G.frunza_L.batali_Evaluation of Hydraulic Properties of Soils. Correlations Between
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Transcript of G.frunza_L.batali_Evaluation of Hydraulic Properties of Soils. Correlations Between
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Evaluation of hydraulic properties of soils. Correlations between
different methods. Application for Bucharest area.
Georgiana Sorina Frunz1, Loretta Batali2
1,2 Technical University of Civil Engineering Bucharest, Faculty of Hydraulic Works, 124 Boul.
Lacul Tei, sector 2, 020396 Bucharest, Romania
Abstract
There are numerous methods for determining hydraulic conductivity of soils: laboratory methods,
in situ tests or methods based on empirical correlations with other physical parameters of the soil.
Hydraulic conductivity is a very sensitive parameter to several factors, which lead to large
differences between the values obtained using different methods.
When a hydro-geological database is to be developed, one of the main problems to be solved is to
interpret and integrate hydraulic conductivity values which were obtained by various authors and
through different methods.
Paper presents part of a research conducted in the framework of SIMPA project Platform for management of sedimentary groundwater in urban areas financed by ANCS. This part of the research aims to define the hydro-geological database to be introduced in the GIS platform.
Comparisons are made between the values determined by different methods, based on which it will
be possible to determine reliable values of the hydraulic conductivity to be used by the GIS
platform.
Keywords: soil, groundwater, empirical correlations, permeability
1. Introduction
Urban groundwater is a risk environment considering both sensitivity and multiple influence
factors that arise in such environment. Their correct management is a relatively difficult task to
accomplish, especially in an area of increased urban development and, in some aspects even
chaotic, as the capital.
Project SIMPA "Platform for the management of sedimentary groundwater in urban areas "
initiated by UTCB, including also the present study, represents an important step in this direction,
its aim being to develop a GIS data platform for managing the existin data. .
Platform for the management of sedimentary groundwater in urban areas - SIMPA proposes
carrying out hydrogeological resources management in Bucharest area, which contributes to a better
geological, geotechnical and hydrogeological knowledge of the Moesic aquifer system, in order to
achieve a better management of it.
The area chosen for study, as also in other areas of the country, there is very little control
over the work performed underground or work of investigation and exploitation of water resources.
This leads to difficulties of management, but also to problems of interpretation of new
investigations due to unknown interactions that may be present. In view of the large amount of
investigations carried out in the area around Bucharest, there is a large quantity of information
related to ground and aquifer structure, without, however, being organized and structured.
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Having a management platform that provides information on everything that underground
environment in this area means is very useful for all actors in the field: authorities, designers,
building companies, etc..Also, such a platform will provide opportunities for more detailed study
when you want building a new underground construction, in order to take into account as many
possible interactions.
In this context, one of the steps is the proper characterization of geological layers by
hydrogeological and geotechnical parameters. For this purpose we used historical data and special
studies were conducted to characterize in terms of permeability coefficient, given that this is a very
sensitive parameter and that different methods for its determining lead to very different results.
Based on these studies will be assigned a correct value of the permeability coefficient for each
layer.
Also, based on different single values, an extrapolation is necessary and spatial extent of the
values to the entire volume of soil, the required tools being included on this platform
The paper presents aspects related to the permeability coefficient assessment through
different methods, with application to Bucharest area.
2. Determination of the coefficient of permeability
2.1. Test Methods
At present, the issues related to the groundwater movement are treated by geologists, hydro-
geologists, geotechniciens, pedologists etc, each and every one of these Communities having
developed their own methods for measuring the permeability coefficient. This proliferation of the
methods has as result that engineers are in the face of such delicate choices to find the proper
method to solve the problem being studied, choices which are often uninspired or even wrong.
Permeability coefficient can be determined in situ, in the laboratory or oby using
correlations with physical soil parameters, for each of these categories existing a large variety of
methods which are the subject of research and improvement even at present (even if many methods
are applied by many years).
Regarding the in situ and laboratory methods for determination of the permeability
coefficient, the main classification of problems and methods refers to the saturation, saturated or
unsaturated environment, respectively. In this paper we refer in particular to saturated enviroments.
