Evolving hazards from Himalayan glacier lake outburst floods

Author(s):  
Georg Veh ◽  
Daniel Garcia-Castellano ◽  
Oliver Korup

<p>The ongoing retreat of glaciers has formed several thousands of meltwater lakes in the Himalayas. Hundreds of these lakes have grown rapidly in area and volume in past decades, raising widely publicised concerns of an increasing hazard from sudden glacier lake outburst floods (GLOFs). Some 40 catastrophic lake outbursts have claimed thousands of fatalities and high losses in the Himalayas, mostly as a consequence of moraine-dam failures. Human and public safety along densely populated river reaches may thus be prone to changes in the lake size-distribution and the frequency of outburst floods. Yet multi-temporal inventories of Himalayan glacier lakes and associated outburst floods that we need for hazard appraisals have been collated only for selected basins with few standardised rules. Objectively tracing changes in regional GLOF hazard through time has thus remained elusive.</p><p>Here we meet this urgent demand for an improved GLOF hazard assessment. We estimate changes in the 100-year GLOF peak discharge from the late 1980s towards a scenario of completely ice-free Himalayas. We use a Random Forest model to predict land cover from seasonal Landsat images, and automatically extract glacier lakes for four time intervals. We obtain credible lake depths and volumes for each interval from a linear model learned from published bathymetric surveys. We further project possible sites for future Himalayan meltwater lakes from three published models of subglacial topography. We assume that these presently ice-covered depressions could fill completely with water though sediment and debris could decrease the storage space for future lakes. We simulate distributions of peak discharge for historic, present, and future lakes, accounting for different combinations of lake area, breach depth, and dam lithology. Most barrier types are unknown and could range from intact metamorphic bedrock to unconsolidated moraine debris. These two end members help to constrain the physically possible boundaries of GLOF peak discharges, which is supported by data from 82 natural dam breaks with known values of erodibility. To estimate the return periods of outburst floods, we used an extreme-value model to couple our simulations of peak discharge with mean annual rates of outburst floods, which remained unchanged in the Himalayas in the past three decades.</p><p>Given this constant rate of outburst floods, we report how hazard—expressed as the 100-year GLOF discharge—varied with regionally changing lake-size distributions in the past decades. We show that the southern Himalayas of Nepal and Bhutan had the largest increase of lake area, feeding notions of a rising GLOF hazard in this region. Hazard in the Western Himalaya, Karakoram, and Hindu Kush increased marginally, in line with the smallest historic abundance of glacier lakes and outburst floods. Future lake abundance and volumes may increase at least six-fold, with the largest lakes appearing in regions that have large glaciers today such as the Western Himalaya and the Karakoram. All other controls held constant, we find that hazard from these future lakes will largely rest on the erodibility of the barrier type, which needs to be acknowledged better in hazard appraisals.</p>

2019 ◽  
Vol 4 (1) ◽  
pp. 61-63
Author(s):  
Alhaji Mustapha Isa

Deforestation and climate change have become global environmental issues. The detection of forest changes in association with climate change can be successfully carried out by the use of multi-temporal remote sensing and modelling. This study undertook analysis of the past and present condition of the forest from the pattern changes of the Kota tinggi district johor state Malaysia, using landsat images of three different periods. These are thematic mapper (TM) data of 1998; enhanced thematic mapper (ETM+) image of 2008 and the operation land imager (OLI) of 2018 were collectively used. The images were geometrically and atmospherically pre-processed then classified, using maximum likelihood (M/C) algorithm to produce thematic land use/cover maps of the district. The accuracy of the classification was assessed through ground truthing and confusion matrices which revealed an accuracy of above 90% and kappa coefficient at 0.9 respectively.


2019 ◽  
Vol 11 (2) ◽  
pp. 180 ◽  
Author(s):  
Junmei Tang ◽  
Liping Di

This study integrated multi-temporal Landsat images, the Markov-Cellular Automation (CA) model, and socioeconomic factors to analyze the historical and future farmland loss in the Delhi metropolitan area, one of the most rapidly urbanized areas in the world. Accordingly, the major objectives of this study were: (1) to classify the land use and land cover (LULC) map using multi-temporal Landsat images from 1994 to 2014; (2) to develop and calibrate the Markov-CA model based on the Markov transition probabilities of LULC classes, the CA diffusion factor, and other ancillary factors; and (3) to analyze and compare the past loss of farmland and predict the future loss of farmland in relation to rapid urban expansion from the year 1995 to 2030. The predicted results indicated the high accuracy of the Markov-CA model, with an overall accuracy of 0.75 and Kappa value of 0.59. The predicted results showed that urban expansion is likely to continue to the year of 2030, though the rate of increase will slow down from the year 2020. The area of farmland has decreased and will continue to decrease at a relatively stable rate. The Markov-CA model provided a better understanding of the past, current, and future trends of LULC change, with farmland loss being a typical change in this region. The predicted result will help planners to develop suitable government policies to guide sustainable urban development in Delhi, India.


