Connections between groundwater flow and transpiration partitioning
Reed M Maxwell1, Laura E Condon2
1Integrated GroundWater Modeling Center, Department of Geology and Geological Engineering, Colorado School of Mines, Golden, CO, USA. rmaxwell@mines.edu.
Summary
Understanding continental freshwater fluxes is crucial for water resource management. Including lateral groundwater flow significantly increases plant transpiration, improving hydrologic models.
Area of Science:
- Earth and Environmental Sciences
- Hydrology
- Ecology
Background:
- Accurate prediction of hydrologic response and management of terrestrial water resources depend on understanding continental-scale freshwater fluxes.
- A key uncertainty in the terrestrial water balance is the partitioning of evapotranspiration into bare soil evaporation and plant transpiration.
Purpose of the Study:
- To investigate transpiration partitioning at the continental scale using integrated hydrologic simulations.
- To assess the impact of lateral groundwater flow on the partitioning of evapotranspiration.
Main Methods:
- Employed integrated hydrologic simulations coupling vegetation, land-energy processes, and surface/subsurface hydrology.
- Analyzed the relationship between water table depth, latent heat flux, and transpiration partitioning.
- Quantified the effect of including lateral groundwater flow on transpiration partitioning.
Main Results:
- Transpiration partitioning is linked to water table depth and latent heat flux.
- Inclusion of lateral groundwater flow increased transpiration partitioning from 47 ± 13% to 62 ± 12%.
- This highlights the significant role of lateral groundwater flow in the terrestrial water balance.
Conclusions:
- Lateral groundwater flow, often simplified or excluded in Earth system models, is critical for accurate hydrologic simulations.
- Accounting for lateral groundwater flow may reconcile discrepancies between observations and global models of terrestrial water fluxes.
- This research provides a missing link for improving continental-scale water resource management and prediction.
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