Loading ...
Sorry, an error occurred while loading the content.

GEOSTATS: Interpolating precipitations

Expand Messages
  • Dubois Gregoire
    Greetings to all, I have realised that I have never sent a summary of the answers related to my request of references about the interpolation of precipitation
    Message 1 of 1 , Feb 4, 1997
      Greetings to all,

      I have realised that I have never sent a summary of the answers related to my
      request of references about the interpolation of precipitation (see archives of october 96 )
      and topographic influence on precipitation.

      Here is a rough summary of it

      I would like first to thank

      Dan Cornford
      L. Mariani
      S. Abelli
      Sjur Kolberg
      Thomas Skaugen
      Olivier Jaquet
      Philippe Aubry
      Maribeth Milner
      Pascal Monestiez

      for their references, contacts and other things they have sent me.

      I will just mention here few comments, references AND (!!) brief reviews
      Dan Cornford <CORNFORD@...> sent me which seems to
      summarize the main papers related to this topic these last
      15 years.

      In few words:

      In general rainfall is very strongly correlated with
      altitude, so this will need to be taken into account for
      most time/space scales.

      There have been several papers dealing with interpolation
      of precipitation, but most of these are catchment scale.

      If you have a DEM then kriging with external drift might
      be suitable if you can model the underlying variogram - but
      this of course depends strongly on the scale.

      Here are references & brief descriptions

      1) Bastin, G., Lorent B., Duque C. & Gevers M. 1984.
      Optimal estimation of the average rainfall and optimal selection
      of rangauge locations. Water Resour. Res., 20(4), 463-470.

      Optimal estimation of areal precipitation and gauge location
      A time dependent variogram is modelled scaled by a seasonal component.
      There is no checking of many of the assumptions of homogeneity / stationarity.

      2) Beek, E. G., Stein, A. & Janssen, L. L. F. 1992.
      Spatial variability and interpolation of daily precipitation amount
      Stochastic Hydrology and Hydraulics, 6, 304-320.

      Interpolation of daily precipitation
      Removes outliers (= 3*IQR). Does not use covariates but stratifies the sample
      by coastal. mountain and interior provided more stable covariances.

      3) Bigg, G. R. 1991.
      Kriging and intraregional rainfall variability in England
      International Journal of Climatology, 11, 663-675.

      Comparing rainfall in the UK
      Looks at the relationship between rainfall and elevation and compares
      this in two regions of the UK

      4) Creutin, J.D. & C. Obled. 1982.
      Objective analysis and mapping techniques for rainfall fields:
      an objective comparison.
      Water Resour. Res. 18 (2) 413-431.

      Another comparison of techniques for rainfall mapping
      Variograms estimated from residuals of trend surface analysis will be significantly biased.
      An alternative approach is suggested based on GCV. Log transforms will be of use with rainfall and
      Gandin's algorithm was identified as optimal in this case. Note EOF is a finite version of spectral analysis.

      5) Daly, C., Neilson, R. P. & Phillips, D. L. 1994.
      A statistical-topographic model for mapping climatological precipitation
      over mountanous terrian.
      Journal of Applied Meteorology, 33, 140-158.

      Statistic/topographic precip climate mapping
      Uses a Digital Elevation Model to derive facets, which are then used to establish
      local altitude regression models. Claims superior results to geostats.

      6) Dingman, S.L.D., M. Seely-Reynolds & R.C. Reynolds III. 1988
      Application of kriging to estimating mean annual precipitation in a region
      of orographic influence.
      Water Res. Bull. 24, 329-339

      Kriging of orographic precipitation
      Kriges the raw and orographically corrected precip.
      Finds the latter produces a smoother suface with smaller errors.

      7) Hevesi, J. A., Flint, A. L. & Istok, J. D. 1992a.
      Precipitation estimation in mountainous terrain using multivariate geostatistics .
      1. Structural-analysis.
      Journal of Applied Meteorology, 31, 661-67

      Structural analysis of rainfall and elevation
      Variograms for elevation and rainfall were calculated and a cross variogram fitted using
      the cauchy-schwartz job. Considering a small neighbourhood allowed for the assumption of
      homogeneity to be met.

      8) Hevesi, J. A., Flint, A. L. & Istok, J. D. 1992b.
      Precipitation estimation in mountainous terrain using multivariate geostatistics .2. Isohyetal maps
      Journal of Applied Meteorology, 31, 677-688.

      Cokriging of rainfall and elevation in mountainous areas
      Cokriging reduced the RMSE of prediction by about 50% over kriging. The neighbourhood
      search radius affected the errors in cokriging and should be optimally selected.

      9) Lebel, T., Bastin, G., Obled, C. & Creutin, J. D. 1987.
      On the accuracy of areal rainfall estimation: a case study
      Water Resources Research, 23, 2123-2134.

      Comparison of techniques for areal rainfall estimation
      Kriging is found to give the best estimates in their study. A climatological variogram is used,
      based on an underlying shape and a scaling factor (based on the sample variance).

      10) Tabios, III G. Q. & Salas, J. D. 1985.
      A comparative analysis of techniques for spatial interpolation of precipitation
      Water Resources Bulletin, 21, 3, 365-380

      Comparison of precip interpolators
      Compares the accuracy (at 5 selected sites) of thiessen polygons,
      polynomial surfaces, IDW, OI and kriging. Suggests OI or kriging perform the


      With the confusion, I most probably have forgotten to add other important references.
      Don't hesitate to send me others which will be summarized on the biblio
      web site so as I have said ...3 months ago ...

      Thanks again for the precious help,

      Best regards,


      Gregoire Dubois (PhD student) Tel. 39-332-78.99.44
      Joint Research Centre Fax. 39-332-78.54.66
      Environment Inst. TP 321 Email: gregoire.dubois@...
      I-21020 Ispra (Va), ITALY URL: http://java.ei.jrc.it/rem/gregoire/
      *To post a message to the list, send it to ai-geostats@....
      *As a general service to list users, please remember to post a summary
      of any useful responses to your questions.
    Your message has been successfully submitted and would be delivered to recipients shortly.