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Estimation of the Water Resources Potential in the
Island System of the Aegean Archipelago, Greece
a
b
Christos A. Karavitis & Petros Kerkides
a
IWRA, Colorado State University , Fort Collins, Colorado, USA
Agricultural University of Athens , Greece
b
Published online: 22 Jan 2009.
To cite this article: Christos A. Karavitis & Petros Kerkides (2002) Estimation of the Water Resources Potential in the Island
System of the Aegean Archipelago, Greece, Water International, 27:2, 243-254, DOI: 10.1080/02508060208686998
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International Water Resources Association
Water International, Volume 27, Number 2, Pages 243–254, June 2002
Estimation of the Water Resources Potential in the Island
System of the Aegean Archipelago, Greece
Christos A. Karavitis, Member IWRA, Colorado State University, Fort Collins,
Colorado, USA, and Petros Kerkides, Agricultural University of Athens,Greece
Abstract: The present paper tries to estimate the surface water resources potential in some of the
major Aegean islands in an effort to provide a means for the continuous development of the region, and,
by extension, for similar areas around the world. The islands have to confront the challenge of surviving
in a semiarid environment under the constraints of uneven water resources distribution both in space
and time. In addition to these, tourism development, industrialization and highly water consumptive life
styles have exacerbated perennial problems in water resources and water resources management. The
framework of the present effort has a two-prong emphasis. In the first part, a simulation model is pre-
sented, which tries to estimate the potential surface runoff under physical, structural organizational,
and institutional constraints. The methodology and the premises of the simulation process are delin-
eated. In the second part, the results of the model’s application in distinct cases are demarcated. The
final product, namely the model and the resulting runoff coefficients, are presented in the form of a
standard, which may provide practitioners in the field as well as decisionmakers the means for an initial
reference in pertinent developmental efforts. Finally, the conclusions and recommendations raise the
question of ecosystem resilience and point towards the urgent and continuous need for the application
of integrated water resources management principles.
Keywords: Water resources estimation, surface runoff coefficient, management in island systems,
simulation models, semi-arid environment, Aegean islands, Greece.
resources interdependencies, high susceptibility to pollu-
Introduction
tion, and by the sensitivity between the water and soil
The difficulty in studying water resources in general, equilibrium. The soils in the islands are extremely vulner-
and in the islands of theAegean Archipelago in particular, able to erosion with resulting problems in developing the
includes not only an assessment of their natural state, ter- water resources (reservoir sedimentation, streambed sta-
ritorial distribution, and fluctuations in time, but also their bility, etc.). Most of the population is concentrated in the
dependence on human socio-economic activities. In re- coastal zone, and increasing tourism causes a strong, sea-
cent decades, the intensified exploitation of water resources sonal water demand. Thus, uneven water demands in both
for urban, agricultural and industrial uses, the population space and time greatly increase the cost of making water
redistribution and growth, as well as alarming indications accessible. Wastewater management problems prolifer-
about climatic shifts (greenhouse effect, droughts, etc.) ate with the expanding urban population during the sum-
have started to elicit significant impacts on the state of the mer and effluents are deteriorating the quality of coastal
available freshwater, despite the ability of stream and waters. Summarizing the key conflicts and concerns com-
groundwater flow for renewal and recharge.
bining integrated water resources management and a sus-
The Aegean Archipelago, as a part of Greece, be- tainable development orientation in the Aegean
longs to the Mediterranean region. In this region water is Archipelago and by extension to similar areas, a few in-
used in an unsustainable manner. The Mediterranean land- terrelated crises and issues may be demarcated in rela-
scape as a whole is ecologically fragile and seriously en- tion to some more extensive comments made by Vlachos
dangered by prevailing social and economic trends. In this and Braga (2001):
regard, the future of the islands may be threatened by in-
creasing coastal areas stress, expanding deferences be- • A demand and water supply crisis representing, pri-
tween tourist areas and the rural hinterlands, serious water
marily, an engineering dimension. Such a dimension
243

244
C. A. Karavitis and P. Kerkides
incorporates measures of water consumption reduc- uisites, etc., which may render the overall effort extremely
tion and water supply augmentation; difficult. Nevertheless, the estimation of the surface run-
A deteriorating water quality crisis producing an eco- off should be a priority in all the efforts of evaluating the
logical dimension. Issues including, lack of adequate potential water resources in the islands.
