hydrologic indicators
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2019 ◽  
Vol 20 (9) ◽  
pp. 1757-1778 ◽  
Author(s):  
Rajesh R. Shrestha ◽  
Alex J. Cannon ◽  
Markus A. Schnorbus ◽  
Hunter Alford

Abstract We describe a state-of-the-art framework for projecting hydrologic impacts due to enhanced warming and amplified moisture fluxes in the subarctic environment under anthropogenic climate change. We projected future hydrologic changes based on phase 5 of the Coupled Model Intercomparison Project global climate model simulations using the Variable Infiltration Capacity hydrologic model and a multivariate bias correction/downscaling method for the Liard basin in subarctic northwestern Canada. Subsequently, the variable importance of key climatic controls on a set of hydrologic indicators was analyzed using the random forests statistical model. Results indicate that enhanced warming and wetness by the end of century would lead to pronounced declines in annual and monthly snow water equivalent (SWE) and earlier maximum SWE. Prominent changes in the streamflow regime include increased annual mean and minimum flows, earlier maximum flows, and either increased or decreased maximum flows depending on interactions between temperature, precipitation, and snow. Using the variable importance analysis, we find that precipitation exerts the primary control on maximum SWE and annual mean and maximum flows, and temperature has the main influence on timings of maximum SWE and flow, and minimum flow. Given these climatic controls, the changes in the hydrologic indicators become progressively larger under the scenarios of 1.5°, 2.0°, and 3.0°C global mean temperature increases above the preindustrial period. Hence, the framework presented in this study provides a detailed diagnosis of the hydrologic changes as well as controls and interactions of the climatic variables, which could be generalized for understanding regional scale changes in subarctic/nival basins.


2016 ◽  
Vol 568 ◽  
pp. 697-711 ◽  
Author(s):  
Michael Bliss Singer ◽  
Lee R. Harrison ◽  
Patrick M. Donovan ◽  
Joel D. Blum ◽  
Mark Marvin-DiPasquale

2016 ◽  
Vol 30 (24) ◽  
pp. 4517-4542 ◽  
Author(s):  
Mun-Ju Shin ◽  
Hyung-Il Eum ◽  
Chung-Soo Kim ◽  
Il-Won Jung

2013 ◽  
Vol 49 (6) ◽  
pp. 1308-1326 ◽  
Author(s):  
Soni M. Pradhanang ◽  
Rajith Mukundan ◽  
Elliot M. Schneiderman ◽  
Mark S. Zion ◽  
Aavudai Anandhi ◽  
...  

2012 ◽  
Vol 93 (8) ◽  
pp. 1219-1231 ◽  
Author(s):  
Sharon E. Nicholson ◽  
Amin K. Dezfuli ◽  
Douglas Klotter

A wealth of historical information on climate and weather exists for the African continent. Documentary information, hydrologic indicators, and rain gauge records have been compiled and combined into a semiquantitative precipitation dataset that extends from 1801 to 1900. That dataset describes “wetness” for 90 regions of Africa, using a seven-category index. A regional gauge dataset for 1901–2000 has been converted to the seven-class system, extending coverage to two centuries. These datasets are available through the Paleoclimate Data Center.


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