sewer sediment halcrow apr08
DESCRIPTION
civil engineerTRANSCRIPT
Halcrow Seminar Series
Sharjah, April 2008
SEWER SEDIMENTS - CHARACTERISTICS AND CONTROL IN ARID AREAS
Mamdouh NOUHProfessor of Civil (Water Resources& Environmental) Engineering
OBJECTIVES
Discuss the sources and characteristics of sewer sediments in arid and semiarid climates.
Recommend a method to predict the transportation and deposition of sediments under the effect of flash floods in arid and semiarid climates.
Discuss the feasible control methods that can prevent (or reduce) sewer-sediment accumulations in arid and semiarid climates.
MAIN PROBLEMS OF DESIGN (developing arid and semiarid catchments)
Scarcity of reliable data High variability of climatic factors (rainfall, temperature,
humidity,…, etc.) Existence of heavy duststorms Traditional method of design oversizes sewers’
diameters to convey many times the anticipated peak flowrates and to accommodate accumulated deposits (This leads to failure of maintaining setteable solids in suspension).
MAIN PROBLEMS OF OPERATIONS (developing arid and semiarid catchments)
Maintenance and management schemes (including cultural and socioeconomic schemes)
Highly polluted first-flush phenomenon of overflow event.
Blockage of sewer by sediment accumulation.
FLOODED URBAN AREA IN SHARJAH
FLOODED URBAN AREA IN SHARJAH
LANDSLIDES IN SOUTHWEST OF SAUDI ARABIA
DAMAGES OF ROADS IN ABHA (SAUDI ARABIA) AND IN MUSCAT (OMAN)
LANDSLIDES AND DAMAGE OF PAVEMENTS IN SAUDI ARABIA
EFFECT OF URBANIZATION ON
SHAPE OF
HYDROGRAPH
INPUT – OUTPUT
RELATIONSHIPS
IN
HYDROLOGIC PROCESSES
MODELS IN ANALYSES OF WATER SYSTEMS
0.01 0.1 1 10 100
TIME (min)
0
20
40
60
80
100M
EA
N S
ED
IME
NT
CO
NC
EN
TR
AT
ION
S (g
pl)
C (With)
C (Without)
Sediment Concentrations With and Without Duststorms
0.01 0.1 1 10 100
TIME (min)
1
1.5
2
2.5
3
CO
NC
EN
TR
AT
ION
WIT
H /
CO
NC
EN
TR
AT
ION
WIT
HO
UT NO2/NO3 (Large) NO2/NO3 (Small)
NH4 (Large) NH4 (Small)
TP (Large) TP (Small)
Variation of Nutrients Concentrations With and Without Duststorms
0 0.2 0.4 0.6 0.8 1
COEFFICIENT OF VARIATION OF DUSTSTORM
0
10
20
30
40
50
60
70
80
90
100
ME
AN
CO
NC
EN
TR
AT
ION
OF
SUSP
EN
DE
D S
ED
IME
NT
"C
", g
pl
TSP (ug/cu.m) = 800 - 1000
TSP (ug/cu.m) = 1800 - 2000
TSP (ug/cu.m) = 3000 - 3200
0 0.5 1 1.5 2 2.5-0.5
COEFFICIENT OF KURTOSIS OF DUSTSTORM
0
10
20
30
40
50
60
70
80
90
100
ME
AN
CO
NC
EN
TR
AT
ION
OF
SUSP
EN
DE
D S
ED
IME
NT
"C
", g
pl
TSP (ug/cu.m) = 800-1000
TSP (ug/cu.m) = 1800 - 2000
TSP (ug/cu.m) = 3000 - 3200
0 500 1000 1500 2000 2500 3000
CONCENTRATION OF TSP, ug/cu.m
30
40
50
60
70
80
90
100
CO
NC
EN
TR
AT
ION
OF
SUSP
EN
DE
D S
ED
IME
NT
"C
", g
pl
C = 33.0 + 0.0147*TSPR-sq = 96.5%
0 1000 2000 3000 4000
TSP CONCENTRATION, ug/cu.m
70
80
90
100
110
120
CO
NC
EN
TR
AT
ION
OF
SUSP
EN
DE
D S
ED
IME
NT
"C
", g
pl
C = 73.2 + 0.00848*TSPR-sq = 59.2%
Summary of performed regression analyses on prediction of Cd
RegressionParticle size diameter
“d”, mm
Correlation
coefficientInter-