safe drinking water supplies in the needed space and Hence, the estimation of the total volume of the ab-
time, groundwater deterioration and contamination, and stractions from a given precipitation volume in a water-
interference of water resources development systems shed may lead to the estimation of the surface water
with the natural environment cycles are surfacing; volume. Abstractions may be accounted for by means of
•
•
An organizational crisis transforming into a manage- runoff coefficients. Therefore, by estimating the runoff
ment dimension. Attention is needed in combining com- coefficient, it is believed that an initial approximation of
petent personnel, facilities and processes, the promotion the surface water may be given for further use, in all de-
of more desirable levels and patterns of use, as well as velopment efforts.
the legal and administrative guidelines (capacity build-
ing); and
Methodological Procedures
An information and data crisis, regarding their validity,
•
reliability, availability, and comparability, as well as com- Problem Definition and Objectives
bining data and judgement, modeling, and the building
The Aegean Archipelago of about 3,000 islands pre-
of applicable Decision Support Systems. In this con- sents a case of many “closed” island systems in a com-
text, all the pertinent factors point towards timely, con- mon enough environment located in the eastern part of
tingency oriented and anticipatory water resources Greece. The axis of the area from north to south is ap-
planning and management for the islands rather than proximately 700 km, where the zone from west to east
waiting for even more serious water shortages, pollu- has a width of about 300 km. A map of the islands are
tion and land erosion to occur.
illustrated on Figure 1. The islands present a unique diver-
sity in their climatic conditions, geologic characteristics,
The total water resources potential of Greece, includ- flora, and fauna. However, they exhibit some common
ing the Aegean islands, has different estimates throughout trends being mostly semiarid and exposed to almost identi-
the literature (Karavitis, 1999b). In this context, the total cal economic and social problems. Therefore, vulnerabil-
water resources potential of the Aegean islands sector ity raises the question of ecosystem resilience, especially
(
one of the 14 water sectors into which Greece has been because of periodic floods, droughts, and increasing an-
divided based on the major watersheds) is estimated at
9 3
about 1.25 x 10 m /yr with the various abstractions al-
ready accounted for. Of that amount, approximately 250 x
6 3
0 m /yr or 20 percent is stored as groundwater and the
1
9
3
remaining 1.0 x 10 m /yr is believed to constitute the sur-
face water potential. Crete (the largest Greek island and
one of the largest in the Mediterranean region) constitutes
another one of the Greek water sectors, and thus it is not
consider as a part of the Aegean islands. However, a few
of its watersheds were included in the present effort in
order to have a more complete representation of the whole
area. In this regard, it is pointed out that the total water
resources potential of Crete is estimated at about 2.6 x
9 3 9 3
0 m /yr. Approximately 1,3 x 10 m /yr or 50 percent is
1
9 3
stored as groundwater and the remaining 1.3 x 10 m /yr
constitutes the surface water potential. The Aegean is-
6 3
lands water sector uses approximately 80 x 10 m /yr for
6 3
irrigation, 33 x10 m /yr for domestic water supply, and
6 3
only about 1 x 10 m /yr for industrial purposes. The per-
6 3
tinent values for Crete water sector are 220 x 10 m /yr,
6 3 6 3
3 x 10 m /yr, and 2 x 10 m /yr, respectively. Overall, the
3
Aegean islands sector exhibits a total water use of 114 x
6 3
0 m /yr predominantly from groundwater, leaving almost
1
all of the potential surface water available for further de-
velopment. However, as in every surface water resources
development effort, additional site-specific constraints are
present, such as geology, morphology, environmental req-
Figure 1. Map of the Aegean Islands.
IWRA, Water International, Volume 27, Number 2, June 2002

Estimation of the Water Resources Potential in the Island System
of the Aegean Archipelago, Greece
245
6 3
Table 1. Indicative Water Demand in Various Watersheds of Selected Aegean Islands and in the Crete Water Sector in 10 m /yr
Island, Watershed Area
Irrigation
Urban and Industrial
Total
Skyros, Ferekampos
Allonesos, Kastanias,
Lesvos
1.5
1.6
46.0
4.0
0.9
15
0.8
0.7
7.0
1.0
0.6
1.8
0.8
0.8
11.0
0.5
0.7
2.3
2.3
53.0
5.0
Thassos, Limenaria
Melos
1.5
Naxos
16.8
5.8
Thassos, Theologos
Thassos, Prinos
Rhodes (UNEP, 1996)
Samothrace
5.0
3.0
16.0
3.2
2.4
3.8
27.0
3.7
Skopelos
3.1
Aegean Islands (total)
Crete (total)
151
415
64
66
215
481
thropogenic disturbances (Vlachos, 1995). The 1999 wa- estimation of the runoff. The literature review has indi-
ter demand estimates in some of the islands are presented cated that only sporadic efforts have been undertaken to-
in Table 1. The same table also reflects the water demand wards this objective in the area (Karavitis, 1999a; Kerkides
in the whole Aegean islands and Crete water sectors et al, 1996; UNEP, 1996). Thus, it is believed that the over-
(Bosdogianni, 1994; Karavitis, 1994; Karavitis, 1999b). It all approach may produce a tool for practitioners in the
is again pointed out that Crete water sector is divided into field, managers, and otherdecision makers in the form of a
separate watersheds due to its size. All in all, water re- standard for the Aegean Archipelago and, by extension, for
sources management efforts have to concentrate so as to other regions around the world facing similar problems.