Among the methods for the determination in laboratory can be mentioned:
- Permeametres with flexible or rigid walls - Permeametres with or without normal stress - Permeametres - with or without suction - Permeametres - with constant or variable head Among the in situ methods the most used are:
- Experimental pumping test - steady or transient - Flow velocity measurement using tracers - Measurements in auger holes and boreholes - Piezometer method - Piezocone method (CPTu) - Experimental water pouring (Boldarev-Nesterov) - Drain line method - Method Lefranc - Method Brillant - Lysimeters
Correlations between different soil parameters is a semi-empirical or empirical method for
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determining some parameters, including the permeability coefficient, that is much appreciated
by engineers, as in this case investigations are limited to a minimum and the literature abounds
in such relationships. It should be noted however, that their use is limited to certain soil types,
possibly to certain specific conditions and cannot be used in any manner whatsoever without
control over the results (differences, as will be shown later, being significant).
2.2 Selection of the determination method
When it comes to determining the soil permeability more questions can be raised:
- Which is the nature of the parameter to be measured - ksat, kunsat,, for example? - How it should be properly measured - in the laboratory, on the field? - Which should be the test duration? - Where should the measurement be performed? the ground is not homogeneous - How many measurements should be conducted to obtain a representative value?- Role of
geostatistics
- What means are available? The following figure presents a summary of methods for determining the permeability that can
provide elements for choosing the optimal method (Figure 1, after Chossat, 2005).
Figure 1. Method for determinining the permeability coefficient in saturated environments (after
Chossat, 2005)
Determination of hydraulic conductivity in
saturated environment
Laboratory tests Empirical methods
Constant head
-cylinder
-permeameter
-triaxial
-centrifuge
Variable head
-cylinder
-centrifuge
- Hazen
- Alyamani & Sen
- Slichter
- Beyer
- Chapuis
- Kruger
- Kozeni
- Puckett et al
- Raawls & Brakensiek
- Shepard
- Sperry & Peirce
- Terzaghi
- Zamarin
- Zunker
- USRIn situ tests
In the saturated area In the unsaturated area
In the saturated area
-piezometer
-tube method
-piezocone
-Pulse test
-Slug test
-Mini-slug test
-Drain line method
-Borehole
-Lefranc
-Multiple wells
-Pumping test
-Lugeon method
-WD-test
-Open tube method
-Dipole flow test
-Infiltrometers under pressure
simple infiltrometers open or
closed ring
double infiltrometers open or
closed ring
Guelph infiltrometer
Infiltration rate
Two tubes method
-Infiltrometers in suction
Multidisc method
Minidisc method
-Guelph permeameter
-Boutwell method
-Nasberg method
-Porchet method
-Lefranc method
-Matsuo method
-Saturated spot test
-Shani method
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In this analysis of methods for determining the permeability coefficient other parameters should
also be considered, as the measurement accuracy, the variability and scale effect.
Accuracy of measurements is very different for the various methods. The causes of lack of
precision are numerous and are different in the case of in situ measurements or laboratory tests and
are not always well known by the operator.
2.3. Accuracy of laboratory measurements
Even when it is well done, sampling has a significant effect on permeability assessment. The
first causes of imprecisions are related to the effect of permeameter walls and to the uncontrolled
water flow. Removing the existing burden stress on sample in the ground when it is removed has
also a significant effect, especially when the sample depth is high.
In the next figure can be seen (after Chossat, 2005) the difference between the values
determined in the laboratory and in situ for a sandy soil. From this comparison resulted a difference
of about 10 m/day for about 60% of values. This difference can be attributed to the disappearance
of normal stress.
Figure 2 Comparison between the values measured in laboratory (permeameter) and in situ
(pumping). Weilbull distribution of obtained values (Chossat, 2005)
2.4. Precision measurements of soil
Installation of test material is the first source of error when determining is made in holes or
boreholes . Effect was revealed regarding irregularities of borehole walls that create preferential
flow areas.
It was also noted that measurements performed by artificial saturation are different from those
performed after a natural saturation, due to successive rains. The reason seems to be the different
distribution of air in the pores.
Nature of the soil is another cause of inaccuracies, considering that only some methods can be
applied regardless of the type of soil. The following table presents after Chossat (2005) limitations
of methods in this regard.
