STUDY OF THE STORM DRAIN SEWER OF THE URBAN CATCHMENT OF LA RIERETA, SAN BOI DE
LLOBREGAT, SPAIN
Team 3:
Aline Veról
José Rivero
Pedro Ramos
Ramiro Pighini
1. Introduction
The traditional canalisation approach for flood control has been complemented or replaced by new
concepts that consider a systemic approach, with distributed interventions over the catchment intending to
recreate flow patterns prior to the urbanisation. LID measures have been proposed to fulfil this aim.
However, the spatio-temporal variability of the phenomenon gives particular characteristics to each
catchment. In this context, a systemic evaluation of flood control projects is needed, providing adequate
spatial coverage without superimposing effects in time. Mathematical modelling emerges as a useful tool
to represent the integrated behaviour of urban drainage and landscape.
This paper presents the proposition of LID measures on the urban catchment of "La Riereta", at Sant Boi de
Llobregat, in Spain, with the aid of EPA Storm Water Management Model (SWMM).
2. Objective
The general objective of this project is to perform an analysis on the model of the storm drain sewer of “La
Riereta”, an urban catchment located in Spain, and propose a sewer rehabilitation process. To carry out this
process, a hydrological and hydraulic model will be developed using the EPA Storm Water Management
Model (EPA SWMM 5.0).
3. LID – Low Impact Development
Low impact development (LID), developed by Coffman et al. (1998), is a relatively new concept in
stormwater management.
LID design adopts a set of procedures that try to understand and reproduce hydrological behaviour prior to
urbanisation. In this context, the use of functional landscapes appear as useful elements in the urban mesh,
in order to allow the recovering of infiltration and detention characteristics of the natural watershed. It is a
change in the traditional design concepts, moving towards a site design that mimics natural watershed
hydrological functions, involving volume, discharge, recharge and frequency. The main principles of this
approach may be briefly described by the following points:

minimise runoff, acting on impervious rates reduction and maintaining green areas;

preserve concentration times of pre-development, by increasing flow paths and surfasse
roughness;

use of retention reservoir for peak discharge control and improve water quality;

use of additional detention reservoirs to prevent flooding, if necessary.
In Brazil, the concept was developed and formalised by Baptista et al. (2005) and is well known as
¨compensatory techniques¨.
Veról, Rivero, Ramos & Pighini, 2012
Some basic LID principles include conservation of natural features, minimisation of impervious surfaces,
hydraulic disconnects, disbursement of runoff and phytoremediation. In this context, permeable
pavements, bioretention facilities, vegetated roof covers, grass swales, dry wells, filter strips, vegetated
buffers, rain barrels, cisterns, infiltration trenches, on-lot detention reservoirs, temporary storage
reservoirs, reforestation, among others, may be good solutions for achieving these goals and can also
integrate harmoniously into the urban environment as they can be designed as recreational areas in dry
weather and, then, assume the characteristics of multifunctional landscapes (Miguez et al. ,2011).
The figures below show some examples of LID measures.
Figure 1. Bioretention
Figure 2. Infiltration trenches
Figure 3. Vegetated roof covers
Veról, Rivero, Ramos & Pighini, 2012
Figure 4. Permeable pavements
Figure 5. Rain Barrels
4. Methodology
To develop the proposed case study, the group followed the methodology suggested by the organisers and
detailed below:

Basin discretisation;

Determination of the input data (for sub-catchments, conducts and manholes);

Calibration and validation of the model using three different rain events and hydrographs
registered at the outlet of the urban basin;

Determination of the design rainfall for TR 10;

Simulation of the drainage network diagnosis;

Analysis of the catchment to evaluate and propose the use of LID measures;

Simulation of the drainage network considering the implementation of the proposed LID measures;

