38. Using CARTODEM Data for Dam Break Flood Hazard Mapping in a Hilly Terrain

With the development of computation capability and readily available computer programs, flow inundation modelling-based flood hazard mapping is widely practiced. For such analysis, digital elevation models (DEMs) are necessary to define the river topography and terrain variability. Fine resolution DEMs are also used to extract the river cross sections that are subsequently utilized in flow model setup. But the availability of fine resolution DEM is the major constrain, especially in hilly and inaccessible terrains, etc. The satellite-based DEMs like SRTM, ASTER, CARTODEM, etc. are the alternative sources in such cases and have been used in several flow modelling studies. In this paper, dam break analysis of a small dam located in Uttarakhand in Kumaon Lesser Himalayas is reported. The various scenarios of flooding due to dam breach of the concrete face rockfill dam on Dhauliganga, a tributary of Kali river by routing flood waves in the downstream reach to compute flood inundation, time of occurrences, etc. are discussed. The hydraulic model for the river reach of about 30 km is developed in MIKE 11 using surveyed river cross sections and 10 m resolution digital elevation model of the study area generated using CartoDEM provided by NRSC, Hyderabad. Three cases of flooding are simulated: (i) flooding due to PMF in the river causing dam break condition; (ii) flooding due to PMF without dam break; and (iii) sunny day failure condition (dam failure with nominal inflow when the reservoir is full). It is observed that the time of travel of the peak flood from the dam site to the major settlement area at Dharchula, about 20 km downstream location, is 42 min for the critical case of dam failure. The maximum flood level and time of travel of the peak flood at the important locations are estimated. However, no settlement/village areas are under inundation for these conditions. The extent of flood hazards for various cases of flooding is estimated by superimposing the inundation map over Google Earth for a detailed description of inundated areas and affected infrastructures.