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Table 1. Applicability of methods for determining the permeability coefficient (Chossat, 2005)
Very permeable soil Permeable medium
soil
Less permeable
soil
Laboratory
Methods
- Permeametre
- Cylinder with
variable head
-Permeametre
- Cylinder with
constant-head
Triaxial
-Centrifuge
Field Methods -Lefranc test with
analog methods
- Boutwell Method
- Double open ring
-Leaking test or
Porchet test
- Slug test
- Auger hole method
-Minidisc
permeameter
- Boutwell Method
-Guelph
permeametre
- Open tube method
-Slug test
-Wells and
piezometers
- Double-seal ring
-Infiltrometre
Guelph
-Pluse test
- Lugeon test
In Table 2 are presented (after Marchidanu, 1996) some common methods used in Romania,
according to the nature of the tested soil.
Table 2. Common methods for determining the coefficient of permeability in Romania
(Marchidanu, 1996)
Type of soil or rock
The range of
permeability
coefficient
k (cm / s)
Recommended methods
In laboratory In situ
Clay < 10-7
Consolidated
oedometer, constant
head permeameter, with
suction
Free pouring in shallow
pits (infiltration spheres
method and Boldarev-
Nesterov method) and in
boreholes Sandy silty clay, sandy
clay, fine sand with silts
and clays, loess
10-7
10-3 Constant head
permeameter, with
suction
Clean sand, with or
without gravel 10
-3 - 1
Constant head
permeameter, without
suction, variable head
permeameter,
calculations based on
granulosity
Pouring and pumping
tests in boreholes
Lefranc and Brilliant
methods, with chemical
or radioactive tracers
Gravel with or without
sand 1 - 10
2
Hard rock, fissured Regardless
the permeability -
Free pouring or injection
of water under pressure
performed in boreholes
holes
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Variability is one of the most important issues for permeability measurement. Variation
obtained by experiments corresponds to a random variability of permeability in the field? In these
conditions how many measurements should be conducted to obtain a correct average value? A
single measurement can not express the variability. Several authors have addressed this issue over
time (Chossat, 2005 for example). For example, Van Beers (1958) recommends a survey every 0.8
ha. Spatial variability of permeability is a problem that can be solved by geostatistical methods.
2.5. Scale effect
Laboratory tests are geneally performed on small size samples, which are far from being
representative of the in situ conditions. Also, they can not reproduce the anisotropy conditions.
Daoud, 1996 (quoted by Chossat, 2005) revealed a marked influence on permeability of soil
clods on the permeability, which can drop by several orders of magnitude when the samples were
compacted with as little clods as possible.
2.6. Conclusions
Considering the large differences between the various methods, the obtained values are difficult
to compare to each other.
There are reference methods in current practice that may be used for reporting. For
measurements in aquifers these are pumping tests on site and the rigid-wall permeameter in
laboratory. Chossat (2005) presents such comparisons between values obtained with different
methods.
3. Case Study
3.1 Introduction
As was previously stated, the main objective of the research is to develop a GIS platform for
characterization of the sedimentary area of Bucharest, in which the soil layers composing the
ground to be defined in terms of hydrogeological and, partially, geotechnical point of view. For this
purpose, we used a database of geological and geotechnical data of UTCB - Department of
Geotechnics and Foundations, as well as of some partners in the program SIMPA. From previous
conducted studies and reported in this database were extracted permeability coefficient values
determined by different methods - on site, usually by pumping tests or, more rarely, with CPTu
(Cone penetration test with pore water pressure measurement) or in laboratory - by direct
permeability testing with or without normal stress, or by indirect method, based on the
consolidation coefficient (for clays).
Also, for all these values were applied correlations taken from literature in order to be later
compared to values determined by tests. From Bucharest area were chosen few sites that were
investigated more in detail, namely: the pilot project located inside Colentina Laboratory Complex
(5, Rascoalei str., sector 2), Titan Park (Liviu Rebreanu str, sector 3.), Casa Radio (Dmbovia Center, Calea Stirbei Voda 174-176.) and Aviatiei ( Avionului str, sector 1).
Area pilot Colentina is shown in more detail below:.
