Articles | Volume 387
https://doi.org/10.5194/piahs-387-25-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/piahs-387-25-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Coupling the Glacio-hydrological Degree-day Model (GDM) with PCRaster for spatial dynamic modeling of Himalayan river basins
Department of Chemical Science and Engineering, School of Engineering, Kathmandu University, Dhulikhel, Nepal
Rijan Bhakta Kayastha
Himalayan Cryosphere, Climate and Disaster Research Center (HiCCDRC), Department of Environmental Science and Engineering, School of Science, Kathmandu University, Dhulikhel, Nepal
Rakesh Kayastha
Himalayan Cryosphere, Climate and Disaster Research Center (HiCCDRC), Department of Environmental Science and Engineering, School of Science, Kathmandu University, Dhulikhel, Nepal
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Rakesh Kayastha, Rijan Bhakta Kayastha, Kundan Lal Shrestha, and Smriti Gurung
Proc. IAHS, 387, 53–58, https://doi.org/10.5194/piahs-387-53-2024, https://doi.org/10.5194/piahs-387-53-2024, 2024
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We have estimated hydropower potential in the two glacierized river basins of the Nepalese Himalayas. The Glacio-hydrological Degree-Day Model (GDM) was used with different geospatial criteria. In order to force the model simulation and to assess potential future hydrological regimes, a variety of climate variables were combined and used. The sensitivity of climate variables and their impact on hydropower potential were investigated with a combination of different climate variables.
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Proc. IAHS, 387, 17–24, https://doi.org/10.5194/piahs-387-17-2024, https://doi.org/10.5194/piahs-387-17-2024, 2024
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This study explores the potential of integrating data science models to enhance the predictive capacity of a theory-guided glacier hydrological model for improved river discharge simulations in the Himalayan basins. By combining data science and physical process models, the study addresses the limitations inherent in each approach.
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Revised manuscript not accepted
Rakesh Kayastha, Rijan Bhakta Kayastha, Kundan Lal Shrestha, and Smriti Gurung
Proc. IAHS, 387, 53–58, https://doi.org/10.5194/piahs-387-53-2024, https://doi.org/10.5194/piahs-387-53-2024, 2024
Short summary
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We have estimated hydropower potential in the two glacierized river basins of the Nepalese Himalayas. The Glacio-hydrological Degree-Day Model (GDM) was used with different geospatial criteria. In order to force the model simulation and to assess potential future hydrological regimes, a variety of climate variables were combined and used. The sensitivity of climate variables and their impact on hydropower potential were investigated with a combination of different climate variables.
Dinesh Joshi, Rijan Bhakta Kayastha, Kundan Lal Shrestha, and Rakesh Kayastha
Proc. IAHS, 387, 17–24, https://doi.org/10.5194/piahs-387-17-2024, https://doi.org/10.5194/piahs-387-17-2024, 2024
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This study explores the potential of integrating data science models to enhance the predictive capacity of a theory-guided glacier hydrological model for improved river discharge simulations in the Himalayan basins. By combining data science and physical process models, the study addresses the limitations inherent in each approach.
Rijan Bhakta Kayastha and Sunwi Maskey
Proc. IAHS, 387, 59–63, https://doi.org/10.5194/piahs-387-59-2024, https://doi.org/10.5194/piahs-387-59-2024, 2024
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Glacial lake outburst flood (GLOF) modeling of Tsho Rolpa showed that, even if the lake breaches by 20 m in 40 years (from 2021), there will be a sufficient lead time of more than 7 h for early warning and human evacuations in the downstream areas. However, precautionary measures such as community-based GLOF early-warning systems and mechanisms allowing close observation in the case of GLOF events should be established in GLOF-prone regions.
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Proc. IAHS, 387, 1–2, https://doi.org/10.5194/piahs-387-1-2024, https://doi.org/10.5194/piahs-387-1-2024, 2024
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Based on balloon-borne measurements performed in India and Nepal in 2016–2017, we infer the vertical distributions of water vapor, ozone and aerosols in the atmosphere, from the surface to 30 km altitude. Our measurements show that the atmospheric dynamics of the Asian summer monsoon system over the polluted Indian subcontinent lead to increased concentrations of water vapor and aerosols in the high atmosphere (approximately 14–20 km altitude), which can have an important effect on climate.
S. H. Ali, I. Bano, R. B. Kayastha, and A. Shrestha
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1487–1494, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1487-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1487-2017, 2017
Koji Fujita, Hiroshi Inoue, Takeki Izumi, Satoru Yamaguchi, Ayako Sadakane, Sojiro Sunako, Kouichi Nishimura, Walter W. Immerzeel, Joseph M. Shea, Rijan B. Kayastha, Takanobu Sawagaki, David F. Breashears, Hiroshi Yagi, and Akiko Sakai
Nat. Hazards Earth Syst. Sci., 17, 749–764, https://doi.org/10.5194/nhess-17-749-2017, https://doi.org/10.5194/nhess-17-749-2017, 2017
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We create multiple DEMs from photographs taken by helicopter and UAV and reveal the deposit volumes over the Langtang village, which was destroyed by avalanches induced by the Gorkha earthquake. Estimated snow depth in the source area is consistent with anomalously large snow depths observed at a neighboring glacier. Comparing with a long-term observational data, we conclude that this anomalous winter snow amplified the disaster induced by the 2015 Gorkha earthquake in Nepal.
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Short summary
The Himalayan river basins have complex terrain and lack detailed hydrological and meteorological information. This has motivated us to develop a fast and distributed model named PyGDM to simulate the hydrology of this region, which is home to both glaciers and snow. PyGDM is good at simulating glacier and snow melt. Hence, the model is suitable for studying different aspects of the Himalayan region, such as the impact of climate change and hydropower scenarios.
The Himalayan river basins have complex terrain and lack detailed hydrological and...