assessed to contemplate susceptibility to erosion for 66 sub-watersheds using geomorphic parameters. The prioritization of subwatersheds has been done using Weighted Sum Analysis (WSA) and Sediment Production Rate (SPR) methods. The quantitative analysis of subwatersheds is categorized into different priority classes viz. very high, high, moderate, low and very low, among which 27 subwatersheds have very high to high susceptibility to erosion.

Floodplain management and mapping are new and applied methods in river engineering and for the prediction of flood hazards. Krishna river basin is the second largest river basin in Peninsular India. This basin is one of the flood prone basins in India. The purpose of this study is to focus on the analysis of HEC-RAS to assess and predict the flood depth and spatial extent of flood in the upper Krishna River basin which is drained by Krishna River. To determine extent of inundation, the hydrodynamic model HEC-RAS with ArcGIS was used. For this, discharge data of two months from August and September 2012 has been processed in the study. A methodology was applied to combine hydraulic simulation model, HEC-RAS and GIS analysis for delineation of flood extents and depths for upper Krishna basin in India. Results obtained by using HEC-RAS Model were used by integrating with Arc-GIS to floodplain maps. Through this floodplain maps, the areas that are vulnerable to hazards, have been identified. The results of this research will benefit in future of flood forecasts on a regional scale, also they will be beneficial for water resources management and planning.

An earthquake is one of the critical natural disasters that causes a massive impact on life and property in the areas it occurs. From the past earthquake patterns, the increase in the number of earthquakes in southern peninsular India can be observed. The increasing number of earthquakes is one of the critical reasons for shifting Chennai from zone II (least active) to zone III (moderately active) by the Bureau of Indian Standards. The soil column's natural frequency and time period are the key parameters for seismic design and construction. Furthermore, compared to shear wave velocity, the fundamental period is a key parameter for site amplification in the recent trend because it accounts for both stiffness and depth of soil sediments. In order to determine the fundamental frequency and typical site period, an equivalent linear 1-D ground response analysis was performed in the Chennai region using ProSHAKE 2.0 software. A contour map was created using ArcGISPro software for the study area's fundamental and characteristic site periods. The longer the soil column's site period, the greater the amplification and the greater the seismic threat. Finally, buildings with a natural period of 0.6 - 1 s should be avoided in the southeastern region of the study area because of the resonance.

Floodplains have become increasingly populated areas throughout Malaysia as shown in the case of Beaufort district situated in the state of Sabah at East Malaysia. This area is now exposed to flood hazards due to the rise of new settlements. Nonetheless, the commpunity in the district has managed to survive and thrive with the prevalence of flood hazards. The aim of this study is to identify the risk of loss level faced by affected communities in the area as well as the coping strategies practised during floods. A survey consisting of 241 heads of households in four villages was conducted in Beaufort. The raw data was analysed using the chisquare, mean score and frequency. The study outcomes reveal that there are various risks of loss present in all villages such as the risk of death (RD), the risk of injury (RI), the risk of property loss (RPL) and the risk of loss of home infrastructure (RLSI). However, the assessed risk levels are low, even at a flood height of 2.5 metres. Two cases in Beaufort, Kampung Bingkul and Kampung Malugus prove that the accessibility of disruption risk remains low with the same flood height level. The affected communities have traditionally developed coping strategies for flood hazards such as owning a boat or building houses on stilts and attics. The research outcomes can assist relevant local authorities to improvise policies related to flood management in high-risk floodplain areas.

Using remote sensing data and Geographical Information System (GIS) methods, this study tries to anticipate the optimal urban expansion areas in Erbil city. The Analytical Hierarchy Process (AHP) concept was used to create a map of urban expansion. Several social, economic, environmental, utility and physical characteristics including land cover, roads, slope, aspect, elevation, soil texture, power lines, water and exclusion, were combined to construct a final land suitability index map. ASTER Digital Elevation Model (DEM) was also followed to derive slope and aspect variables. While organic growth is prominent, considerable growth is expected to occur around the outskirts of current settlements. This research highlights the use of modelbased prediction of urban sprawl in the development of the city’s master plan and road network plan. The findings of this study can help planners and policymakers adopt preventative or regulating measures in advance and make better informed strategic decisions.

Flood is a natural disaster worldwide and it occurs primarily in any plain area due to geological and environmental phenomena like geomorphological process, monsoonal effect, lithology etc. Such plains are also severely affected often by catastrophic flooding and are currently recommended to be the worst flood-affected region in the world. This research aims to classify the flood-prone areas of the Deoha River basin based on the weighted overlay assessment method using Arc-GIS-10 and ERDAS-14. by multi-criteria assessment, in which weights are assigned for each class based on multi parameters with restricted variables to prepare a map of the flood-prone areas. The average annual rainfall (80-200 cm), stream frequency (0.0001 to 0.3563 stream number/km2), slope (0-50-350), drainage density (0-545.94 magnitude/m2), channel gradient (0.27-22.52 m/km), landuse/landcover (cropland>water bodies>built-up>scrubland >forest.) and soil type (loam>sand>clay) prefer the susceptibility of flood-prone in the basin area. The weighting maps are generated by providing ranks and weights to these thematic maps. As a result, the flood hazard risk zonation map would show the total area vulnerable to hazards as very medium, low, moderate, high and very high-risk regions. By creating a risk zonation map, we will recommend measures to reduce the danger of these hazards in Deoha basin.

Sea surface salinity, sea surface temperature and oil spills in coastal zone observations are significant geophysical parameters in the Earth’s weather and climate system. These are critical for understanding dispersion and biogeochemical interaction between marine and land ecosystems. Coastal habitats such as wetlands, mangroves, seagrass beds, salt marshes, estuaries, coral reefs and sand beaches provide invaluable benefits to marine life and humans. Natural calamities such as tropical cyclones, coastal flooding and turbidity impact coastal ecosystems. Anthropogenic activities like aquaculture, infrastructure development, tourism services and ship mooring severely affect coastal habitats. The restoration and conservation of these coastal habitats are essential to achieve sustainable coastal management to protect natural resources and the global environment. Traditional methods of sampling and monitoring the marine habitats have various limitations as they are very costly and time-consuming as well as have less spatial coverage making it impossible to investigate the whole ecosystem. With the advancement of earth observation capabilities in recent decades, remote sensing technology has expanded to include a wide range of issues including biophysical parameter inversion and ecosystem process characterization. Remote sensing technology has been extensively utilized to map the coastline and it has the potential to update maps continuously. So, this study provides a comprehensive update on the remote sensing technologies that have been providing immense services to monitor and analyze coastal habitat changes.