Deo Raj Gurung

Geomorphic and geologic controls of geohazards induced by Nepal’s 2015 Gorkha earthquake

Nepals quake-driven landslide hazards Large earthquakes can trigger dangerous landslides across a wide geographic region. The 2015 Mw 7.8 Gorhka earthquake near Kathmandu, Nepal, was no exception. Kargal et al. used remote observations to compile a massive catalog of triggered debris flows. The satellite-based observations came from a rapid response team assisting the disaster relief effort. Schwanghart et al. show that Kathmandu escaped the historically catastrophic landslides associated with earthquakes in 1100, 1255, and 1344 C.E. near Nepals second largest city, Pokhara. These two studies underscore the importance of determining slope stability in mountainous, earthquake-prone regions. Science, this issue p. 10.1126/science.aac8353; see also p. 147 Satellite imaging isolated hazard potential for earthquake-triggered landslides after the 2015 Gorkha earthquake in Nepal. INTRODUCTION On 25 April 2015, the Gorkha earthquake [magnitude (M) 7.8] struck Nepal, followed by five aftershocks of ≥M 6.0 until 10 June 2015. The earthquakes killed ~9000 people and severely damaged a 550 by 200 km region in Nepal and neighboring countries. Some mountain villages were completely destroyed, and the remote locations, blocked roads, and landslide-dammed rivers prevented ground access to many areas. RATIONALE Our “Volunteer Group” of scientists from nine nations, motivated by humanitarian needs, focused on satellite-based systematic mapping and analysis of earthquake-induced geohazards. We provided information to relief and recovery officials as emergency operations were occurring, while supported by one of the largest-ever NASA-led campaigns of responsive satellite data acquisitions over a vast disaster zone. Our analysis of geohazards distribution allowed evaluation of geomorphic, tectonic, and lithologic controls on earthquake-induced landsliding, process mechanisms, and hazard process chains, particularly where they affected local populations. RESULTS We mapped 4312 coseismic and postseismic landslides. Their distribution shows positive associations with slope and shaking intensity. The highest areal densities of landslides are developed on the downdropped northern tectonic block, which is likely explained by momentary reduction of the normal stress along planes of weakness during downward acceleration. The two largest shocks bracket the high-density landslide distribution, the largest magnitudes of the surface displacement field, and highest peak ground accelerations (PGAs). Landslides are heavily concentrated where PGA was >0.6g and slope is >30°. Additional controls on landslide occurrence are indicated by their clustering near earthquake epicenters and within specific lithologic units. The product of PGA and the sine of surface slope (defined as the landslide susceptibility index) is a good indicator of where most landslides occurred. A tail of the statistical distributions of landslides extends to low values of the landslide susceptibility index. Slight earthquake shaking affected vulnerable materials hanging on steep slopes—such as ice, snow, and glacial debris—and moderate to strong shaking affected poorly consolidated sediments deposited in low-sloping river valleys, which were already poised near a failure threshold. In the remote Langtang Valley, some of the most concentrated destruction and losses of life outside the Kathmandu Valley were directly due to earthquake-induced landslides and air blasts. Complex seismic wave interactions and wave focusing may have caused ridgetop shattering and landslides near Langtang but reduced direct shaking damage on valley floors and at glacial lakes. CONCLUSION The Gorkha earthquake took a tremendous, tragic toll on human lives and culture. However, fortunately no damaging earthquake-caused glacier lake outburst floods were observed by our satellite analysis. The total number of landslides was far fewer than those generated by comparable earthquakes elsewhere, probably because of a lack of surface ruptures, the concentration of deformation along the subsurface thrust fault at 10 to 15 km depth, and the regional dominance of competent high-grade metamorphic and intrusive igneous rock types. Landslide distribution and effects of a huge landslide. (A) Landslides (purple dots) are concentrated mostly north of the tectonic hinge-line. Also shown are the epicenters of the main shock and largest aftershock. Displacements are from the JAXA ALOS-2 ScanSAR interferogram (21 Feb and 2 May 2015 acquisitions). (B and C) Before-and-after photographs obtained by D. Breashears in Langtang Valley showing complete destruction of a large part of Langtang village by a huge landslide. The Gorkha earthquake (magnitude 7.8) on 25 April 2015 and later aftershocks struck South Asia, killing ~9000 people and damaging a large region. Supported by a large campaign of responsive satellite data acquisitions over the earthquake disaster zone, our team undertook a satellite image survey of the earthquakes’ induced geohazards in Nepal and China and an assessment of the geomorphic, tectonic, and lithologic controls on quake-induced landslides. Timely analysis and communication aided response and recovery and informed decision-makers. We mapped 4312 coseismic and postseismic landslides. We also surveyed 491 glacier lakes for earthquake damage but found only nine landslide-impacted lakes and no visible satellite evidence of outbursts. Landslide densities correlate with slope, peak ground acceleration, surface downdrop, and specific metamorphic lithologies and large plutonic intrusions.