correlation coefficient
1 2
Value (95% confidence
level)
Value (95% confidence
level)
Value (95% confidence
level)
Original regression All regression data 0.812 0.242 12.83 (16.48,
9.18)
0.56(0.68, 0.44)
0.06(0.051,0.039
)
1st particle size diameter class regression
d > 0.20 0.96 0.102 5.68(6.79, 4.57)
0.68(0.89, 0.49)
0.05 (0.059, 0.041)
2nd particle size diameter class regression
0.20 d > 0.06 0.96 0.273 4.67(5.92, 3.42)
0.65(0.78, 0.52)
0.06 (0.068, 0.052)
3rd particle size diameter class regression
0.06 d > 0.02 0.94 0.280 3.95(5.00, 2.90)
0.59(0.75, 0.43)
0.07(0.079, 0.061)
4th particle size diameter class regression
0.02 d > 0.002 0.95 0.286 2.85 (3.98, 1.72)
0.51 (0.62, 0.40)
0.07(0.079,0.061
)
5th particle size diameter class regression
0.002 d 0.93 0.286 2.58 (3.41, 1.75)
0.48 (0.60, 0.36)
0.08(0.096, 0.064)
ddddd SqC 21
where C is the concentration of suspended sediments (gram per liter); q is the average stormwater runoff depth over
catchment (mm); S is the concentration of duststorm over the catchment (g/ m 3 ); , and are regression parameters
0
50
100
150
200
250
0 50 100 150 200 250Predicted concentrations (gram per liter)
Mea
sure
d c
on
cen
trat
ion
s (g
ram
per
lit
er)
Measured and predicted suspended sediment concentrations
-60
-40
-20
0
20
40
60
0 50 100 150 200 250
Measured concentrations (gram per liter)
Err
or p
redi
ctio
n (g
ram
per
lite
r)
Error of prediction against measured suspended sediment concentration
0
50
100
150
200
250
0 50 100 150 200 250
Predicted concentrations (gram per liter)
Mea
sure
d co
ncen
trat
ions
(gr
am p
er li
ter)
Measured and predicted suspended sediment concentrations using division diameter size
0
50
100
150
200
250
-40 -30 -20 -10 0 10 20 30 40 50
Error in prediction (gram per liter)
Mea
sure
d co
ncen
trat
ions
(gra
m p
er li
ter)
Error of prediction against measured suspended sediment concentration using division diameter size
Regression analyses for heavy metals concentrations.
Metal Particle diameter “d”, mm
a b Coefficient of determination “R2”
Sum of squares for error
Mean square for error
Calculated F statistics Critical F-statistics
“Fc”
Copper “Cu” d > 0.20 0.032 0.046 0.8921 4.20765 0.242 17.387 4.08
0.20 d > 0.06 0.042 0.057 0.8744 4.60672 0.305 15.104
0.06 d > 0.02 0.776 0.093 0.8921 4.50954 0.315 14.316
0.02 d > 0.002 0.916 0.153 0.8216 3.70962 0.333 11.140
0.002 d 1. 034 0.196 0.7649 3.23248 0.356 9.080
Lead “Pb” d > 0.20 0.007 0.051 0.8844 0.02861 0.002 14.306
0.20 d > 0.06 0.009 0.063 0.8869 0.09272 0.007 13.245
0.06 d > 0.02 0.005 0.096 0.8761 0.07513 0.009 8.348
0.02 d > 0.002 0.006 0.162 0.8196 0.06351 0.009 7.057
0.002 d 0.011 0.123 0.7929 0.06949 0.013 5.345
Nickel “Ni” d > 0.20 0.056 0.009 0.8521 0.33768 0.016 21.105
0.20 d > 0.06 0.062 0.031 0.8249 0.35435 0.019 18.650
0.06 d > 0.02 0.061 0.053 0.7481 0.30378 0.027 11.251
0.02 d > 0.002 0.072 0.096 0.8096 0.22719 0.022 10.327
0.002 d 0.083 0.104 0.7761 0.37713 0.039 9.670
Zinc “Zn” d > 0.20 0.033 0.106 0.8241 0.44357 0.019 23.346
