Pelak & Porporato, 2018

Talk/Poster

The ecohydrological cost of lawns

Pelak, Norman F., and Amilcare Porporato (2018)
American Geophysical Union Fall Meeting, Washington, DC, December 10-14, 2018  

Abstract

Vegetation-mediated evapotranspiration (ET) plays a significant role in land-atmosphere interactions by influencing the energy and water budgets. Although plant physiological dynamics control the magnitude and timing of water transfer through the soil-plant-atmosphere continuum, most land surface models simulate ET without explicitly accounting for plant hydraulics. While interest in incorporating plant hydraulics in land surface models has grown, doing so is challenged in part by parametrization difficulties due to the limited measurements of hydraulic traits and heterogeneity of traits at a stand scale.

This study investigates the conditions under which plant hydraulic models can better simulate observed ET fluxes than conventional models. To overcome uncertainty related to parametrization, we adopt a model-data fusion approach to retrieve plant hydraulic traits using a soil-plant-atmosphere continuum model and observed ET at multiple FLUXNET sites covering a range of climate and land cover types. Prior knowledge on physiologically reasonable ranges and coordination among hydraulic traits are incorporated to reduce equifinality. Hydraulic traits, and their associated uncertainties, are estimated using a Markov Chain Monte Carlo method. ET estimated using these retrieved hydraulic traits is then compared with ET from the widely used Penman-Monteith approach across a range of temporal scales. We will discuss differences in estimated ET between the two approaches to understand the role of climate and soil types in controlling the impact of plant hydraulics. The results will facilitate further integration of plant hydraulics in land surface models at larger scales.

Citation

Pelak, Norman F., and Amilcare Porporato (2018): The ecohydrological cost of lawns. American Geophysical Union Fall Meeting, Washington, DC, December 10-14, 2018.

This Paper/Book acknowledges NSF CZO grant support.