Analysis and discussion of results.
Veról, Rivero, Ramos & Pighini, 2012
5. Case Study
5.1. Description
The present case study is an urban catchment located in Sant Boi de Llobregat, a town near Barcelona,
Spain (Figure 6).
This catchment has a surface area of approximately 17 ha and it presents high indexes of impermeability.
Its slope varies from high to medium values. Roof drainage discharges directly to the streets through
downspouts. Additionally, a group of inlets distributed in the streets ensure the collection of the generated
runoff after the occurrence of rainfall.
The drainage system of “La Riereta” is a combined sewer network and it is mainly composed by circular
cross-section pipes with different diameters and made by concrete.
Figure 6. Sant Boi de Llobregat
Veról, Rivero, Ramos & Pighini, 2012
6. Results
The obtained results are presented in the following items.
a) Discretisation
The first step of all the work was to divide the studied area into sub-catchments, each one with an
approximate area of 1ha (Figures 7 and 8). Also, the hydrologic and hydraulic parameters which SWMM
incorporates were defined.
Figure 7. Definition of the working catchment
Figure 8. Definition of the working catchment in SWMM
Veról, Rivero, Ramos & Pighini, 2012
b) Rainfall
Three different rainfall events, with their corresponding flows – measured at the catchment outfall – were
assigned for each group. Each of these events is identified by the name of the saint of the day in which the
registration started.
Table 1 presents the rainfall events assigned for team 3 and figures 9 to 11 show these events.
Table 1. Rainfall events assigned for Team 3
Rainfall event – Team 3
Efrén
Santa Cecilia
Susana
Figure 9. Rainfall event – Santa Cecilia
Veról, Rivero, Ramos & Pighini, 2012
Figure 10. Rainfall event – Efren
Figure 11. Rainfall event – Susana
Veról, Rivero, Ramos & Pighini, 2012
c) Calibration / Validation
The chosen rainfall events for calibration of the model were: Susana and Efrén. The resulting hydrographs
are showed in Figures 12 and 13.
Susana Rainfall Event
0.5
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
0
10
20
30
Measured flow(m3/s)
40
50
Calculated flow (m3/s)
Figure 12. Calibration of the model with Susana rainfall event
Efrén Rainfall Event
0.5
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
0
20
40
60
80
100
120
140
Measured flow (m3/s)Time [min]Calculated flow (m3/s)
Figure 13. Calibration of the model with Efrén rainfall event
Veról, Rivero, Ramos & Pighini, 2012
Santa Cecilia rainfall event was used to validate the model. The corresponding hydrograph is showed on
Figure 14.
Santa Cecilia Rainfall Event
0.5
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
0
10
20
30
40
Measured flow (m3/s)
50
60
70
80
90
100
Calculated flow (m3/s)
Figure 14. Validation of the model with Santa Cecilia rainfall event
After the calibration and validation of the model, the adopted parameters for sub catchments, conducts
and junctions were, respectively:
Veról, Rivero, Ramos & Pighini, 2012
Table 2. Parameters adopted for sub catchments
Name
S06
S12
S13
S01
S02
S03
S05
S07
S08
S09
S4A
S4B
S4C
S10A
S10B
S11B
S11A
S14A
Raingage
Pluv1
Pluv1
Pluv1
Pluv1
Pluv1
Pluv1
Pluv1
Pluv1
Pluv1
Pluv1
Pluv1
Pluv1
Pluv1
Pluv1
Pluv1
Pluv1
Pluv1
Pluv1
Outlet
N12
N9
N2
N13
N14
2
N12
N11
N11
N6
N10
N10
N10
N7
N15
N16
N9
N4
Total
Area
0.5
0.66
2.06
0.77
0.44
1
0.66
0.55
0.9
0.69
0.6
0.09
0.5
0.87
0.57
1.1
0.95
0.2
Pcnt.
Imperv
81.16
94.87
90.73
87.8
92.23
71.73
84.08
98.06
88.5
92.64
89.3
89.3
89.3
96.37
96.37
95.97
95.97
95.3
Width
500
660
2060
770
440
1000
660
550
900
690
600
90
500
870
570
1100
950
200
Pcnt.
Slope
2.28
1.52
4.09
6.63
3.16
4.65
1.9
4.09
4.39
6.46
2.34
2.34
2.34
4.72
4.72
4.01
4.01
5.49
Curb N-Imperv N-Perv S-Imperv
Length
0
0.04
0.15
0.65
0
0.04
0.15
0.65
0
0.04
0.15
0.65
0
0.04
0.15
0.65
0
0.04
0.15
0.65
0
0.04
0.15
0.65
0
0.04
0.15
0.65
0
0.04
0.15
0.65
0
0.04
0.15
0.65
0
0.04
0.15
0.65
0
0.04
0.15
0.65
0
0.04
0.15
0.65
0
0.04
0.15
0.65
0
0.04
0.15
0.65
0
0.04
0.15
0.65
0
0.04
0.15
0.65
0
0.04
0.15
0.65
0
0.04
0.15
0.65
S-Perv
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
PctZero RouteTo