0.20 d > 0.06 0.029 0.098 0.8329 0.30628 0.026 11.780
0.06 d > 0.02 0.045 0.102 0.8084 0.30690 0.031 9.900
0.02 d > 0.002 0.061 0.120 0.7896 0.40032 0.048 8.340
0.002 d 0.097 0.155 0.8225 0.33825 0.055 6.150
Iron “Fe” d > 0.20 0.089 0.117 0.8384 1.12902 0.093 12.140
0.20 d > 0.06 0.097 0.103 0.7561 1.20175 0.115 10.450
0.06 d > 0.02 0.107 0.125 0.7861 1.73152 0.172 10.067
0.02 d > 0.002 0.126 0.216 0.7269 1.98288 0.216 9.180
0.002 d 0.133 0.238 0.7981 1.65858 0.231 7.180
dbddddCaP
1
1.5
2
2.5
1 1.5 2 2.5
Measured Cu concentrations (mg per liter)
Cu
conc
entr
atio
ns (
mg
per
liter
) pr
edic
ted
by E
q. 4
1
1.5
2
2.5
1 1.5 2 2.5
Measured Cu concentrations (mg per liter)
Cu
conc
entr
atio
ns (m
g pe
r lit
er)
pred
icte
d by
Eqs
1 &
4
-0.1
-0.08
-0.06
-0.04
-0.02
0
0.02
0.04
0.06
0.08
0.1
1 1.5 2 2.5
Measured Cu concentrations (mg per liter)
Err
or o
f pr
edic
tion
usin
g E
q. 4
(mg
per
liter
)
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
1 1.5 2 2.5
Measured Cu concentrations (mg per liter)
Err
or o
f pr
edic
tion
usin
g E
qs 1
& 4
(m
g pe
r lit
er)
Measured and predicted concentrations (top) and error of prediction (bottom) of copper “Cu”
2
4
6
8
10
2 4 6 8 10
Measured Pb concentrations (0.001xmg per liter)
Pb c
once
ntra
tions
(0.
001x
mg
per
liter
) pr
edic
ted
by E
q. 4
2
4
6
8
10
2 4 6 8 10Measured Pb concentrations (0.001xmg per liter)
Pb c
once
ntra
tions
(0.
001x
mg
per
liter
) pr
edic
ted
by E
qs 1
& 4
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
2 4 6 8 10
Measured Pb concentrations (0.001xmg per liter)
Err
or o
f pr
edic
tion
(0.
001x
mg
per
liter
) by
usi
ng E
q. 4
-1.5
-1
-0.5
0
0.5
1
1.5
2
2 4 6 8 10
Measured Pb concentrations (0.001xmg per liter)
Err
or o
f pr
edic
tion
(0.0
01xm
g pe
r lit
er)
by u
sing
Eqs
1 &
4
Measured and predicted concentrations (top) and error of prediction (bottom) of lead “Pb”
4
6
8
10
4 6 8 10
Measured "Ni" concentrations (0.01xmg per liter)
"Ni"
con
cent
ratio
ns (
0.01
xmg
per
liter
) pr
edic
ted
by E
q. 4
4
6
8
10
4 6 8 10
Measured "Ni" concentrations (0.01xmg per liter)
"Ni"
con
cent
ratio
ns (
0.01
xmg
per
liter
) pr
edic
ted
by E
qs 1
& 4
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
4 6 8 10
Measured Ni concentrations (0.01xmg per liter)
Err
or o
f pr
edic
tion
(0
.01
xmg
per
liter
) by
usi
ng E
q. 4
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
4 5 6 7 8 9 10 11
Measured "Ni" concentrations (0.01xmg per liter)
Erro
r of p
redi
ction
(0
.01
xmg
per l
iter
) by
usin
g Eq
s 1
& 4
Measured and predicted concentrations (top) and error of prediction (bottom) of Nickel “Ni”
4
8
12
16
4 8 12 16
Measured "Zn" concentrations (0.01xmg per liter)
"Zn
" co
ncen
trat
ions
(0.
01xm
g pe
r lit
er)
pred
icte
d by
Eq
. 4
4
8
12
16
4 8 12 16Measured "Zn" concentrations (0.01xmg per liter)
"Zn"
con
cent
rati
ons
(0.0
1xm
g pe
r lit
er)
pred
icte
d by
Eqs
1 &
4
0
0.5
1
1.5
2
2.5
4 8 12 16Measured Zn concentrations (0.01xmg per liter)
Err
or o
f pr
edic
tion
(0.
