scholarly journals Assessment of Imja Glacier Lake outburst Flood (GLOF) Risk in Dudh Koshi River Basin using Remote Sensing Techniques

1970 ◽  
Vol 7 (1) ◽  
pp. 75-91 ◽  
Author(s):  
Kamal P Budhathoki ◽  
OR Bajracharya ◽  
BK Pokharel
Keyword(s):  
Remote Sensing ◽  
Risk Assessment ◽  
Statistical Methods ◽  
Linear Regression Analysis ◽  
Coefficient Of Determination ◽  
Lake Area ◽  
Decision Criteria ◽  
Outburst Flood ◽  
Hazard Potential ◽  
Remote Sensing Techniques

Glacier lakes are common phenomena in the Himalaya region of Nepal. Glacier lake outburst floods have repeatedly caused the death tolls and severe damage to downstream infrastructures. In Himalayas, a vital uncertainty about the glacier lake hazard potential still exists, thereby the effects of accelerating rates of glacier retreat and expansion of Glacier Lake could be the wake of recent global warming and resulting climatic changes. The paper, first describes the general different-level approach upon which the study is based. Then, in the methodological part, applicable remote sensing techniques, geographic information system (GIS) and statistical methods are presented. Observed data of lake area, volume, and depth having similar lake characteristics reported in the different literature are used to develop empirical equations by using statistical methods. The values of r2 (coefficient of determination) - obtained are very high (r2=0.939 for depth – area relationship and r2= 0.990 for volume – area relationship). The comparison of the empirical expression clearly indicated that there is more than 90% variation in the dependent variable, lake volume,as explained by the linear regressions in both cases. Area of Imja glacier lake for different years are determined from the available satellite imagery and volume of the Imja glacier lake are estimated using the expression: V = 0.094A1.453.developed from linear regression analysis of the observed data. Similarly, mean depth can be estimated by using the expression: D = 0.94A0.452. After the preparation of maps and data, a scheme of decision criteria for the evaluation of hazard potential of Imja glacier lake is established. A list of decision criteria is a documented set of factors that are used to examine and compare for evaluating the hazard potential of a glacier lake. The empirical scores are given in terms of hazard magnitude for hazard rating. Analysis of Imja glacier lake based on the empirical scoring system clearly indicated that GLOF risk of the possible outburst from Imja glacier lake is MODERATE. A systematic application of remote sensing based methods for glacier lake outburst flood risk assessment is applicable and thus recommended. Keywords: Glacier lake outburst; remote sensing; risk assessment; hazard potential; empirical parameters; climate change DOI: http://dx.doi.org/10.3126/jhm.v7i1.5618 JHM 2010; 7(1): 75-91

scholarly journals Slope Activity Analysis in the Rogun Catchment Area, Tajikistan, using Remote Sensing Techniques

2020 ◽  
Author(s):  
Nina Jones ◽  
Andrea Manconi ◽  
Alexander Strom
Keyword(s):  
Remote Sensing ◽  
Catchment Area ◽  
Surface Displacement ◽  
Tien Shan ◽  
Slope Failures ◽  
Ground Acceleration ◽  
Mountain Areas ◽  
Hazard Potential ◽  
Slope Instabilities ◽  
Remote Sensing Techniques

<p>The stability and lifetime of construction projects in mountain areas are strongly dependent on local slope activity. Hydropower projects in particular are often affected and endangered by landslide damming and flood wave generation due to slope failures, and thus extensive studies of ground surface instability are vital to assess associated hazards. The Rogun Hydropower Project HPP located in Tajikistan in the Vakhsh – Surkhob River network is currently under construction. The site lies within the seismically active Tien Shan and Pamir Mountain ranges of Central Asia and in particular the Peter the First Range. This region is marked by extreme topography, steep slopes and extensive valley networks and has experienced large and catastrophic slope failures in the past, of which a multitude have been triggered by earthquakes of magnitude M≥4. Co-seismic failures are thus common in the area and present a high geotechnical hazard; however, to date no information on active slope instabilities in its catchment area exists.</p><p>Here we present an inventory of slope instabilities in the Rogun Dam catchment area based on optical and synthetic aperture radar differential interferometry (DInSAR) remote sensing techniques. Sentinel-1 multi–temporal differential interferograms are generated for summer periods of 2016 – 2018 to detect surface displacements. Slope velocities are estimated based on a comparison between differential interferograms, while landslide types are identified based on a geomorphological classification. A likelihood analysis is developed to understand the state of activity of slopes and provide a semi-quantitative confidence thereof. The collected data is subsequently integrated to perform spatial and statistical analyses in order to perform a proximity analysis, assess a co-seismic link and evaluate the damming hazard potential to the Rogun HPP. Results show that a clear majority of detected features are located within 10 km of major faults and in zones of high peak ground acceleration, indicating a potential seismic influence or triggering. Some active slopes show an increase in surface displacement after a particular earthquake event and equally suggest a potential link. Moreover, we developed a damming hazard analysis for slopes detected as active in Sentinel-1 differential interferograms, considering the likelihood of movements, their distance to rivers and faults, as well as estimated volume and velocity per year. The results indicate that a total of 29.6 % of all features constitute a high damming hazard potential in case of catastrophic failure, with 4.5 % located within 1 km of the Rogun Dam reservoir. Although many potential sites are not directly on the slopes rising above the future reservoir, hazardous locations in the catchment upstream pose a threat due to possibility of significant outburst floods in case of the dammed lake outburst.</p>

scholarly journals Cryosphere hazards in Ladakh: the 2014 Gya glacial lake outburst flood and its implications for risk assessment

