Publications

Listed below are selected publications relating to SILO.

KEY paper

• Jeffrey, S.J., Carter, J.O., Moodie, K.M and Beswick, A.R. (2001). Using spatial interpolation to construct a comprehensive archive of Australian climate data, Environmental Modelling and Software, Vol 16/4, pp 309-330.
  
  This is the Patched Point Dataset and Data Drill primary reference. This article describes the interpolations of daily rainfall, temperature, radiation, evaporation and vapour pressure that have been used in the Data Drill and the Patched Point Dataset. An estimation of expected errors is included. An update (PDF, 18K, last updated 09:13AM, 24 June 2010)* describes the reduction in errors achieved by interpolation improvements.

Reviews

• Beesley, C. A., Frost, A. J. and Zajaczkowski, J. A comparison of the BAWAP and SILO spatially interpolated daily rainfall datasets. 18th World IMACS / MODSIM Congress, Cairns, Australia 13-17 July 2009. http://www.mssanz.org.au/modsim09/I13/beesley.pdf (PDF)* 
• Tozer, C. R., Kiem, A. S., and Verdon-Kidd, D. C.: On the uncertainties associated with using gridded rainfall data as a proxy for observed, Hydrol. Earth Syst. Sci. Discuss., 8, 8399-8433, doi:10.5194/hessd-8-8399-2011, 2011 http://www.hydrol-earth-syst-sci-discuss.net/8/8399/2011/hessd-8-8399-2011.html

Methodology

• Carter, J.O., Flood, N.F., Danaher, T., Hugman, P., Young, R., Duncalfe, F., Barber, D., Flavel, R., Beeston, G., Mlodawski, G., Hart, D., Green, D., Richards, R., Dudgeon, G., Dance, R., Brock, D. and Petty, D. (1996). Development of data rasters for model inputs, In Development of a National Drought Alert Strategic Information System Volume 3. Final Report on QPI 20 to Land and Water Resources Research and Development Corporation.
• Hutchinson, M.F. (1995). Interpolating mean rainfall using thin plate smoothing splines, International Journal of Geographical Information Systems, 9:385-403.
• Queensland Government. The Natural Resources and Mines climate-archive rainfall surfaces. Department of Natural Resources and Mines.
  
  This report describes the algorithm currently used by DERM for rainfall interpolation. It is based heavily on Jeffrey et al. (2001).
• Rayner, D.P., Moodie, K.B., Beswick, A.R., Clarkson, N.M., Hutchinson, R.L. (2004), New Australian daily historical climate surfaces using CLIMARC (PDF, 2.5M, last updated 09:13AM, 24 June 2010)*. Queensland Department of Natural Resources, Mines and Energy Report QNRME04247.
• Wahba, G. and Wendelberger, J. (1980). Some new mathematical methods for variational objective analysis using splines and cross validation, Monthly Weather Review, 108:1122-1143.

Modelling evaporation and evapotranspiration

• Allen, R.G., Pereira, L.S., Raes, D. and Smith M. (1998). Crop evapotranspiration - Guidelines for computing crop water requirements. FAO Irrigation and drainage Paper 56. Food and Agriculture Organization of the United Nations, p.300.
  
  This is the original paper for the calculation of FAO56 reference evapotranspiration.
• Australian Academy of Science (2004). Pan evaporation: An example of the detection and attribution of trends in climate variables. Proceedings of a workshop held at the Shine Dome, Australian Academy of Science, Canberra 22-23 November 2004. Roger M Gifford (ed.). http://www.science.org.au/natcoms/nc-ess/documents/nc-ess-pan-evap.pdf (PDF)* 
• Chiew, F. H. S., and T. A. McMahon (1991). Applicability of Morton’s and Penman’s evapotranspiration estimates in rainfall-runoff modelling. Water Resources Bulletin, 27, 611-620.
  
  Chiew compared Morton’s wet environment evapotranspiration with Penman’s potential evapotranspiration. Both are similar in wet conditions, but Morton’s is smaller than Penman’s in dry conditions.
  
  Abstract: Estimates of the upper constraint on actual evapotranspiration are required as input data in the majority of rainfall-runoff models. This paper compares and discusses the applicability of Penman’s potential evapotranspiration estimates and Morton’s wet environment evapotranspiration estimates in rainfall-runoff modelling applications. Morton’s wet environment evapotranspiration depends only on the atmospheric variables and is the estimate of evapotranspiration that would occur when water supply is not limiting. It is a conceptually more correct representation of the upper constraint on actual evapotranspiration compared to Penman’s potential evapotranspiration which is dependent on the water supply to the soil-plant surfaces. Although Penman’s potential evapotranspiration and Morton’s wet environment evapotranspiration are two different quantities, comparison of the two estimates using data from different climatic regions throughout Australia indicate that they provide similar magnitudes of the upper limit of actual evapotranspiration at moderate climatic conditions when reliable estimates are required in rainfall-runoff models. The two estimates can therefore be used interchangeably in rainfall-runoff modelling applications.
  
