alternative methods to predict actual evapotranspiration illustrate the importance of accounting for phenology – part 2: the event driven phenology model

alternative methods to predict actual evapotranspiration illustrate the importance of accounting for phenology – part 2: the event driven phenology model

;V. Kovalskyy;G. M. Henebry
tetrahedron letters 2012 Vol. 9 pp. 161-177
180
kovalskyy2012biogeosciencesalternative

Abstract

Evapotranspiration (ET) flux constitutes a major component of both the water and energy balances at the land surface. Among the many factors that control evapotranspiration, phenology poses a major source of uncertainty in attempts to predict ET. Contemporary approaches to ET modeling and monitoring frequently summarize the complexity of the seasonal development of vegetation cover into static phenological trajectories (or climatologies) that lack sensitivity to changing environmental conditions. The Event Driven Phenology Model (EDPM) offers an alternative, interactive approach to representing phenology. This study presents the results of an experiment designed to illustrate the differences in ET arising from various techniques used to mimic phenology in models of land surface processes. The experiment compares and contrasts two realizations of static phenologies derived from long-term satellite observations of the Normalized Difference Vegetation Index (NDVI) against canopy trajectories produced by the interactive EDPM trained on flux tower observations. The assessment was carried out through validation of predicted ET against records collected by flux tower instruments. The VegET model (Senay, 2008) was used as a framework to estimate daily actual evapotranspiration and supplied with seasonal canopy trajectories produced by the EDPM and traditional techniques. The interactive approach presented the following advantages over phenology modeled with static climatologies: (a) lower prediction bias in crops; (b) smaller root mean square error in daily ET – 0.5 mm per day on average; (c) stable level of errors throughout the season similar among different land cover types and locations; and (d) better estimation of season duration and total seasonal ET.

Citation

ID: 242654
Ref Key: kovalskyy2012biogeosciencesalternative
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
242654
Unique Identifier:
10.5194/bg-9-161-2012
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet