Errors and parameter estimation in precipitation-runoff modeling. 1. Theory

Errors in complex conceptual precipitation‐runoff models may be analyzed by placing them into a statistical framework. This amounts to treating the errors as random variables and defining the probabilistic structure of the errors. By using such a framework, a large array of techniques, many of which...

Full description

Saved in:
Bibliographic Details
Published in:Water resources research 1985-08, Vol.21 (8), p.1195-1213
Main Author: Troutman, B.M
Format: Article
Language:English
Subjects:
ERRORS
ESCORRENTIA
HIDROLOGIA
HYDROLOGIE
HYDROLOGY
MODELE
MODELOS
PARAMETRIC METHODS
PRECIPITACION ATMOSFERICA
PRECIPITATION
RUISSELLEMENT
RUNOFF
RUNOFF WATER
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Errors in complex conceptual precipitation‐runoff models may be analyzed by placing them into a statistical framework. This amounts to treating the errors as random variables and defining the probabilistic structure of the errors. By using such a framework, a large array of techniques, many of which have been presented in the statistical literature, becomes available to the modeler for quantifying and analyzing the various sources of error. A number of these techniques are reviewed in this paper, with special attention to the peculiarities of hydrologic models. Known methodologies for parameter estimation (calibration) are particularly applicable for obtaining physically meaningful estimates and for explaining how bias in runoff prediction caused by model error and input error may contribute to bias in parameter estimation.
ISSN:0043-1397
1944-7973
DOI:10.1029/WR021i008p01195