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Analyzing Large-Scale Hydrologic Processes Using GRACE and Hydrometeorological Datasets

Author

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  • Chandan Banerjee

    (Indian Institute of Science)

  • D. Nagesh Kumar

    (Indian Institute of Science)

Abstract

Water demand in India is growing due to its increasing population, economic growth and urbanization. Consequently, knowledge of interdependencies of large-scale hydrometeorological processes is crucial for efficient water resources management. Estimates of Groundwater (GW) derived from Terrestrial Water Storage (TWS) data provided by Gravity Recovery and Climate Experiment (GRACE) satellite mission along with various other satellite observations and model estimates now facilitates such investigations. In an attempt which is first of its kind in India, this study proposes Independent Component Analysis (ICA) based spatiotemporal analysis of Precipitation (P), Evapotranspiration (ET), Surface Soil Moisture (SSM), Root Zone Soil Moisture (RZSM), TWS and GW to understand such interdependencies at intra- and interannual time scales. Results indicate that 84–99% of the total variability is explained by the first 6 ICs of all the variables, analyzed for a period 2002–2014. The Indian Summer Monsoon Rainfall (ISMR) is the causative-factor of the first component describing 61–82% of the total variability. The phase difference between all seasonal components of P and that of RZSM and ET is a month whereas it is 2 months between the seasonal components of P and that of SSM, TWS and GW. ET is observed to be largely dependent on RZSM while GW appears as the major component of TWS. GW and TWS trends of opposite nature were observed in northern and southern part of India caused by inter-annual rainfall variability. These findings when incorporated in modelling frameworks would improve forecasts resulting in better water management.

Suggested Citation

  • Chandan Banerjee & D. Nagesh Kumar, 2018. "Analyzing Large-Scale Hydrologic Processes Using GRACE and Hydrometeorological Datasets," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(13), pages 4409-4423, October.
    • Handle: RePEc:spr:waterr:v:32:y:2018:i:13:d:10.1007_s11269-018-2070-x
    DOI: 10.1007/s11269-018-2070-x
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    References listed on IDEAS

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    1. Scott Jasechko & Zachary D. Sharp & John J. Gibson & S. Jean Birks & Yi Yi & Peter J. Fawcett, 2013. "Terrestrial water fluxes dominated by transpiration," Nature, Nature, vol. 496(7445), pages 347-350, April.
    2. Matthew Rodell & Isabella Velicogna & James S. Famiglietti, 2009. "Satellite-based estimates of groundwater depletion in India," Nature, Nature, vol. 460(7258), pages 999-1002, August.
    3. World Bank, 2014. "Republic of India : Accelerating Agricultural Productivity Growth," World Bank Publications - Reports 18736, The World Bank Group.
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    Cited by:

    1. Behnam Khorrami & Shoaib Ali & Orhan Gündüz, 2023. "Investigating the Local-scale Fluctuations of Groundwater Storage by Using Downscaled GRACE/GRACE-FO JPL Mascon Product Based on Machine Learning (ML) Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(9), pages 3439-3456, July.
    2. Peijun Li & Yuanyuan Zha & Liangsheng Shi & Hua Zhong & Chak-Hau Michael Tso & Mousong Wu, 2022. "Assessing the Global Relationships Between Teleconnection Factors and Terrestrial Water Storage Components," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(1), pages 119-133, January.

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