2020 ◽  
Vol 104 (3) ◽  
pp. 2071-2095 ◽  
Author(s):  
Susanne Schmidt ◽  
Marcus Nüsser ◽  
Ravi Baghel ◽  
Juliane Dame
Keyword(s):  
Remote Sensing ◽  
Risk Assessment ◽  
Integrated Approach ◽  
Glacial Lake ◽  
Glacial Lakes ◽  
Outburst Flood ◽  
Field Surveys ◽  
Depth Analysis ◽  
Glacial Lake Outburst Flood

Abstract This article attempts to reconstruct the causes and consequences of the 2014 glacial lake outburst flood (GLOF) event in Gya, Ladakh. We analyse the evolution of the Gya glacial lake using a high temporal and high spatial resolution remote sensing approach. In order to frame the case study in a larger picture, we produce a comprehensive inventory of glacial lakes for the entire Trans-Himalayan region of Ladakh. Changes in the extent and number of glacial lakes have been detected for the years 1969, 1993, 2000/02 and 2018 in order to assess the potential risk of future GLOFs in the region. The remote sensing approach was supported by field surveys between 2014 and 2019. The case study of the Gya GLOF illustrates the problem of potentially hazardous lakes being overlooked in inventories. The broader analysis of the Ladakh region and in-depth analysis of one GLOF lead us to propose an integrated approach for detecting undocumented GLOFs. This article demonstrates the necessity for using multiple methods to ensure robustness of risk assessment. The improved understanding can lead to a more accurate evaluation of exposure to cryosphere hazards and identification of alternative mechanisms and spatial patterns of GLOFs in the Himalaya.

scholarly journals SENSORIAMENTO REMOTO APLICADO A MODELAGEM DE PRODUTIVIDADE DA CULTURA DA CANA-DE-AÇÚCAR

2019 ◽  
Vol 34 (2) ◽  
pp. 263-270
Author(s):  
Victor Costa Leda ◽  
Aline Kuramoto Golçalves ◽  
Natalia da Silva Lima
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Sao Paulo ◽  
Coefficient Of Determination ◽  
Landsat 8 ◽  
São Paulo ◽  
Vegetation Indexes ◽  
Production Area ◽  
Remote Sensing Techniques ◽  
Sugarcane Productivity

SENSORIAMENTO REMOTO APLICADO A MODELAGEM DE PRODUTIVIDADE DA CULTURA DA CANA-DE-AÇÚCAR   VICTOR COSTA LEDA1, ALINE KURAMOTO GOLÇALVES2, NATALIA DA SILVA LIMA3   1 Departamento de Solos e Recursos Ambientais, Universidade Paulista “Júlio de Mesquita Filho” – Unesp, Fazenda Experimental Lageado, Avenida Universitária, nº 3780, Altos do Paraíso, CEP 18610-034, Botucatu, São Paulo, Brasil, [email protected]. 2 Departamento de Solos e Recursos Ambientais, Universidade Paulista “Júlio de Mesquita Filho” – Unesp, Fazenda Experimental Lageado, Avenida Universitária, nº 3780, Altos do Paraíso, CEP 18610-034, Botucatu, São Paulo, Brasil, [email protected]. 3 Departamento de Solos e Recursos Ambientais, Universidade Paulista “Júlio de Mesquita Filho” – Unesp, Fazenda Experimental Lageado, Avenida Universitária, nº 3780, Altos do Paraíso, CEP 18610-034, Botucatu, São Paulo, Brasil, [email protected].   RESUMO: O trabalho objetivou modelar as correlações de produtividade da cana-de-açúcar com índices de vegetação obtidos por meio de análise de imagens orbitais. Para análise, foram elaborados modelos matemáticos que expliquem a produtividade da cana-de-açúcar por meio das técnicas de geoprocessamento e sensoriamento remoto. O experimento foi realizado na área de produção comercial da Agrícola Rio Claro, parceira do grupo Zilor, que está localizada nos municípios de Lençóis Paulista e Pratânia, SP. A área ocupa aproximadamente 6000 ha, com altimetrias variando entre 600 e 700 m. Foi constatado que as modelagens foram satisfatórias, variando o coeficiente de determinação entre 0,15 a 0,97, sendo que, em períodos de colheita com elevados coeficientes de determinação, podem geralmente ser encontradas áreas de forma aglomerada, o que sugere uma menor incidência de variáveis. Enquanto áreas que apresentaram coeficientes de determinação baixos, podem ser explicadas devido a fatores como, dispersão dos talhões na área, classes de solo, precipitação e variedades da cultura, provavelmente distintos.   Palavras-chaves: índices de vegetação, Landsat 8, regressão linear múltipla.   REMOTE SENSING FOR THE SUGARCANE PRODUCTIVITY MODELING   ABSTRACT: The aim of this study was to model the sugarcane productivity correlations with vegetation indexes obtained through orbital image analysis. From the analysis was elaborated      mathematical models to explain sugarcane productivity through geoprocessing and remote sensing techniques. The experiment was carried out in the commercial production area of Agrícola Rio Claro, a partner of the Zilor group, located in the municipalities of Lençóis Paulista and Pratânia, SP, with approximately 6,000 hectares, with altimetry varying between 600 and 700 meters. It was verified that the modeling was satisfactory, varying the coefficient of determination between 0,15 and 0,97. Once      in periods with high determination coefficients, areas of agglomerated form can usually be found, which suggests a lower incidence of variables. While, in periods with low determination coefficients, can be explain due to listed factors that occurred as dispersion of the stands in the area, classes of soil, precipitation and probably different varieties of the crop.   Keywords: vegetation index, landsat8, multiple linear regression.