breach the gap between water availability and the esca-
lating water demand, before it becomes chasmic through
Methodological Framework
time. Given the state of overexploitation of groundwater
resources, surface water resources may offer an alterna-
tive for the pertinent efforts.
The estimation of the runoff coefficient was based on
the utilization of simple general principles in the areas un-
In this regard, the main challenge of this research has der study. Hence, a simulation of the water balance pro-
been to estimate the overall surface water resources po- cess has been chosen to be applied. The criteria for such
tential in some of the major islands, in order to relate present an application were the standardization of the procedure,
resources with on-going and future water demands in an common inputs, and an accurate as possible representa-
already stressed environment. The surface water runoff tion of the reality, given the limited meteorological and
constitutes one of the major components of the islands hydrological databases. In this context, the basic water
water balance, and has to be identified for any water re- balance equation fulfills the pertinent criteria, even though
lated development projects. The precipitation and the ma- it is a very well known technique. However, the absence
jority of surface runoff takes place in the winter months, of any pertinent hydrological information in most of the
creating a strong time demand for water in the dry sum- area may point towards the necessity of such an effort.
mer season, where most of the activities are concentrated. Thus, despite the plethora of the existing modeling tools, it
Given the size of the islands, the corresponding small size was decided to develop a simulation model based on the
2
of the watersheds (average area less than 15 km ), and pertinent premises in order to approximate as closely as
the morphologiacal characteristics, the surface runoff is possible the context of the area. The process has followed
usually quickly lost to the sea. The absence of runoff mea- the principles of systems engineering techniques as a part
surements (except for a few cases), the overall data defi- of an integrated water resources management approach
ciencies, as well as the ephemeral character of the streams (Grigg, 1996). The methodological framework may be
giving often winter floods and completely drying up in the briefly delineated as follows:
summer are additional constraints. At the same time, the
continuing deforestation of the recent decades has in- • problem definition and objectives;
creased the estimated surface runoff creating also severe • area identification and data collection;
flood and erosion hazards (e.g., Thassos Island).
In order to identify the annual surface runoff, the an- • application of the Penman method for the estimation
nual surface runoff coefficient was chosen to be estimated. of evaporation and evapotranspiration;
• evaluation of the meteorological parameters;
The estimated runoff coefficients are plotted and the re- • estimation of the runoff coefficients; and
sulting curve may provide a handy reference for an initial • results and evaluation (including feed-back loop).
IWRA, Water International, Volume 27, Number 2, June 2002

246
C. A. Karavitis and P. Kerkides
All the pertinent steps are summarized in the next sec- perature, and wind velocity. The values were average
tions.
monthly ones. The precipitation data for the various areas
were taken from a number of stations presented on Table
3. Wherever needed (and possible), the Thiessen method
Area Identification and Data Collection
The estimation of the annual surface runoff coeffi- for aerial average rainfall was applied and/or elevation
cients involved the islands and regions, which are presented rainfall correction was computed. The final rainfall values
in Table 2. The area of the Kazantzes River, a tributary of used are presented on Table 6.
Erythropotamos in the Evros river watershed (Thrace),
has also been chosen for the application of the method.
Estimation of Evapotranspiration
This area would serve as a reference for the Northeast-
ern inland part of the country, for the necessary compari-
The modified Penman method was used for the esti-
sons to be drawn. Elements of the effort were parts of a mation of the evaporation and consequently of the evapo-
greater project for the development of water resources in transpiration (Cuenca, 1989). The general form of the
the islands by the Ministry of Agriculture. The current Penman equation used is (Kerkides et al., 1996):
study took place from 1993 to 1999. Numerous visits have
been conducted in every area of interest, and the water-
sheds, their morphology, and geology have been explicitly
studied. Flow data, where available, and meteorological
information have been collected. Demographic, economic,
(∆*R + E *γ)
a
PEVT =
(1)
∆
+ γ
Where PEVT is the potential evapotranspiration (mm
-1
and agricultural conditions have been recorded. Finally, day ); ∆ is the slope of the saturation vapor pressure-
information was also collected through the local authori- temperature curve calculated at mean air temperature (hPa
-1
-1
ties and agencies (MECPPW, 1993; Michailidis, 1994; K ); ∆ is the psychometric constant (hPa K ); and R is
n
-1
Kerkides et al., 1996; Karavitis, 1994; 1996; 1997).
