Kriging Residuals

Discussion created by perstabo on May 14, 2012
Latest reply on May 15, 2012 by perstabo

Please forgive me if this is a beginner's question, but I am a beginner :)

I have a kriging model of rainfall for an area. For each point rainfall station I have a rainfall total and elevation.
Unfortunately, the root mean squared error is not very good - it's around 13. I wanted to know about different ways to improve my model and reduce the rmse.

I have read that the residuals of kriging (i.e. the actual minus predicted values) for each rainfall station can be themselves kriged and the results of this added back to the original model to improve prediction quality. So my questions are:

1. Is this a valid approach to improving a model, and if so, why?
2. If this is a valid approach, can you provide a quick step by step description of how to add the residual kriging results back to the original kriging model?
3. Do you have any other suggestions for techniques which I could use to improve my kriging results? Note that I also have elevation data, but co-kriging with this hardly seems to improve the model.

I hope this is a sensible question.

Many thanks for all your help

Stephen Vitoria