Remote sensing based assessment of hazards from glacier lake outbursts: a case study in the Swiss Alps

2002 ◽  
Vol 39 (2) ◽  
pp. 316-330 ◽  
Author(s):  
Christian Huggel ◽  
Andreas Kääb ◽  
Wilfried Haeberli ◽  
Philippe Teysseire ◽  
Frank Paul
Keyword(s):  
Remote Sensing ◽  
Hazard Assessment ◽  
Swiss Alps ◽  
High Mountain ◽  
Mountain Areas ◽  
Runout Distance ◽  
Hazard Potential ◽  
Empirical Relations ◽  
Scale Levels ◽  
Remote Sensing Techniques

Glacier lakes are a common phenomenon in high mountain areas. Outbursts from glacier lakes have repeatedly caused the loss of human lives as well as severe damage to local infrastructure. In several high mountain ranges around the world, a grave uncertainty about the hazard potential of glacier lakes still exists, especially with respect to the effects of accelerating rates of glacier retreat as a consequence of atmospheric warming. Area-wide detection and modeling of glacier lake hazard potentials is, therefore, a major challenge. In this study, an approach integrating three scale levels allows for the progressive focus on critical glacier lakes. Remote sensing methods for application in glacier lake hazard assessment are presented, and include channel indexing, data fusion, and change detection. Each method matches the requirements of a certain scale level. For estimating potential disaster amplitudes, assessments must be made of maximum discharge and runout distance of outbursts floods and debris flows. Existing empirical relations are evaluated and complementary ones as derived from available data are proposed. Tests with observations from a recent outburst event from a moraine-dammed lake in the Swiss Alps show the basic applicability of the proposed techniques and the usefulness of empirical relations for first hazard assessments. In particular, the observed runout distance of the debris flow resulting from the outburst does not exceed the empirically estimated maximum runout distance. A list of decision criteria and related remote sensing techniques are discussed in conclusion. Such a list is an essential tool for evaluating the hazard potential of a lake. A systematic application of remote sensing based methods for glacier lake hazard assessment is recommended.Key words: glacier lake outburst, hazard potential, remote sensing, empirical parameters.

scholarly journals Surface water extent dynamics from three periods of continuous Landsat time series; subregional differences across Argentine plains

2021 ◽  
pp. 131
Author(s):  
Vanina S. Aliaga ◽  
María C. Piccolo ◽  
Gerardo M. E. Perillo
Keyword(s):  
Remote Sensing ◽  
Shallow Lakes ◽  
Dominant Role ◽  
Positive Association ◽  
Lake Area ◽  
Surface Hydrology ◽  
Social Functions ◽  
Pampean Region ◽  
Remote Sensing Techniques ◽  
Lake Number

<p>The Pampean region in Argentina is an extensive plain characterized by abundant shallow lakes that fulfill many environmental, ecological, and social functions. This study aims to detect the multiannual lake area changes in this region during 2001-2009 using remote sensing, including lakes as small as ≥10,000 m<sup>2</sup> or 1 ha. Landsat scenes of the wet (2008-2009), normal (2006), and dry (2008-2009) seasons were obtained, and using remote sensing techniques, the number and area of shallow lakes were calculated. The spatiotemporal variation of shallow lakes was studied in different climate periods in eight singular subregions. Spatial associations between annual precipitation and lake number and area were analyzed through the development of a Geographic Information System (GIS) at a subregional scale. During the study period the total lake area in the Pampean region decreased by 5257.39 km<sup>2 </sup>(62 %), but each subregion showed different responses to climatic events. In seven of them, the differences between climate periods prove to be statistically significant (P&gt;0.01). The relationship between precipitation and lake number and area revealed the domain of positive association. We conclude that climate factors play a dominant role in lake changes across the Pampean plains. However, other factors such as origin, topographic and edaphic characteristics intensify or mitigate changes in surface hydrology.</p>

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