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
OUTLET
OUTLET
OUTLET
OUTLET
OUTLET
OUTLET
OUTLET
OUTLET
OUTLET
OUTLET
OUTLET
OUTLET
OUTLET
OUTLET
OUTLET
OUTLET
OUTLET
OUTLET
Veról, Rivero, Ramos & Pighini, 2012
Table 3. Parameters adopted for conduits
Name
C2
C4
C6
C7
C9
C10
C11
C12
C13
C14
C5
C8
C15
C16
C12A
Inlet
Node
N2
N4
N6
N7
N9
N10
N11
N12
N13
N14
N5
N8
N15
N16
2
Outlet
Node
N4
N5
N7
N8
N11
N11
N12
2
N14
1
N9
N9
N7
N9
N14
Length
70.86
50.56
80.59
59.12
123.33
61.14
108.06
36
120.34
45.52
64.88
10.73
105
145
50
Manning
N
0.013
0.013
0.013
0.013
0.013
0.013
0.013
0.013
0.013
0.013
0.013
0.013
0.013
0.013
0.013
Inlet
Offset
30.89
23.33
26.46
24.57
21.46
21.73
15.46
15.7
16.22
13.13
22.31
23.18
28.518
26.193
14
Outlet
Offset
24.18
22.51
24.57
23.28
15.46
18.06
15.9
14.2
13.73
12.51
21.46
22.87
24.574
22.87
13.13
Init.
Flow
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max.
Flow
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Link
C2
C4
C6
C7
C9
C10
C11
C12
C13
C14
C5
C8
C15
C16
C12A
Shape
Geom1
CIRCULAR
0.5
CIRCULAR
0.4
CIRCULAR
0.4
CIRCULAR
0.4
CIRCULAR
1
CIRCULAR
0.3
CIRCULAR
1
CIRCULAR
1
CIRCULAR
0.6
CIRCULAR
1.2
CIRCULAR
0.6
CIRCULAR
0.5
CIRCULAR
0.5
CIRCULAR
0.6
CIRCULAR
1.2
Geom2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Geom3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Geom4
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Barrels
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Veról, Rivero, Ramos & Pighini, 2012
Table 4. Parameters adopted for junctions
Name
N2
N4
N6
N7
N9
N10
N11
N12
N13
N14
N5
N8
N15
N16
2
Invert
Elev.
30.696
23.33
26.263
24.57
21.46
21.725
15.46
15.7
16.22
13.13
22.31
23.17
28.518
26.193
14
Max.
Depth
0
0
0
0
0
0
4
0
0
0
0
0
0
0
0
Init. Surcharge Ponded
Depth
Depth
Area
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Veról, Rivero, Ramos & Pighini, 2012
d) Diagnosis of drainage network
Once the model was calibrated and validated, the team modelled the diagnosis of the drainage network for
a design rainfall.
A design rainfall of 10 years of recurrence time is used not only in the city of Barcelona, but also in some
municipalities around it, like Sant Boi de Llobregat. In this case, the design rainfall should be obtained from
the IDF curve Barcelona-Fabra, based on precipitation series registered between the years of 1927-1993.
This IDF curves are described by the following expressions:
Where:
I: (mm/h)
T: (years)
D: (minutes)
The duration of the design rainfall is 1 hour. Figure 15 shows it.
250.00
200.00
150.00
100.00
50.00
0.00
5
10
15
20
25
30
35
40
45
50
55
60
Figure 15. Design rainfall obtained for TR 10
Veról, Rivero, Ramos & Pighini, 2012
1
N14
2
N12
N11
N8
N9
N7
N6
Water Elevation Profile: Node N6 - 1
28
27
26
25
24
23
Elevation (m)
22
21
20
19
18
17
16
15
14
13
0
50
100
150
200
250
Distance (m)
300
350
400
450
500
07/24/2012 00:24:00
N14
450
500
1
2
N12
N11
N9
N5
N4
N2
Water Elevation Profile: Node N2 - 1
33
32
31
30
29
28
27
26
Elevation (m)
25
24
23
22
21
20
19
18
17
16
15
14
13
0
50
100
150
200
250
300
Distance (m)
350
400
550
07/24/2012 00:24:00
Veról, Rivero, Ramos & Pighini, 2012
1
N14
N13
Water Elevation Profile: Node N13 - 1
17
Elevation (m)
16
15
14
13
0
10
20
30
40
50
60
70
80
90
Distance (m)
100
110
120
130
140
150
160
07/24/2012 00:24:00
1
N14
2
N12
N11
N10
Water Elevation Profile: Node N10 - 1
22
21
20
Elevation (m)
19
18
17
16
15
14
13
0
20
40
60
80
100
120
140
160
Distance (m)
180
200
220
240
260
280
300
07/24/2012 00:24:00
Veról, Rivero, Ramos & Pighini, 2012
1
N14
2
N12
N11
N9
N16
Water Elevation Profile: Node N16 - 1
28
27
26
25
24
23
Elevation (m)
22
21
20
19
18
17
16
15
14
13
0
50
100
150
200
250
Distance (m)
300
350
400
450
500
07/24/2012 00:24:00
1
N14
2
N12
N11
N8
N7
N15
Water Elevation Profile: Node N15 - 1
30
29
28
27
26
25
Elevation (m)
24
23
22
21
20
19
18
17
16
15
14
13
0
50
100
150
200
250
300
Distance (m)
350
400
450
500
07/24/2012 00:24:00
Veról, Rivero, Ramos & Pighini, 2012
e) Intervention Proposal
Once the diagnosis for the drainage network of “La Riereta” was made, the team made a particular study
for the current catchment, considering the implementation of LID measures and the aid of SWMM.
The chosen LID measures were:

