Abstract
Abstract. This study considers the overall uncertainty affecting river flow measurements and proposes a framework for analysing the uncertainty of rating-curves and its effects on the calibration of numerical hydraulic models. The uncertainty associated with rating-curves is often considered negligible relative to other approximations affecting hydraulic studies, even though recent studies point out that rating-curves uncertainty may be significant. This study refers to a ~240 km reach of River Po and simulates ten different historical flood events by means of a quasi-twodimensional (quasi-2-D) hydraulic model in order to generate 50 synthetic measurement campaigns (5 campaigns per event) at the gauged cross-section of interest (i.e. Cremona streamgauge). For each synthetic campaign, two different procedures for rating-curve estimation are applied after corrupting simulated discharges according to the indications reported in the literature on accuracy of discharge measurements, and the uncertainty associated with each procedure is then quantified. To investigate the propagation of rating-curve uncertainty on the calibration of Manning's roughness coefficients further model simulations are run downstream Cremona's cross-section. Results highlight the significant role of extrapolation errors and how rating-curve uncertainty may be responsible for estimating unrealistic roughness coefficients. Finally, the uncertainty of these coefficients is analysed and discussed relative to the variability of Manning's coefficient reported in the literature for large natural streams.
Highlights
During the last decades the increased computational resources and advances in numerical modelling have led to the spread of different hydrological and hydraulic models characterized by different complexity
Considering results obtained from the Traditional approach to rating-curve construction, left and right panels of Fig. 4 reports two examples of empirical rating-curves constructed by fitting Eq (1) to synthetic data for two events characterized by different magnitudes, showing a large part of extrapolation without any data, i.e. for Q > 6000 or 3000 m3 s−1 respectively
No measurement of a physical quantity is exact, or certain, it is always very important to quantify the deviation, or uncertainty, of the measured value relative to the unknown true value. Keeping this concept in mind, we focussed on the quantification of the overall uncertainty that normally affects river discharge measurements and stage-discharge relationships
Summary
During the last decades the increased computational resources and advances in numerical modelling have led to the spread of different hydrological and hydraulic models characterized by different complexity (e.g. mono dimensional model – 1-D model: MIKE11, Danish Hydraulic Institute, 2003, HEC-RAS, Hydrologic Engineering Center, 2001; quasi-twodimensional models, quasi-2-D, or fully 2-D models: LISFLOOD-FP, Bates and De Roo, 2000; TELEMAC, Galland et al, 1991). The capability of mathematical models to well reproduce the hydraulic behaviour of natural rivers is closely related to the availability and accuracy of observed streamflow data for calibrating and validating the models themselves. In this context streamflow data plays a dominant role and the accurate set up of a stagedischarge relation in a specific gauged station becomes of utmost importance for the reliability of results The curve is generally calibrated over a series of h(t) − Q(t) pairs, where h(t) is the water level measured at time t and Q(t) the concurrent river discharge, which, in turn, is often estimated trough the velocity-area method (Herschy, 1999; Fenton and Keller, 2001). For instance uncertainty affects the velocity-area method
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