EXPERIMENTAL FLOOD EARLY WARNING SYSTEM IN PARTS OF BEAS BASIN USING INTEGRATION OF WEATHER FORECASTING, HYDROLOGICAL AND HYDRODYNAMIC MODELS
| Autor: | Arpit Chouksey, V. C. Sharma, Praveen K. Thakur, Vaibhav Garg, Bhaskar R. Nikam, S. P. Aggarwal, Pankaj R. Dhote |
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| Rok vydání: | 2018 |
| Předmět: |
lcsh:Applied optics. Photonics
0106 biological sciences Warning system Flood myth lcsh:T Hydrological modelling 0208 environmental biotechnology Weather forecasting lcsh:TA1501-1820 02 engineering and technology MIKE 11 computer.software_genre Monsoon lcsh:Technology 01 natural sciences 020801 environmental engineering lcsh:TA1-2040 Weather Research and Forecasting Model Climatology Early warning system Environmental science lcsh:Engineering (General). Civil engineering (General) computer 010606 plant biology & botany |
| Zdroj: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-5, Pp 221-225 (2018) |
| ISSN: | 2194-9034 |
| DOI: | 10.5194/isprs-archives-xlii-5-221-2018 |
| Popis: | The flood early warning for any country is very important due to possible saving of human life, minimizing economic losses and devising mitigation strategies. The present work highlights the experimental flood early warning study in parts of Beas Basin, India for the monsoon season of 2015. The entire flood early warning was done in three parts. In first part, rainfall forecast for every three days in double nested Weather Research and Forecasting (WRF) domain (9 km for outer domain and 3 km for inner domain) was done for North Western Himalaya NWH using National Centres for Environmental Prediction (NCEP) Global Forecasting System (GFS) 0.25 degree data as initialization state. Rainfall forecast was validated using Indian Meteorological Department (IMD) data, the simulation accuracy of WRF in rainfall prediction above 100 mm is about 60%. Rainfall induced flood event of August 05–08, 2015 in Sone River (tributary of Beas River) Basin, near Dharampur, Mandi district of Himachal Pradesh caused very high damages. This event was picked three days in advance by WRF model based rainfall forecast. In second part, mean rainfall at sub-basin scale for hydrological model (HEC-HMS) was estimated from forecasted rainfall at every three hours in netcdf format using python script and flood hydrographs were generated. In third part, flood inundation map was generated using Hydrodynamic (HD) model (MIKE 11) with flood hydrographs as boundary condition to see the probable areas of inundation. |
| Databáze: | OpenAIRE |
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