Porous pavements,

Bioretention cells, and

Rain barrels.
The obtained results are showed above.
PP1
PP1
PP1
PP1
PP1
Type/Layer Parameters
PP
SURFACE
2
PAVEMENT
120
STORAGE
250
DRAIN
0
0
0.18
0.75
0.5
0.018
0
10
0
2
100
0
6
5
0
PP2
PP2
PP2
PP2
PP2
PP
SURFACE
PAVEMENT
STORAGE
DRAIN
2
120
250
0
0
0.18
0.75
0.5
0.018
0
10
0
3
100
0
6
5
0
RB1
RB1
RB1
RB
STORAGE
DRAIN
1500
2
0.75
0.5
10
0
0
2
BR1
BR1
BR1
BR1
BR1
BC
SURFACE
SOIL
STORAGE
DRAIN
4
500
500
0
0.5
0.3
0.75
0.5
0.2
0.2
100
0
0.5
0.1 0.5
0
6
5
10.0
3.5
Veról, Rivero, Ramos & Pighini, 2012
SubcatchmentLID Process Number
S06
S12
S12
S13
S13
S13
S01
S01
S02
S02
S03
S03
S05
S05
S07
S07
S08
S08
S09
S09
S4A
S4A
S4B
S4B
S4C
S4C
S10A
S10A
S10B
S10B
S11B
S11B
S11A
S11A
S14A
S14A
RB1
RB1
PP1
PP1
RB1
BR1
RB1
PP1
RB1
PP1
PP1
RB1
PP1
RB1
RB1
PP1
PP1
RB1
PP1
RB1
PP1
RB1
RB1
PP1
PP1
RB1
PP1
RB1
PP1
RB1
RB1
PP2
RB1
PP1
PP1
RB1
Area
15
15
1
1
22
1
28
1
32
1
1
30
1
15
23
1
1
24
2
30
1
23
2
1
1
25
1
15
2
21
20
2
30
1
1
6
Width
0.8
0.8
700
2150
0.8
1200
0.8
800
0.8
500
500
0.8
700
0.8
0.8
868
812
0.8
900
0.8
500
0.8
0.8
280
500
0.8
942
0.8
1040
0.8
0.8
700
0.8
840
400
0.8
InitSatur
0
0
7
7
0
40
0
7
0
5
7
0
7
0
0
7
7
0
7
0
5
0
0
7
5
0
6
0
7
0
0
7
0
7
7
0
FromImprv
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
70
70
12
12
40
48
75
12
80
13
8
30
13
80
80
17
11
85
30
70
11
85
65
35
12
85
12
80
19
80
75
10
70
10
21
60
ToPerv
Report File
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Veról, Rivero, Ramos & Pighini, 2012
Design Rainfall Tr=10 and Flow Discharge
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
105
110
115
120
125
130
135
140
145
150
155
160
165
170
175
180
185
190
195
200
205
210
215
220
225
230
235
240
Time [min]
0
6.00
Desing Rainfall Tr=10
5.00
50
4.00
100
3.00
150
2.00
Flow Discharge [m3/s]
Flow Discharge with LID
measures
200
1.00
0.00
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
105
110
115
120
125
130
135
140
145
150
155
160
165
170
175
180
185
190
195
200
205
210
215
220
225
230
235
240
250
Time [min]
1
N14
2
N12
N11
N8
N9
N7
N6
Water Elevation Profile: Node N6 - 1
28
27
26
25
24
23
22
Elevation (m)
Intensity [mm/h]
Flow Discharge
21
20
19
18
17
16
15
14
13
0
50
100
150
200
250
Distance (m)
300
350
400
450
500
07/24/2012 00:24:00
Veról, Rivero, Ramos & Pighini, 2012
1
N14
2
N12
N11
N9
N5
N4
N2
Water Elevation Profile: Node N2 - 1
33
32
31
30
29
28
27
26
Elevation (m)
25
24
23
22
21
20
19
18
17
16
15
14
13
0
50
100
150
200
250
300
Distance (m)
350
400
450
500
550
07/24/2012 00:24:00
Veról, Rivero, Ramos & Pighini, 2012
1
N14
2
N12
N11
N10
Water Elevation Profile: Node N10 - 1