the net long-wave and short-wave radiation (mm day
water equivalent) given by:
Meteorological Parameters
The necessary meteorological data included precipi-
tation, sunshine hours, and solar radiation, humidity, tem-
1
4
2
R = (1− r)R − σT (0.34 − 0.44(e ) )(0.10 + 0.90n / N)
n
s
a
a
(2)
Table 2. Islands, Regions, and Key Characteristics
Island or Region
North to South)
2
(
Area km
Population
Water Resources Characteristics
Thassos
380.1
4.0
13,527
Groundwater, springs, ephemeral streams
•
•
•
Prinos watershed
Limenaria watershed
Theologos watershed
7.4
9.4
Samothrace
Karavi watershed
Xeropotamos watershed
Lesvos
Eastern part
Western part
Allonnessos
Kastanias watershed
Skopelos
Panormos watershed
Skyros
Ferekampos watershed
Chios
178.0
8.0
3,083
Springs, streams, groundwater
•
•
9.0
1626.0
1081.0
545.0
129.6
4.5
87,151
Groundwater, springs, ephemeral streams
•
•
2,985
4,658
Groundwater, torrents
•
96.3
Groundwater, torrents
•
223.1
13.0
2,901
Groundwater, torrents
•
842.6
34.1
51,746
Groundwater, springs, ephemeral streams
•
Scardanas watershed
Psara
Naxos
37.5
438
Groundwater, springs, ephemeral streams
Groundwater, springs, ephemeral streams
428.0
10.2
14,838
•
Apeiranthos watershed
Melos
151.0
279.6
1400.0
625.8
184.3
237.3
76.0
4,390
3,021
Groundwater, springs, torrents
Groundwater, torrents
Kythera
Rhodes
98,181
93,394
137,111
21,025
1,281
Groundwater, springs, ephemeral streams
Springs, streams, groundwater
Groundwater, springs, ephemeral streams
Groundwater, springs, ephemeral streams
Streams, groundwater
Chania Region (Crete)
Heraklion Region (Crete)
Ierapetra Region (Crete)
Kazantzes Area (Thrace)
IWRA, Water International, Volume 27, Number 2, June 2002

Estimation of the Water Resources Potential in the Island System
of the Aegean Archipelago, Greece
247
Table 3. Meteorological Stations Used for Rainfall Data
Elevation
in m a.s.l.
Average Annual
Area
Station
Lat. (N)
Rainfall in mm
Time Period
Thassos
Samothrake
Thassos (NMS)
Kavala (NMS)
Alexandroupolis (NMS)
Thassos
40°46’
40°51’
40°51’
2
60
3
786.2
592.7
551.0
786.2
592.7
618.2
424.9
774.8
462.2
774.8
462.2
579.0
774.8
579.0
735.3
579.0
600.8
1932-41, 1960-92
1978-87, 1931-93
Kavala (NMS)
Mytilene (NMS)
Antessa (M.A.)
Skopelos (NMS)
Skyros (NMS)
Skopelos (NMS)
Skyros
Lesvos
39°04’
39°13’
39°59’
38°54’
3
150
11
1961-1990, 1975-
1997-1999
Alonnessos
1931-1994
4
Skopelos
Skyros
1932-39, 1955-94
1931-94, 1950-92,
1955-94
Chios (NMS)
Skopelos (NMS)
Chios
38°21’
37°46’
60
48
Chios
1950-92, 1931-40,
1946-92
Samos (NMS)
Mytilene (NMS)
Chios (NMS)
Psara
1931-39, 1951,
1
953-1980
351.2
Naxos
Naxos (NMS)
37°06’
36°44’
9
1980-92, 1970-90
Melos (NMS)
182
411.0
411.0
Melos
Melos (NMS)
1960-1987
1960-1987
1960-1987
1960-1987
1960-1987
1931-1992
1932-1996
Kythera
Rhodes
Kythera (NMS)
36°08’
36°24’
35°30’
35°20’
35°00’
(41°21’)
167
35
544.0
Rhodes (NMS)
712.0
Chania
Chania (NMS)
62
518.0
Heraklion
Ierapetra
Kazantzes
Heraklion (NMS)
14 Stations (MECPPW, MA)
9 Stations (NMS< MECPPW,
Sugar Ind., S.A.)