01xm
g pe
r lit
er)
by u
sing
Eq.
4
-4
-3
-2
-1
0
1
2
3
4 8 12 16
Measured "Zn" concentrations (0.01xmg per liter)
Err
or o
f pr
edic
tion
(0.0
1xm
g pe
r lit
er)
by u
sing
E
qs 1
& 4
Measured and predicted concentrations (top) and error of prediction (bottom) of Zinc “Zn”
2
3
4
5
2 3 4 5
Measured "Fe" concentrations (0.1xmg per liter)
"Fe"
con
cent
ratio
ns (
0.1x
mg
per
liter
) pr
edic
ted
by E
q. 4
2
3
4
5
2 3 4 5
Measured "Fe" concentrations (0.1xmg per liter)
"Fe"
con
cent
ratio
ns (
0.1x
mg
per
liter
) pr
edic
ted
by E
qs 1
& 4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
2 3 4 5
Measured "Fe" concentrations (0.1xmg per liter)
Err
or o
f pr
edic
tion
(0.
1xm
g pe
r lit
er)
by u
sing
Eq.
4
-0.4
-0.2
0
0.2
0.4
0.6
0.8
2 3 4 5
Measured "Fe" concentrations (0.01xmg per liter)
Err
or o
f pr
edic
tion
(0.0
1xm
g pe
r lit
er)
by u
sing
E
qs 1
& 4
Measured and predicted concentrations (top) and error of prediction (bottom) of Iron “Fe”
Transport of Sewer Sediments
• Bedload TransportComposed of relatively heavy particles; move near the sewer bottom;
travel by rolling, sliding, or saltating along the pipe invert (or deposited bed). Its rate is a function of shear velocity, particle size, density of
water, hydraulic radius of flow, and energy slope.
• Suspended-Load TransportFine lighter particles that have at one time been deposited and have
subsequently been swept from the bed load into the overlaying flow. Its travel is in suspension and is primary influenced by turbulent fluctuations
in the flow, which in turn are influenced by bed shear. Its rate is computed by integrating relationships identifying the concentration of suspended
sediments at various depths of sewer.
• Washload TransportParticles inter the pipe at its upstream junction and remained in suspension
under certain flow conditions but may settle when the flow conditions change. Critical conditions are identified in literature.
Bedload Transport:
qsb = f (shear velocity, median particle diameter)
Qsb(d) = 0.035 (Nouh, et al. (2004)
Suspended Load Transport:
Qss(d) = 0.685 (Nouh, et. al., 2004)
Total Solid Deposition:
TSD (d) = 0.006904 L-0.47 …….(R2 = 0.87)
…………………………(Nouh, 2005)
ddC
672.0
ddC
098272.0
ddC
3572.0
Traditional Method of DesignPreliminary investigation
To evaluate the feasibility of a project and to justify bond issues, assessments against property, or other methods of fund raising.
Preliminary designs are based on estimated flows, approximate ground contours, the location of the streets or sewer easement, and the location or
locations to which the sewage is to be taken.
Design principles
Detailed maps (or aerial photography) are used.
Flows are assumed STEADY and SEDIMENT free.
Flow velocities are high enough to keep solids in suspension (at least 0.60 m/s; normally 0.75 – 2.50 m/s).
A vertical profile is prepared for each sewer line at a horizontal scale of 1:500 to 1:1000 and a vertical scale about 10 times greater.
Self-Cleansing & the Limit of Deposition Method of Design
Sewer sediments may be defined as any settable materials found in water sewage, which is able to form bed deposits in the sewerage system.
The design is based on specifying a minimum “self-cleansing” flow velocity that should be achieved at a particular depth of flow (or with a particular
frequency of occurence).
• EntrainmentWhen the hydrodynamic lift and drag forces on the bed particles exceed the restoring forces of sediment
submerged weight, interlocking, and cohesion (if present) entrainment occurs, resulting in movement of the particles.
• TransportEntrained sediments travel in suspension or as a bed load. Finer lighter material tends to travel in suspension,
whereas heavier material travels as bedload.
• DepositionIf the flow velocity and/or turbulence level decreases transport of suspended sediment and/or bed load will cease,
and deposition of particles occurs.
