Articles | Volume 387
https://doi.org/10.5194/piahs-387-25-2024
https://doi.org/10.5194/piahs-387-25-2024
Post-conference publication
 | 
18 Nov 2024
Post-conference publication |  | 18 Nov 2024

Coupling the Glacio-hydrological Degree-day Model (GDM) with PCRaster for spatial dynamic modeling of Himalayan river basins

Kundan Lal Shrestha, Rijan Bhakta Kayastha, and Rakesh Kayastha

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Revised manuscript not accepted

Cited articles

Adnan, M., Kang, S.-c., Zhang, G.-s., Anjum, M. N., Zaman, M., and Zhang, Y.-q.: Evaluation of SWAT Model performance on glaciated and non-glaciated subbasins of Nam Co Lake, Southern Tibetan Plateau, China, J. Mt. Sci., 16, 1075–1097, https://doi.org/10.1007/s11629-018-5070-7, 2019. a
Arora, M., Kumar, R., Kumar, N., and Malhotra, J.: Hydrological Modeling and Streamflow Characterization of Gangotri Glacier, in: Geostatistical and Geospatial Approaches for the Characterization of Natural Resources in the Environment, edited by: Raju, N., Springer, Cham., 909–915, https://doi.org/10.1007/978-3-319-18663-4_141, 2016. a
Azam, M. F., Kargel, J. S., Shea, J. M., Nepal, S., Haritashya, U. K., Srivastava, S., Maussion, F., Qazi, N., Chevallier, P., Dimri, A. P., Kulkarni, A. V., Cogley, J. G., and Bahuguna, I.: Glaciohydrology of the Himalaya-Karakoram, Science, 373, eabf3668, https://doi.org/10.1126/science.abf3668, 2021. a
Baig, S., Sayama, T., and Takara, K.: Hydrological Modeling of the Astore River Basin, Pakistan, by Integrating Snow and Glacier Melt Processes and Climate Scenarios, Journal of Disaster Research, 16, 1197–1206, https://doi.org/10.20965/jdr.2021.p1197, 2021. a
Buch, A., Mazumdar, H., and Pandey, P.: Application of artificial neural networks in hydrological modeling: a case study of runoff simulation of a Himalayan glacier basin, Proceedings of 1993 International Conference on Neural Networks (IJCNN-93-Nagoya, Japan), 25–29 October 1993, Nagoya, Japan, https://doi.org/10.1109/ijcnn.1993.714073, 1993. a, b, c
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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.