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Comparison of Snowmelt Runoff from the River Basins in the Eastern and Western Himalayan Region of India using SDSRM

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Abstract

The runoff from the Indian Himalayan Region (IHR) acts as a vital source of water, and therefore, estimation of runoff from snowmelt is very important. This study has been done with an objective to evaluate and compare snowmelt runoff for Mago basin in Arunachal Pradesh (Eastern Himalaya) and Alaknanda basin in Uttarakhand (Western Himalaya) using Spatially Distributed Snowmelt Runoff Model (SDSRM) with MODIS data. The performance of SDSRM was found to be satisfactory with model efficiency (ME) greater than 0.65 and R2 greater than 0.7 in both the basins. The temperature was adjusted using temperature lapse rate, and snow parameters like snow density, snow depth, snow water equivalent, degree day factor and snowmelt depth were generated. Comparatively, the Eastern Himalayan basin was found to have higher mean values of these snow parameters than the Western Himalayan basin. The highest contribution of snowmelt runoff in the Eastern Himalayan basin was found to be 31.23% in the month of April and in the Western Himalayan basin, it was found as 44.70% in the month of May. It was also found from this study that snowmelt in both the Eastern and Western Himalayan basins starts from April and continues till September. The snowmelt contribution was comparatively higher in the Western Himalayan basin.

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References

  • Adnan, M., Nabi, G., Poommee, M. S., & Ashraf, A. (2016). Snowmelt runoff prediction under changing climate in the Himalayan cryosphere: A case of Gilgit river basin. Geoscience Frontiers, 8(5), 941–949.

    Article  Google Scholar 

  • Ahluwalia, R., Rai, S., Jain, S., Kumar, B., & Dobhal, D. (2013). Assessment of snowmelt runoff modelling and isotope analysis: A case study from the western Himalaya, India. Annals of Glaciology, 54(62), 299–304. https://doi.org/10.3189/2013AoG62A133

  • Anderson, E. A. (1973). National weather service river forecast system-snow accumulation and ablation model. National Oceanographic and Atmospheric Administration, Silver Springs, Technical Memorandum, NWS_HYDRO-17.

  • Armstrong, R. L., Rittger, K., Brodzik, M. J., Racoviteanu, A., Barrett, A. P., Khalsa, S. S., Raup, B., Hill, A. F., Khan, A. L., Wilson, A. M., Kayastha, R. B., Fetterer, F., & Armstrong, B. (2019). Runoff from glacier ice and seasonal snow in High Asia: Separating melt water sources in river flow. Regional Environmental Change, 19, 1249–1261.

    Article  Google Scholar 

  • Azam, M. F., & Srivastava, S. (2020). Mass balance and runoff modelling of partially debris-covered Dokriani glacier in monsoon-dominated Himalaya using ERA5 data since 1979. Journal of Hydrology, 590, 125432.

  • Bandyopadhyay, A., Bhadra, A., Maza, M., & Shelina, R. K. (2014). Monthly variations of air temperature lapse rates in Arunachal Himalaya. Journal of Indian Water Resources Society, 34(3), 16–25.

    Google Scholar 

  • Barnett, T. P., Adam, J. C., & Lettenmaier, D. P. (2005). Potential impacts of a warming climate on water availability in snow-dominated regions. Nature, 438(17), 303–309.

    Article  Google Scholar 

  • Bavera and Michele. (2009). Snow water equivalent estimation in the Mallero basin using snow gauge data and MODIS images and fieldwork validation. Hydrological Processes, 23, 1961–1972.

    Article  Google Scholar 

  • Bookhagen, B., & Burbank, D. W. (2010). Toward a complete Himalayan hydrological budget: Spatiotemporal distribution of snowmelt and rainfall and their impact on river discharge. Journal of Geophysical Research: Earth Surface, 115(F3).

  • Chiphang, N., Bandyopadhyay, A., & Bhadra, A. (2020). Assessing the effects of snowmelt dynamics on streamflow and water balance components in an Eastern Himalayan river basin using SWAT model. Environmental Modelling & Asessment, 25(6), 861–883.

    Article  Google Scholar 

  • Copernicus Climate Change service (C3S). (2019). C3S ERA5-Land reanalysis.

  • Grover, S., Tayal, S., Beldring, S., & Li, H. (2020). Modeling hydrological processes in ungauged snow-fed catchment of Western Himalaya. Water Resources, 47(6), 987–995.

    Article  Google Scholar 

  • Grunewald, T., Buhler, Y., & Lehning, M. (2014). Elevation dependency of mountain snow depth. The Cryosphere, 8, 2381–2394.

    Article  Google Scholar 

  • Hock, R. (2003). Temperature index melt modelling in mountain areas. Journal of Hydrology, 282, 104–115.

    Article  Google Scholar 

  • Hughes, D. A., Hannart, P., & Watkins, D. (2003). Continuous baseflow separation from time series of daily and monthly streamflow data. Water SA, 29(1), 43–48.

    Google Scholar 

  • IMD. (2009). Annual Report, India Meteorological Department (IMD), Ministry of Earth Sciences, Government of India, New Delhi. https://metnet.imd.gov.in/imdnews/ar2009.pdf

  • Jain, S. K., Goswami, A., & Saraf, A. K. (2010). Snowmelt runoff modelling in a Himalayan basin with the aid of satellite data. International Journal of Remote Sensing, 31(24), 6603–6618.

    Article  Google Scholar 

  • Jeelani, G., Feddema, J. J., van der Veen, C. J., & Stearns, L. (2012). Role of snow and glacier melt in controlling river hydrology in Liddar watershed (western Himalaya) under current and future climate. Water Resources Research, 48, W12508.

