Hydromorphological attributes for all Australian river reaches

Hydromorphological data including temporal and spatial river width dynamics, flow regime, and river gradient for 1.4 million Australian river reaches are presented. This river hydromorphology dataset is developed based on surface water recurrence information from the WOfS Landsat-derived dynamic water mapping product and GIS-based hydrological features from the Australian Geofabric. We also propose a parameter which can be used to classify reaches by the degree to which flow regime tends towards permanent, frequent, intermittent, or ephemeral. This dataset provides fundamental information for understanding hydrological, biogeochemical, and ecological processes in floodplain–river systems; describing river width features in hydrological modelling; estimating river depth and discharge; assessing river conveyance capacity; identifying flooding-prone areas, and determining potential locations for satellite-based river gauging.


Hou, J., van Dijk, A. I. J. M., Renzullo, L. J., Vertessy, R. A., and Mueller, N.: Hydromorphological attributes for all Australian river reaches derived from Landsat dynamic inundation remote sensing, Earth Syst. Sci. Data, 11, 1003-1015, https://doi.org/10.5194/essd-11-1003-2019, 2019.




Global 5-km resolution estimates of secondary evaporation including evaporation

A portion of generated surface and groundwater resources evaporates from wetlands, water bodies and irrigated areas. At the global scale, a lack of detailed water balance studies and direct observations limits our understanding of the magnitude and spatial and temporal distribution of this ‘secondary’ evaporation.

We assimilated satellite-derived information into the landscape hydrological model W3 at 0.05°, or ca. 5km resolution globally. The assimilated data are all derived from MODIS observations, including surface water extent, surface albedo, vegetation cover, leaf area index, canopy conductance and land surface temperature (LST). The information from these products is imparted on the model in a simple but efficient manner, through a combination of direct insertion of the surface water extent, an evaporation flux adjustment based on LST and parameter nudging for the other observations.


van Dijk, A. I. J. M., Schellekens, J., Yebra, M., Beck, H. E., Renzullo, L. J., Weerts, A., and Donchyts, G.: Global 5 km resolution estimates of secondary evaporation including irrigation through satellite data assimilation, Hydrol. Earth Syst. Sci., 22, 4959-4980, https://doi.org/10.5194/hess-22-4959-2018, 2018.


Data access

You can find daily 0.05° estimates of ET and its components for the period 2000-2014 via our OpenDAP THREDDS catalogue:  http://dapds00.nci.org.au/thredds/catalog/ub8/global/W3/v2/0_05d/catalog.html

Available ET variables include:

  • potential evaporation (E0)
  • total ET (ETtot)
  • secondary ET (Elat)
  • transpiration (Et)
  • soil evaporation (Es)
  • water evaporation (Er)

Estimates of other radiation, water and energy balance terms as well as gross primary production are also available from the same location.


  • It is recommended to disregard data for 2000 as spin-up artefacts can occur.
  • secondary ET has not been attributed to the evaporation mechanism. A method to do so can be found in the reference paper.

Satellite-based river gauging

On this web page you can find background information and data for satellite gauging reaches (SGRs) as published in Van Dijk et al. (2016). You are welcome to use these data in any way you see fit. To cite them do not refer to these web site but to the original paper, which includes this URL:

Van Dijk, A. I. J. M., G. R. Brakenridge, A. J. Kettner, H. E. Beck, T. De Groeve, and J. Schellekens (2016), River gauging at global scale using optical and passive microwave remote sensing, Water Resour. Res., 52, doi:10.1002/2015WR018545. LINK TO ARTICLE  

The easiest way to explore the available SGRs is by downloading the KML-formatted files and exploring them in Google Earth, which also gives you direct access to estimated hydrographs, performance metrics and the location of SGR cells. The KML files are organised and named by upstream catchment area, viz. large (1000-10,000 km2) and largest (>10,000 km2) and by performance, viz. best (Rmax>0.9), good (0-8-0.9), moderate (0.6-0.8) and poor (<0.6) (see paper for further details on the calculation of Rmax). DATA LINK

Alternatively, if you wish to replicate our experiment or undertake your own research using the same data we used, you can download all constructed SGRs including estimated the inundation signal from MODIS or GFDS, as well as the discharge observations used to construct and evaluate the SGRs. The data are formatted in 3 separate, self-described NetCDF files. DATA LINK

