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Flow Analysis at the Snow Covered High Altitude Catchment via Distributed Energy Balance Modeling
Energy budget-based distributed modeling at high-altitude glacio-nival watersheds is essential to accurately describe hydrological processes and quantify the flow rates. In this study, SNOWPACK model and its distributed version Alpine3D are applied for the first time in Pakistan to simulate the runo...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6423137/ https://www.ncbi.nlm.nih.gov/pubmed/30886161 http://dx.doi.org/10.1038/s41598-019-39446-1 |
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author | Shakoor, Abdul Ejaz, Naeem |
author_facet | Shakoor, Abdul Ejaz, Naeem |
author_sort | Shakoor, Abdul |
collection | PubMed |
description | Energy budget-based distributed modeling at high-altitude glacio-nival watersheds is essential to accurately describe hydrological processes and quantify the flow rates. In this study, SNOWPACK model and its distributed version Alpine3D are applied for the first time in Pakistan to simulate the runoff response of a high altitude glaciated catchment. The basic aim was to explore the feasibility of this modeling system and its future applications in the region. Final results demonstrated satisfactory performance of the model between measured and modeled discharges with Nash-Sutcliff Efficiency of 0.54. However, total simulated flow volume differs only 1.3 times as compared to measured discharge of the lake, located at the glacier snout. Flow composition analysis revealed that the runoff regime of the study site is strongly influenced by the snow and glacier melt runoff representing 53% snowmelt and 38% glacier melt contribution. Low model efficiency has been observed during glacier melting season due to inaccurate wind speed distribution and biased input met-data. It is concluded that high performance of this model can be achieved if the model is optimized over the catchment similar to the study site provided with long term data sets. This study leaves a firm foundation for the potential application of a highly accurate distributed energy balance model in the entire Karakoram and Himalaya region to understand the melt dynamics of such a rugged terrain glacier rich mountains. |
format | Online Article Text |
id | pubmed-6423137 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-64231372019-03-26 Flow Analysis at the Snow Covered High Altitude Catchment via Distributed Energy Balance Modeling Shakoor, Abdul Ejaz, Naeem Sci Rep Article Energy budget-based distributed modeling at high-altitude glacio-nival watersheds is essential to accurately describe hydrological processes and quantify the flow rates. In this study, SNOWPACK model and its distributed version Alpine3D are applied for the first time in Pakistan to simulate the runoff response of a high altitude glaciated catchment. The basic aim was to explore the feasibility of this modeling system and its future applications in the region. Final results demonstrated satisfactory performance of the model between measured and modeled discharges with Nash-Sutcliff Efficiency of 0.54. However, total simulated flow volume differs only 1.3 times as compared to measured discharge of the lake, located at the glacier snout. Flow composition analysis revealed that the runoff regime of the study site is strongly influenced by the snow and glacier melt runoff representing 53% snowmelt and 38% glacier melt contribution. Low model efficiency has been observed during glacier melting season due to inaccurate wind speed distribution and biased input met-data. It is concluded that high performance of this model can be achieved if the model is optimized over the catchment similar to the study site provided with long term data sets. This study leaves a firm foundation for the potential application of a highly accurate distributed energy balance model in the entire Karakoram and Himalaya region to understand the melt dynamics of such a rugged terrain glacier rich mountains. Nature Publishing Group UK 2019-03-18 /pmc/articles/PMC6423137/ /pubmed/30886161 http://dx.doi.org/10.1038/s41598-019-39446-1 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Shakoor, Abdul Ejaz, Naeem Flow Analysis at the Snow Covered High Altitude Catchment via Distributed Energy Balance Modeling |
title | Flow Analysis at the Snow Covered High Altitude Catchment via Distributed Energy Balance Modeling |
title_full | Flow Analysis at the Snow Covered High Altitude Catchment via Distributed Energy Balance Modeling |
title_fullStr | Flow Analysis at the Snow Covered High Altitude Catchment via Distributed Energy Balance Modeling |
title_full_unstemmed | Flow Analysis at the Snow Covered High Altitude Catchment via Distributed Energy Balance Modeling |
title_short | Flow Analysis at the Snow Covered High Altitude Catchment via Distributed Energy Balance Modeling |
title_sort | flow analysis at the snow covered high altitude catchment via distributed energy balance modeling |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6423137/ https://www.ncbi.nlm.nih.gov/pubmed/30886161 http://dx.doi.org/10.1038/s41598-019-39446-1 |
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