Determination of snow cover from MODIS data for the Tibetan Plateau region

This paper addresses a snow-mapping algorithm for the Tibetan Plateau region using Moderate Resolution Imaging Spectroradiometer (MODIS) data. Accounting for the effects of the atmosphere and terrain on the satellite observations at the top of the atmosphere (TOA), particularly in the rugged Tibetan Plateau region, the surface reflectance is retrieved from the TOA reflectance after atmospheric and topographic corrections. To reduce the effect of the misclassification of snow and cloud cover, a normalized difference cloud index (NDCI) model is proposed to discriminate snow/cloud pixels, separate from the MODIS cloud mask product MOD35. The MODIS land surface temperature (LST) product MOD11_L2 is also used to ensure better accuracy of the snow cover classification. Comparisons of the resulting snow cover with those estimated from high spatial-resolution Landsat ETM+ data and obtained from MODIS snow cover product MOD10_L2 for the Mount Everest region for different seasons in 2002, show that the MODIS snow cover product MOD10_L2 overestimates the snow cover with relative error ranging from 20.1% to 55.7%, whereas the proposed algorithm estimates the snow cover more accurately with relative error varying from 0.3% to 9.8%. Comparisons of the snow cover estimated with the proposed algorithm and those obtained from MOD10_L2 product with in situ measurements over the Hindu Kush-Himalayan (HKH) region for December 2003 and January 2004 (the snowy seasons) indicate that the proposed algorithm can map the snow cover more accurately with greater than 90% agreement

Abe Barek landslide and landslide susceptibility assessment in Badakhshan Province, Afghanistan

Landslide is one of the most widely distributed mass movements in mountainous areas. With its wide spreading, abrupt, and seasonal characteristics, landslide always causes huge risks towards transportation, human settlements, industrial and mining plants, water resources facilities, and hydropower stations. Abe Barek landslide, which happened in the morning of May 2, 2014, in Ago District, Badakhshan Province, Afghanistan, buried 86 houses and took the lives of almost 2700 people. Many factors triggered the occurrence of this disaster. Firstly, the landslide-impacted area has a complex geologic structure that bears concentrated faults with mountain slopes covered by thick loess. Secondly, at the time of landslide, a continuous rainfall had deepened the level of moisture in the loess layer, which made the loess mass heavier and changed the soil body’s mechanical properties. Thirdly, a similar landslide once happened on the same slope, which destroyed the land cover and transformed the topology of the slope. In addition, farming and irrigating activities may have also affected the stability of loess mass in this area. Upon an initial examination of landslide distribution in Badakhshan Province by using high-resolution remote sensing images from Google Earth, a total number of 609 landslide sites were identified in this area, and a landslide susceptibility assessment was completed by utilizing weight-of-evidence method. Several suggestions on landslide risk reduction in this remote mountainous area are proposed at the end of this paper.

