Dr Tim McVicar

Dr Tim McVicar leads the Biophysical Dynamics Team in the Living Landscapes Program of CSIRO Environment.
To better manage water resources, agricultural industries and ecosystems across all of Australia dynamic, accurate, high-resolution estimates of AET are needed and Tim generates these using satellite imagery. To (a) accurately estimate AET requires accurate inputs of (b) vegetation dynamics and vegetation attributes; and (c) gridded meteorological data; Tim is a world-class science leader in these three related areas. His expertise is broad straddling scientific domains (ecohydrology and climatology) and geotechnologies (satellite remote sensing and spatial interpolation). He has over 35-years experience researching this field and has led both national and international projects aimed at better monitoring and modelling moisture availability, actual evapotranspiration and vegetation dynamics. By assessing the patterns of these variables (in space and time) the catchment water balance (including catchment water yield) can be better simulated.

His primary areas of research interest include:
1. modelling rates of actual evapotranspiration (AET) across all of Australia at high spatial resolutions (30 m) and at high frequency (monthly) by "blending" satellite AET estimates from Landsat-MODIS and Landst-VIIRS;
2. monitoring vegetation dynamics and trends including Leaf Area Index (LAI) and fraction Absorbed Photosynthetically Available Radiation (fAPAR) for both over-story and under-story vegetation;
3. developing monitoring systems to rapidly assess climate variability (primarily drought conditions) and climate change;
4. developing methods to assess atmospheric water demand, including spatially distributing crop reference evapotranspiration and pan evaporation;
5. developing approaches that enable water resource / forestry / land-use managers to simulate the impact of re-vegetation activities on catchment water yield;
6. develop novel methods to assess error and propagate uncertainty in spatially distributed eco-hydrological analysis and models;
7. understanding surface-energy properties at sub-diurnal time-steps by linking 10-min geostationary Himawari data with hourly meteorological grids.