Nepal is considered as of the most multi hazard prone countries in the world. It is ranked 4th, 11th and 30th position in climate change, earthquake, and flood risk respectively. Monsoon in Nepal starts in June and lasts until August contributing around 80% of the annual rainfall in the country. Tens of thousands of lives and large number of properties are affected by climate induced disasters every year. On the 15th June, 2021; at onset of the year’s Monsoon, Melamchi Bazar, a city around 45Km north-east of Kathmandu, was hit by heavy flash flood claiming at least 5 deaths, and millions of economic losses including major damage to ambitious Melamchi Drinking Water Supply Project that aims to bring 170 million liters of water per day to serve population in Kathmandu valley. Temporal analysis of freely available high resolution remote sensing images and geospatial datasets can help early assessment of the damages during such disasters. SRTM DEM was used for watershed delineation of Melamchi and Indrawati rivers. Pre and Post flooding inundation area was obtained from Sentinel 2B images by calculating normalized differential water index. Infrastructure database like building, road network, bridge was extracted from open street map. Landcover were taken from living atlas of ESRI global landcover 2020. The early assessment of the damage was then performed using geospatial and geostatistical analysis of the datasets. At least 300 houses, 12 bridges, and 12km of road network was found affected by the disaster. Assessment was further carried with buffer of 25m, 50m, and 75m to get further insights. The study has proven the usefulness of the freely available geospatial data and technologies for early assessment of disaster impact. Such preliminary results and findings are helpful for rapid response and rescue operation. Howver, the freely available datasets collected through croud-sourcing are not sufficient enough and there is a huge scope of further improving the quality of data collected this way. A detailed field-based assessments would improve the result for more realistic statistics.