Liquefaction hazard assessment and ground failure probability analysis in the Kathmandu Valley of Nepal

During the 2015 Gorkha Earthquake (Mw7.8), extensive soil liquefaction was observed across the Kathmandu Valley. As a densely populated urban settlement, the assessment of liquefaction potential of the valley is crucial especially for ensuring the safety of engineering structures. In this study, we use borehole data including SPT-N values of 410 locations in the valley to assess the susceptibility, hazard, and risk of liquefaction of the valley soil considering three likely-to-recur scenario earthquakes. Some of the existing and frequently used analysis and computation methods are employed for the assessments, and the obtained results are presented in the form of liquefaction hazard maps indicating factor of safety, liquefaction potential index, and probability of ground failure (PG). The assessment results reveal that most of the areas have medium to very high liquefaction susceptibility, and that the central and southern parts of the valley are more susceptible to liquefaction and are at greater risk of liquefaction damage than the northern parts. The assessment outcomes are validated with the field manifestations during the 2015 Gorkha Earthquake. The target SPT-N values (Nimproved) at potentially liquefiable areas are determined using back analysis to ascertain no liquefaction during the aforesaid three scenario earthquakes.

Using VIIRS nightlights to estimate the impact of the 2015 Nepal earthquakes

We use Visible Infrared Imaging Radiometer Suite (VIIRS) nightlight data to model the impact of the 2015 Nepal earthquakes. More specifically, the data—showing nightlight emissions—are used to examine the extent to which there is a difference in nightlight intensity between cells damaged in the earthquake versus undamaged cells based on (1) mean comparisons; and (2) fixed effect regression models akin to the double difference method. The analysis is carried out for the entire country as well as smaller regions in and around the Central area and Kathmandu, which were the hardest hit areas. Overall, the regressions find a significant and negative effect from the initial shock, followed by a positive net effect from aid and relief efforts, which is consistent with what one would expect to find. However, the mean analysis results are inconclusive and there is substantial noise in the nightlight measurements due to how the values are produced and persistent cloud cover over Nepal.

Evaluating underlying causative factors for earthquake-induced landslides and landslide susceptibility mapping in Upper Indrawati Watershed, Nepal

The main objective of this study is to understand the overall impact of earthquake in upper Indrawati Watershed, located in the high mountainous region of Nepal. Hence, we have assessed the relationship between the co-seismic landslide and underlying causative factors as well as performed landslide susceptibility mapping (LSM) to identify the landslide susceptible zone in the study area. We assessed the landslides distribution in terms of density, number, and area within 85 classes of 13 causal factors including slope, aspect, elevation, formation, land cover, distance to road and river, soil type, total curvature, seismic intensity, topographic wetness index, distance to fault, and flow accumulation. The earthquake-induced landslide is clustered in Northern region of the study area, which is dominated by steep rocky slope, forested land, and low human density. Among the causal factors, 'slope' showed positive correlation for landslide occurrence. Increase in slope in the study area also escalates the landslide distribution, with highest density at 43%, landslide number at 4.34/km2, and landslide area abundance at 2.97% in a slope class (> 50°). We used logistic regression (LR) for LSM integrating with geographic information system. LR analysis depicts that land cover is the best predictor followed by slope and distance to fault with higher positive coefficient values. LSM was validated by assessing the correctly classified landslides under susceptibility categories using area under curve (AUC) and seed cell area index (SCAI). The LSM approach showed good accuracy with respective AUC values for success rate and prediction rate of 0.843 and 0.832. Similarly, the decreasing SCAI value from very low to very high susceptibility categories advise satisfactory accuracy of the LSM approach.