Practically:A single value of minimum velocity, unrelated to the characteristics of the
sediment and other hydraulic behavior of the sewers, does not properly represent the ability of sewer flows to transport sediment.
Recommended Method of Design in Arid and Semiarid Climates
• Consideration of the large amounts of transported sediments• Consideration of shortage of data• Consideration of the high variability of rainfall, temperature…etc
(characteristics of arid climates)• Consideration of the local management and operation
constraints
Variation of Rainfall with Height
Flood Estimate by Extension of Short Record (3-10 yrs):
1. Extract maximum flows at the short term station
2. Extract maximum flows at nearby long term station
3. Normalize data (take the logarithms)
4. Derive regression equations for the short term
station using long term station “s”5. The regression equations are used to extend
the short term record.
Relative Information is defined as the variance
of the record estimate divided by the variance of the
estimate based on the extended records.
When this is greater than unity it is worth extending
the series.
sss
s
sss
ss
I
II I
I
I
I
II
OO
OO O
OO
O
210 ELEVAREAQav
Growth Curves for M5 of Various Rainfall Durations
Growth Factors
Percentage of Seasonal to Annual Rainfall Maxima for Different Return Periods
Areal Reduction Factors (%)
Prediction of Runoff:
Qp = 0.129(A)0.025 (S)0.87 (h)0.54 (TMP) 4.38 ………..[R 2 =0.82]
C v = 310.7 (A)0.025(1+TSP/1000) (S)1.87 (T)4.38 (h)0.54 (TMP)2.78 ……..[R 2 = 0.89]
The volumetric sediment concentration “Cv” (discharge rate of sediment/discharge rate of water) as a function of the average of total suspended particulate matter concentrations “TSP” (g/m 3 ) over catchment, area of catchment “A” (ha), slope of land “S” (cm/km), average depth of rainstorm over catchment “h” (mm), dry period preceding the rainstorm “T” (days), and the coefficient of kurtosis of rainstorm (measure of temporal variation of rainstorm over catchment) “TMP”.
Equ.Regression variable R2
Cv A h S TMP TSP T 0.89
A h S 0.56
A h S TSP 0.61
A h S TSP T 0.71
A h S TMP TSP 0.76
Q A h S TMP 0.82
A h S 0.69
A h TMP 0.74
Routing flows through sewers(Development in Muskingum Flow routing method)
Q 0 = a Q i ……………………………………. (1)
Where 0 ‹ a ‹ 1 = coefficient, determined by using a regression equation developed in this study as
a = 0.0136 D 0.46 n -0.72 S 0 -0.028 Qp
-0.18 C v 0.54 . (2)
where Q p is the peak inflow discharge, D is the sewer diameter, and n is Manning coefficient.
The routing of flow is as follow:1. Select ∆t and ∆x2. Calculate “a” using Eq. 23. Calculate Q0 with Eq. 1 and inflow discharge4. Calculate the initial depth and angle of the flow cross sections
2
0
0
sin2
2sin225
3
Q
LA
K
sin)sin2
2sin25(16
2sin2(3
2
1
20
LS
DX ]}1)
sin2
2sin25(
3
1{1[ 2
02
2 F
KXt
XKtC
)1(5.0
5.01
KXt
XKtC
)1(5.0
5.02
KXt
KXtC
)1(5.0
)1(5.03
ni
nni
ni QCQCQCQ 1312
11
11
Calculate K and X as
Calculate C1 , C2 , and C3 by
Route flows by
Ratios of Computed to Measured Parameters of Ratios of Computed to Measured Parameters of Hydrographs and PollugraphsHydrographs and Pollugraphs
(average of 38 events)(average of 38 events)
Peak Average Duration
Ratio “q”
(hydrograph) 0.82 0.92 0.96
Ratio “C”
(pollugraph) 0.74 0.86 0.79
Sewer-Sediment Control
Solids-source management Inline and in-sewer control Treatment facilities
Effect of sewer slope on solids removalEffect of sewer slope on solids removal(circular cross section of s = 0.0008 m/m)(circular cross section of s = 0.0008 m/m)
0
10
20
30
40
50
60
70
20 30 50 100
0.001
0.0012
0.0015
Sewer Diameter in Centimeter
Per
cen
tag
e o
f S
oli
d R
emo
vals
Effect of sewer shape of cross section Effect of sewer shape of cross section on solids removalon solids removal
(slope = 0.0008 m/m)(slope = 0.0008 m/m)
0
10
20
30
40
50
60
70
Circular Square Rectangular Trapezoidal
0.001
0.0012
0.0015
Per
cen
tag
e o
f S
oli
d R
emo
vals
Shape of Cross Section
Effect of circular sewer cleansing on solids removal
(slope = 0.0008 m/m)
0
10
20
30
40
50
60
70
80
90
100
Circular Square Rectangular Trapezoidal
Once YearlyTwice YearlyAfter Each Rainstorm
Per
cen
tag
e o
f S
oli
d R
emo
vals
Shape of Cross Section
A hypothetical Sewer Network
Sewer network design with and without consideration of transported sediment to sewer
Sewernumber
With sediment washoff
Without sediment washoff
Diam. (mm)
Bed slope a coeff.
