This project focuses on the seasonal dynamics of Amazon evapotranspiration (ET), its control by land hydrology, and its consequences on regional and continental precipitation. It will tests two hypotheses, (1) the groundwater reservoir under the Amazon can enhance root-zone soil moisture and dry-season ET, and (2) this enhanced ET can influence local and downwind precipitation. Water table observations suggest that the groundwater is sufficiently shallow to influence the land surface, and the literature suggest that Amazon ET is a key driver of regional precipitation.

These hypotheses will be tested in two steps. First, an integrated groundwater-land surface model (LEAF-Hydro, developed by the Rutgers Team) will be used to simulate land surface fluxes forced by observed atmospheric fields (South American Land Data Assimilation System (SALDAS)). LEAF-Hydro has a prognostic groundwater coupled to the soil moisture with hydraulic redistribution (roots as conduits to move water up and down). Various process combinations will be simulated to isolate the effect of deeper model soil, deeper roots, hydraulic redistribution and the presence of the groundwater. Second, the WRF-Hydro will be used as the land model to simulate the wind and humidity fields over South America, which will be used to trace vapor transport pathways using the Dynamic Recycling Model (DRM, developed by the Arizona Team). DRM will delineate, in space and time, the source and sink regions over the continent, and hence the Amazon groundwater will be linked to the climate of the continent.

The research evaluates a potentially fundamental process in the Amazon water cycle: the role of groundwater in ET, and thus improves our understanding of the linkages among terrestrial water stores. It may also have implications to understanding the functions of the world's largest rainforest at the present and in the future under deforestation and climate change. A mechanism whereby deforestation affects the climate is the loss of deep roots and hence a reduced ET and precipitation. This study will shed lights on the functions of deep roots interacting with the groundwater. Under projected future climate with a longer dry season, some models have predicted an Amazon forest die-down, which, via positive carbon feedbacks, may accelerate warming. Improving our understanding of how the Amazon forest survives the dry season today will shed lights on how it may fare in the future.

Agency
National Science Foundation (NSF)
Institute
Division of Atmospheric and Geospace Sciences (AGS)
Application #
1045110
Program Officer
Anjuli Bamzai
Project Start
Project End
Budget Start
2011-07-01
Budget End
2015-06-30
Support Year
Fiscal Year
2010
Total Cost
$307,724
Indirect Cost
Name
Rutgers University
Department
Type
DUNS #
City
Piscataway
State
NJ
Country
United States
Zip Code
08854