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First International Conference for PhD students in Civil Engineering

CE-PhD 2012, 4-7 November 2012,Cluj-Napoca, Romania www.sens-group.ro/ce2012

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.



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



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



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.



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



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).



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



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)



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



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



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



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



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



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



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



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



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



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



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 .



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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