Water storage change in the Himalayas from the Gravity Recovery and Climate Experiment (GRACE) and an empirical climate model

Authors

  • Juana Paul Moiwo,

    1. Key Laboratory for Agricultural Water Resources, Agricultural Resources Research Center, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, China
    2. Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
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  • Yonghui Yang,

    1. Key Laboratory for Agricultural Water Resources, Agricultural Resources Research Center, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, China
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  • Fulu Tao,

    1. Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
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  • Wenxi Lu,

    1. College of Environment and Resources, Jilin University, Jilin, China
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  • Shumin Han

    1. Key Laboratory for Agricultural Water Resources, Agricultural Resources Research Center, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, China
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Abstract

[1] The Himalayas and Tibetan Plateau harbor hundreds of mountain lakes along with thousands of glaciers and high-elevation snowfields. This is the source of water for the upper reaches of Asia's main river systems, providing the livelihood for millions of people in the subregion. Climate change is therefore critical for the Himalaya snow and glacier hydrology, the dependent ecosystems, and the people. Whereas temperature and precipitation are common indicators for climate change, snow and glacier dynamics are reliable precursors of a warming or cooling climate. This study uses a simple empirical climate model (ECM) and the Gravity Recovery and Climate Experiment (GRACE) satellite data to analyze water storage dynamics in the 5.072 × 106 km2 Himalayas and Tibetan Plateau region. About 72 consecutive months (January 2003 through December 2008) of data are used in the study. The temperature and precipitation (snow plus rain) data are acquired from the Global Land Data Assimilation System (GLDAS) Noah land surface model and are validated with ground truth data from 205 meteorological stations. Total water storage change derived from the GRACE gravity data is fitted with a simple sinusoidal least squares regression model. A favorable agreement exists between the GRACE and sinusoidal curve (R2 = 0.81 and root-mean-square error (RMSE) = 8.73 mm), suggesting that random errors in GRACE data are small. However, the sinusoidal fit does not quantify systematic errors in GRACE data. Agreements between the GRACE- and ECM-estimated storage changes are also favorable at both monthly (R2 = 0.93, RMSE = 5.46 mm) and seasonal (R2 = 0.83, RMSE = 7.64 mm) cycles. The agreements (significant at p < 0.01) indicate not only GRACE's ability to detect storage signal but also that of the ECM model to characterize storage change in the snow and glacier hydrology. There is clear seasonality in the storage anomaly, with the highest in summer and lowest in winter. The corresponding storage change is delayed by a quarter of the year. The GRACE and ECM model indicate an overall negative storage trend of 0.36 ± 0.03 mm/month or 21.91 ± 1.95 km3/yr for the study area (significant at p < 0.1). Given that snow and glaciers are particularly sensitive to temperature change, the negative storage trend could be indicative of warming climate conditions in the region. Groundwater abstraction (mainly for irrigation) in the southern plains, coupled with dwindling snowfall in the northern massifs, is a critical storage loss factor in the region. Invariably, storage loss in the Himalayan-Tibetan Plateau region could have negative implications for the hydrology, dependent ecosystems, and livelihoods of millions of people.

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