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Estimating Runoff Using Hydro-Geodetic Approaches

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Abstract

Given the continuous decline in global runoff data availability over the past decades, alternative approaches for runoff determination are gaining importance. When aiming for global scale runoff at a sufficient temporal resolution and with homogeneous accuracy, the choice to use spaceborne sensors is only a logical step. In this respect, we take water storage changes from Gravity Recovery And Climate Explorer (grace) results and water level measurements from satellite altimetry, and present a comprehensive assessment of five different approaches for river runoff estimation: hydrological balance equation, hydro-meteorological balance equation, satellite altimetry with quantile function-based stage–discharge relationships, a rudimentary instantaneous runoff–precipitation relationship, and a runoff–storage relationship that takes time lag into account. As a common property, these approaches do not rely on hydrological modeling; they are either purely data driven or make additional use of atmospheric reanalyses. Further, these methods, except runoff–precipitation ratio, use geodetic observables as one of their inputs and, therefore, they are termed hydro-geodetic approaches. The runoff prediction skill of these approaches is validated against in situ runoff and compared to hydrological model predictions. Our results show that catchment-specific methods (altimetry and runoff–storage relationship) clearly outperform the global methods (hydrological and hydro-meteorological approaches) in the six study regions we considered. The global methods have the potential to provide runoff over all landmasses, which implies gauged and ungauged basins alike, but are still limited due to inconsistencies in the global hydrological and hydro-meteorological datasets that they use.

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Acknowledgments

We gratefully acknowledge the support of projects SN13/1, BA1150/11, KU2090/1 by the Deutsche Forschungsgemeinschaft (dfg) in the framework of the priority program SPP1257 Mass Transport and Mass Distribution in the System Earth. We would like to thank the following data providers: Global Runoff Data Centre (grdc) www.bafg.de/GRDC, Global Precipitation Climatology Project (gpcp) precip.gsfc.nasa.gov, European Centre for Medium-Range Weather Forecasts (ecmwf) www.ecmwf.int, University of Texas at Austin, Center for Space Research (csr) www.csr.utexas.edu/, NASA’s Earth Science Division and Goddard Earth Sciences (ges) Data and Information Services Center (disc) ldas.gsfc.nasa.gov. Further thanks are due to Dr. Diego Miralles (University of Bristol) for kindly providing the gleam evapotranspiration data. All graphics have been produced with the Generic Mapping Tools (gmt) gmt.soest.hawaii.edu (Wessel and Smith 1991).

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  1. Institute of Geodesy, University of Stuttgart, Geschwister-Scholl-str. 24D, 70174, Stuttgart, Germany

    Nico Sneeuw, Balaji Devaraju & Mohammad J. Tourian

  2. Institute of Meteorology and Climate Research, Atmospheric Environmental Research, Karlsruhe Institute of Technology, Kreuzeckbahnstraße 19, 82467, Garmisch-Partenkirchen, Germany

    Christof Lorenz & Harald Kunstmann

  3. Institute for Modelling Hydraulic and Environmental Systems, University of Stuttgart, Pfaffenwaldring 61, 70569, Stuttgart, Germany

    Johannes Riegger & András Bárdossy

  4. Institute for Geography, University of Augsburg, Universitätsstraße 10, 86159, Augsburg, Germany

    Harald Kunstmann

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  1. Nico Sneeuw
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Sneeuw, N., Lorenz, C., Devaraju, B. et al. Estimating Runoff Using Hydro-Geodetic Approaches. Surv Geophys 35, 1333–1359 (2014). https://doi.org/10.1007/s10712-014-9300-4

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