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Sikkim Himalaya (India)
Sikkim Himalaya (India)

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Sikkim Himalaya (India)
Sikkim Himalaya (India)

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Conferences

Conference Papers

European Geophysical Union (EGU) General Assembly 2019 at Vienna, Austria from April 07 - 12, 2019.

Title: Assessing Glacial Lake Outburst Flood Risk in the Upper Teesta River Basin of Eastern Himalaya, India.

References:

  • Quincey, D.J., Richardson, S.D., Luckman, A., Lucas, R.M., Reynolds, J.M., Hambrey, M.J., and Glasser, N.F. 2007. Early recognition of glacial lake hazards in the Himalaya using remote sensing datasets. Global and Planetary Change. 56, 137-152.

  • Watson, C.S., Carrivick, J. and Quincey, D. 2015. An improved method to present DEM uncertainty in glacial lake outburst flood propagation using stochastic simulations. J. Hydrol. 529, 1373-1389.

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4th World Congress on Disaster Management (WCDM) at the Indian Institute of Technology (IIT), Mumbai from Jan 29- Feb 01, 2019. [details]

Title: Modelling the outburst flood from Lhonak Glacial Lake of Sikkim Himalaya for GLOF risk assessment using GIS and HEC-RAS.

Abstract: ‘Himalaya’ is known as the third pole and the water tower of Asia which is the home of many natural hazards. Glacial Lake Outburst Floods (GLOFs) are among the most gigantic natural hazards posing significant threats to the livelihoods and infrastructures downstream. This study assesses the potential downstream risk from the Lhonak glacial lake by modelling the GLOF using GIS based Monte Carlo Least Cost path (MC-LCP) method and compare the model output with more stochastic two dimensional (2D) HEC-RAS model. The Lhonak Lake (27°54'45.14"N, 88°11'32.97"E) is located at an elevation of 5218m and is expanding drastically over few decades. High resolution multispectral satellite images of spatial resolution 5.8m (Resourcesat-1, LISS-IV) for two different time periods (2018 and 2011) and the ALOS PALSAR Digital Elevation Model (DEM) data of spatial resolution 12.5m, were processed in Erdas Imagine and ArcGIS software environments to derive the required information for modelling. The MC-LCP model was then executed at three different iterations (50, 100 and 500) for simulating the potential GLOF scenarios. The latest glacial lake inventory database of January 2018 revealed that it covered an area of 1.3 km2 which had increased by 0.2 km2 from 2011, probably due to an overall temperature rise across the entire Teesta River Basin, inducing further glacial melt, and held an estimated 51054972 m³ volume of water. The MC-LCP model output showed that an area of 11.9 km2 was inundated at 50 iterations, which increased to 14 km2 and 15.7 km2 at 100 and 500 iterations respectively. The model run with 100 iterations was considered for assessing GLOF risk and compared with the HEC-RAS model output. At 100 iterations, the lake had the potential to generate a 73.4 km long GLOF event downstream, which would inundate an area of 14 km2 and adversely affect 43 buildings (covering 0.02 km²), 3.2 km length of roads and 1.4 km² and 9 km² of vegetation cover and open land respectively. Whereas, the HEC-RAS flood inundation model showed that a similar GLOF event (73.7 km long) would inundate 23.8 km² of total catchment area and affect 113 buildings (0.01 km²), 14.9 km road lengths, 5.4 km² of vegetation cover and 13.8 km² of open land. Based on the cumulative score of all possible risks of a GLOF event in an outburst scenario using the GIS based MC-LCP model, this lake was considered to be highly hazardous, requiring urgent action to mitigate its high potential risk. It was also noticed that the newly developed MC-LCP method enabled an improved flow routing scenario and was capable of generating acceptable flood extents, even in a region of complex topography, enhancing its status as a significant first-pass hazard assessment tool for flood inundation mapping in the data poor Himalayan region. Such output maps can then be disseminated among local disaster management bodies for risk awareness and mitigation. In conclusion, further research is required to develop an early warning system using more stochastic models to mitigate the risks related to any GLOF events from this lake.

7th International Conference on Water and Flood Management (ICWFM) at Bangladesh University of Engineering and Technology (BUET), Dhaka from Mar 02-04, 2019. [details​]

Title: A GIS-based Monte Carlo Least Cost Path (MC-LCP) method for assessing the outburst flood risk from Phunri Glacial Lake, Sikkim Himalayas, India.

INTRODUCTION:

Glacial Lake Outburst Floods (GLOFs) are one of the most potent natural hazards in the Himalayan region, posing significant threat to the millions residing downstream from their occurrence sites along the region’s foothills and extensively threatening built infrastructure and livelihoods. This paper examines the efficacy of a GIS-based Monte Carlo Least Cost Path (MC-LCP) method for assessing the GLOF induced risks from the Phunri Lake, which is located in the source region of the Teesta River, an important right bank tributary of the River Brahmaputra. The Lake is located at 27°59'26.62"N and 88°48'55.90"E, in the eastern Indian state of Sikkim and previous studies have identified it as a potential GLOF site.

METHODOLOGY

High resolution multispectral satellite images of spatial resolution 5.8m (Resourcesat-1, LISS-IV) for two different time periods (2018 and 2011) and the ALOS PALSAR Digital Elevation Model (DEM) data of spatial resolution 12.5m, were processed in Erdas Imagine and ArcGIS software environments to derive the required information for modelling. The GIS based MC-LCP model developed by Watson et al., (2015) was then executed at three different iterations (50, 100 and 500) for simulating the potential GLOF scenarios.

