Mapping spatial and temporal variation in tree water use with an elevation model and gridded temperature data

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@Article{Gharun:2015:AFM,
  author =       "Mana Gharun and Tarryn L. Turnbull and 
                 Joseph Henry and Mark A. Adams",
  title =        "Mapping spatial and temporal variation in tree water
                 use with an elevation model and gridded temperature
                 data",
  journal =      "Agricultural and Forest Meteorology",
  volume =       "200",
  pages =        "249--257",
  year =         "2015",
  ISSN =         "0168-1923",
  DOI =          "doi:10.1016/j.agrformet.2014.09.027",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0168192314002512",
  abstract =     "Tree water use is a major component of the water
                 balance in forested catchments of semi-arid areas, as
                 more than 80percent of the incoming rainfall may be
                 used by overstory trees. Managers are unable to easily
                 predict water use and thus water yield, for the
                 majority of eucalypt-dominated catchments in south-east
                 Australia, owing to the variety of dominant and
                 co-dominant species, their distributions with respect
                 to landform, and the lack of species- and
                 landform-specific knowledge of the regulation of water
                 use. Moreover, the costs incurred to quantify input
                 variables for available complex, process-based models,
                 generally encourage finding alternative approaches.
                 This study tested the adequacy of using just two easily
                 measured variables for estimating rates of tree water
                 use, using a model derived from data-learning
                 techniques. The inputs are (1) measured daily
                 atmospheric demand for water and (2) potential incoming
                 radiation derived from surface topography and solar
                 declination. Artificial neural networks (ANNs) and
                 genetic programming (GP) models were trained and
                 validated using in situ observations of vapour pressure
                 deficit (VPD) and estimates of potential solar
                 radiation (Qpot), for a period of two years, at each of
                 10 forest stands across the high country of the states
                 of New South Wales and Victoria. The models were tested
                 using a random 50percent of the collected data that was
                 independent, i.e. not used in model development.
                 Atmospheric demand was selected because it strongly
                 affects tree water use irrespective of site and
                 species. Potential solar radiation was selected as a
                 proxy for radiation, because it is relatively easy to
                 estimate for any location for which elevation data are
                 available in digital format, and since radiation
                 strongly controls photosynthesis (through stomatal
                 behaviour) and thermal balance. Genetic programming
                 resulted in models better able to predict rates of sap
                 flux. A selected GP model was able to describe the
                 relationship between tree sap flux, VPD, and potential
                 radiation with good accuracy, and was used to map tree
                 water use across the catchment.",
  keywords =     "genetic algorithms, genetic programming, Potential
                 incoming radiation, Sap flux, Eucalypt, Neural
                 networks",
}

Genetic Programming entries for Mana Gharun Tarryn L Turnbull Joseph Henry Mark A Adams

Citations