Small-scale analysis to rank municipalities requiring slow-moving landslide risk mitigation measures: the case study of the Calabria region (southern Italy)

This paper proposes a three-phase method that combines multi-source (i.e. topographic, thematic, monitoring) input data in a GIS environment to rank—at small (1:250,000) scale—administrative units (e.g. municipalities) based on their exposure to slow-moving landslide risk within a selected area (e.g. a region) and, accordingly, detect those primarily requiring mitigation measures. The method is applied in the Calabria region (southern Italy) where several municipalities are widely affected by slow-moving landslides that systematically cause damage to buildings and infrastructure networks resulting in significant economic losses. The results obtained are validated based on the information gathered from previous studies carried out at large (municipal) scale. The work undertaken represents a first, fundamental step of a wider circular approach that can profitably facilitate the decision makers in addressing the issue of the slow-moving landslide risk mitigation in a sustainable way.

Slope stability analysis of a landfill subjected to leachate recirculation and aeration considering bio-hydro coupled processes

During the operation of landfills, leachate recirculation and aeration are widely applied to accelerate the waste stabilization process. However, these strategies may induce high pore pressures in waste, thereby affecting the stability of the landfill slope. Therefore, a three-dimensional numerical analysis for landfill slope stability during leachate recirculation and aeration is performed in this study using strength reduction method. The bio-hydro coupled processes of waste are simulated by a previously reported landfill coupled model programmed on the open-source platform OpenFOAM and then incorporated into the slope stability analysis. The results show that both increasing the injection pressure for leachate recirculation and maximum anaerobic biodegradation rate will reduce the factor of safety (FS) of the landfill slope maximally by 0.32 and 0.62, respectively, due to increased pore pressures. The ignorance of both waste biodegradation and gas flow will overestimate the slope stability of an anaerobic bioreactor landfill by about 20–50%, especially when the landfilled waste is easily degradable. The FS value of an aerobic bioreactor landfill slope will show a significant reduction (maximally by 53% in this study) when the aeration pressure exceeds a critical value and this value is termed as the safe aeration pressure. This study then proposes a relationship between the safe aeration pressure and the location of the air injection screen (i.e., the horizontal distance between the top of the injection screen and the slope surface) to avoid landfill slope failure during aeration. The findings of this study can provide insights for engineers to have a better understanding of the slope stability of a bioreactor landfill and to design and control the leachate recirculation and aeration systems in landfills.

Land subsidence and aquifer compaction in Montgomery County, Texas, U.S.: 2000–2020

Groundwater-withdrawal-induced land subsidence has been a big concern in Montgomery County, Texas, U.S. since the 2000s. As of 2020, approximately half of the entire county is experiencing subsidence over 5 mm/year. This study aims to investigate ongoing land subsidence in Montgomery County using groundwater-level, extensometer, and GPS datasets. According to this study, land subsidence in Montgomery County since the mid-2000s is primarily contributed by sediment compaction in the Evangeline and Jasper aquifers; the compaction of Jasper aquifer contributes approximately one-third of the land subsidence since the mid-2000s; the pre-consolidation heads of the Chicot, Evangeline, and Jasper aquifers in Montgomery County are close to each other, approximately 15–25 m below mean sea level; the virgin-compaction/head-decline ratio is approximately 1:250 in the Evangeline aquifer and 1:800 in the Jasper aquifer in central and southern Montgomery County. As of 2020, the Jasper groundwater-level altitude is approximately 20–40 m below the pre-consolidation head in the central and southern Montgomery County; the Evangeline groundwater-level altitude is about 40–60 m below the pre-consolidation head. Land subsidence will continue to occur as long as the groundwater-level altitude in either the Evangeline or the Jasper aquifer remains below the pre-consolidation head.