39
543.0
3 to 1150
44 to 380
413.0 to 1320.0
505.0 to 860.0
M.A.- Ministry of Agriculture. MECPPW - Ministry of Environment, City Planning and Public Works. NMS - National Meteorological Service
a.s.l. - above sea level. The latitude values in paraentheses are apprxoiate of the whole area.
where r is the surface albedo (0.06 for water surface and
Suggested values for the empirical coefficients a and
u
0
.25 for short green cover); s is the Stefan-Boltzman con- b are 1 and 0.537, respectively, when u is measured in m/
u
-1
-4
stant (mm day water equivalent K ); T is the mean air sec at 2 m above the ground or the water surface
a
temperature (K) and n/N is the ratio of actual to possible (Brutsaert, 1982). The stations for each area that were
hours of sunshine; and R is the incident short-wave solar used for the necessary data input are presented in Table 4
s
-1
radiation (mm day water equivalent) estimated by:
and the results are shown in Table 6.
(
3)
Surface Runoff Estimation
R = R (a + bn / N)
s a
Model Architecture
R is the extraterestrial radiation received at the top
a
The water balance model is a simulation model that
-1
of the atmosphere (mm day water equivalent), and a and may perform a rainfall runoff budget for a watershed on a
b are coefficients derived for various locations in Greece monthly basis. The current approach treats each island as
Kerkides et al., 1996). Furthermore, E is the aerody- either a single unified region, or considers the presented
(
a
-1
namic vapor transport term (mm day ) expressed by:
watershed(s) as representative and typical for the whole
island. Such an approximation has been accepted due to:
the limited meteorological and hydrological data, the areal
extent of the predominant geological formations, which in
(
4)
E = f(u)(e − e )
a s a
Again, e is the saturated vapor pressure and e the most cases were not corresponding to the watershed bar-
s a
actual vapor pressure, both in (hPa) and evaluated at mean riers and finally, the common physical characteristics among
air temperature and at 2 m above the ground or the water the various watersheds in a given island. The islands
surface. The term f(u) is given by:
Lesvos, Naxos, and Rhodes were examined in detail tak-
ing into consideration all the major watersheds. The model
estimates the runoff, the groundwater recharge and the
f (u) = 0.263(a + b u)
u u
(5)
IWRA, Water International, Volume 27, Number 2, June 2002

248
C. A. Karavitis and P. Kerkides
Table 4. Stations Used for the Penman Method
I is the infiltration (including deep percolation); AEVT is
the actual evapotranspiration; and ∆S is the change in the
soil moisture content
Area
Station
The actual evapotranspiration depends, in part, on the
precipitation and the soil moisture content. In this regard,
at some stages of crop or plant growth and in low soil
moisture conditions, the potential evaporation rate is not
realized. As soil moisture is gradually depleted, suction
increases, and soil hydraulic conductivity acquires smaller
and smaller values. And although the potential gradient
from the soil water to the leaves increases, the leaves
water potential decreases, and, therefore, the moisture flow
rate decreases. The effect is the reduction of evapotrans-
piration from the potential rate (PEVT) to some other value
Thassos
Samothrake
Lesvos
Thassos, Alexandroupolis
Thassos, Alexandroupolis, Lemnos
Mytilene
Skopelos, Skyros
skopelos, Skyros
Skyros
Alonnesos
Skopelos
Skyros
Chios
Chios
Psara
Chios
Naxos
Naxos
Melos
Melos
Kythera
Rhodes
Chania
Kythera
Rhodes
Chania
(
AEVT).
Various soil suction/plant evapotranspiration curves
Heraklion
Ierapetra
Kazantzes
Heraklion
Ierapetra
Orestias
exist ranging from a horizontal line at AEVT/PEVT equal
to 1.0, indicating equal availability of water from field ca-
pacity to permanent wilting point, to a line joining AEVT/
actual evapotranspiration. Each year’s values are based PEVT=1.0 at field capacity, to the point AEVT/PEVT=0,
on the values of the previous one, in order to achieve a at permanent wilting point (Withers and Vipond, 1988).
continuous time series. The only exception is the value of The model accepts the linear relationship based on the
the simulated field capacity (FC) of the first month of the pertinent declining line. Hence, the estimation of AEVT is
first year, which is the mean of the corresponding months being preceded by the calculation of field capacity (FC).