    Article  Google Scholar 

  • Jonas, T., Marty, C., & Magnusson, J. (2009). Estimating the snow water equivalent from snow depth measurements in the Swiss Alps. Journal of Hydrology, 378, 161–167.

    Article  Google Scholar 

  • Kuusisto, E. (1980). On the values and variability of degree-day melting factor in Finland. Nordic Hydrology, 11, 235–242.

    Article  Google Scholar 

  • Lang, H., & Braun, L. (1990). On the information content of air temperature in the context of snowmelt estimation. In L. Molnar (Ed.), Hydrology of mountainous areas, Proceedings of the strbske pleso symposium 1990: IAHS Publ. no. 190, pp. 347–354.

  • Lewis, C. D. (1982). Industrial and business forecasting methods: A practical guide to exponential smoothing and curve fitting. Butterworth Scientific.

    Google Scholar 

  • Mahar, G., Dhar, U., Rawal, R. S., & Bhatt, I. D. (2009). Implications of location specific data and their usefulness in conservation planning: An example from Indian Himalayan Region (IHR). Biodiversity and Conservation. https://doi.org/10.1007/s10531-008-9450-0

    Article  Google Scholar 

  • Martinec, J. (1960). The degree-day factor for snowmelt runoff forecasting. Presented at IUGG General Assembly of Helsinki, IAHS Commission of Surface Waters, IAHS Publication No. 51, pp. 468–477.

  • Martinec, J. (1975). Snowmelt runoff model for river flow forecasts. Nordic Hydrology, 6, 145–154.

    Article  Google Scholar 

  • Martinec, J., Rango, A., & Roberts, R. (2008). Snowmelt Runoff Model (SRM) user’s manual. New Mexico State University.

    Google Scholar 

  • Mott, R., Vonnet, V., & Grünewald, T. (2018). The seasonal snow cover dynamics: Review on wind-driven coupling processes. Frontiers in Earth Science, 6, 197. https://doi.org/10.3389/feart.2018.00197

    Article  Google Scholar 

  • Nunchhani, V., Bandyopadhyay, A., & Bhadra, A. (2021). Spatio-temporal variability in snow parameters from MODIS data using Spatially Distributed Snowmelt Runoff Model (SDSRM): A case study in Dibang basin, Arunachal Pradesh. Journal of the Indian Society of Remote Sensing, 49, 325–340.

  • Panday, P. K., Williams, C. A., Frey, K. E., & Brown, M. E. (2013). Application and evaluation of a snowmelt runoff model in the Tamor River basin, Eastern Himalaya using a Markov Chain Monte Carlo (MCMC) data assimilation approach. Hydrological Processes. https://doi.org/10.1002/hyp.10005.

  • Qi, J., Li, S., Jamieson, R., Xing, Z., & Meng, F. (2017). Modifying SWAT with an energy balance module to simulate snowmelt for maritime regions. Environmental Modelling Software, 93, 146–160.

    Article  Google Scholar 

  • Rajkumari, S., Chiphang, N., Kiba, L. G., Bandyopadhyay, A., & Bhadra, A. (2019). Development and application of a spatially distributed snowmelt runoff model for limited data condition. Arabian Journal of Geosciences, 12, 488.

    Article  Google Scholar 

  • Rango, A., & Martinec, J. (1995). Revisitingthe degree-day method for snowmelt computations. American Water Resources Bulletin, 31(4), 657–669.

    Article  Google Scholar 

  • Sexstone, G. A., & Fassnacht, S. R. (2014). What drives basin scale spatial variability of snowpack properties in northern Colorado? The Cryosphere, 8, 329–344.

    Article  Google Scholar 

  • Singh, P., & Jain, S. (2003). Modelling of streamflow and its components for a large Himalayan basin with predominant snowmelt yields. Hydrological Sciences Journal, 48, 257–276.

    Article  Google Scholar 

  • Smith, J. L., & Halverson, H. G. (1979). Estimating snowpack density from albedo measurement. Research Paper PSW-RP-136. Berkeley, CA: U.S. Department of Agricultural Forest Service, Pacific Southwest Forest and Range Experiment Station. 

  • Tiwari, S., Kar, S. C., & Bhatla, R. (2015). Snowfall and snowmelt variability over Himalayan region in Inter-annual timescale. Aquatic Procedia, 4, 942–949.

    Article  Google Scholar 

  • Viviroli, D., Durr, H. H., Messerli, B., Meybeck, M., & Weingartner, R. (2007). Mountains of the world, water towers for humanity: Typology, mapping and global significance. Water Resources Research, 43, W07447. https://doi.org/10.1029/2006WR005653

    Article  Google Scholar 

  • Welderufael, W. A., & Woyessa, Y. E. (2010). Stream flow analysis and comparison of base flow separation methods – Case study of the Modder river basin in central south Africa. European Water, 31, 3–12.

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Acknowledgements

The authors acknowledge the help received from the Department of Science and Technology, Government of India under National Mission for Sustaining the Himalayan Ecosystem and Space Application Centre, Ahmedabad, under PRACRITI-II Hydrology Project. The authors also express sincere thanks to the Central Water Commission, Itanagar, and Central Water Commission, Lucknow, for providing the data used in this study.

Funding

This study was financially supported by the Department of Science and Technology, Government of India, under Climate Change Programme through Grant No. DST/CCP/NHC/154/2018.

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Correspondence to A. Bandyopadhyay.

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Kiba, L.G., Rajkumari, S., Chiphang, N. et al. Comparison of Snowmelt Runoff from the River Basins in the Eastern and Western Himalayan Region of India using SDSRM. J Indian Soc Remote Sens 49, 2291–2309 (2021). https://doi.org/10.1007/s12524-021-01384-9

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