Statistical Modeling of the Global River Runoff Using GCMs: Comparison with the Observational Data and Reanalysis Results-Reference-Cited by-同舟云学术

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Statistical Modeling of the Global River Runoff Using GCMs: Comparison with the Observational Data and Reanalysis Results

Published:2019-10-21 Issue:S2 Volume:46 Page:S17-S24
ISSN:0097-8078
Container-title:Water Resources
language:en
Short-container-title:Water Resour

Author:

Dobrovolski S. G.,Yushkov V. P.,Istomina M. N.

Publisher

Pleiades Publishing Ltd

Subject

Water Science and Technology

Link

http://link.springer.com/content/pdf/10.1134/S0097807819080050.pdf

Reference14 articles.

1. Climate Data Operators. User’s Guide. Ver. 1.6.1, 2016, http://code.zmaw.de/ projects/cdo/.

2. Dai, A., Qian, T., Trenberth, K.E., and Milliman, J.D., Changes in continental freshwater discharge from 1948–2004, J. Climate, 2009, vol. 22, pp. 2773–2791.

3. Dobrovolsky, S.G., Year-to-year and many-year runoff variations in world rivers, Water Resour., 2011, vol. 38, no. 6, pp. 693–708.

4. Dobrovolsky, S.G., Global’nye izmeneniya rechnogo stoka (Global Changes in River Runoff), Moscow: GEOS, 2011.

5. Dobrovolsky, S.G., Global’naya gidrologiya. Protsessy i prognozy (Global Hydrology. Processes and Predictions). Moscow: GEOS, 2017.

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