Jalawaayu ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 57-77
Author(s):  
Nabin Gurung ◽  
Sudeep Thakuri ◽  
Raju Chauhan ◽  
Narayan Prasad Ghimire ◽  
Motilal Ghimire

Shrinkage of some of the glaciers has direct impacts on the formation and expansion of glacial lakes. Sudden glacial lake outburst floods (GLOFs) are a major threat to lives and livelihoods downstream as they can cause catastrophic damage. In this study, we present the dynamics of the Lower-Barun glacier and glacial lakes and their GLOF susceptibility. We used multi temporal Landsat and Sentinel satellite imagery and extracted the lake outlines using the Normalized Difference Water Index (NDWI) with manual post-correction while the glacier outline was digitized manually. Multi-criteria decision-based method was used to assess the GLOF susceptibility. For the estimation of peak discharge and failure time, an empirical model developed by Froelich (1995) was used. The surface area of the Lower-Barun glacial lake was increased by 86% in the last 40 yrs (from 1979 to 2018), with a mean increase of 0.0432 km2/yr. The shrinkage in the glacier area is around 0.49 km2/yr and has shrunk by 8% in the last four decades. The retreat of the Lower-Barun glacier was 0.20% per year in the last four decades. The susceptibility index was 0.94, which suggests that the lake is very highly susceptible to the GLOF. The peak discharge of 5768 m3/s is produced when the breach depth is 20 m and the entire water volume is released. Likewise, in the case of 15 m breach depth, the peak discharge of 4038 m3/s is formed. Breach depth scenario of 10 m, peak discharge of 2442 m3/s is produced and in case of breach depth of 5 m produces the peak discharge of 1034 m3/s. If GLOF occurs, it can exert disastrous impacts on the livelihood and infrastructure in the downstream. So, it is necessary to examine such lakes regularly and mitigation measures to lower the GLOF susceptibility should be emphasized.


2021 ◽  
Author(s):  
Junxue Ma ◽  
Jian Chen ◽  
Zhijiu Cui ◽  
Wendy Zhou ◽  
Ruichen Chen ◽  
...  

Abstract Landslide-dammed lake outburst floods (LLOFs) may pose serious safety threats to nearby residents and their livelihoods, as well as cause major damages to the downstream areas in mountainous regions. This study presents the Diexi ancient landslide-dammed lake (DALL) in the Upper Minjiang River at the eastern margins of the Tibetan Plateau, which was known to an estimated previous maximal lake area of 1.1 × 107 m2 and an impounded volume of 2.9 × 109 m3. Then, at approximately 27 ka BP, the ancient landslide dam failed and catastrophic LLOFs occurred. It was determined that the peak discharge of the Diexi ancient LLOFs could be reconstructed using regression, parametric, and boulder competence approaches. The reconstructed maximum peak discharge might be 72,232.66 m3/s, with an average velocity of 17.23 m/s, indicating that the Diexi ancient LLOFs were the most gigantic outburst floods to occur in the Upper Minjiang River Valley since the Late Pleistocene Period. The differences in the widths and slopes within the former and the later reaches of the dam indicated that the geomorphic influences on the river channel resulting from the DALL and its LLOFs have existed for tens of thousands of years. These findings were of major significance in deepening the understanding of the existence and disappearances of important river-knickpoints on a time scale of tens of thousands of years.


2021 ◽  
Vol 13 (13) ◽  
pp. 2570
Author(s):  
Teng Li ◽  
Bozhong Zhu ◽  
Fei Cao ◽  
Hao Sun ◽  
Xianqiang He ◽  
...  

Based on characteristics analysis about remote sensing reflectance, the Secchi Disk Depth (SDD) in the Qiandao Lake was predicted from the Landsat8/OLI data, and its changing rates on a pixel-by-pixel scale were obtained from satellite remote sensing for the first time. Using 114 matchups data pairs during 2013–2019, the SDD satellite algorithms suitable for the Qiandao Lake were obtained through both the linear regression and machine learning (Support Vector Machine) methods, with remote sensing reflectance (Rrs) at different OLI bands and the ratio of Rrs (Band3) to Rrs (Band2) as model input parameters. Compared with field observations, the mean absolute relative difference and root mean squared error of satellite-derived SDD were within 20% and 1.3 m, respectively. Satellite-derived results revealed that SDD in the Qiandao Lake was high in boreal spring and winter, and reached the lowest in boreal summer, with the annual mean value of about 5 m. Spatially, high SDD was mainly concentrated in the southeast lake area (up to 13 m) close to the dam. The edge and runoff area of the lake were less transparent, with an SDD of less than 4 m. In the past decade (2013–2020), 5.32% of Qiandao Lake witnessed significant (p < 0.05) transparency change: 4.42% raised with a rate of about 0.11 m/year and 0.9% varied with a rate of about −0.09 m/year. Besides, the findings presented here suggested that heavy rainfall would have a continuous impact on the Qiandao Lake SDD. Our research could promote the applications of land observation satellites (such as the Landsat series) in water environment monitoring in inland reservoirs.


