Skip to main navigation Skip to search Skip to main content

Incorporating remote sensing data in physically based distributed agro-hydrological modelling

  • E. Boegh
  • , M. Thorsen
  • , M.B. Butts
  • , S. Hansen
  • , J.S. Christiansen
  • , P. Abrahamsen
  • , C.B. Hasager
  • , N.O. Jensen
  • , P. van Der Keur
  • , J.C. Refsgaard
  • , K. Schelde
  • , H. Soegaard
  • , A. Thomsen

Research output: Contribution to journalArticleResearchpeer-review

141 Citations (Scopus)

Abstract

Distributed information on land use and vegetation parameters is important for the correct predictions of evapotranspiration rate and soil water balance while, in turn, the growth and function of vegetation are also highly dependent on the soil water availability. In this study, the relationship between the soil water balance and the vegetation growth is represented by coupling a hydrological model (MIKE SHE) and a vegetation-SVAT model (Daisy) which simulates the interactions between soil, vegetation and atmosphere including the seasonal variation in plant structure and function. Because the coupling of process models is accompanied by increasing difficulties in obtaining values for the numerous parameters required, the utility of satellite data to set up, verify and update such a model system is the focus of the present paper. To achieve spatially distributed information on surface conditions, field data of leaf area index (L) and eddy covariance fluxes were collected, and high-resolution remote sensing (RS) data were acquired to produce maps of land cover, leaf area index and evapotranspiration rates (E). The land cover map is used to set up the model which is run throughout 1998 for a Danish agricultural area with a time step of 1 h. In May, the spatial heterogeneity of the leaf area index is at its largest, and the model performance is evaluated in time and space using the field measurements and the RS-based maps of L and E. Finally, the effect of adjusting the simulated L to match the RS-based L is investigated. The adjustment strategy includes synchronization of all vegetation parameters to maintain congruity of the model canopy representation. While the predicted crop yields were improved, a large micro-scale spatial heterogeneity in L within the operational modelling units restricted improvements in the simulated E. The delineation of modelling units that are homogeneous with respect to the assimilated variable, L, requires separation of land use classes with respect to the temporal development in vegetation cover.

Original languageEnglish
Pages (from-to)279-299
Number of pages21
JournalJournal of Hydrology
Volume287
Issue number1-4
DOIs
Publication statusPublished - 25 Feb 2004
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 15 - Life on Land
    SDG 15 Life on Land

Keywords

  • Data assimilation
  • Distributed model
  • Evapotranspiration
  • Remote sensing
  • Validation

Programme Area

  • Programme Area 2: Water Resources

Fingerprint

Dive into the research topics of 'Incorporating remote sensing data in physically based distributed agro-hydrological modelling'. Together they form a unique fingerprint.

Cite this