It is essential to understand the soil characteristics of the subsurface layers for any engineering construction. In difficult terrains like hilly areas, conventional methods of investigation are expensive and difficult to conduct. It calls for nondestructive testing methods to get reliable estimates of subsurface properties. In the present study, seismic refraction tomography (SRT) technique and multichannel analysis of surface waves (MASW) methods were carried out along five selected profiles in Phuentsholing region of Bhutan Himalaya. The profile length ranges from 37 to 81.5 m, and depth of imaging down to 10 m. While the SRT data imaged the P-wave velocity (Vp) structures, the MASW imaged the shear wave velocity (Vs) structures. The P-wave images provide a fair knowledge of geological layers, while the MASW images provide S-wave velocity structures (Vs). These results are useful to estimate soil parameters, like the density, Poisson’s ratio, Young’s modulus, shear modulus, N-value and the ultimate bearing capacity. The seismic images reveal the presence of sand, sandy clay, gravels and shale layers below the selected sites. Bhutan Himalayas being seismically vulnerable, the obtained results in terms of shear wave velocity were accustomed to categorize the sites as per NEHRP site classes, and a ground response analysis was performed to determine the reliable amplification factors. From the study, it is suggested that the engineering construction is feasible at all the sites except in one site, where an indication of saturated soil is observed which is vulnerable for liquefaction, and ground needs to be improved before construction at that site.
Missing data has been a common problem and has been confronted by many researchers in the field of hydrology. Rainfall and Temperature time series data are often found missing and such missingness have huge implication on hydrological modelling, flood frequency analysis, trend analysis and dam operation schemes. Owing to the presence of missing data it hinders the performance analysis of the data and inhibits in concluding the correct inferences from the data. In this study, missing data in the rainfall and temperature has been imputed using kNN model and Tree-based model and subsequently these imputed data have been used as predictors to predict the river flow data using Artificial Neural Network (ANN). Uncertainty from kNN imputation model has been found with bootstrapping techniques, while the tree based and ANN model were assessed by Root Mean Square Error (RMSE) and Mean Absolute Error (MAE).
Landslides, floods, fires, windstorms, hailstorms, and earthquakes are major dangers in Bhutan due to historical events and their potential damage. At present, systematic collection of data is scarce and no multi-hazard zoning is reported in the existing literature for Bhutan. In addition, for proper disaster management, recognizing the existence of the hazards and identifying the vulnerable areas are the first important tasks for any multi-hazard risk studies. To fill the gap, the main objective of this study is to prepare the multi-hazard zoning and assess the multi-hazard population risk for Bhutan on seven historical hazard events. To achieve this, we first collected data on the historical events of different periods based on the data availability and created a district-level database. A total of 1224 hazard events were retrieved. We then calculated the weighted score for individual hazards based on the number of occurrences and the degree of impact through a multi-criteria decision analysis model (MCDA) using the analytic hierarchy process (AHP). The district-wise individual hazard scores are then obtained using the weighted scores. The total hazard score (THS) was aggregated and normalized to obtain the district-wise multi-hazard scores. A multi-hazard zoning map was created in the open-source software QGIS, highlighting 70% of districts with moderate to severe multi-hazard vulnerability. Considering the population distribution in each district at the local levels, the multi-hazard score is integrated and the multi-hazard population risk is mapped.
In places where surface water sources are insufficient for drinking purpose, groundwater serves as an alternative source. This report highlights all the different methods that can be used for exploration of the groundwater and to analyse this different exploration methods considering various parameters such as economy, suitability, accuracy, etc, hence providing an individual with various choices regarding the selection of particular method during the exploration of groundwater potential zone. Considering the availability of the instrument in Department of Geology and Mines (DGM) and the economic factor in our project, seismic refraction Tomography (SRT) and Geographical Information System (GIS) was used to delineate the potential zones of groundwater in Phuentsholing, Bhutan. GIS focuses on the surface features for groundwater indicator while SRT identify the subsurface layers and the depth of groundwater. The various information regarding existing bore well in the study area were also collected to validate the potential zones developed both by surface and subsurface method.
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