ShuttlePRO v2’s spring loaded jog shuttle wheel allows multi speed scanning both forwards and backwards along your timeline.ġ5 Programmable buttons. Attempting to scan your Timeline is a clumsy process when you’re relying on a mouse and keyboard.
Pre-configured for many of the industry’s leading audio and video editing applications, 15 customizable buttons will make working amazingly fast and precise by utilizing commonly used macros. A brief analysis of possible sources of error inĮstimation for bank erosion area has also been provided.The ShuttlePROv2 multi-media controller will maximize your audio and video editing, graphic design, or other shuttle and jog productivity with both ideal form and function. Of the study reach sustained minimal bank erosion. Section has suffered the most extensive bank erosion whereas Rajadanga-Kranti section Spatially, the Oodlabari Bazaar-Nipuchapur Tea Garden The total area of bank erosion from 1955-1970 equaled 34.77 km2, of which 12.4 km2 occurred along the left bank and 22.4 km2 along the right bank. We identified 342 erosion plots (all plots >1m2 has been considered, plots <1m2 were neglected). We have deployed overlay method for determination of areas of bank erosion and accretion by superimposing and comparing sequential changes in the position of banks in these years. Extensive field survey was also conducted to supplement the study and thereby verify the findings derived from GIS analysis. We have studied bank erosion and accretion along the Putharjhora-Kranti reaches of the Chel River, piedmont Sikkim Himalaya using SOI topographical maps of 19, and Landsat images of 1976, 1987, 1994, 2005, 20. The results of the study perceived to help execute appropriate remedial measures to extenuate the potential flash floods in the study area. The field observation and 2010 flood reports by WHO and NDMA suggest that the flash flood susceptibility modeling results by the MRA are more accurate as compared with El-Shamy's approach. El-Shamy-based modeling suggests that sub-basins B12, B14, and B16 (18% of total sub-basins) have high flood susceptibility while sub-basin B5 has the lowest. While sub-basins B4, B6, B11, B13, and B17 (59% of the total sub-basin) are moderately susceptible to flash flood risk. The MRA-based flash flood risk assessment suggests that sub-basins B1 and B2 (12% of total sub-basins) are highly susceptible to flash flooding. The analysis suggests that the Swat river watershed consists of 17 sub-basins. A total of 15 morphometric parameters have been used for flash flood modeling. The digital elevation model was utilized to delineate the watershed and drainage network using the ArcHydro tool of ArcGIS. The current study employed two widely used approaches for flash flood risk modeling, i.e., morphometric ranking approaches (MRAs) and El-Shamy's approach to analyzing their effectiveness for flash flood susceptibility modeling in Swat river watershed, district Swat, Pakistan. Flash floods triggered by thunderstorms are frequent in the high mountainous area of Hindukush Himalaya in the north of Pakistan. Globally, flash floods are the most damaging natural hazards, because of its sudden nature and difficulty in forecasting that restrains emergency responses.
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