Models of river flow, even relatively simple ones such as GenRiver, are over-parameterized relative to the information that we can use to check the statistical validity of the model. There are multiple ways of achieving a similar level of “model fit” between measured and predicted river flow patterns, and the fit obtained may thus be right for the wrong reasons. Using the validated model outside of the calibration range may then be as risky as using a simple regression line. In testing the lack of fit of a model we can benefit from having a null-model: a model that takes basic properties of the data into account, without specific hypotheses about the way rainfall translates into river flow.
Año de publicación
2016
Autores
Idioma
English
Palabras clave
watershed, water cycle, models
