Himalayan glaciers: combining remote sensing, field techniques and indigenous knowledge to understand spatio-temporal patterns of glacier changes and their impact on water resources

With contradictory statements about \u22disappearing Himalayan glaciers\u22 in the last few years, increasing concerns have been raised about the impact of snow and glacier changes on regional water supplies. Concomitantly, local communities in the western Himalaya report changes in glacier extents, snow cover and weather patterns. In response to perceived water scarcity, indigenous Himalayan cultures have begun a number of adaptive responses such as meltwater harvesting to construct \u22artificial\u22 glaciers. This research addresses the need for a detailed assessment of glacier and climate parameters in the Himalaya, with the goal of identifying \u22at risk\u22 glacierized areas and helping these local communities plan future water resources. The objectives of the research are threefold: 1) to review existing knowledge about glacier fluctuations and remote sensing methods for glacier mapping in the Himalaya; 3) to quantify spatio-temporal patterns of glacier changes in the eastern Himalaya in the last decades using remote sensing techniques and field measurements and 3) to quantify the role of glacier melt to streamflow using a combination of remote sensing and isotopic techniques. This thesis focuses on the monsoon-influenced eastern Himalaya (the Langtang and Khumbu regions in the Nepal Himalaya, and Sikkim in the Indian Himalaya). The research is grounded in extensive field surveys conducted from 2006 to 2010 across the Himalaya, including glacier mass balance expeditions, water sampling, ground-control point (GCP) acquisition and GPS-enabled photos. The goal of this research is to understand how topographic and climatic factors influence the rates of glacier change at various spatial scales, and how these changes re likely to affect future water resources. Multi-temporal (decadal) glacier datasets were derived from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor, Landsat ETM+, older topographic maps, declassified Corona imagery and very high-resolution QuickBird and Ikonos imagery. I used a combination of visible, near infrared and thermal multispectral data combined with texture analysis and topography for glacier mapping. The results of this research help fill a gap in the understanding of glacier patterns in the data-scarce eastern Himalaya. The results of this research are useful for assessing vulnerability of the Himalaya to water scarcity due to future glacier or climate changes

Optical remote sensing of glacier characteristics::A review with focus on the Himalaya

The increased availability of remote sensing platforms with appropriate spatial and temporal resolution, global coverage and low financial costs allows for fast, semi-automated, and cost-effective estimates of changes in glacier parameters over large areas. Remote sensing approaches allow for regular monitoring of the properties of alpine glaciers such as ice extent, terminus position, volume and surface elevation, from which glacier mass balance can be inferred. Such methods are particularly useful in remote areas with limited field-based glaciological measurements. This paper reviews advances in the use of visible and infrared remote sensing combined with field methods for estimating glacier parameters, with emphasis on volume/area changes and glacier mass balance. The focus is on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor and its applicability for monitoring Himalayan glaciers. The methods reviewed are: volumetric changes inferred from digital elevation models (DEMs), glacier delineation algorithms from multi-spectral analysis, changes in glacier area at decadal time scales, and AAR/ELA methods used to calculate yearly mass balances. The current limitations and on-going challenges in using remote sensing for mapping characteristics of mountain glaciers also discussed, specifically in the context of the Himalaya

An integrated deep learning and object-based image analysis approach for mapping debris- covered glaciers

Evaluating glacial change and the subsequent water stores in high mountains is becoming increasingly necessary, and in order to do this, models need reliable and consistent glacier data. These often come from global inventories, usually constructed from multi-temporal satellite imagery. However, there are limitations to these datasets. While clean ice can be mapped relatively easily using spectral band ratios, mapping debris-covered ice is more difficult due to the spectral similarity of supraglacial debris to the surrounding terrain. Therefore, analysts often employ manual delineation, a time-consuming and subjective approach to map debris-covered ice extents. Given the increasing prevalence of supraglacial debris in high mountain regions, such as High Mountain Asia, a systematic, objective approach is needed. The current study presents an approach for mapping debris-covered glaciers that integrates a convolutional neural network and object-based image analysis into one seamless classification workflow, applied to freely available and globally applicable Sentinel-2 multispectral, Landsat-8 thermal, Sentinel-1 interferometric coherence, and geomorphometric datasets. The approach is applied to three different domains in the Central Himalayan and the Karakoram ranges of High Mountain Asia that exhibit varying climatic regimes, topographies and debris-covered glacier characteristics. We evaluate the performance of the approach by comparison with a manually delineated glacier inventory, achieving F-score classification accuracies of 89.2%–93.7%. We also tested the performance of this approach on declassified panchromatic 1970 Corona KH-4B satellite imagery in the Manaslu region of Nepal, yielding accuracies of up to 88.4%. We find our approach to be robust, transferable to other regions, and accurate over regional (>4,000 km2) scales. Integrating object-based image analysis with deep-learning within a single workflow overcomes shortcomings associated with convolutional neural network classifications and permits a more flexible and robust approach for mapping debris-covered glaciers. The novel automated processing of panchromatic historical imagery, such as Corona KH-4B, opens the possibility of exploiting a wealth of multi-temporal data to understand past glacier changes.publishedVersio

