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Increasing intensity and frequency of rainfall coupled with gradual retreating of glaciers due to climate change in Himalayan region likely to increase the risk of floods. A better understanding of risk zones which are vulnerable to flood disasters can be evolved from the detailed studies on slope, geomorphology and land use/ land cover pattern. Information of these parameters is an important input for the identification of vulnerable areas. Flood risk maps provide useful information about places that may be at risk from flooding. It offers a cost-effective solution for planning, management and mitigation strategies in risky areas. Traditional methods of flood risk mapping are based on ground surveys and aerial observations, but when the phenomenon is widespread, such methods are time consuming and expensive. The possible combination of DEM and other maps of area using an overlay operation method within the Geographical Information System (GIS) platform can lead to derivation and the understanding of spatial association between various parameters which could be used to predict flood risk zones. The study area i.e. Satluj River Basin has been broadly divided into five risk zones viz., very low, low, moderate, high and very high which helped to differentiate between areas that are at risk of different intensities of flood. The very high flood risk zone covers only 3.25 % of total study area, while the very low risk zone covers 13.63 %. The area falls within the very high and high risk constitutes 9.52 % of total basin area. Domain of moderate risk covers an area of 30.66 %. But the maximum area of river basin is constituted by low risk zone i.e. 46.19 %. Identification of such zones will help in timely adopting of mitigation and adaptation measures. Preparation of flood risk zoning maps also helps in regulating indiscriminate and unplanned land use practices in risky areas.
Climate change arising from anthropogenic driven emissions of greenhouse gases has emerged as one of the most important environmental issues in the last two decades. One of the most significant potential consequences of climate change may be alteration in regional hydrological cycle and river flow regimes. Increased temperature is expected to increase the peak flows in snowfed rivers of Himalayas. The changing pattern of regional temperature on flood peaks deserves urgent and systematic attention over a basin which provides an insight view of historical trends. Lower reaches of Satluj River is selected for the present study. Testing the significance of observed trends in flood peaks has received a great attention recently, especially in connection with climate change. The data series available was 48 years (1967-2010). The records were subjected to trend analysis by using both non-parametric (Mann-Kendall test) and parametric (linear regression analysis) procedures. For better understanding of the observed trends, flood peaks were computed into standardised flood peak indices (SFPI). These standardised data series were plotted against time and the linear trends observed were represented graphically. The analysis of flood peaks at different observation stations in lower reaches of Satluj River showed a large variability in the trends and magnitudes. The trend analysis results of flood peaks and gauge heights indicate that the flood peaks at all sites i.e. Rampur, Suni and Kasol show increasing but statistically insignificant trends. The trends in gauge height at all sites are also showing increasing trend but Kasol is statistically significant at 95% confidence level. The fast melting of glaciers, incessant monsoon rainfall and the synchronisation of the discharge peaks are the main causes of river floods. The past flood peaks will help us to observe the frequency of occurrence of floods in certain region and to determine whether the flood peaks in the past have been same with that of the present or whether there is any deviation in the trend in relation to climate change. Such studies will help in designing mitigation and adaptation strategies towards extreme hydrological events.
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