Sensitivity of monthly rainfall-runoff models to input errors and data length

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Abstract
Two problems are addressed which arise when using monthly water balance models as an aid to making decisions in water resources engineering: what is the influence of data errors on model performance, and what is the data length required in order to obtain reliable models? Two previously defined types of models are used: in PE type models the input series are precipitation and potential evapotranspiration; in P type models the only input is precipitation. The main conclusions are: (1) random errors in precipitation data, when great enough, affect model performance significantly; (2) systematic errors in precipitation data are less important for the estimation of river flow; and (3) a data length of 10 years is necessary and sufficient for a reliable calibration of monthly water balance models of humid basins.