Cultural advice

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

Aboriginal and Torres Strait Islander peoples are advised that ANU Library collections may include images, names, voices, and other representations of deceased persons.

Material in the collection may contain terms, language or views that reflect the period in which the item was created and may be considered inappropriate today.

Scaling of potential evapotranspiration with MODIS data reproduces flux observations and catchment water balance observations across Australia

dc.contributor.authorGuerschman , Juan Pablo
dc.contributor.authorVan Dijk, Albert
dc.contributor.authorMattersdorf, Guillaume
dc.contributor.authorBeringer, Jason
dc.contributor.authorHutley, Lindsey
dc.contributor.authorLeuning, Ray
dc.contributor.authorPipunic, Robert C.
dc.contributor.authorSherman, Bradley
dc.date.accessioned2015-12-13T22:45:34Z
dc.date.issued2009
dc.date.updated2016-02-24T09:40:50Z
dc.description.abstractWe developed a new algorithm for estimating monthly actual evapotranspiration (AET) based on surface reflectance from MODIS-Terra and interpolated climate data. The algorithm uses monthly values of the Enhanced Vegetation Index (EVI) and the Global Vegetation Moisture Index (GVMI) derived from the MODIS nadir bidirectional reflectance distribution function - adjusted reflectance product (MOD43B4) to scale Priestley-Taylor potential evapotranspiration derived from the climate surfaces. The EVI is associated with evapotranspiration through its relationship with leaf area index. The GVMI allows separation between surface water and bare soil when EVI is low and provides information on vegetation water content when EVI is high. The model was calibrated using observed AET data from seven sites in Australia, including two forests, two open savannas, a grassland, a floodplain and a lake. Model outputs were compared with four year average difference between precipitation and streamflow (a surrogate for mean AET) in 227 unimpaired catchments across Australia. We tested four different model configurations and found that the best results both in the calibration and evaluation datasets were obtained when a precipitation interception term (Ei) and the GVMI were incorporated into the model. The Ei term and the GVMI improved AET estimates in the forest, savanna and grassland sites and in the lake and floodplain sites respectively. The most comprehensive model estimated monthly AET at the seven calibration sites with a RMSE of 18.0 mm mo-1 (22% of the mean AET, r2 = 0.84). In the evaluation dataset, mean annual AET was estimated with a RMSE of 137.44 mm y-1 (19% of the mean AET, r2 = 0.61). The model was able to reproduce the main spatial and temporal patterns in AET across Australia. The main advantages of the proposed model are that it uses a single set of parameters (i.e. does not need an auxiliary land cover map) and that it is able to estimate AET in areas with significant direct evaporation, including lakes and floodplains. Crown
dc.identifier.issn0022-1694
dc.identifier.urihttp://hdl.handle.net/1885/79852
dc.publisherElsevier
dc.sourceJournal of Hydrology
dc.subjectKeywords: Actual evapotranspirations; Australia; Average differences; Bare soils; Bi-directional reflectance distribution functions; Calibration sites; Catchment water balances; Climate datum; Comprehensive models; Data sets; Direct evaporations; Enhanced vegetatio Australia; Evapotranspiration; MODIS; Remote sensing
dc.titleScaling of potential evapotranspiration with MODIS data reproduces flux observations and catchment water balance observations across Australia
dc.typeJournal article
local.bibliographicCitation.issue1-2
local.bibliographicCitation.lastpage119
local.bibliographicCitation.startpage107
local.contributor.affiliationGuerschman , Juan Pablo, CSIRO
local.contributor.affiliationVan Dijk, Albert, College of Medicine, Biology and Environment, ANU
local.contributor.affiliationMattersdorf, Guillaume, CSIRO
local.contributor.affiliationBeringer, Jason, Monash University
local.contributor.affiliationHutley, Lindsey, Charles Darwin University
local.contributor.affiliationLeuning, Ray, CSIRO
local.contributor.affiliationPipunic, Robert C., The University of Melbourne
local.contributor.affiliationSherman, Bradley, CSIRO Land and Water
local.contributor.authoruidVan Dijk, Albert, u5250651
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.identifier.absfor040607 - Surface Processes
local.identifier.absseo960913 - Water Allocation and Quantification
local.identifier.ariespublicationf5625xPUB8224
local.identifier.citationvolume369
local.identifier.doi10.1016/j.jhydrol.2009.02.013
local.identifier.scopusID2-s2.0-63649128940
local.identifier.thomsonID000266130600010
local.type.statusPublished Version

Downloads

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
01_Guerschman _Scaling_of_potential_2009.pdf
Size:
3.35 MB
Format:
Adobe Portable Document Format