Actual evapotranspiration estimation by ground and remote sensing methods: the Australian experience

Abstract

Abstract:On average, Australia is a dry continent with many competing uses for water. Hence, there is an urgent need to know actual evapotranspiration (ET a ) patterns across wide areas of agricultural and natural ecosystems, as opposed to just point measurements of ET a . The Australian Government has tasked the science agencies with operationally developing monthly and annual estimates of ET a and other hydrological variables, and with forecasting water availability over periods of days to decades, as part of its national water assessment programme. To meet these needs, Australian researchers have become leaders in developing large-area methods for estimating ET a at regional and continental scales. Ground methods include meteorological models, eddy covariance towers, sap flow sensors and catchment water balance models. Remote sensing methods use thermal infrared, mid infrared and/or vegetation indices usually combined with meteorological data to estimate ET a . Ground and remote sensing ET a estimates are assimilated into the Australian Water Resource Assessment, which issues annual estimates of the state of the continental water balance for policy and planning purposes. The best ET a models are estimated to have an error or uncertainty of 10% to 20% in Australia. Developments in Australian ET a research over the past 20 years are reviewed, and sources of error and uncertainty in current methods and models are discussed.

Diurnal Dynamics of Wheat Evapotranspiration Derived from Ground-Based Thermal Imagery

“…RMSE and MAE for the complete data set and for different subsets (nighttime: 21.00 h-03.00 h UTC, daytime: 6 h-18.00 h UTC, cloud fraction ≥ 0.8, cloud fraction ≥ 0.2-0.8, cloud fraction < 0.2) are computed (Tables 3 and 4). Calculated errors using T rad,WE and T rad,mean (20- , see [3,4] for recent reviews and [88][89][90][91][92] for studies using ground-based data) and below the range of errors reported for eddy covariance (EC) measurements [42], which are here used as reference data. The highest errors (up to 90%) in latent heat flux estimates (using the surface temperature to predict the sensible heat flux) have been reported for natural semiarid areas [8].…”

“…The diurnal and seasonal cycles of the surface temperature are affected by the relative efficiency of the components of the surface energy balance (SEB) in dissipating the available energy. Thus, SEB key components, such as the turbulent latent (λE) and sensible (H) heat flux, are frequently inferred from observations of the radiometric temperature over a wide range of spatial and temporal scales [1][2][3][4][5][6][7][8][9][10][11][12].…”

Spatial evapotranspiration, rainfall and land use data in water accounting – Part 1: Review of the accuracy of the remote sensing data

“…Although here the period was not sufficiently long to encompass one growing season. The Commonwealth Science and Industrial Research Organisation (CSIRO) in Australia studied the predictions of eight different ET products, at a minimum monthly frequency and at a spatial resolution of at least 5 km, using flux tower observations and watershed data across the entire continent as part of the Water Information Research and Development Alliance (WIRADA) project (Glenn et al, 2011). The studied ET products were based on different methods including largescale water balance modeling, thermal imagery Jupp, 1999, 2002), spectral imagery , and the global MODIS reflectance-based algorithm .…”

“…Since the primary purpose of this study was to quantify errors in accumulated ET, only papers that report errors on ET estimates over a minimum period of one growing cycle which on average is about 5-6 months, hereafter called seasonal ET, were consulted. Papers dealing with ET over shorter periods were thus excluded in our review (e.g., Anderson et al, 2011;Chávez et al, 2008;Gonzalez-Dugo et al, 2009;Mu et al, 2011). This, also, implies that GEWEX (Global Energy and Water Exchanges Project)-related field experiments could not be used because intensive campaigns with multiple flux covered periods of weeks only.…”

“…The free access Landsat-8 data may thus set the directions for near future development of land use classifications, especially when being complemented with Sentinel data. The Finer Resolution Observation and Monitoring -Global Land Cover (Gong et al, 2013) is an example of that.…”