Membrane Bioreactors Used for Treatment of Food Industry Effluents

Effluents from the food industry determine pollution problems due to high COD and BOD concentrations. Compared to other industrial divisions, food industry requires large amounts of water. In this study, MBR was based on submerged hollow fibers membranes functioning by low vacuum. Two phases of bioreactor treatment were carried out with different HRTs (2-8) and (2-24) hours. Sixteen water samples collected from the influent and the effluent of the bioreactor during the two phases. NaOCl compound was added during the backwashing process for all tests, and the same compound was added with mixed liquid for the second test at period 24 hour of aeration. The samples were tested for twelve water quality tests: temperature, Dissolved Oxygen, pH, Turbidity, Total Suspended Solids, Mixed Liquor Suspended Solids, Chemical Oxygen Demand, Biochemical Oxygen Demand, Nitrate Nitrogen, Ammonium Nitrogen, Total Phosphate, and Ortho Phosphate. The results indicated that the bioreactor system can be used efficiently to treat industrial wastewater from the food industry. The efficiency of the technology was evaluated with sodium hypochlorite addition to removing the adherent bacteria on the surface area of hollow fibers. The results showed that the bioreactor under the conditions of the second phase was excellent in removing Turbidity, TSS, COD, and BOD5 with a removal efficiency 99.96%, 89.52%, 93.56%, and 99.36% respectively, when added 82 ml of NaOCl in the bioreactor tank, and was a good removing of TP, and Ortho-P with removal efficiency 60.76% and 48.95% respectively. Otherwise, a negative effect of NaOCl on both of NO3-N and NH4-N was obtained in term of removal where the minimum removal efficiency was observed when adding 82 ml of NaOCl under the conditions of the second phase

Debris-covered glacier systems and associated glacial lake outburst flood hazards:Challenges and prospects

Glaciers respond sensitively to climate variability and change, with associated impacts on meltwater production, sea-level rise and geomorphological hazards. There is a strong societal interest in understanding the current response of all types of glacier systems to climate change and how they will continue to evolve in the context of the whole glacierized landscape. In particular, understanding the current and future behaviour of debris-covered glaciers is a 'hot topic' in glaciological research because of concerns for water resources and glacier-related hazards. The state of these glaciers is closely related to various hazardous geomorphological processes which are relatively poorly understood. Understanding the implications of debris-covered glacier evolution requires a systems approach. This includes the interplay of various factors such as local geomorphology, ice ablation patterns, debris characteristics and glacier lake growth and development. Such a broader, contextualized understanding is prerequisite to identifying and monitoring the geohazards and hydrologic implications associated with changes in the debris-covered glacier system under future climate scenarios. This paper presents a comprehensive review of current knowledge of the debris-covered glacier landsystem. Specifically, we review state-of-the-art field-based and the remote sensing-based methods for monitoring debris-covered glacier characteristics and lakes and their evolution under future climate change. We advocate a holistic process-based framework for assessing hazards associated with moraine-dammed glacio-terminal lakes that are a projected end-member state for many debris-covered glaciers under a warming climat

Recent Evolution of Glaciers in the Manaslu Region of Nepal From Satellite Imagery and UAV Data (1970–2019)

