Annualmeeting:2017 CSDMS meeting-129: Difference between revisions

From CSDMS
(Created page with "{{CSDMS meeting personal information template-2014 |CSDMS meeting first name=Chaopeng |CSDMS meeting last name=Shen |CSDMS meeting institute=Penns |CSDMS meeting city=Universi...")
 
No edit summary
Line 6: Line 6:
|CSDMS meeting country=United States
|CSDMS meeting country=United States
|CSDMS meeting state=Pennsylvania
|CSDMS meeting state=Pennsylvania
|CSDMS meeting email address=231C Sackett Building
|CSDMS meeting email address=cshen@engr.psu.edu
Civil and Environmental Engineering
Pennsylvania State University
|CSDMS meeting phone=8148635844
|CSDMS meeting phone=8148635844
}}
}}

Revision as of 11:19, 2 April 2017






Browse  abstracts




Vicken Hillis choose to not submit an abstract for this conference.

Kuai Fang, Pennsylvania State University University Park Pennsylvania, United States. kxf227@psu.edu
Xinye Ji, Pennsylvania State University University Park Pennsylvania, United States. xzj102@psu.edu


[[Image:|300px|right|link=File:]]In the desert, mountainous region of Southeast California, recently-developed energy plants rely on groundwater resources for their cooling needs. Different cooling methods require vastly different amounts of water. Quantifying regional water balance fluxes such as recharge and trans-valley groundwater flow is challenging due to the importance of run-on infiltration, yet it is important for estimating the impacts of the water withdrawals. Previous research employed isolated groundwater models were run independently using crude and uniform estimate of recharge. Here, we employ a surface-subsurface processes model, PAWS+CLM, to provide estimates of recharge including run-on and mountain front recharge. The properties of the desert mountains, soil and aquifers are constrained by in-situ moisture measurements, hydrostratigraphic surveys, and well logs data. The recharge concentrates along alluvial fans at the mountain edges and at end-of-wash depressions that holds water running down from washes. As a result, the spatial distribution of recharge is very different from a uniform, diffuse recharge commonly assumed by practitioners. Using concentrated recharge, the pumping by solar plants lead to much steeper drawdown than that simulated using commonly assumed diffuse recharge. The land surface model provides a valuable solution to estimating water balance for this data-scarce region.