3.1. Pilot area Colentina
The study area chosen in Bucharest, called pilot area, is located in 5, Rascoalei Street, sector 2.
within the complex of laboratories Colentina belonging to UTCB (Figure 3).
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Figure 3. Location of pilot area
To achieve correlations were used five hydrogeological boreholes, one geotechnical borehole
and two piezometers.
From a morphologic point of view, the area belongs to interfluvial area Dambovita - Colentina
rivers, with absolute levels ranging from 70.0 to 80.0 mdMN. This area belongs to Campia Vlasiei ,
morphological subunit of the Romanian Plain.
From a geological point of view, the succession of ground deposits, attributed to Quaternary
age, Upper Pleistocene floor, comprises:
- loess deposits of river Dambovita terrace; - Complex of Colentina gravel deposits - Intermediary deposits of sandy clays - Mostistea sands deposits. The thickness of the aforementioned horizons, as well as their homogeneity is variable, the total
average thickness of 15.0 25.0m.
The analysis of general lithological column observed on field during the geotechnical
exploration works, as well from the analysis of geotechnical laboratory test results, revealed the
following stratification:
Layer I: top soil layer (about 0.20 m thick) and man-made fill; fill thickness is ranging from
2.00 - 2.50m in the inner platform of the laboratories area, to 3.60 - 4.80m in the terrace area (upper
plateau); man-made fill consists of granular material, building materials fragments, in cohesive
matrix heterogeneous, unconsolidated, etc.
Layer II: clayey complex made of silty clay, clay, sandy clayey silt, brown - yellow, medium
soft to stif consistency, with weathered limestone and concretions; the thickness of the cohesive
layer is ~ 2.00 6.00m below the man-made fill; at the layer base, the fine medium sand fraction is increasing, the soil becoming sandy (sandy clay to clayey sand), medium soft to soft in the area
of the phreatic groundwater (capillary frange) ;
Layer III: clayey sand to fine medium sand, yellowish brown to yellowish gray, poorly graded; the thickness of the slightly cohesive - granular layer is of 2.0 4.0m, this making the
transition to granular materials representing the foundation of the main riverbed of the river
Colentina, in which the groundwater level can also be found .
Layer IV: silty clay to clay, passing to sandy clayey silt, brown yellow, medium soft, with concretions; the cohesive layer thickness is ~ 3.00 4.00m, below the sand layer being found an
alluvium layer; at the layer base, the fine medium sand percentage is increasing, the soil bcoming sandy, in medium soft to soft state (in the vicinity of the groundwater level capillary area
Layer V: fine medium sand, gray to yellowish gray, poorly graded, micaceous; the thickness
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of the granular layer is of at least 7.00m.
The permeability coefficient on site was determined by experimental pumpings in boreholes
which provide the most conclusive data on the hydrogeological parameters of an aquifer.
Boreholes are drilled to the depth of 25 m and were equipped with filter columns made of
plastic (Figure 4).
Figure 4.Schematic equipment of a borehole with filtering
column and filter material
The methodology for determining the permeability coefficient supposes to pump the water from
the borehole and to measure the flow rate for a constant draw-down (Figure 5). .
Depending on the equipment of the boreholes, it results a groundwater draw-down and of the
specific aquifer capacity.
For obtaining a conclusive pumping at least 3 draw-down stages are required to be maintained
until achieving a constant flow rate
Figure 5. Scheme of experimental pumping performed with pump
located on the surface: 1 - whirlpool, 2 - inlet, 3 - pump, 4 -
measurement vessel flow (referinta)
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During the experimental pumpings the following data were obtained: lithological column of the
borehole, equipment scheme, depth of groundwater level, flow charts variation in time for each
draw-down stage and graphs of flow rates vs draw-down.
In laboratory, the pemeability coefficient was determined using permeametres without normal
stress, with constant or variable head and oedopermeametrs (both direce and indirect method based
on consolidation coefficient).
Besides the permeability coefficient determination, were also performed tests for soil
identification and characterization (grainsize analysis, Atterberg limit, water content, porosity, etc..)
3.3 Empirical correlations
In literature are available numerous empirical relationships through which the permeability
coefficient can be determined based on other physical indices of soil.