• Chiew, F, Wang, Q., McConachy, F., James, R., Wright, W. and deHoedt, G., (2002). Evapotranspiration Maps for Australia. (PDF)* In Wang et al. 2002.
• Doyle, P. (1990). Modelling catchment evaporation: an objective comparison of the Penman and Morton approaches. Journal of Hydrology, 121, 257-276.
  
  Abstract: The first uses the more traditional approach: evaporation is taken as Penman potential evaporation (PE), unless water is not freely available, in which case the reduction of actual evaporation (AE) from PE is calculated using a simple Thornthwaite-style soil-moisture model. The second model makes use of the relatively recent work by Bouchet and Morton which suggests, inter alia, that AE and PE are inversely related in the absence of an abundant supply of moisture. The resulting objective criteria of efficiency for the final models are similar, but other results from the model calibration process indicate some of the relative strengths and weaknesses of the two models. In particular, it is shown that the Bouchet-Morton approach provides a valuable alternative to the empiricism of the Thornthwaite-style reduction of AE from PE, but this is achieved at a high cost: the introduction of a strong degree of empiricism into the process of advection modelling.
• Granger, R. J., and D. M. Gray (1990). Examination of Morton’s CRAE model for estimating daily evaporation from field-sized areas. Journal of Hydrology, 120, 309-325.
  
  This paper shows that Morton’s method has several deficiencies: 1) The assumption water transfer coefficient is not dependent on wind, leading to overestimate at low wind and underestimate at high wind. 2) The calculation of albedo may lead to significant errors. It also shows that the use of Morton’s method is not very good for short periods such as daily.
  
  Abstract: Daily estimates by Morton’s complementary relationship areal evapotranspiration (CRAE) model of atmospheric radiation fluxes during the summer months are compared with monitored values. It is shown that errors in estimation of the extra-terrestrial flux, the transmittancy of clouds to short-wave radiation, the surface albedo and the net long-wave flux result in standard deviations of the difference between "modelled’ and "measured’ net all-wave radiation for 1-, 5- and 10-day periods of 2.58, 1.8 and 1.50 MJ m-2 day-1 respectively. The assumption in CRAE that the vapour transfer coefficient is independent of wind speed may lead to appreciable error in computing evapotranspiration. A procedure for incorporating a wind correction factor is described and the improvement in estimating regional evaporation is illustrated.
  
• Hobbins M.T., Ramirez J.A., Brown T.C., and Claessens L.H.J.M (2001). The complementary relationship in estimation of regional evapotranspiration: The Complementary Relationship Areal Evapotranspiration and Advection-Aridity models. Water Resources Research, 1367-1387.
  
  Abstract: Two implementations of the complementary relationship hypothesis for regional evapotranspiration, the Complementary Relationship Areal Evapotranspiration (CRAE) model and the Advection-Aridity (AA) model, are evaluated against independent estimates of regional evapotranspiration derived from long-term, large-scale water balances (1962-1988) for 120 minimally impacted basins in the conterminous United States. The CRAE model overestimates annual evapotranspiration by 2.5% of mean annual precipitation, and the AA model underestimates annual evapotranspiration by 10.6% of precipitation. Generally, increasing humidity leads to decreasing absolute errors for both models, and increasing aridity leads to increasing overestimation by the CRAE model and underestimation by the AA model, with the exception of high, arid basins, where the AA model overestimates evapotranspiration. Overall, the results indicate that the advective portion of the AA model must be recalibrated before it may be used successfully on a regional basis and that the CRAE model accurately predicts monthly regional evapotranspiration.
  
• Morton, F. I. (1983a). Operational estimates of areal evapotranspiration and their significance to the science and practice of hydrology. Journal of Hydrology, 66, 1-76.
  
  This is the original paper for Morton’s calculations including shallow lake evaporation.
• Morton, F. I. (1983b). Operational estimates of lake evaporation. Journal of Hydrology, 66, 77-100.
  
  This paper provides theories of evaporation over shallow lakes, deep lakes and ponds. The actual calculation of Morton shallow lake evaporation is provided in Morton, F. I. (1983a).
• Morton, F. I. (1986). Practical estimates of lake evaporation. Journal of Climate & Applied Meteorology, 25, 371-387.
  
  This paper provides a lot of cases comparing lake evaporation, pan evaporation and various estimates.
• Nash, J. E. (1989). Potential evaporation and "the complimentary relationship". Journal of Hydrology, 111, 1-7.
  
  This paper gives a thorough analysis the theoretical difference between Morton and Penman’s approach to calculate evapotranspiration.
• Rayner, D.P. (2005), Australian synthetic daily Class A pan evaporation (PDF, 1.8M, last updated 09:13AM, 24 June 2010)*. Queensland Department of Natural Resources and Mines. Technical Report.

* Requires Adobe Reader

Last updated 29 November 2011

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