2021 ◽  
Vol 13 (2) ◽  
pp. 205
Author(s):  
Philipp Hochreuther ◽  
Niklas Neckel ◽  
Nathalie Reimann ◽  
Angelika Humbert ◽  
Matthias Braun

The usability of multispectral satellite data for detecting and monitoring supraglacial meltwater ponds has been demonstrated for western Greenland. For a multitemporal analysis of large regions or entire Greenland, largely automated processing routines are required. Here, we present a sequence of algorithms that allow for an automated Sentinel-2 data search, download, processing, and generation of a consistent and dense melt pond area time-series based on open-source software. We test our approach for a ~82,000 km2 area at the 79°N Glacier (Nioghalvfjerdsbrae) in northeast Greenland, covering the years 2016, 2017, 2018 and 2019. Our lake detection is based on the ratio of the blue and red visible bands using a minimum threshold. To remove false classification caused by the similar spectra of shadow and water on ice, we implement a shadow model to mask out topographically induced artifacts. We identified 880 individual lakes, traceable over 479 time-steps throughout 2016–2019, with an average size of 64,212 m2. Of the four years, 2019 had the most extensive lake area coverage with a maximum of 333 km2 and a maximum individual lake size of 30 km2. With 1.5 days average observation interval, our time-series allows for a comparison with climate data of daily resolution, enabling a better understanding of short-term climate-glacier feedbacks.


2016 ◽  
Author(s):  
Wang Shijin

Abstract. The paper analyzed synthetically spatial distribution and evolution status of moraine-dammed lakes in the Nyainqentanglha Mountain, revealed risk degree of county-based potential dangerous glacial lakes (PDGLs) outburst floods disaster by combining PDGLs outburst hazard, regional exposure, vulnerability of exposed elements and adaptation capability and using the Analytic Hierarchy Process and Weighted Comprehensive Method. The results indicate that 132 moraine-dammed lakes (> 0.02 km2) with a total area of 38.235 km2 were detected in the Nyainqentanglha in the 2010s, the lake number decreased only by 5 %, whereas total lake area expanded by 22.72 %, in which 54 lakes with a total area of 17.53 km2 are identified as PDGLs and total area increased by 144.31 %, higher significantly than 4.06 % of non-PDGLs. The zones at very high and high integrated risk of glacial lakes outburst floods (GLOFs) disaster are concentrated in the eastern Nyainqentanglha, whereas low and very low integrated risk zones are located mainly in the western Nyainqentanglha. On the county scale, Nagque and Nyingchi have the lowest hazard risk, Banbar has the highest hazard and vulnerability risk, Sog and Lhorong have the highest exposure risk. In contrast, Biru and Jiali have the highest vulnerability risk, while Gongbo'gyamda and Damxung have lowest adaptation capacity. The regionalization results for GLOF disaster risk in the study are consistent with the distribution of historical disaster sites across the Nyainqentanglha.


2017 ◽  
Vol 145 (11) ◽  
pp. 4501-4519 ◽  
Author(s):  
John T. Allen ◽  
Michael K. Tippett ◽  
Yasir Kaheil ◽  
Adam H. Sobel ◽  
Chiara Lepore ◽  
...  

The spatial distribution of return intervals for U.S. hail size is explored within the framework of extreme value theory using observations from the period 1979–2013. The center of the continent has experienced hail in excess of 5 in. (127 mm) during the past 30 yr, whereas hail in excess of 1 in. (25 mm) is more common in other regions, including the West Coast. Observed hail sizes show heavy quantization toward fixed-diameter reference objects and are influenced by spatial and temporal biases similar to those noted for hail occurrence. Recorded hail diameters have been growing in recent decades because of improved reporting. These data limitations motivate exploration of extreme value distributions to represent the return periods for various hail diameters. The parameters of a Gumbel distribution are fit to dithered observed annual maxima on a national 1° × 1° grid at locations with sufficient records. Gridded and kernel-smoothed return sizes and quantiles up to the 200-yr return period are determined for the fitted Gumbel distribution. These results are used to illustrate return levels for hail greater than a given size for at least one location within each 1° × 1° grid box for the United States.


2017 ◽  
Vol 8 (2) ◽  
pp. 288-292 ◽  
Author(s):  
R. Casa ◽  
F. Pelosi ◽  
S. Pascucci ◽  
F. Fontana ◽  
F. Castaldi ◽  
...  

Nitrogen fertilization of silage maize in Central Italy is typically carried out with two applications at early stages of crop development: 2nd (V2) and 6th (V6) leaf respectively. In such conditions, the crop has not yet fully covered the soil and proximal or remote sensing of the canopy is hindered by the strong soil background signal. There is thus great interest in rapid and inexpensive approaches to N fertilization prescription. Therefore, an indirect method for inferring information on yield potential and soil variability, through a field-based clustering of multi-temporal satellite data, has been developed using archive Landsat images to identify temporally constant patterns. This method is potentially useful for the creation of prescription maps. The usefulness of the method was evaluated during an N fertilisation field trial in Maccarese (Central Italy), in 2016. At the V2 stage, both uniform and variable rate applications were performed and compared. A pseudo-cross variogram and a standardized ordinary co-kriging methodology was used to highlight spatially variable significant differences among the treatments.


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