Of these, in this study were used the following correlations:
Hydraulic conductivity (K) can be estimated according to the grain-size distribution of samples,
related also with other properties of the soil. Vukovic and Soro (1992) present a general form of
more studied empirical relationships:
(1)
where K, hydraulic conductivity, g the gravitational acceleration, - kinematic viscosity, C-coefficient of sorting, f (n) - function of porosity and effective diameter.
Values of C, f (n) and de depend on the various methods used for grain-size analysis. According
to Vukovic and Soro (1992), porosity (n) can be determined using an emipirical relationship based
on coefficient of uniformity:
(2)
where U is the coefficient of uniformity resulting from the equation
(3)
where d60 and d10 is the diameter for 60% and 10% of particles, respectively, expressed in mm.
Here below are presented the empirical relationships taking the form of the general equation (1)
above.
Alyamani & Sen
(
4)
Where K (m / day), I0 interception (mm) a straight line formed by joining points d50 and d10 of
the grading curve (mm), d10 and d50 are taken in mm.
Breyer:
(5)
This method doesnt consider the porosity, therefore the porosity value is equal to the unity. The formula is useful for heterogeneous soils, an uniformity coefficient ranging from 1 to 20 and an
effective diameter, de comprised between 0.06 - 0.6 mm.
Hazen:
(6)
Hazen formula was originally developed for the determination of hydraulic conductivity for
poorly graded sands, but is also useful for fine sand with fine gravel, provided that the soil has an
uniformity coefficient less than 5 and the grain-size is between 0.1 and 3 mm
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Kozeny-Carman:
(7)
Kozeny-Carman equation has a wide field of use. This equation was originally proposed by
Kozeny (1927) and was later modified by Carman (1937, 1956), becoming Kozeny-Carman
equation.
Slichter
(8)
This formula applies to soils with effective diameter between 0.01 mm and 5 mm.
Terzaghi
(9)
where Ct = coefficient of sorting, 6.1x10-3
< Ct
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Table 3. Laboratory-determined parameters for the locations Colentina
Borehole Share
(m)
Level d10
(mm)
d17
(mm)
d20
(mm)
d30
(mm)
d50
(mm)
d60
(mm)
I0
(mm)
W % WL % Wp % Ip Ic n lab
%
e lab %
G1 63.5 Brown-yellow
clay with iron
oxides and
weathered
limestone
0.0016 0.003 24.2 65.8 20.05 44.75 0.93
G1 59.5 Sand, gray and
brown with gray
intercalations and
mica
0.18 0.22 0.25 0.32 0.42 0.48 0.14 7.2 36.19 0.57
G1 54.5 Medium dark gray
sand
0.1 0.12 0.14 0.16 0.18 0.2 0.08 9.8 38.00 0.61
G1 40.5 Medium sand,
gray yellow and
brown
intercalations
0.18 0.24 0.28 0.32 0.38 0.4 0.16 6.83 37.37 0.60
G1 27.5 Yellowish gray
sandy clay, stiff
0.0038 0.005 25.05 59 19.66 39.34 0.91
F3 56.3 Yellowish -
brown medium
sand
0.0018 0.004 0.012 0.024