Seismic microzonation of a region with complex surficial geology based on different site classification approaches

A seismic microzonation study was conducted to refine the seismic hazard model for the city of Saguenay, Canada. The Quaternary geology underlying Saguenay shows complex glacial and post-glacial stratigraphy with a number of buried valleys filled with fluvioglacial and glaciomarine sediments. High impedance contrast between rock formations and surficial sediments is prone to seismic amplification. To evaluate their applicability, advantages and limitations in capturing the geological specificity of the study area, four site classification methods were applied: the current National Building Code of Canada (NBCC) and Eurocode 8, both mainly based on the average shear-wave velocity for the surficial sediments (VS,avg) and for the top 30 m (VS,30); a method based on the fundamental site period (T0); and a hybrid method based on the combination of VS,30, T0 and VS,avg. The study specifically aimed to evaluate the importance of the site classification parameters on the resulting microzonation maps. VS,30 is capable to present the geological and geotechnical site conditions, however, the results may be further improved by considering Vs,avg in shallow and T0 in thick layers of soil sediments as secondary parameters. The T0 method gives also satisfactory results with T0 showing a better correlation to Vs,30 than to Vs,avg. The versatile hybrid method may be challenging to apply in certain cases with its nine different site categories and parameters.

Report on the 19th international symposium on geo-disaster reduction/high-level academic forum on disaster mitigation and integrated risk defense on the Plateau, 12–15 July 2021, Xining, China

The joint event of 19th International Symposium on Geo-disaster Reduction (19ISGdR) and High-Level Academic Forum on Disaster Mitigation and Integrated Risk Defense on the Plateau was held on 11–15 July in Xining, Qinghai Province, China, focusing on the theme of “Geological disaster and integrated risk defense”. This event consisted of keynote lectures, invited lectures, and Youth forum, which provided a platform for scientists, industrial professionals and young scholars to share their research progress and exchange novel ideas on geo-disaster reduction in a hybrid way of offline and online. A post-symposium field trip for three days was also conducted in the joint area between Qinghai-Tibet plateau and Loess plateau.

Near real time flood inundation mapping using social media data as an information source: a case study of 2015 Chennai flood

During and just after flash flood, data regarding water extent and inundation will not be available as the traditional data collection methods fail during disasters. Rapid water extent map is vital for disaster responders to identify the areas of immediate need. Real time data available in social networking sites like Twitter and Facebook is a valuable source of information for response and recovery, if handled in an efficient way. This study proposes a method for mining social media content for generating water inundation mapping at the time of flood. The case of 2015 Chennai flood was considered as the disaster event and 95 water height points with geographical coordinates were derived from social media content posted during the flood. 72 points were within Chennai and based on these points water extent map was generated for the Chennai city by interpolation. The water depth map generated from social media information was validated using the field data. The root mean square error between the actual water height data and extracted social media data was ± 0.3 m. The challenge in using social media data is to filter the messages that have water depth related information from the ample amount of messages posted in social media during disasters. Keyword based query was developed and framed in MySQL to filter messages that have location and water height mentions. The query was validated with tweets collected during the floods that hit Mumbai city in July 2019. The validation results confirm that the query reduces the volume of tweets for manual evaluation and in future will aid in mapping the water extent in near real time at the time of floods.

Investigating the spatial correlations in univariate random fields of peak ground velocity and peak ground displacement considering anisotropy

The results of seismic risk assessment of spatially distributed infrastructure systems are significantly influenced by spatial correlation of earthquake intensity measures (IM). The assumption of isotropy is a basis for most of the existing correlation models of earthquake IMs. In this study, the isotropy assumption of intra-event residuals of peak ground velocity (PGV) and peak ground displacement (PGD) is investigated by implementing a nonparametric statistical test. Using recorded IMs of 9 earthquakes, it is concluded that there is not sufficient evidence to support the assumption of isotropy in general, and the set of intra-event residuals of PGV and PGD should be considered as the realization of anisotropic random fields. Investigations show that the anisotropy properties of intra-event residuals of PGV and PGD are related to anisotropy properties of local soil characteristics indicated by average shear wave velocity of soil profile from the 30 m depth to the surface (Vs30). Finally, predictive models are proposed based on obtained results in order to simulate the correlated univariate random fields of PGV and PGD considering anisotropy.