Hydroclimatic influence on particle size distribution of suspended sediments evacuated from debris-covered Chorabari Glacier, upper Mandakini catchment, central Himalaya

Kumar, Amit; Gokhale, Anupam Anand; Shukla, Tanuj; Dobhal, D. P.

doi:10.1016/j.geomorph.2016.04.019

Cited by 32 publications

(28 citation statements)

References 67 publications

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“…This work has gained support from previous field-based studies conducted in the Chorabari glacier valley (i.e. Bhambri et al, 2016;Dobhal et al, 2013a, b;Karakoti et al, 2017;Kumar et al, 2016;Mehta et al, 2012Mehta et al, , 2014Mehta et al, , 2017Shukla et al, 2017) and strengthen the outcome of Shukla et al (2020). On the bases of lake chemistry and variability of environmental magnetic properties, Shukla et al (2020) has been subdivided the ~8 m lake profile into three section, that is, (1) section I ( 260 BCE and 270 CE), (2) section II (900 and 1260 CE) and (3) section III (~1370 and 1720 CE).…”

Section: Introductionsupporting

confidence: 63%

“…We would like to highlight the fact that the approach of Shukla et al (2020) was based on magnetic mineralogy, grain size and geochemistry. The data were correlated (except magnetic proxy data) with presentday glacial sediment response patterns at the Chorabari glacier (Kumar et al, 2016). We reasonably approached the proxy based on our long experiences in present and past studies conducted in the Chorabari valley (i.e.…”

Section: Interpretationsmentioning

confidence: 65%

“…High altitude glacial environments are characterized by high rates of erosion and sediment transport derived from glacial/subglacial substrates (Haldorsen, 1981;Haritashya et al, 2010;Kirkbride 1995;Kumar et al, 2016;Owen et al, 2003). Processes responsible for sediment production and transfer in high altitude debriscovered glaciers have been extensively studied and the uniqueness of glacial sediment production is adequately understood (Evans et al, 2006;Hammer and Smith, 1983;Haritashya et al, 2010;Kumar et al, 2016;Owen et al, 2003). Valley-scale climatic and geological controls on sediment evacuation pattern have also been presented and used to interpret sediment records (Cook and Swift, 2012;Evans et al, 2006;Menzies et al, 2006;Wulf et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

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Misinterpreting proxy data for paleoclimate signals: A reply to Srivastava and Jovane, 2020

et al. 2020

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Srivastava and Jovane (2020) have made several comments on our assessment of proxy data and challenged the outcome of Shukla et al. (2020) based mainly on interpretation of environmental magnetic parameters. We respond to their criticisms and re-evaluate our paper, remove ambiguities and validate our conclusions through additional proxies (grain-size and geochemistry). We welcome their comments and do not entirely rule out their interpretation for magnetic mineralogy. We highlight the importance of proxy validation for high-energy environments like Chorabari lake. However, single proxy data correlation is likely to produce biased results with no relevant meaning. The objective of our study was to understand complexities in the glacial-climate system by reconstructing late-Holocene climate variations using the glacial lake sediment records from the Mandakini River Basin, Central Himalaya, India. We presented the complexities in Shukla et al. (2020), and this was also highlighted by Srivastava and Jovane (2020). In response, we provide additional justification of proxy response and substantiate our results with present-day estimates from the Chorabari glacier valley. We disagree with the thesis put forward by Srivastava and Jovane (2020) in their conclusion as they overemphasize the interpretation of a single proxy. We maintain that the investigation of present-day glacial settings is an important precursor of paleoclimatic data interpretation and that this supports our conclusions. We will try to incorporate the important suggestions of Srivastava and Jovne (2020) relating to the interpretation of magnetic data in future work.

