The document discusses research activities related to hydrology conducted by Prof. Salvatore Manfreda. It provides an overview of his educational background and experience, as well as projects he has led. It then summarizes some of his recent research interests, which include soil moisture modeling, river basin modeling, model calibration, flow rating curves, detection of flood prone areas, and river monitoring using unmanned aerial systems. It provides examples of some of this work, including the soil moisture analytical relationship model, modeling soil water dynamics at the basin scale, and the geomorphic flood index tool.

1. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 1/25
INTRODUCTION ON HYDROLAB
RESEARCH ACTIVITIES
Prof. Salvatore Manfreda
salvatore.manfreda@unibas.it
www2.unibas.it/manfreda
REDES Project Nr. 170021. International Workshop on Bridge Scour
caused by Supercritical Flows
UdeC, May 14 - 18th, 2018

2. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 2/25
A Short Introduction
[2001-2004] Ph.D. in Environmental Modelling and Monitoring Techniques,
University of Basilicata, University of Rome La Sapientia, University of
Genoa, University of L’Aquila and University of Florence, Italy.
[2004-05] Research Associate at the Department of Civil and
Environmental Engineering, Princeton University, USA.
[2008-2014] Assistant Professor at the Faculty of Engineering, University
of Basilicata, Italy.
[2014 - …] Associate Professor in hydraulic construction and hydrology at
the University of Basilicata.
Scientific Interests: stochastic processes in hydrology, distributed
modeling, flood prediction, soil moisture process, delineation of flood
prone areas, mathematical filters, scour process, vegetation patterns,
remote sensing, environmental monitoring, use of UASs in hydrology.

3. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 3/25
Relevant Projects
[2017-2021] Chair of the Cost Action Entitled “Harmonization of UAS techniques for
agricultural and natural ecosystems monitoring”
(http://www.cost.eu/COST_Actions/ca/CA16219) (Budget available about 710.000 €)
[2015-2018] Participant of the Research Project Smart
Basilicata (http://smartbasilicata.tern.it) (Budget available about 18.500.000 €)
[2015-2018] Scientific coordinator of the research agreement for the Startup of the
Warning System for hydrologic and hydraulic risks. Civil Protection of Basilicata
(Budget available 680.000 €).
[2014-2019]: Member of the research group for the Project "Technologies to stabilize
soil organic carbon and farm productivity, promote waste value and climate change
mitigation - CarbOnFarm" LIFE12 ENV/IT/00719 (Budget available 3.051.265 €)
[2012-2016] Scientific coordinator of the research agreement entitled:
"Implementazione e sperimentazione di sistemi di allertamento e controllo del rischio
idrologico". Civil Protection of Basilicata (Budget available 370.000 €).

4. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 4/25
Recent Research Activities and Interests
1. Soil Moisture Modelling and Monitoring;
2. Modelling Runoff at the Basin Scale;
3. Model Calibration exploiting physical information;
4. Flow rating curves in data-scarce environment;
5. Detection of Flood Prone Areas;
6. River Monitoring with UASs.
7. Scour process
1. SM
Monitoring
3. Model
Calibration
2. River
Basin
5. Scour4. FRC
5. River
Monitoring
5. Flood Prone
Areas

5. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 5/25
Model Complexity versus Performances

6. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 6/25
Soil Moisture Analytical Relationship (SMAR)
between surface and root zone soil moisture
Using this assumption, Manfreda et al. [HESS – 2014] derived the
mathematical relationship between s1 and s2
!! !! = !! + (!! !!!! − !!)!!!! !!!!!!!
+ 1 − !! !!! !! !! − !!!!
s1(t)
s2(t)
Zr2
Zr1
The water flux from the top layer can be considered significant only
when the soil moisture exceeds field capacity.
where n1 [-] is the soil porosity of the first layer, Zr1 [L] is the depth of the
first layer, s1 (θ1/n1) [-] is the relative saturation of the first layer, and sc1 [-]
is the value of relative saturation at field capacity.
Y(t)
First layer
Second
layer
Y(t)

7. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 7/25
SMAR’s results obtained with parameter assigned
based on physical information
01/01/06 01/01/08 01/01/10 01/01/12
0
0.1
0.2
0.3
0.4
0.5
time (days)
relativesaturation(−)
Niger at Tondikiboro
S10cm
01/01/06 01/01/08 01/01/10 01/01/12
0
0.1
0.2
0.3
0.4
R=0.872, RMSE=0.025, a=0.049, b=0.08, sw
=0.085, sc1
=0.143
time (days)
relativesaturation(−)
S
10−135cm
S*
10−135cm
(B)
(A)
A) Time series of relative
saturation, at the daily time-
scale, in the first layer of soil
measured at the station of
Tondikiboro in Niger.
B) Averaged relative saturation in
the lower layer of soil measured
(continuous line) and filtered
(dashed line) at the station of
Tondikiboro. Parameters values
used in the present application
are a=0.049, b=0.08, sw=0.085,
and sc1=0.143, respectively.

8. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 8/25
Modelling Soil Water Dynamics at the Basin scale
The watershed heterogeneity is described by a
parabolic curve for the water storage capacity
of the soil [Zhao et al., 1980]
f/F is the fraction of the basin with water
storage capacity ≤WM’, Wmax represents the
maximum value of the water storage capacity
and b is a shape parameter that according to
Zhao [1992] assumes values between 0.1-0.4.
Total water storage capacity
a0
WM'
1
Soil Water
Content
WMM
Saturated portion of
the basin
Wmax
Wmax
Wmax
2. River
Basin
1. SM
Monitoring
3. Model
Calibration
5. Scour4. FRC
5. Flood Prone
Areas
5. River
Monitoring

9. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 9/25
Daily Runoff Probability Distributions
Rainfall PDF

10. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 10/25
Model Calibration Strategies
2. River
Basin
1. SM
Monitoring
3. Model
Calibration
5. Scour4. FRC
5. Flood Prone
Areas
5. River
Monitoring

11. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 11/25
Model Calibration Strategies
2. River
Basin
1. SM
Monitoring
3. Model
Calibration
5. Scour4. FRC
5. Flood Prone
Areas
5. River
Monitoring

12. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 12/25
Flow Rating
Curves
2. River
Basin
1. SM
Monitoring
3. Model
Calibration
5. Scour4. FRC
5. Flood Prone
Areas
5. River
Monitoring
Topographic
measurements
W=6.09H1.88 + 5
Calibration Validation

13. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 13/25
Geomorphic Methods
River basin morphology intrinsically
contains an extraordinary amount of
information on flood-driven erosion
and depositional phenomena,
constituting a useful indicator of the
flood exposure of a given area [e.g.
Arnaud-Fassetta et al., 2009; Tucker
et al., 2001; Tucker and Whipple,
2002]
Flood Plain
1) Does exist a physical attribute of the surface able to reveal if a portion
of a river basin is exposed to flooding?
2) Is it possible to use such descriptor to map the flood exposure over
large scale/unstudied areas?
2. River
Basin
1. SM
Monitoring
3. Model
Calibration
5. Scour4. FRC
5. Flood Prone
Areas
5. River
Monitoring

14. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 14/25
The Geomorphic Flood Index - GFI
hr is computed as a function of the contributing area Ar in the section of the drainage network
(‘R’ stands for river) hydrologically connected to the point under exam.
(A)
hr ≈ bAr
n
H
D
(B)
Location under exam
Nearest element of
the river network
along the flow path
Flow path
The results suggest that the classifier based on the index ln(hr/H) named the Geomorphic
Flood Index (GFI) is the most suitable for the preliminary detection of the flood-prone areas
in data sparse environments and for large-scale applications.
Its performances are less sensitive to:
ü the different topography of the training area.
ü the size of the calibration area;
ü the resolution of the adopted Digital Elevation Model (DEM);
ü the reference hydraulic map used for calibration.
[Manfreda et al., 2016;
Samela et al., 2017]

15. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 15/25
GFA – Tool for QGIS
The plugin can be downloaded from the repository github:
https://github.com/HydroLAB-UNIBAS/GFA-Geomorphic-Flood-Area.
[Samela et al., 2017]

16. Pictorial representation of the 100 yr
flood-prone areas for the continental
U.S. according to the linear binary
classifier based on the GFI.
The large-scale map allows to see that
the index produces a realistic
description of the flood prone areas, with
the possibility to extend the flood hazard
information in those portions of the
Country where the FEMA’s maps are
lacking (grey areas).
Example
of application

17. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 17/25
Monitoring River Systems
2. River
Basin
1. SM
Monitoring
3. Model
Calibration
5. Scour4. FRC
5. Flood Prone
Areas
5. River
Monitoring

18. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 18/25
Field Measurements

19. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 19/25
Optimal parameter settings for PTV techniques

20. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 20/25
Pier Scour
2. River
Basin
1. SM
Monitoring
3. Model
Calibration
5. Scour4. FRC
5. Flood Prone
Areas
5. River
Monitoring
q Dimensionless Effective Flow Work W*:
4
*
0
1endt
R
R
R
u I
W dt
ut
d
æ ö-
= ç ÷
è ø
ò
ENERGY
EXPERIMENTS: Lanca et al. (2013)
ü Multi-peaked hydrographs
ü Hydraulic Effects (h, u)
ü Sediment Effects (D*)
ü Scale effects (D/d50)

21. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 21/25
Pier Scour
2. River
Basin
1. SM
Monitoring
3. Model
Calibration
5. Scour4. FRC
5. Flood Prone
Areas
5. River
Monitoring
EXPERIMENTS: Lanca et al. (2013)

22. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 22/25
Independent Stochastic Process: Poisson
Process

23. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 23/25
Probability distribution of Scour
z [m]
0.5 0.7 0.9 1.1 1.3 1.5 1.7 1.9 2.1 2.3 2.5 2.7 2.9 3.1
P(Z>z)[-]
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
1
5
10
25
50
100

24. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 24/25
Thanks…

25. Salvatore Manfreda, International Workshop on Bridge Scour caused by Supercritical Flows,
UdeC, May 14 - 18th, 2018 25/25
Related Publication
Manfreda, S., On the derivation of flow rating-curves in data-scarce environments, Journal of Hydrology (doi: 10.1016/j.jhydrol.2018.04.058), 2018.
Dal Sasso, S. F., A. Pizarro, C. Samela, L. Mita, and S. Manfreda, Exploring the optimal experimental setup for surface flow velocity measurements using
PTV, Environmental Monitoring and Assessment, (submitted), 2018.
Samela, C., R. Albano, A. Sole, S. Manfreda, An open source GIS software tool for cost effective delineation of flood prone areas, Computers,
Environment and Urban Systems, (doi: 10.1016/j.compenvurbsys.2018.01.013), 2018.
Manfreda, S.,Mita, L., S. F. Dal Sasso, C. Samela, L. Mancusi, Exploiting the Use of Physical Information for the Calibration of a Lumped Hydrological
Model, Hydrological Processes, (doi: 10.1002/hyp.11501), 2018.
Pizarro A., C. Samela, M. Fiorentino, O. Link, S. Manfreda, An entropy-based model for bridge-pier scour estimation under complex hydraulic scenarios,
Water (MDPI), 9(11), 889 (doi:10.3390/w9110889), 2017.
Samela, C., T.J. Troy, S. Manfreda, Geomorphic classifiers for flood-prone areas delineation for data-scarce environments, Advances in Water
Resources, 102, 13–28, (doi: 10.1016/j.advwatres.2017.01.007), 2017.
Baldwin, D., Manfreda, S., Keller, K., and Smithwick, E.A.H., Predicting root zone soil moisture with soil properties and satellite near-surface moisture data
at locations across the United States, Journal of Hydrology, 546, 393–404, (doi: 10.1016/j.jhydrol.2017.01.020), 2017.
Pizarro, A., B. Ettmer, S. Manfreda, A. Rojas, and O. Link, Effective Flow Work for Estimation of Pier Scour under Flood Waves, Journal of Hydraulic
Engineering, 06017006-1-7, (doi: 10.1061/(ASCE)HY.1943-7900.0001295), 2017.
Link, O., C. Castillo, A. Pizarro, A. Rojas, C. Escauriaza, B. Ettmer, S. Manfreda, A Model for Local scour during Flood Waves, Journal of Hydraulic
Research, (doi: 10.1080/00221686.2016.1252802), 2016.
Samela, C., S. Manfreda, F. De Paola, M. Giugni, A. Sole, M. Fiorentino, DEM-based approaches for the delineation of flood prone areas in an ungauged
basin in Africa, Journal of Hydrologic Engineering, 21(2), (doi: 10.1061/(ASCE)HE.1943-5584.0001272), 2016.
Manfreda, S., F.Nardi, C. Samela, S. Grimaldi, A. C. Taramasso, G. Roth and A. Sole, Investigation on the Use of Geomorphic Approaches for the
Delineation of Flood Prone Areas, Journal of Hydrology, 517, 863-876, (doi: 10.1016/j.jhydrol.2014.06.009), 2014.
Manfreda, S., L. Brocca, T. Moramarco, F. Melone, and J. Sheffield, A physically based approach for the estimation of root-zone soil moisture from surface
measurements, Hydrology and Earth System Sciences, 18, 1199-1212, (doi:10.5194/hess-18-1199-2014), 2014.
Manfreda, S., M. Di Leo, A. Sole, Detection of Flood Prone Areas using Digital Elevation Models, Journal of Hydrologic Engineering, 16(10), 781-790 (doi:
10.1061/(ASCE)HE.1943-5584.0000367), 2011.
Manfreda, S., Runoff Generation Dynamics within a Humid River Basin, Natural Hazard and Earth System Sciences, 8, 1349-1357, (doi:10.5194/nhess-8-
1349-2008), 2008.
Manfreda, S., M. Fiorentino, A Stochastic Approach for the Description of the Water Balance Dynamics in a River Basin, Hydrology and Earth System
Sciences, 12, 1189-1200, (doi:10.5194/hess-12-1189-2008), 2008.