Journal of Remote Sensing & GIS

Assessment of water use of different land covers using surface energy balance algorithms for rainfed agriculture (SEBARA) in Western Victoria, South Australia

World Congress on GIS & Remote Sensing

August 01-03, 2016 New Orleans, Louisiana, USA

Rakhshan Roohi, John A Webb and Simon A Jones

La Trobe University, Australia
RMIT University, Australia

Scientific Tracks Abstracts: J Remote Sensing & GIS

Abstract:

Evaporation and transpiration components of the energy balance are influenced by many factors especially in water-limited ecosystems: surface temperature, soil moisture, vegetation type and growth stage, and atmospheric advection and therefore are the most difficult ones to estimate. Any shift in landuse/Landcover (LULC) can disturb the hydrological balance and thus put stress on the water resources. Following the principals of energy balance equation, Surface Energy Balance Algorithm for Rainfed Agriculture (SEBARA) has been devised to estimate the evapotranspiration (ET) of different LULCs in western Victoria using medium spatial resolution Landsat data. ET estimates of four LULCs: Crops, plantations, natural vegetation and pastures revealed that generally the crops and plantations have 12-20% higher evapotranspirtation rate than the natural vegetation and pasture which is due to lower surface albedo and emissivity, resulting in lower outgoing long wave radiation. As a consequence, the higher available net radiation and lower soil heat flux in crops and plantations result in higher ET rate. It is observed that the tree roots can reach extend down to 12m to access groundwater which is deeper than the 6-8m previously measured. The younger plantation with an open canopy has lower ET than the older plantation, but similar to the pastures and natural vegetation. The cultivated oats have similar evapotranspiration rate as that of old plantation. Overall the ET from pastures is lowest however; the rate depends upon the pasture species. The estimated ET compares well with ET measured using flux tower and adjusted sap flow readings (accuracy >95%).

Biography :

Rakhshan Roohi has completed her first PhD from Colorado State University, USA. She stayed involved in research, research management and education for more than more than 30 years in different capacities at Pakistan Agricultural Research Council. She took an early retirement and moved to Australia and is currently working as a causal staff/Associate Research Fellow at La Trobe University besides perusing her second PhD at La Trobe University, Australia. She has participated in more than 20 international trainings/conferences/workshops mostly related to remote sensing and GIS and has more than 30 publications including journal articles and book chapters.

Email: r.roohi@latrobe.edu.au