F3 51.3 Medium sand,
gray
0.16 0.22 0.24 0.26 0.34 0.38 0.14 36.95 0.59
F5 55.4 Medium gray
brown sand
0.18 0.22 0.26 0.3 0.38 0.42 0.16 37.07 0.59
F5 46.4 Medium gray
sand
0.02 0.06 0.12 0.2 0.25 0.26 0.014 24.50 0.32
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Table 4 Parameters determined in the field and empirical method for location Colentina
Bore
-hole
Sh
are
(m)
Lev
el (
m)
K l
abora
tor
(m/s
) S
lich
ter
(m/s
)
Zam
arin
(m
/s)
Aly
aman
i&S
en
(m/s
)
Chap
uis
(m
/s)
Haz
en (
1892)
(m/s
)
Koze
ny (
m/s
)
Kru
nger
(m
/s)
Pav
chic
h (
m/s
)
Sper
ry &
Pei
rce
(m/s
)
Shep
ard (
m/s
)
Sau
erbre
i
Vukovic
&S
oro
,
(m/s
) US
BR
(Vukovic
&S
oro
, m
/s)
Raw
ls &
Bra
ken
siek
(m/s
)
Puck
ett
et a
l
(m/s
)
Jabro
(m
/s)
Bre
yer
(m
/s)
G1 63.5
Brown-yellow
clay with iron
oxides and
weathered
limestone 4.5
8E
-12
2.4
1E
-11
3.5
E-1
0
1.0
7E
-08
2.8
2E
-06
G1 59.5
Sand, gray and
brown with
gray
intercalations
and mica 5.7
8E
-05
4.4
3E
-07
7.9
4E
-05
3.2
1E
-04
1.9
8E
-04
4.8
6E
-04
7.7
5E
-02
3.5
E-0
6
7.4
E-0
7
1.1
0E
-04
6.5
0E
-04
9.8
3E
-05
1.4
8E
-02
8.3
3E
-04
G1 54.5
Medium dark
gray sand
1.0
4E
-05
1.3
7E
-07
2.3
3E
-05
1.0
1E
-04
5.1
9E
-05
1.5
0E
-04
2.5
1E
-02
1E
-06
2.2
E-0
7
1.1
0E
-04
2.4
6E
-04
3.0
6E
-05
3.9
1E
-03
2.7
1E
-04
G1 40.5
Medium sand,
gray yellow
and brown
intercalations 5.0
0E
-05
4.4
3E
-07
7.6
7E
-05
4.1
0E
-04
2.0
4E
-04
4.8
6E
-04
7.9
9E
-02
3.4
E-0
6
8.8
E-0
7
1.1
0E
-04
6.5
0E
-04
1.2
1E
-04
1.9
3E
-02
8.6
2E
-04
G1 27.5
Yellowish
gray sandy
clay, stiff
1.8
4E
-11
1.3
6E
-10
3.5
E-1
0
1.0
8E
-08
2.8
9E
-06
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Bore
-hole
Shar
e (m
)
Level (m)
K p
om
par
e
Sli
chte
r (m
/s)
Zam
arin
(m
/s)
Aly
aman
i&S
en
(m/s
)
Chap
uis
(m
/s)
Haz
en
(1892)
(m/s
)
Koze
ny (
m/s
)
Kru
nger
(m
/s)
Pav
chic
h (
m/s
)
Sper
ry
&
Pei
rce
(m/s
)
Shep
ard (
m/s
)
Sau
erbre
i
Vukovic
&S
oro
,
(m/s
)
US
BR
(Vukovic
&S
oro
, m
/s)
Bre
yer
(m
/s)
F3 56.3 Yellowish - brown medium sand
6.9
2E
-05
F3 51.3 Medium sand, gray
6.9
2E
-05
3.5
0E
-07
6.1
4E
-05
3.1
4E
-04
1.5
3E
-04
3.8
4E
-04
6.2
5E
-02
2.7
E-0
6
7.4
E-0
7
1.1
0E
-04
5.3
5E
-04
1.0
0E
-04
1.3
5E
-02
6.7
3E
-04
F5 55.4 Medium gray brown sand
1.0
9E
-04
4.4
3E
-07
7.7
4E
-05
4.1
0E
-04
2.0
2E
-04
4.8
6E
-04
7.9
3E
-02
3.4
E-0
6
7.4
E-0
7
1.1
0E
-04
6.5
0E
-04
1.0
0E
-04
1.6
2E
-02
8.5
4E
-04
F5 46.4 Medium gray sand
1.0
9E
-04
1.4
9E
-06
5.8
7E
-06
8.4
1E
-07
6.6
6E
-04
6.6
E-0
8
5.5
E-0
8
1.1
0E
-04
1.7
3E
-05
5.0
8E
-06
2.7
4E
-03
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3.4. Comparisons between obtained values
For location Colentina, which benefited from detailed investigations regarding the permeability
coefficient, as well as for the aforementioned other sites, but based on archive date, comparisons
were made in graphical form for the values obtained by different methods. These are presented in
the following figures (6-11).