after the initial run of the model (the initial value of FC is Such a calculation is based on the following pre-
an arbitrary approximation). A schematic representation mises:
of the model is shown in Figure 2, and a more detailed
n
description of the model and its parameters is demarcated
in the following sections. The runoff estimation was per-
formed based on the evapotranspiration method. The equa-
,
n=1,2,3
(7)
FC =∑
i=1
(ϕud c )
i i
tion used for the simulation of the water balance (for a where (McWhorter and Sunada, 1988; Danalatos, et al.,
given time step) is delineated in the following equation:
1994; Kosmas, et al., 2000) φ is the average porosity
value of the soils equal to 0.45; u is the available for ex-
tractable water pore volume equal to 0.6, if it is assumed
that the capillary water and the air entrapped in the soil,
P = R + I + AEVT ∆S
(6)
where P is the total precipitation; R is the surface runoff; they each have an average value of 0.2 of the porosity; d
i
is the depth of the root system approximately equal to 1.0
m for the forest, 0.60 m for the bushes, and 0.20 m for the
plants with a shallow one (i signifies forest, bushes, and
Rain Evapotranspiration
shallow plants); and c is the percentages of plant cover
i
differ for each island catchment and they are estimated
based on the available information.
Root Zone Storage
The resulted various field capacities are presented on
Table 5. For the estimation of PEVT, the modified Penman
method was used as it was previously described. The es-
timation, then, of the surface runoff, may proceed based
also on the following prepositions:
Excess Water
Runoff
•
The monthly rainfall satisfies first of all the field ca-
pacity. Thus, the soil moisture is estimated on the first
and thirtieth of each month. Then, the average value
of soil moisture dictates the AEVT according to the
already described methodology.
Temporary
Storage
Released with
a time delay
Deep Percolation
Figure 2. Schematic representation of the Water Balance Model.
•
Runoff is generated only when both the field capacity
and the evapotranspiration components are satisfied.
IWRA, Water International, Volume 27, Number 2, June 2002

Estimation of the Water Resources Potential in the Island System
of the Aegean Archipelago, Greece
249
Hence, the soil moisture for the consequent month returning in each time step chosen specifically for every
would become case according to the geology where a + a + ... a are
i
i-1
i-n
equal to 1.
All of the above model parameters are presented in
Table 5. The percentages have been converted on the same
where SM is the soil moisture at a given time increment; unit base. The average monthly runoff was computed solv-
SM = SM + P - AEVT - R
i
(8)
i+1
i
i
i
i
SM is the soil moisture on the next time increment; AEVT
i+1
ing Equation 6 for R , where the infiltration component I
i i
i
is the actual evapotranspiration, which in the cases of run- (including losses to deep percolation) was adjusted by
off becomes PEVT P is the rainfall; and R is the poten- subtructing Rn if any. AEVT (the actual evapotranspira-
i; i i
i
i
tial surface runoff (excess water equal to zero, if the field tion) in the cases of runoff becomes PEVT , hence:
i
capacity and the evapotranspiration component are not
satisfied by the amount of rainfall).
R = P – (I – Rn ) – PEVT – ?S
i i i i i
(10)
•
Provision has been taken in the model’s code for the
The component ∆S reflects the amount of water (com-
cases where the soil moisture may exceed the field ing from P ) that has been consumed so as the SM value
i i
capacity so that in the various calculations the soil to reach field capacity (FC) according to the previously
moisture reaches only its maximum value, the field stated premises. Provision has been taken so as monthly
capacity. runoff does not take negative values. Finally, the annual
On the next step, 5 percent of the potential surface runoff coefficient (f) was computed using the formula:
•
runoff is lost due to deep percolation. For a loss it is
supposed that water leaves the system and feeds very
deep strata and formations, which are not considered
aquifers for the area. In situ investigations as well as
the pertinent literature have pointed towards such an
estimate (McWhorter and Sunada, 1988; Danalatos et
al., 1994; Michailidis, 1994).
n
R
∑
i=1
n
i
,
n =12
(11)
f =
P
∑
i=1
i
where R is the potential average monthly surface runoff
i
•
The various watersheds differ also in their geology. In in mm, and P is the average monthly rainfall in mm. The
i
some of the areas the geologic formations are aquifer model application based on the pertinent premises is pre-
materials, while in some others are not. The model, sented in the following section.
hence, has a different approach for each one of the
pertinent cases. In this regard, if the geology dictates
the presence of aquifers, a percent of the excess wa-
Model Application
The model has been designed to run in Microsoft
ter, depending on the specific area, is lost to the ground- EXCEL under Windows. It is believed that the spread-
water recharge, and it does not correspondingly sheet format allows for a user-friendlier interface particu-
contribute to the surface runoff. If the geologic strata larly for the non-expert user, a standardized output
are not aquifer materials, then the model takes into presentation, and a built-in communication capability with
consideration the generation of groundwater flow in other office automation tools (Word, etc.). Given such
the upper part of the formations in the shallow water considerations, the various inputs and outputs of the model
tables that are usually formed. Hence, the simulation are presented in the next paragraphs.
