UNCERTAINTY ASSESSMENT AND ANALYSIS OF THE CALIBRATED PARAMETER VALUES OF AN URBAN STORM WATER-QUALITY MODEL

Real uncertainties in the parameter values of conceptual models used i n hydrology sometimes remain after calibration. While this is unaccept able, uncertainty analysis can provide useful information on the struc tural properties of the model. This information may then be used to mo dify the model or establish the limits of usefulness of the measured d ata. This paper focuses on the estimation and interpretation of the pa rameter uncertainties in such cases. The standard estimation method, b ased on the second-order approximation of the shape of the objective f unction in the vicinity of the optimum parameter set, provides an inac curate description of these uncertainties. Instead a global approach, consisting of scanning the hypercube of the possible parameter values, is shown to give a good overview of these uncertainties. This gives n ot only a good general view of the shape of the objective function, bu t a good basis for interpretation as well. The efficiency of the metho d is illustrated using a four parameter urban stormwater quality model . The main conclusion is that the lack of measured data and its relati ve redundancy cause a significant interaction between the parameters, hindering calibration. Another example is given of something being rep orted by a growing number of authors: that data available in hydrology are only sufficient to support the development of models with limited complexity. (C) 1998 Elsevier Science B.V. All rights reserved.