Lecture given during the Hydrology days at University of Roma La Sapienza

1. On the derivation of flow rating
curves in data-scarce environments
Salvatore Manfreda1
1Dipartimento delle Culture Europee e del Mediterraneo: Architettura,
Ambiente, Patrimoni Culturali (DiCEM), Università degli Studi della
Basilicata, Matera, Italia – salvatore.manfreda@unibas.it
Poster SESSIONE I
Giornate dell’Idrologia della
Società Idrologica Italiana 2018, Roma, 18-20 Giugno 2019

2. Methodology
FRCs are generally obtained using
curve fitting methods with river
stage (H) and discharge (Q)
observations.
The most common equation is:
topographic surveys
Velocity Measurements
! = # $ − ℎ0
(

3. Local minima
Parameter space
Scheme 1
Scheme 3
Scheme 2
Scheme 4
Fitness Function
The Key Idea
Impact of physical information
on the parameter space domain
Manfreda et al. (HP - 2018)
Time
Q (m3/s)
SURFACE RUNOFF
SNOW MELT
BASE FLOW
Decomposing the parameter
calibration according to the
existing processes leads to more
reliable model calibrations.
Physical
constrains
Model Performances
Including physical info
Stream Flow Components

4. Q(m3/s)
H (m)
Decoupling
Streamflow
measurements
Classic Method V W Method
H (m)
topographic
surveys
V(m/s)
The Proposed Method
The rating curve can be obtained as the product of two functions:
! = #(% − ℎ0)Ω(% − ℎ0)

5. Comparison of the two methodologies
• FRCs derived with different permutation of the same
dataset;
• Comparison is made on the calibration dataset and on
the data excluded from the calibration.

6. Associated References
Manfreda, S., On the derivation of flow rating-curves in data-scarce
environments, Journal of Hydrology, 562, 151-154, (doi:
10.1016/j.jhydrol.2018.04.058) 2018.
Manfreda, S., L. Mita, S. F. Dal Sasso, C. Samela, L. Mancusi, Exploiting the Use
of Physical Information for the Calibration of a Lumped Hydrological Model,
Hydrological Processes, 32(10), 1420-1433, (doi: 10.1002/hyp.11501) 2018.