process has considered that on a monthly time step
certain percent of the remaining potential surface run-
off feeds the shallow water table. The percent was
Inputs
Since the model operates on a monthly time step (sec.
chosen due to the geology of each area in accordance 3.1) all the input constant physical paramaters (deep per-
with pertinent studies (Michailidis, 1994). Table 4 pre- colation, excess stored water, etc.) are expressed in the
sents these parameters. Furthermore, this amount of corresponding time dimension. Furthermore, the model
water was also considered that returns to the surface requires the following data input:
runoff with a certain time delay, as diffuse discharge
to the drainage points. The delay pattern may be de- • Rainfall: Rainfall data on monthly average values are
scribed
necessary. Ideally, for each watershed rainfall data
within the watershed should be provided. However, in
the absence of such information, watershed rainfall was
assumed to be given by point rainfall measured at the
closest existing station.
Rn = a GF + a GF ...+ a GF
i i i i -1 i-n i-n
(9)
i-1
where Rn is the total delayed monthly component of the
i
surface runoff from roundwater; GF is the total ground- • Potential Evapotranspiration: Average monthly po-
i
water flow in a given time step (in this case a month); and
tential evapotranspiration data are required. Again dif-
ferent evapotranspiration rates should be used
a ,...i-n are the percentages of the total groundwater flow
i
IWRA, Water International, Volume 27, Number 2, June 2002

250
C. A. Karavitis and P. Kerkides
calculated or measured within the watershed. Instead, tinent values of rainfall for each area and a trendline is
the values discussed in sec. 2.5 and 3.1 were used, calculated. The best-fit line was found to be a logarithmic
2
with all the resulting constraints.
Field Capacity: The field capacity values estimated sented in Figure 3.
in sec. 3.1 were used as input and presented in Table
curve, with an R of 0.5855. The pertinent effort is pre-
•
5.
y = 0,3518Ln(x) - 2,02
2
R
= 0,5855
0
0
.7
.6
Finally, the parameters presented in Table 5 were used
accordingly for the calculation of the annual runoff coeffi-
cients.
0.5
Output
0
0
0
.4
.3
.2
For the simulated years in each case the model pro-
duces distinct tables for each year. Hence, each annual
table presents the actual evapotranspiration, the runoff,
the ground water recharge (if any), and finally the runoff
coefficients. The total number of the generated tables is a
few hundred with the corresponding values of annual run-
off coefficients, for all the pertinent years and island cases.
Table 6 summarizes the results of all the areas, presenting
only the final average annual values. The estimated aver-
age annual runoff coefficients are plotted against the per-
0.1
0
0
200
400
600
800
1000
1200
1400
1600
Rainfall in mm
Figure 3. Average annual rainfall (x) vs. average annual runoff coeffi-
cients (y) and trendline.
Table 5. Input Parameters
Excess Water
Stored Tempor-
arily in Shallow
Acquifers and
Released
Field
Aquifer
System
Capacity
Deep
Gradually
Area
(FC) mm
Predominent Geological Formations
Percolation %
Recharge %
(Rn) %
Thassos
•
•
•
Prinos
187
195
184
Gneisses, Schists
5
5
40
Limenaria
Theologos
Gneisses, Schists
40
Gneisses, Schists, Marbles
Samothrace
Karavi
Xeropotamas
Lesvos
•
102
150
Ophiolites, Basalt,
Schist
5
5
20
20
•
•
•
Eastern part
230
Limestone, Schists,
Volcanites,Alluvial
Volcanic, Igneous
5
40
Western part
105
194
139
5
5
5
10
30
30
Chios
Schists, Limestones
Gneisses, Schists, Rhyolites
Psara
Allonnessos
•
Kastanias
Skopelos
Panormos
Skyros
Ferekampos
Naxos
162
257
171
Limestones, Phyllites
5
5
5
60
60
30
•
Limestones, Flycsh
•
Marbles, Phyllites, Ophiolites
•
Apeiranthos
140
140
182
226
Schists, Quartz, Marbles
5
5
5
5
30
20
Melos
Kythera
Rhodes
Crete
Volcanic (rhyolites, dacites, andecites)
Limestones, Phyllites
40
40
Flycsh, Marbles, Alluvial
•
•
•
Chania
183
150
172
225
Marbles, Schists
Marbles, Alluvial
Marbles, Phyllites
Marbles, Schists
5
5
5
5
10
10
10
5
Heraklion
Ierapetra
Kazantzes
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Estimation of the Water Resources Potential in the Island System
of the Aegean Archipelago, Greece
251
Table 6. Estimated Average Annual Runoff Coefficients, Evaporation, Potential, and Actual Evaportranspiration
Average Annual
Rainfall
Average Annual
Potential Evtrsp.