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Section: Introductionsupporting

confidence: 63%

Section: Interpretationsmentioning

confidence: 65%

Section: Introductionmentioning

confidence: 99%

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Misinterpreting proxy data for paleoclimate signals: A reply to Srivastava and Jovane, 2020

et al. 2020

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“…Therefore, the main source of ice-melt during September and October could be from the subglacial ice-melt due to pressure melting [32]. It has been observed that by the end of September the supraglacial melting reduced substantially, and a major contribution to the stream melt water were supplied by the melting of subglacial ice [61]. A three-component hydrograph separation of the Sutri Dhaka stream revealed that the contribution of ice-melt, snowpack and fresh snow are 65 ± 14, 15 ± 9 and 20 ± 5%, respectively ( Figure 10).…”

Section: Hydrograph Separationmentioning

confidence: 99%

Moisture Sources for Precipitation and Hydrograph Components of the Sutri Dhaka Glacier Basin, Western Himalayas

Singh

Rahaman

Sharma

et al. 2019

Water

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Himalayan glaciers are the major source of fresh water supply to the Himalayan Rivers, which support the livelihoods of more than a billion people living in the downstream region. However, in the face of recent climate change, these glaciers might be vulnerable, and thereby become a serious threat to the future fresh water reserve. Therefore, special attention is required in terms of understanding moisture sources for precipitation over the Himalayan glaciers and the hydrograph components of streams and rivers flowing from the glacierized region. We have carried out a systematic study in one of the benchmark glaciers, “Sutri Dhaka” of the Chandra Basin, in the western Himalayas, to understand its hydrograph components, based on stable water isotopes (δ18O and δ2H) and field-based ablation measurements. Further, to decipher moisture sources for precipitation and its variability in the study region, we have studied stable water isotopes in precipitation samples (rain and snow), and performed a back-trajectory analysis of the air parcel that brings moisture to this region. Our results show that the moisture source for precipitation over the study region is mainly derived from the Mediterranean regions (>70%) by Western Disturbances (WDs) during winter (October–May) and a minor contribution (<20%) from the Indian Summer Monsoon (ISM) during summer season (June–September). A three-component hydrograph separation based on δ18O and d-excess provides estimates of ice (65 ± 14%), snowpack (15 ± 9%) and fresh snow (20 ± 5%) contributions, respectively. Our field-based specific ablation measurements show that ice and snow melt contributions are 80 ± 16% and 20 ± 4%, respectively. The differences in hydrograph component estimates are apparently due to an unaccounted snow contribution ‘missing component’ from the valley slopes in field-based ablation measurements, whereas the isotope-based hydrograph separation method accounts for all the components, and provides a basin integrated estimate. Therefore, we suggest that for similar types of basins where contributions of rainfall and groundwater are minimal, and glaciers are often inaccessible for frequent field measurements/observations, the stable isotope-based method could significantly add to our ability to decipher moisture sources and estimate hydrograph components.

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“…Li et al [17] used a unified expression to reflect the changes in grain composition. Particle size distribution of sediments in stormwater runoff generated from exposed soil surfaces at active construction sites and surface mining operations can be used to predict the erosion in soil 2 Advances in Materials Science and Engineering [18][19][20][21][22]. A comprehensive understanding of soil structural characteristics is based on establishment of different particle distribution functions.…”

Section: Introductionmentioning

confidence: 99%

Fitting Performance of Different Models on Loess Particle Size Distribution Curves

Liu

Chen

et al. 2017

Advances in Materials Science and Engineering

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The soil water characteristic curve (SWCC) describes the relationship between matric suction and moisture of soil, the testing process of which is time-consuming. The test time of particle size distribution (PSD), in contrast, is relatively short. Thus, it is quite important to establish a proper model for PSD to forecast SWCC. This paper analyzed PSD of 25 groups of loess by way of laser diffraction technique (LD) and sieve-settlement method. Works were carried out on fitting analysis on PSD with Logarithmic model, Fredlund model, Jaky model, and Gompertz model. Statistical method was used to explain the fitting performance. Meanwhile, an empirical model was put forward. Compared to the four models, the empirical model has fewer parameters, simple model form, and smaller fluctuations of parameters. Results of LD showed higher clay content but lower silt content. It is suggested that Fredlund model or the empirical model be adopted to forecast SWCC of Malan loess.

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Hydroclimatic influence on particle size distribution of suspended sediments evacuated from debris-covered Chorabari Glacier, upper Mandakini catchment, central Himalaya

Cited by 32 publications

References 67 publications

Misinterpreting proxy data for paleoclimate signals: A reply to Srivastava and Jovane, 2020

Misinterpreting proxy data for paleoclimate signals: A reply to Srivastava and Jovane, 2020

Moisture Sources for Precipitation and Hydrograph Components of the Sutri Dhaka Glacier Basin, Western Himalayas

Fitting Performance of Different Models on Loess Particle Size Distribution Curves

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