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Quantification of spatial temporal variability of snow cover and hydro-climatic variables based on multi-source remote sensing data in the Swat watershed, Hindukush Mountains, Pakistan

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Abstract

The northern part of Hindukush Mountains has a perplexing environment due to the influence of adjacent mountains of Himalaya, Karakoram, and Tibetan Plateau. Although reliable evidences of climate change are available; however, a clear knowledge of snow cover dynamics in the context of climate change is missing for this region. In this study, we used various remotely sensed (TRMM precipitation product, while MODIS temperature and snow cover products) and gauge-based datasets to quantify the spatiotemporal variability of climatic variables and their turn effects over the snow cover area (SCA) and river discharge in the Swat watershed, northern Hindukush Mountains, Pakistan. The Mann–Kendall method and Sen’s slope estimator were used to estimate the trends in SCA and hydro-climatic variables, at 5% significant level (P = 0.05). Results show that the winter and springs temperatures have increased (at the rate of 0.079 and 0.059 °C year−1, respectively), while decreasing in the summer and autumn (at the rate of 0.049 and 0.070 °C year−1, respectively). Basin-wide increasing tendency of precipitation was identified with a highest increasing rate of 3.563 mm year−1 in the spring season. A decreasing trend in the winter SCA (at the rate of -0.275% year−1) and increasing trends in other seasons were identified. An increasing tendency of river discharge on annual and seasonal scales was also witnessed. The seasonal variations in discharge showed significant positive and negative relationships with temperature and SCA, respectively. We conclude that the future variations in the temperature and SCA in the higher altitudes of the Swat watershed could substantially affect the seasonality of the river discharge. Moreover, it implies that the effect of ongoing global warming on the SCA in the snowmelt-dominated river basins needs to be considered for sustainable regional planning and management of water resources, hydropower production, and downstream irrigation scheduling.

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Acknowledgements

This work was financially supported by the Ministry of Science and Technology of the People’s Republic of China (Grant no. 2013CBA01808), the National Natural Science Foundation of China (Grant nos. 41671066; 41625001; 91425303) and SKLCS-ZZ-2017. The authors would like to thank the Pakistan Meteorological Department (PMD) and Water and Power Development Authority (WAPDA) for providing hydro-climatic data. They would also like to express their sincere gratitude to the Chinese Academy of Sciences and The World Academy of Sciences (CAS-TWAS) for providing fellowship to the first author of the paper for doctoral degree at the Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China.

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Authors and Affiliations

  1. Division of Hydrology Water-Land Resources in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, Gansu, People’s Republic of China

    Muhammad Naveed Anjum & Yongjian Ding

  2. State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, People’s Republic of China

    Muhammad Naveed Anjum, Yongjian Ding & Donghui Shangguan

  3. University of Chinese Academy of Sciences, Beijing, 100049, People’s Republic of China

    Muhammad Naveed Anjum

  4. School of Environmental Science and Engineering, South University of Science and Technology of China, Shenzhen, 518055, People’s Republic of China

    Junguo Liu

  5. Centre of Excellence in Water Resources Engineering, University of Engineering and Technology, Lahore, 54890, Pakistan

    Ijaz Ahmad

  6. United States-Pakistan Centre for Advance Studies in Water, Mehran University of Engineering and Technology, Jamshoro, Sindh, 76062, Pakistan

    Muhammad Wajid Ijaz

  7. School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin, Heilongjiang, 150030, People’s Republic of China

    Muhammad Imran Khan

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  1. Muhammad Naveed Anjum
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Anjum, M.N., Ding, Y., Shangguan, D. et al. Quantification of spatial temporal variability of snow cover and hydro-climatic variables based on multi-source remote sensing data in the Swat watershed, Hindukush Mountains, Pakistan. Meteorol Atmos Phys 131, 467–486 (2019). https://doi.org/10.1007/s00703-018-0584-7

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