Glacierized mountain ranges such as the Himalaya comprise a variety of glacier types, including clean and debris-covered glaciers. Monitoring their behaviour over time requires an assessment of changes in area and elevation along with surface features and geomorphology. In this paper we quantify the surface evolution of glacier systems in the Manaslu region of Nepal over the last five decades using 2013/2019 multi-sensor imagery and elevation data constructed from 1970 declassified Corona imagery and 1970 declassified Corona imagery. We investigate area changes, glacier thickness, geodetic glacier mass balance and surface velocity changes at regional scales and focus on the Ponkar Glacier and Thulagi Glacier and Lake for an in-depth assessment of surface geomorphology and surface feature dynamics (ponds, vegetation and ice cliffs). The time series of surface elevation changes for the lower ablation area of Ponkar Glacier is extended using 2019 UAV-based imagery and field-based ablation rates measured over the period 2016–2019. Glaciers in the Manaslu region experienced a mean area loss of −0.26 ± 0.0001% a−1 between 1970 and 2019. The mean surface lowering was −0.20 ± 0.02 ma−1 over the period 1970 to 2013, corresponding to a regional geodetic mass balance of −0.17 ± 0.03 m w. e.a−1. Overall, debris-covered glaciers had slightly higher thinning rates compared to clean ice glaciers; lake-terminating glaciers had double thinning rates compared to land-terminating glaciers. Individual glacier mass balance was negatively controlled by glacier slope and mean glacier elevation. During the period 1970 to 2013, Ponkar Glacier had a geodetic mass balance of −0.06 ± 0.01 m w. e.a−1, inversely correlated with parts of the central trunk thickening. Between 2013 and 2019 there was a nine-fold increase in the thinning rates over the lower parts of the glacier tongue relative to the period 1970–2013. Ice-surface morphology changes between 1970 and 2019 on Ponkar Glacier include a decrease in ogives and open crevasses, an increase in ice cliffs and ponds and the expansion of the supraglacial debris and ice-surface vegetation. These changes point to reduced ice-dynamic activity and are commensurate with the observed recession and negative glacier mass balance over the last five decades.publishedVersio

Recent Evolution of Glaciers in the Manaslu Region of Nepal From Satellite Imagery and UAV Data (1970–2019)

Glacierized mountain ranges such as the Himalaya comprise a variety of glacier types, including clean and debris-covered glaciers. Monitoring their behaviour over time requires an assessment of changes in area and elevation along with surface features and geomorphology. In this paper we quantify the surface evolution of glacier systems in the Manaslu region of Nepal over the last five decades using 2013/2019 multi-sensor imagery and elevation data constructed from 1970 declassified Corona imagery and 1970 declassified Corona imagery. We investigate area changes, glacier thickness, geodetic glacier mass balance and surface velocity changes at regional scales and focus on the Ponkar Glacier and Thulagi Glacier and Lake for an in-depth assessment of surface geomorphology and surface feature dynamics (ponds, vegetation and ice cliffs). The time series of surface elevation changes for the lower ablation area of Ponkar Glacier is extended using 2019 UAV-based imagery and field-based ablation rates measured over the period 2016–2019. Glaciers in the Manaslu region experienced a mean area loss of −0.26 ± 0.0001% a−1 between 1970 and 2019. The mean surface lowering was −0.20 ± 0.02 ma−1 over the period 1970 to 2013, corresponding to a regional geodetic mass balance of −0.17 ± 0.03 m w. e.a−1. Overall, debris-covered glaciers had slightly higher thinning rates compared to clean ice glaciers; lake-terminating glaciers had double thinning rates compared to land-terminating glaciers. Individual glacier mass balance was negatively controlled by glacier slope and mean glacier elevation. During the period 1970 to 2013, Ponkar Glacier had a geodetic mass balance of −0.06 ± 0.01 m w. e.a−1, inversely correlated with parts of the central trunk thickening. Between 2013 and 2019 there was a nine-fold increase in the thinning rates over the lower parts of the glacier tongue relative to the period 1970–2013. Ice-surface morphology changes between 1970 and 2019 on Ponkar Glacier include a decrease in ogives and open crevasses, an increase in ice cliffs and ponds and the expansion of the supraglacial debris and ice-surface vegetation. These changes point to reduced ice-dynamic activity and are commensurate with the observed recession and negative glacier mass balance over the last five decades.publishedVersio