sr. no Author study findings 4. Bhattacharjee, S., Kumar, P., Thakur, P. K., & Gupta, K. (2021). Hydrodynamic modelling and vulnerability analysis to assess flood risk in a dense Indian city using geospatial techniques. the present study is an attempt to understand the urban flood risks in parts of Bhubaneswar City, India, based on its hydrodynamic set-up and level of urbanisation. The Storm Water Management Model is used for peak flow analysis, and the flooding extent has been assessed while taking into consideration the elevation, slope, land use/land cover (LULC) and design Storm Water Drain (SWD) infrastructure of the city. 5. Bisht, M. P. S., & Rautela, P. (2010). Disaster looms large over Joshimath. Current Science, The article focuses on the Joshimath Formation, which is a streaky and banded gniesses and schists thrusts over the rocks of Munsiari Formation along the Vaikrita Thrust in India. Joshimath is reportedly showing signs of distress due to burgeoning anthropogenic pressure and being situated in close proximity of major tectonic discontinuities. 6. Chaudhary, S. K., Srivastava, P. K., Gupta, D. K., Kumar, P., Prasad, R., Pandey, D. K., Das, A. K., & Gupta, M. (2022) Machine learning algorithms for soil moisture estimation using Sentinel-1: Model development and implementation. The present study provided the first-time comprehensive evaluation of 12 advanced statistical and machine learning (ML) algorithms for the Soil Moisture (SM) estimation from dual polarimetric Sentinel-1 radar backscatter. The ML algorithms namely support vector machine (SVM) with linear, polynomial, radial and sigmoid kernel, random forest (RF), multi-layer perceptron (MLP), radial basis function (RBF), Wang and Mendel’s (WM), subtractive clustering (SBC), adaptive neuro fuzzy inference system (ANFIS), hybrid fuzzy interference system (HyFIS), and dynamic evolving neural fuzzy inference system (DENFIS) were used.