Characteristics of landslide in Koshi River Basin, Central Himalaya

Koshi River basin, which lies in the Central Himalayas with an area of 71,500 km2, is an important trans-boundary river basin shared by China, Nepal and India. Yet, landslide-prone areas are all located in China and Nepal, imposing alarming risks of widespread damages to property and loss of human life in both countries. Against this backdrop, this research, by utilizing remote sensing images and topographic maps, has identified a total number of 6877 landslides for the past 23 years and further examined their distribution, characteristics and causes. Analysis shows that the two-step topography in the Himalayan region has a considerable effect on the distribution of landslides in this area. Dense distribution of landslides falls into two regions: the Lesser Himalaya (mostly small and medium size landslides in east-west direction) and the Transition Belt (mostly large and medium size landslides along the river in north-south direction). Landslides decrease against the elevation while the southern slopes of the Himalayas have more landslides than its northern side. Change analysis was carried out by comparing landslide distribution data of 1992, 2010 and 2015 in the Koshi River basin. The rainfall-induced landslides, usually small and shallow and occurring more frequently in regions with an elevation lower than 1000m, are common in the south and south-east slopes due to heavy precipitation in the region, and are more prone to the slope gradient of 20°~30°. Most of them are distributed in Proterozoic stratum (Pt3ε, Pt3 and Pt2-3) and Quaternary stratum. While for earthquake-induced landslides, they are more prone to higher elevations (2000~3000 m) and steeper slopes (40°~50°).

Lemthang Tsho glacial Lake outburst flood (GLOF) in Bhutan: cause and impact

BackgroundThe Hindu Kush Himalayan (HKH) region being seismically active and sensitive to climate change is prone to glacial lake outburst flood (GLOF). The Lemthang Tsho GLOF breached in the evening of 28 July 2015 innorth-western Bhutan is reminds of the looming threat, and stresses the need to have good risk management plan. The need to understand the physical processes in generating GLOF to is therefore imperative in order to effectively manage the associated risk. The paper therefore assesses the cause and impact of the Lemthang Tsho GLOF event using field and remote sensing data.ResultsThe collapse of near vertical wall of supraglacial lake triggered by 2 days of incessant rainfall, opened up the englacial conduit resulting in emptying of interconnected supraglacial lakes into Lemthang Tsho. The5.1 magnitude earthquake epicentered 187 km to southeast in the Indian state of Assam in the morning (7:10 am Bhutan Standard Time) of the same day is unlikely to have played any role in triggering the event. The estimated volume of water unleased is 0.37 million m3, with peak discharge estimated to be ranging from 1253 to 1562 m3/s, and velocity of 7.14–7.57 m/s. The impact was minimal and confined up to 30 km downstream from the lake. The flood took lives of 4 horses, washed away 4 timber cantilever bridges, 148 pieces of timber, damaged 1 acre of land, and washed away 1 km of trail. The team also monitored 3 out of 25 identified critical glacial lakes and downgraded the risk of all 3 critical glacial lakes based on the finding. This brings the number of critical glacial lakes in Bhutan to 22.ConclusionThe threat of GLOF still looms large in the Himalaya, particularly in view of impact of climate change and frequent seismic activities. There is a need for good risk management practices which starts fromidentification of critical glacial lakes, to prioritize in-depth investigation. As the present list of critical glacial lakes are largely based on inventory done over a decade based on topographic maps some of which datedback to 1960s, we need to revisit the critical glacial lakes and assess the risk considering recent changes. The new assessment needs to consider supraglacial lakes as one of the criteria in evaluating the GLOF risk, as highlighted by the Lemthang Tsho GLOF.

Reform Earth Observation Science and Applications to Transform Hindu Kush Himalayan Livelihoods—Services-Based Vision 2030

The Hindu Kush Himalayas (HKH) region with 210 million people living in the region poses significant scientific and technological challenges for livelihood improvement due to subsistence economy, livelihood insecurity, poverty, and climate change. The inaccessibility and complex mountain environmental settings carved special niche for Earth Observation (EO) science and significant contributions were made in the food security and disaster risk reduction sectors. The differentiated capacities of users to develop and use EO capabilities, challenges in outreaching the EO products to last mile users call for innovative ways of packaging EO products into actionable knowledge and services. This calls for great degree of reformation on EO community to tailor-made region specific EO sensors and models, mechanisms of synergizing EO knowledge with local traditional systems in addressing multiscale, and integrated end-to-end solutions. The paper addresses prospects and challenges of 2015–2030 to achieve success in three critical livelihood support themes viz food security, floods, and forest-based carbon mitigation. Different improvements in EO sensor and models to extend less than a day, all-weather imaging, improved hydro-meteorological forecasts, vegetation stress, and community carbon monitoring models are identified as priority areas of improvement. We envisage and propose mechanisms on how these EO advances could amalgamate into Essential HKH Variables (EHVs) on the lines of global Essential Climate Variables (ECVs) to provide turnkey-based actionable knowledge and services through global and regional cooperation. The complex web of users and orienting them toward adoption of EO services through multi-tier awareness, expertise development, policy advocacy, and institutionalization is also discussed. The paper concludes that the EO community needs to reform significantly in blending their science and applications with user-driven, need-based domains to provide better societal services and HKH livelihood transformation.

