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Impact of climate change on snowmelt runoff in a Himalayan basin, Nepal

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Abstract

The Hindu Kush Himalaya (HKH) is one of the major sources of fresh water on Earth and is currently under serious threat of climate change. This study investigates the future water availability in the Langtang basin, Central Himalayas, Nepal under climate change scenarios using state-of-the-art machine learning (ML) techniques. The daily snow area for the region was derived from MODIS images. The outputs of climate models were used to project the temperature and precipitation until 2100. Three ML models, including Gated recurrent unit (GRU), Long short-term memory (LSTM), and Recurrent neural network (RNN), were developed for snowmelt runoff prediction, and their performance was compared based on statistical indicators. The result suggests that the mean temperature of the basin could rise by 4.98 °C by the end of the century. The annual average precipitation in the basin is likely to increase in the future, especially due to high monsoon rainfall, but winter precipitation could decline. The annual river discharge is projected to upsurge significantly due to increased precipitation and snowmelt, and no shift in hydrograph is expected in the future. Among three ML models, the LSTM model performed better than GRU and RNN models. In summary, this study depicts severe future climate change in the region and quantifies its effect on river discharge. Furthermore, the study demonstrates the suitability of the LSTM model in streamflow prediction in the data-scarce HKH region. The outcomes of this study will be useful for water resource managers and planners in developing strategies to harness the positive impacts and offset the negative effects of climate change in the basin.

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Data availability

The datasets generated during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

We express our thanks to the Department of hydrology and meteorology, Nepal for providing local hydrometeorological data and the Regional database system, ICIMOD for providing climate data for this work. This work was supported by the National Natural Science Foundation of China (grant number 51979066) and the State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology (grant number 2018TS01).

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Authors and Affiliations

  1. State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin, China

    Samit Thapa, Bo Li, Donglei Fu, Xiaofei Shi, Stephen Yabo, Lu Lu & Hong Qi

  2. School of Environment, Harbin Institute of Technology, Harbin, China

    Samit Thapa, Bo Li, Donglei Fu, Xiaofei Shi, Stephen Yabo, Lu Lu & Hong Qi

  3. Heilongjiang Provincial Environmental Monitoring Center Station, Harbin, China

    Haizhi Li

  4. CASIC Intelligence Industry Development Co. Ltd, Beijing, 100854, China

    Xiaofei Shi

  5. School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China

    Wei Zhang

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  1. Samit Thapa
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  3. Bo Li
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Highlights

• GRU, LSTM, and RNN models were developed for snowmelt runoff prediction.

• The increase in temperature and precipitation is projected in the future in the Langtang basin.

• Water availability in the basin is likely to increase until the end of this century.

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Thapa, S., Li, H., Li, B. et al. Impact of climate change on snowmelt runoff in a Himalayan basin, Nepal. Environ Monit Assess 193, 393 (2021). https://doi.org/10.1007/s10661-021-09197-6

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