Rapid urban growth processes give rise to impervious surfaces and are regarded as the primary cause of urban flooding or waterlogging in urban areas. The high rate of urbanization has caused waterlogging and urban flooding in many parts of Dhaka city. Therefore, the study is undertaken to quantify the changes in land use/land cover (LULC) and urban runoff extent based on the Natural Resources Conservation Service (NRCS) Curve Number (CN) during 1978–2018. The five-decadal LULC has been analyzed using three-generation Landsat time-series data considering six different classes, namely agriculture, built-up, wetland, open land, green spaces, and water bodies for the years 1978, 1988, 1998, 2007, and 2018. Significant changes in LULC for the study area from 1978–2018 are observed as 13.1%, 4.8%, and 7.8% reduction in agricultural land, green spaces, and water bodies, respectively, and a 22.1% increase in the built-up area is estimated. Within Dhaka city, 14.6%, 16.0%, and 12.3% reduction in agricultural land, green spaces, and water bodies, respectively, and a radical increase of 41.9% in built-up area are reckoned. The decadal runoff assessment has been carried out using the NRCS-CN method, considering an extreme rainfall event of 341 mm/day (13 September 2004). The catchment area under very high runoff category is observed as 159.5 km² (1978) and 318.3 km² (2018), whereas, for Dhaka city, the setting is dynamic as the area under the very high runoff category has increased from 74.24 km² (24.44%) to 174.23 km² (57.36%) in years 1978 and 2018, respectively, and, mostly, the very high runoff potential areas correspond to the dense built-up surfaces.

With advancements in computational technology, data assimilation techniques, high-resolution remote sensing, and complex climate models, numerous precipitation products are available with different spatiotemporal resolutions; however, their evaluation, especially in the Himalayan region, is unexplored. Therefore, this study attempts to assess four sources (gridded observation dataset, reanalysis, satellite, and numerical weather prediction models) of precipitation through hydrological modelling for the catastrophic 2013 floods of Uttarakhand, India. The Upper Ganga Basin located in Western Himalayas is selected as the study area consisting of Alaknanda and Bhagirathi streams in the eastern and western parts. The Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) is employed for rainfall-runoff modelling. The rainfall from IMD, ERA-5, GPM-IMERG-Final, and WRF model outputs are forced into the calibrated HEC-HMS model for assessing their performance in hydrological simulations. The correlation coefficient of IMD, ERA-5, GPM-IMERG-Final, and WRF simulations with respect to the observed flow is 0.89, 0.88, 0.55, and 0.89, respectively, whereas their corresponding Modified Kling-Gupta Efficiency (KGE) is 0.66, 0.72, 0.48, and 0.71. Flash flood prioritization of the sub-watersheds based on morphometric characteristics suggests that the Alaknanda basin is relatively more vulnerable to flash floods due to their elongated nature, highest relative relief, and high mean slope.

This study has been done using Polarimetric Synthetic Aperture Radar (SAR) data to estimate the snow physical properties (snow wetness and snow density), inManali sub-basin of Himachal Pradesh, India. The SAR data used are of Radarsat-2 (RS2) and Environmental Satellite, Advanced Synthetic Aperture Radar (ASAR). SAR-based inversion models were implemented in Mathematica and MATLAB, and have been used for finding out wet and dry snow dielectric constant, snow wetness and snow density. The SAR-based inversion models were implemented separately for fully polarimetric RS2 and dual polarimetric ASAR Alternate Polarization System datasets. Masks for forest, built area, layover and shadow were considered in estimating snow parameters. The overall accuracy in terms of R ² value comes out to be 0.86 for snow wetness and 0.84–0.72 for snow density based on the ground truth data for subset area of Manali sub-basin of Beas river up to Manali.