22
21
20
Elevation (m)
19
18
17
16
15
14
13
0
20
40
60
80
100
120
140
160
Distance (m)
180
200
220
240
260
280
300
07/24/2012 00:24:00
1
N14
2
N12
N11
N9
N16
Water Elevation Profile: Node N16 - 1
28
27
26
25
24
23
Elevation (m)
22
21
20
19
18
17
16
15
14
13
0
50
100
150
200
250
Distance (m)
300
350
400
450
500
07/24/2012 00:24:00
Veról, Rivero, Ramos & Pighini, 2012
Veról, Rivero, Ramos & Pighini, 2012
7. Conclusion
The calibration of the model showed a reasonable result, but the validation showed an exaggerated over
estimation in the total volume.
Considering the design rainfall, the nodes N4, N7 and N10 surcharged.
The main purpose of this work was to treat this flooding problem using the LID concept.
The use of LID, such as permeable pavements, rain barrels and bioretention cells, showed a good result on
the main drainage line, where the actions in the catchment context are more sensible. The nodes that were
flooded in the borders of the catchment were less sensible to LID measures because the surfaces related to
these nodes were small and the distributed measures could not be as effective as they were in the
catchment context.
Another problem was that in the borders of the catchment there may occur, in reality, a diversion to the
neighbouring catchments. As it has not been considered in the modelling, possibly the discharge in these
nodes may be overestimated.
This problem may also be the explanation for the calibration/validation results.
In a real situation, a good result could be achieved by the use of LID combined with other flooding control
measures. As an example, detention catchments or drainage net rehabilitation could be jointly considered.
Veról, Rivero, Ramos & Pighini, 2012
8. References
EPA. Low Impact Development: A Literature Review. 2000.
Batista, M.; Nascimento, N. & Barraud, S. Compensatory Techniques on Urban Drainage. ABRH: Porto
Alegre, Brazil, 2005. (in Portuguese).
Miguez, M.G.; Verol, A. P. Carneiro, P. R. F. Sustainable Drainage Systems: An Integrated Approach,
Combining Hydraulic Engineering Design, Urban Land Control and River Revitalisation Aspects. In: Drainage
Systems. Intech, 2012.
Miguez, M.G.; Mascarenhas, F.C.B.; Magalhães, L. P. C. Multifunctional landscapes for urban flood control:
the case of Rio de Janeiro (Chapter 2). Flood Prevention and Remediation, ed. Mascarenhas, F.C.B., WIT
Press: Southampton, Boston, pp. 33-52, 2011.
PRINCE GEORGE’S COUNTY, Department of Environment Resources. Low Impact Development Design
Strategies: An Integrated Design Approach. 1999.
Veról, Rivero, Ramos & Pighini, 2012