Dear all,
Assuming that we identified different sources of errors in hydrological modelling. Lets say rainfall is estimated with its error(uncertainty) band, the ET is estimated with its error(uncertainty) band, and other inputs (model parameters) of the model also have been estimated with its errors, what are the state of art in propagating all the errors into the discharge uncertainty. Unlike the rainfall and ET which is instantaneous each-time step errors, there will also be some initial condition error, that i want to include in the error propagation . So what is the best way to include all of these ?
Best regards
Wuletawu
My colleagues Dmitri Kavetski and Mark Thyer have published a lot on this topic - I'd recommend having a look at their Bayesian Total Error Analysis (BATEA) papers (e.g. "Kuczera G, Kavetski D, Franks SW and Thyer M (2006) Towards a Bayesian total error analysis of conceptual rainfall-runoff models: Characterizing model error using storm-dependent parameters, Journal of Hydrology, 331(1-2), pp. 161-177.")
Source of error in the underlying hydrological models are very different and require separate study and their integration.
We must see what is the purpose of modeling?
Or what we want model the phenomenon?
Appropriate to answer this question, we seek to cause errors in the model
Dear Fulvio M.Rivano,
Thanks for interesting attachments, they are close to what I am looking.
Best regards
wuletawu
Dear Wuletawu Abera,
You may take a look at my paper:
Rimmer, A., & Gal, G. (2003). Estimating the saline springs component in the solute and water balance of Lake Kinneret, Israel. Journal of hydrology, 284(1), 228-243.
It includes detailed, yet simple analysis of propagation of errors in lake water and solute balance.
Alon Rimmer
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