How size and trigger matter: analyzing rainfall- and earthquake-triggered landslide inventories and their causal relation in the Koshi River basin, Central Himalaya

Inventories of landslides caused by different triggering mechanisms, such as earthquakes, extreme rainfall events or anthropogenic activities, may show different characteristics in terms of distribution, contributing factors and frequency–area relationships. The aim of this research is to study such differences in landslide inventories and the effect they have on landslide susceptibility assessment. The study area is the watershed of the transboundary Koshi River in the central Himalaya, shared by China, Nepal and India. Detailed landslide inventories were generated based on visual interpretation of remote-sensing images and field investigation for different time periods and triggering mechanisms. Maps and images from the period 1992 to 2015 were used to map 5858 rainfall-triggered landslides, and after the 2015 Gorkha earthquake, an additional 14 127 coseismic landslides were mapped. A set of topographic, geological and land cover factors were employed to analyze their correlation with different types and sizes of landslides. The frequency–area distributions of rainfalland earthquake-triggered landslides (ETLs) have a similar cutoff value and power-law exponent, although the ETLs might have a larger frequency of a smaller one. In addition, topographic factors varied considerably for the two triggering events, with both altitude and slope angle showing significantly different patterns for rainfall-triggered and earthquake-triggered landslides. Landslides were classified into two size groups, in combination with the main triggering mechanism (rainfallor earthquake-triggered). Susceptibility maps for different combinations of landslide size and triggering mechanism were generated using logistic regression analysis. The different triggers and sizes of landslide data were used to validate the models. The results showed that susceptible areas for smalland large-size rainfalland earthquake-triggered landslides differed substantially.

Landslides Inventory and Trans-boundary Risk Management in Koshi River Basin, Himalaya

Koshi River basin, which is a trans-boundary basin shared by China, Nepal and India, covers an area of about 87,500 km2. This study investigated the landslide locations in this basin by means of interpreting remote sensing images as well as field work. We could map 5653 landslides that are located within China and Nepal. Landslide caused different kinds of disasters including damage to public and private properties. The most common hazard pattern is supplying sources to debris flow, accounting for 48.38% of the number of landslides. The following patterns are soil erosion and blocking river, accounting for 25.18 and 18.98%, respectively. Cascading hazards related to landslides are very common in Koshi River basin. Three main cascading events were found there: landslide-dammed lake-outburst flood, GLOF-landslide and landslide-debris flow. These features make the disasters extend temporally and spatially. A framework for risk management in trans-boundary river basin was proposed to develop cooperation at academic and administrative levels among the involved countries.

Improvement of MODIS snow cover algorithm for the Hindu Kush-Himalayan region

This work aimed to refine the Moderate Resolution Imaging Spectroradiometer (MODIS) based snow cover algorithm for the Hindu Kush-Himalayan (HKH) region. Taking into account the effect of the atmosphere and terrain on the satellite observations at the top of the atmosphere (TOA), particularly in heavily rugged Tibet plateau region, the surface reflectances were retrieved from the TOA reflectances after atmospheric and topographic corrections. To reduce the effects of the snow/cloud confusion, a normalized difference cloud index (NDCI) model was proposed to discriminate snow/cloud pixels, apart from use of the MODIS cloud mask product MOD35. Furthermore, MODIS land surface temperature (LST) product MOD11_L2 have been used to ensure better accuracy of the snow cover pixels. Comparisons of the resultant MODIS snow cover with those obtained respectively from high resolution Landsat ETM+ data and the MODIS snow cover product MOD10_L2 for the Mount Everest region at different seasons, showed overestimation of the MOD10_L2 snow cover with the differences of 50%, whereas the improved algorithm can estimate the snow cover for HKH region more precisely with absolute accuracy of 90%.