RESULT AND DISCUSSION

The latest lake inventory database (of January 2018) revealed that it covered an area of 1.8 km2, which had increased by 0.1 km2 from 2011, probably due to an overall temperature rise across the entire Teesta River Basin (as substantiated by climatic datasets for the area), inducing further glacial melt, and held an estimated 76711132.9 m³ volume of water. The model runs showed that an area of 18.8 km2 was inundated at 50 iterations, which increased to 22.8 km2 and 29.3 km2 at 100 and 500 iterations, respectively. At 100 iterations, the Lake had the potential to generate an 89.1 km long GLOF event downstream, which would inundate an area of 22.8 km2 and adversely affect 205 buildings (covering 0.07 km2), 31.8 km length of roads and 1.8 km2 of vegetation cover, despite it being located 91.7 km upstream of the basin outlet.

Based on the cumulative score of all possible risks of a GLOF event in an outburst scenario, this lake was considered to be highly hazardous, requiring urgent action to mitigate its high potential risk. It was also discerned that the newly developed MC-LCP method enabled an improved flow routing scenario and was capable of generating acceptable flood extents, even in a region of complex topography, enhancing its status as a significant first-pass hazard assessment tool for flood inundation mapping in the data poor Himalayan region. The study also highlighted some drawbacks of this model, in that it lacked a physical basis for the performed simulations and showed that at 500 iterations, the flood inundation probability (confidence level) was only 25%, as the model could successfully run only up to 127 times, possibly due to its inability to process a high resolution DEM dataset.

CONCLUSION

Further research is thus required to develop a more stochastic model for generating more robustly modelled scenarios. Such output maps can then be disseminated among local disaster management bodies for risk awareness, mitigation and forecasting of GLOF hazard which can potentially save many lives and properties.

 

REFERENCES

Watson, C.S., Carrivick, J. and Quincey, D. 2015. An improved method to present DEM uncertainty in glacial lake outburst flood propagation using stochastic simulations. J. Hydrol. 529, pp. 1373-1389.

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National Seminar on Negotiating Nature, Culture and the Future at the Department of Geography, Presidency University, Kolkata, India from Feb 28- Mar 01, 2019. [details ]

Title: First-Pass GIS-based MC-LCP method for GLOF modelling in the data-poor Himalayan region.

Abstract: Glacial Lake Outburst Flood (GLOF) is considered as the most serious natural hazard in the High-Mountain Himalaya (HMH) which poses significant threats to the livelihoods and infrastructures downstream. This study assesses the suitability of using GIS-based Monte Carlo Least Cost Path (MC-LCP) method for GLOF modelling, particularly in the data-poor Himalayan region by comparing the model outputs with more stochastic physically based two dimensional (2D) HEC-RAS model. Upper Teesta River Basin in the Sikkim Himalaya was chosen for the purpose of an updated lakes inventory study using higher resolution satellite imageries, such as LISS-IV (5.8m) MSS and AlosPalsar DEM (12.5m) PAN. Further, the MC-LCP model was then executed at 100 iterations for simulating the potential GLOF scenarios and the model output was tested by comparing with HEC-RAS model results over the Lhonak Lake (EHS_UT_085). The MC-LCP model output showed that at 100 iterations, the Lhonak Lake had the potential to generate a 73.4 km long GLOF event to the downstream, which would inundate an area of 14 km2 and adversely affect 43 buildings (covering 0.02 km²), 3.2 km length of roads and 1.4 km² and 9 km² of vegetation cover and open land respectively. Whereas, the output from HEC-RAS 2D flood inundation model envisaged that a similar GLOF event (73.7 km long) would inundate 23.8 km² of the total catchment area and affect 113 buildings (0.01 km²), 14.9 km road lengths, 5.4 km² of vegetation cover and 13.8 km² of open land. The MC-LCP method enabled an improved flow routing scenario by generating acceptable flood inundation extents which were similar to the HEC-RAS model outputs for a complex topographical region and for this reason, it was considered as an effective first-pass hazard assessment tool for flood inundation mapping in the data-poor Himalayan region.

Royal Geographical Society's Annual International Conference at Cardiff University, UK from Aug 28-31, 2018. [details​]

Title: Dynamics of Land Use Change in the Middle Teesta Watershed (India) between Pre-Monsoon and Post-Monsoon Study Periods, Using Remote Sensing and GIS Technique.

Abstract: Teesta Watershed in the Eastern Himalayan region is predominant by monsoon rainfall on which most of the agricultural activities depend. The aim of this paper is to analyse the changes in Land Use between Pre and Post Monsoon period of a year in the Middle Teesta Watershed of India. Landsat 8 OLI and Cartosat 1 DEM data have been used in both the Erdas Imagine and ArcGIS environments to prepare the Land Use / Land Cover map using supervised classification with maximum likelihood (MXL) method. Based on the land use map of Pre Monsoon (March 2016) and Post-Monsoon (December 2016), a change map has been generated to understand the pattern of land use transformation in terms of changed and unchanged area. Normalised Difference Vegetation Index (NDVI) and Normalised Difference Water Index (NDWI) were used to assess the vegetation cover and distinguish the water body from non-water surface respectively.  The study area covers 168293.79 hectares (1682.94 sq. km) of land from two districts (Darjeeling and Jalpaiguri) of West Bengal State which received 720. 36 cm annual rainfall in 2016. The result shows that the vegetation covered 54.16% of the total area during pre-monsoon period which reduced by 0.76% in post-monsoon and the area of agricultural land decreased by 1.01% during the time because of a massive flood on August 2016 in the study area, whereas, built-up area increased by 1.61% because of new roads, canals and buildings constructed for flood damage control. The change map illustrates that 1713.06 hectares (17.13 sq. km) of agricultural land have been transformed to other land use classes during the study period. An accuracy assessment has also been performed using Kappa Coefficient which shows the coefficient value 1 for pre monsoon land use and 0.99 for post-monsoon land use land cover of the Middle Teesta watershed.

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