Simulated hydrologic response to projected changes in precipitation  and temperature in the Congo River basin

Aloysius, Noel; Saiers, James

doi:https://doi.org/10.5194/hess-21-4115-2017

Articles | Volume 21, issue 8

https://doi.org/10.5194/hess-21-4115-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/hess-21-4115-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 21, issue 8

Research article

|

16 Aug 2017

Research article |

| 16 Aug 2017

Simulated hydrologic response to projected changes in precipitation and temperature in the Congo River basin

Noel Aloysius and James Saiers

Supplement

https://doi.org/10.5194/hess-21-4115-2017-supplement

Data sets

Evaluation of historical and future simulations of precipitation and temperature in Central Africa from CMIP5 climate models (http://hydrology.princeton.edu/data.php) N. Aloysius, J. Shefﬁeld, J. E. Saiers, H. Li, H. and E. F. Wood https://doi.org/10.1002/2015JD023656

Long-Term Mean Monthly Discharges and Annual Characteristics of GRDC Stations Global Runoff Data Center http://www.bafg.de/GRDC/EN/Home/homepage_node.html

Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling (http://hydrology.princeton.edu/data/pgf/Readme.txt) J. Shefﬁeld, G. Goteti, and E. F. Wood https://doi.org/10.1175/JCLI3790.1

Global River Discharge, 1807–1991, Version 1.1 (RivDIS), Data set, Oak Ridge National Laboratory Distributed Active Archive Center C. J. Vorosmarty, B. M. Fekete, and B. A. Tucker http://www.daac.ornl.gov

Short summary

With the aid of a hydrological model and outputs from global climate models (GCMs), we elucidate the spatiotemporal variability of rainfall–runoff in the Congo River basin in the past and in the future under multiple greenhouse gas emission scenarios. We show that the hydrologic model that is forced with outputs from 25 GCMs and two emission scenarios reveal a range of projected changes in precipitation and runoff, and that runoff dynamics are highly sensitive to GCM forcing.