Fig7 Examples of good, bad and ugly satellite-gauging reaches (see paper for detailed explanation)

Global above-ground biomass carbon (v1.0)

ABC_450_ms Global estimates of annual average above-ground biomass carbon (ABC) for 1993-2012, based on a harmonised time series of Vegetation Optical Depth (VOD) derived from a series of satellite passive microwave instruments. Both VOD and ABC are available. [data description – download data]
Reference: Liu, Y.Y., A.I.J.M. van Dijk, R.A.M. de Jeu, J.G. Canadell, M.F. McCabe, J.P. Evans and G. Wang (2015) Recent reversal in loss of global terrestrial biomass, Nature Climate Change 5, doi: 10.1038/NCLIMATE2581. [read]


Global Water Cycle Reanalysis

 Estimates of monthly average water storage in different components of the water cycle for 2003-2012 at 1⁰. Estimates were derived by assimilating satellite data into a model ensemble. Data are available for sub-surface (soil and groundwater) storage and storage in ice & snow, rivers, lakes, and oceans.

Reference: Van Dijk, A. I. J. M., Renzullo, L. J., Wada, Y., and Tregoning, P. A global water cycle reanalysis (2003–-2012) merging satellite gravimetry and altimetry observations with a hydrological multi-model ensemble (2014) Hydrology and Earth System Sciences 18, 2955-2973. [read]


Global Canopy Conductance

Canopy conductance at a global scale based on three vegetation indices (NDVI, EVI and Kc) derived from the MODIS MCD43C4 reflectance product. The data is produced globally at 0.05⁰ and every 8 days. Monthly and annual climatologies are also available.

Reference: Yebra, M., Van Dijk, A., Leuning, R., Huete, A., Guerschman, J.P., 2013. Evaluation of optical remote sensing to estimate actual evapotranspiration and canopy conductance. Remote Sensing of Environment, 129, 250-261 [read]


High-resolution Evapotranspiration for Australia

CMRSETEstimates of actual evapotranspiration across Australia based on MODIS reflectance and short wave infra-red data, and gridded meteorological surfaces.  The data have 8-day and 500 m resolution.

Reference: Guerschman J.P., van Dijk, A.I.J.M., Mattersdorf, G., Beringer, J., Hutley, L.B., Leuning, R., Pipunic, R.C. and Sherman, B.S. (2009), Scaling of potential evapotranspiration with MODIS data reproduces flux observations and catchment water balance observations across Australia. Journal of Hydrology, 369, 107-119.  [read]


Global 0.05° Gross Primary Production estimates

GPP in GPP.mean.2000-2012 AmazonGlobal estimates of monthly gross primary production for 2000-2012 at 0.05° resolution (~5 km) derived from MODIS remote sensing using a simple and effective method considering radiation and canopy conductance limitations on GPP.

Reference: Yebra, M, Van Dijk, A.I.J.M., Leuning, R., Guerschman, J.P. (2015) Global vegetation gross primary production estimation using satellite-derived light-use efficiency and canopy conductance, Remote Sensing of Environment 163: 206–216 [ read ]


MSWEP : Multi-Source Weighted-Ensem­ble Pre­cip­i­ta­tion


A new global terres­trial pre­cip­i­ta­tion (P) dataset (1979–2015) with a high 3-hourly temporal and 0.25° spa­tial res­o­lu­tion (Beck et al., 2016). The dataset is unique in that it takes advan­tage of a wide range of data sources, includ­ing gauge, satel­lite, and reanaly­sis data, to obtain the best pos­si­ble P esti­mates at global scale. download data [Australia (THREDDS)Europe (FTP)]

Reference: Beck, H.E., A.I.J.M. van Dijk, V. Lev­iz­zani, J. Schellekens, D.G. Miralles, B. Martens, A. de Roo: MSWEP: 3-hourly 0.25° global grid­ded pre­cip­i­ta­tion (1979–2015) by merg­ing gauge, satel­lite, and reanaly­sis data, Hydrol­ogy and Earth Sys­tem Sci­ences Dis­cus­sions, doi:10.5194/hess-2016–236, 2016.[ read ]