Diam. (mm)
Bed slope
1 2,000 0.005 0.11 2,000 0.006
2 2,000 0.005 0.13 3,000 0.006
3 2,000 0.008 0.19 3,000 0.01
4 4,000 0.008 0.21 5,000 0.01
5 5,000 0.007 0.23 7,000 0.02
6 5,000 0.005 0.32 9,000 0.03
7 6,500 0.005 0.39 10,000 0.03
8 6,500 0.004 0.43 10,000 0.02
9 8,000 0.004 0.44 12,000 0.015
10 8,000 0.003 0.49 12,000 0.015
11 9,000 0.003 0.41 14,000 0.01
12 10,000 0.0025 0.43 14,000 0.01
13 12,000 0.0025 0.39 15,000 0.0025
14 14,000 0.002 0.29 15,000 0.002
Effect of sewer flushing on removal of deposits.
Shape of cross section
% of slope increase
Frequency of flushing % deposits removals
Circular 5 Once/yr 13
Twice/yr 31
7 Once/yr 28
Twice/yr 55
10 Once/yr 42
Twice/yr 73
15 Once/yr 76
Twice/yr 89
Square 5 Once/yr 7
Twice/yr 29
7 Once/yr 12
Twice/yr 50
10 Once/yr 31
Twice/yr 58
15 Once/yr 56
Twice/yr 69
Rectangular 5 Once/yr 9
Twice/yr 32
7 Once/yr 39
Twice/yr 55
10 Once/yr 70
Twice/yr 73
15 Once/yr 70
Twice/yr 75
CONCLUSIONSCONCLUSIONS
Suspended sediment concentrations in the stormwater runoff of arid residential catchments are significantly affected by the characteristics of both stormwater runoff and duststorms over the catchments. Thus, stormwaters runoff and duststorms are recommended to be considered for proper prediction of the sediments in the stormwater runoff.
The concentrations of heavy metals in the stormwater runoff in arid catchments vary with variations in the concentrations of transported
suspended sediments. Thus, the developed regression equations relating these types of concentrations are recommended to be used by scientists
and engineers.
The concentrations of transported suspended sediment and those of heavy metals in the runoff of the investigated arid catchments vary with the
variations in the particle size of transported sediment. Thus, identification of the transported suspended sediment particle size range is of importance
for accurate prediction of the concentrations in the runoff.
CONCLUSIONSCONCLUSIONS The developed regression equations for the prediction of both concentrations of
transported suspended sediment and those of heavy metals in the stormwater runoff of the investigated catchments with considerations of particle sizes of transported suspended sediment are more accurate than those developed without considerations of the sediment sizes. Thus, the equations which consider the particle sizes of transported suspended sediment are recommended, if possible, to be used for the prediction of the concentrations of suspended sediment and heavy metals in the stormwater runoff of the investigated arid residential catchments
Transported sediments in arid and semiarid areas are influenced by rainstorm and duststorm as well as by catchment characteristics.
Suspended, bedload as well as wash load transport loads from arid and semiarid catchments may be predicted by a simple regression type relationships.
Increase of sewer slope increases the removal of deposited solids
The removal volume of deposited solids by increasing the sewer slope varies with the shape of sewer cross section.
Sewer flushing is an effective way to increase the removal volume of deposited solids
An optimization methodology could be applied for the sewer slope, sewer shape of cross section, and interval of sewer flushing in order to identify the conditions of feasible maximum removal of deposited solids.
The removal of deposited solids from the sewer system should be integrated with a management scheme to reduce solids from source, and with treatment of facilities
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