Figure 6.Comparison between the values of the permeability coefficient determined in
laboratory (permeameter method) and empirical correlations for cohesive materials from
the Colentina site
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Figure 7. Comparison between the values obtained for the permeability coefficient determined on
site, literature values and based on empirical correlations for granularmaterials from Colentina site
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Figure 8. Comparison of permeability coefficient values determined on site using
CPTu and based on empirical correlations for location Titan Park
Figure 9.1. Comparisons between values of the permeability coefficient determined by field
pumping tests and based on empirical correlations for location Titan Park
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Figure 9.2. Comparisons between values of the permeability coefficient determined by field
pumping tests and based on empirical correlations for location Titan Park
Figure 10. a) Comparison of permeability coefficient values obtained from pumping tests
and various empirical correlations for Casa Radio site
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Figure 10.b. Comparison of permeability coefficient values obtained by pumping tests
and based on different correlations for Casa Radio site
Figure 11. Comparison of permeability coefficient values obtained from laboratory
inverse method (consolidation) and based on correlation obtained for a clay sample taken
from Aviation site
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A first observation that can be made is that it is confirmed a rather large variability in the values
obtained by different methods.
For example, between the values determined by field pumping tests and those obtained by using
empirical relations there are differences varying from 0.68. to 132 %. The differences between the
laboratory determined values and the empirical methods vary from 15.3 to 25.25%.
The comparisons show that for sands the closest empirical methods are Hazen, Zamarin and
Alyamani & Sen. Using USBR, Sauberbei, Vukovic & Soro, Krunger, Sperry & Peirce and Chapuis
relationships the resulting values are underestimating the hydraulic conductivity. While
relationships Sheard and Kozeny have overestimated values of hydraulic conductivity compared to
those resultes from the laboratory using permeameters.
For cohesive soils, the values obtained from literature USBR are the closest to the values
obtained in laboratory and taken from literature, while the other two relations, Puckett et al and
Rawls & Brakensiek have overestimated values of hydraulic conductivity.
4. Conclusions
The platform for the management of groundwater in sedimentary environment in urban areas SIMPA, program of UTCB, aims at achieving a hydrogeological resource management program for
Bucharest area, which contribute to a better geological, geotechnical and hydrogeological
knowledge of the Moesia aquifer system in order to improve its management.
In developing this platform, one of the steps is the proper characterization of geological layers
by hydrogeological and geotechnical parameters.
The main objective of this stage is assigning a realistic value of permeability coefficient for
each soil layer.
To achieve this we used historical data from many different sites in Bucharest area and were
performed also specific studies only to characterize in terms of permeability coefficient, given that
this is a very sensitive parameter and that various methods for determining lead to very different
results.
Archive data and those obtained for the pilot area Colentina, located inside the complex of
laboratories Colentina belonging to UTCB, including in situ determined values (usually by pumping
experimental tests, but also CPTu) and in laboratory (permeameter, oedopermeameter, based on
consolidation coefficient) were processed and compared with values obtained by different empirical
methods or literature. Significant differences were obtained in some cases, showing that the mere
use of literature data or empirical correlations for any type of soil is not sufficient.
Also, the correct choice of methods for direct determination, in laboratory and field, and their
correct implementation (closing of aquifers during the on site tests or the realistic reproduction of
field conditions in case of laboratory testing, for example) is crucial in obtaining a realistic value of
the permeability coefficient.
As in most situations geotechnical reports dont contain determination of the permeability coefficient and only limited data regarding the geotechnical characterization of soils are available
the engineer is required to use data from the literature or apply empirical correlations with other
available parameters. An inappropriate choice of these relationships lead to errors of several orders
of magnitude, which can have a decisive impact on the results of hydrogeological analysis. It is
recommended, therefore, that whenever it is necessary to perform such a hydrogeological study ,
including a proper determination of the permeability coefficient.
The paper presents some aspects regarding the determination of soil permeability coefficient
and comparisons, based on a large amounts of data, between the values obtained by different
methods, drawing useful conclusions for assigning correct values of permeability parameters within
SIMPA groundwater management platform .
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Acknowledgements This research was funded by the National Authority for Scientific Research of Romania in the
research project GROUNDWATER MANAGEMENT PLATFORM IN URBAN AREAS IN SEDIMENTARY ENVIRONMENT (SIMPA).
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