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River basin flood potential inferred using GRACE gravity observations at several months lead time

Abstract

The wetness of a watershed determines its response to precipitation1,2,3, leading to variability in flood generation4. The importance of total water storage—which includes snow, surface water, soil moisture and groundwater—for the predisposition of a region to flooding is less clear, in part because such comprehensive observations are rarely available. Here we demonstrate that basin-scale estimates of water storage derived from satellite observations of time-variable gravity can be used to characterize regional flood potential and may ultimately result in longer lead times in flood warnings. We use a case study of the catastrophic 2011 Missouri River floods to establish a relationship between river discharge, as measured by gauge stations, and basin-wide water storage, as measured remotely by NASA’s Gravity Recovery and Climate Experiment (GRACE) mission. Applying a time-lagged autoregressive model of river discharge, we show that the inclusion of GRACE-based total water storage information allows us to assess the predisposition of a river basin to flooding as much as 5–11 months in advance. Additional case studies of flood events in the Columbia River and Indus River basins further illustrate that longer lead-time flood prediction requires accurate information on the complete hydrologic state of a river basin.

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Figure 1: GRACE water storage anomaly data for March 2011.
Figure 2: Observed river discharge versus GRACE TWSA.
Figure 3: Autoregressive model results.
Figure 4: Autoregressive model performance.

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References

  1. Sayama, T., McDonnell, J. J., Dhakal, A. & Sullivan, K. How much water can a watershed store? Hydrol. Process. 25, 3899–3908 (2011).

    Article  Google Scholar 

  2. Kirchner, J. W. Catchments as simple dynamical systems: Catchment characterization, rainfall-runoff modeling, and doing hydrology backwards. Wat. Resour. Res. 45, W02429 (2009).

    Article  Google Scholar 

  3. Brutsaert, W. Long-term groundwater storage trends estimated from streamflow records: Climatic perspective. Wat. Resour. Res. 44, W02409 (2008).

    Article  Google Scholar 

  4. Li, L. & Simonovic, S. P. System dynamics model for predicting floods from snowmelt in North American prairie watersheds. Hydrol. Process. 16, 2645–2666 (2002).

    Article  Google Scholar 

  5. Beven, K. J. Rainfall-Runoff Modeling: The Primer 360 (John Wiley, 2001).

    Google Scholar 

  6. Horton, R. E. Surface Runoff Phenomena, Part 1. Analysis of the Hydrograph (Horton Hydrological Laboratory, Publication 101, Edward Bros, 1935).

    Google Scholar 

  7. Hall, F. R. Base flow recessions—A review. Wat. Resour. Res. 4, 973–983 (1968).

    Article  Google Scholar 

  8. Appleby, V. C. Recession and the baseflow problem. Wat. Resour. Res. 6, 1398–1403 (1970).

    Article  Google Scholar 

  9. Wetterhall, F. et al. Forecasters priorities for improving probabilistic flood forecasts. Hydrol. Earth Syst. Sci. Discuss. 10, 2215–2242 (2013).

    Article  Google Scholar 

  10. Guo, Y., Liu, S. & Baetz, B. W. Probabilistic rainfall-runoff transformation considering both infiltration and saturation excess runoff generation processes. Wat. Resour. Res. 48, W06513 (2012).

    Article  Google Scholar 

  11. Siccardi, F., Boni, G., Ferraris, L. & Rudari, R. A hydrometeorological approach for probabilistic flood forecast. J. Geophys. Res. 110, D05101 (2005).

    Article  Google Scholar 

  12. Reager, J. T. & Famiglietti, J. S. Global terrestrial water storage capacity and flood potential using GRACE. Geophys. Res. Lett. 36, L23402 (2009).

    Article  Google Scholar 

  13. Famigilietti, J. S. & Rodell, M. Water in the balance. Science 340, 1300 (2013).

    Article  Google Scholar 

  14. Tapley, B. D., Bettadpur, S., Ries, J. C., Thompson, P. F. & Watkinse, M. M. GRACE measurements of mass variability in the Earth system. Science 305, 503–505 (2004).

    Article  Google Scholar 

  15. Ramillien, G., Famiglietti, J. S. & Wahr, J. Detection of continental hydrology and glaciology signals from GRACE: A review. Surv. Geophys. 29, 361–374 (2008).

    Article  Google Scholar 

  16. Syed, T. H., Famiglietti, J. S. & Chambers, D. GRACE-based estimates of terrestrial freshwater discharge from basin to continental scales. J. Hydromet. 10, 22–40 (2009).

    Article  Google Scholar 

  17. Rodell, M., Velicogna, I. & Famiglietti, J. Satellite-based estimates of groundwater depletion in India. Nature 460, 999–1002 (2009).

    Article  Google Scholar 

  18. Famiglietti, J. S. et al. Satellites measure recent rates of groundwater depletion in California’s Central Valley. Geophys. Res. Lett. 38, L03403 (2011).

    Article  Google Scholar 

  19. Crowley, J. W., Mitrovica, J. X., Bailey, R. C., Tamisiea, M. E. & Davis, J. L. Land water storage within the Congo Basin inferred from GRACE satellite gravity data. Geophys. Res. Lett. 33, L19402 (2006).

    Article  Google Scholar 

  20. Spring Flooding Underway, Expected to Worsen through April (NOAA news website, 2011); http://www.noaanews.noaa.gov/stories2011/20110317_springoutlook.html

  21. US Army Corps of Engineers, Post 2011 Flood Event Analysis of Missouri River (USACE, 2012)

  22. Swenson, S. & Wahr, J. Methods for inferring regional surface-mass anomalies from Gravity recovery and Climate Experiment (GRACE) measurements of time-variable gravity. J. Geophys. Res. 107, 2193 (2002).

    Google Scholar 

  23. Wahr, J., Swenson, S. & Velicogna, I. Accuracy of GRACE mass estimates. Geophys. Res. Lett. 33, L06401 (2006).

    Article  Google Scholar 

  24. Advanced Hydrologic Prediction Service: Portland: Columbia River (NWS, 2011); http://water.weather.gov/ahps2/hydrograph.php?wfo=pqr&gage=vapw1

  25. Natural Hazards: Unusually Intense Monsoon Rains (NASA Earth Observatory, 2010); http://earthobservatory.nasa.gov/NaturalHazards/view.php?id=45177

  26. Rodell, M. et al. The global land data assimilation system. Bull. Am. Meteorol. Soc. 85, 381–394 (2004).

    Article  Google Scholar 

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Acknowledgements

This work was supported by grants from the NASA GRACE Science Team, from the NASA Earth and Space Science Fellowship program, from the University of California Office of the President, Multicampus Research Programs and Initiatives, and from the Gordon and Betty Moore Foundation (GBMF3269). We offer a special thanks to S. Swenson of the National Center for Atmospheric Research for GRACE data processing and early discussion.

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J.T.R. and J.S.F. conceived the project; J.T.R. designed the study, performed the data analysis and wrote the manuscript; B.F.T. advised on methods and interpretation; B.F.T. and J.S.F. assisted in writing the manuscript.

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Correspondence to J. T. Reager.

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The authors declare no competing financial interests.

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Reager, J., Thomas, B. & Famiglietti, J. River basin flood potential inferred using GRACE gravity observations at several months lead time. Nature Geosci 7, 588–592 (2014). https://doi.org/10.1038/ngeo2203

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