(PEVT) mm
Average Annual
Actual Evtrsp.
(AEVT) mm
Average
Average Annual
Evaporation mm
Annual Runoff
Coefficient (f)
Area
(P) mm
Thassos
•
•
•
Prinos
786.2
786.2
786.2
1180
1180
1180
684.0
684.0
684.0
393.0
470.9
467.4
0.476
0.403
0.248
Limenaria
Theologos
Samothrake
Karavi
Xeropotamos
Lesvos
Eastern part
Western part
Allonnessos
Kastanias
Skopelos
Panormos
Skyros
Ferekampos
Chios
•
(737.8) 1295.4*
(737.8) 1491.7*
1298
1298
764.7
764.7
539.8
591.0
0.572
•
0.580 (0.608)
•
618.2
424.9
1554
1554
895.5
895.5
439.0
323.7
0.291
0.229
•
•
774.8
774.8
462.2
1278
1278
1341
732.7
732.75
773.7
446.3
502.6
366.5
0.172
0.150
0.151
•
•
•
Scardanas
579.0
600.8
1430
1384
1056
336.0
(0.2-0.45)
0.288
Psara
Naxos
1033.23
341.07
•
Apeiranthos
(351.2) 737.5•
1624
1487
1532
1621
1720
937.2
1090
373.8
365.0
434.0
465.8
468.9
(0.083) 0.468
0.09
Melos
411
Kythera
544
1125
0.115
Rhodes
712
1199.7
1270.9
0.20
Rhodes (UNEP data)
Crete
620.9
0.14
•
•
•
Chania
518
1275
1581
1784
2096
-
946
1159
1320
-
396.0
459.0
397.0
-
0.223
0.15
Heraklion
Ierapetra
543
511
0.213
Myrtos
740.4**
721.44**
665.0**
(0.173)
(0.255)
0.252
Kalamaukianos
Kazantzes
-
-
1245
710.0
489.5
1
2
3
. The values in parenthesis are from the closest station or presenting existing measurements (Samothrace, Ierpetra, Chios).
. *The values used after the elevation correction.
. **The values are estimated using the Thiessen method.
It is pointed that the simulation process output is pre-
ture etc., has minimized the efforts of validating the
model and estimating parameter values. In such an
absence, the best that could be achieved with the model
were magnitude estimates of the major components of
the water balance, predictions eliciting from invalidated
parameter values and a nascent form of sensitivity
analysis.
sented and compared with existing river flow measure-
ments for Samothrace and Ierapetra, and existing runoff
estimates for Chios and Rhodes.
Sensitivity Analysis
The built-in disadvantages of the modeling techniques
are also present in the current effort. Specifically, the simu- • There is an absence of any rainfall measuring stations
lation was based on a set of mathematical expressions,
which represent reality only to a certain degree and are
based on simplified concepts. In addition to such a pitfall,
some other sources of ambiguity producing also the cor-
(and by extension of any meteorological stations) within
the watersheds, with the exception of Ierapetra.
Given, then, the above considerations, a sensitivity
responding risks for the application of the overall approach, analysis was attempted. The constraints and premises of
are presented here: the applied method as well as the obtained results are briefly
illuminated:
•
The existing hydrological databases are incomplete and
sometimes conflicting. Therefore, the lack of suitable, • All the input values have been kept constant (rainfall,
reliable, and systematically collected data, such as dis- evapotranspiration, etc.), and only the field capacity
charge measurements, groundwater levels, soil mois- has been allowed to vary. The model reacted positively,
IWRA, Water International, Volume 27, Number 2, June 2002

252
C. A. Karavitis and P. Kerkides
producing lower values of runoff and higher actual logical inputs. Based on the available information, it fol-
evapotranspiration for higher values of field capacity. lows reasonably the variability of the year-to-year hydro-
The opposite results were recorded for lower values logical fluctuations. However, it cannot be independently
of field capacity. The same values of field capacity validated at the present stage, except for Samothrace,
produced the same results in the corresponding model Chios, Rhodes, and Ierapetra. In these cases, it presented
subsections.
a close approximation of the existing conditions for the
•
All the input values were kept constant and the per- given data and time series. Namely, for Samothrace the
centage of excess water feeding the aquifers was var- model value of average annual runoff coefficient was
ied. Again the model reacted positively with less runoff 0.580, whereas flow measurements by Public Power Cor-
for a higher infiltration rate and more runoff for a lesser poration indicated one of 0.608 (Bosdogianni, 1994). For
one.
Chios, the model predicted an average value of 0.19 and
the existing estimates in Skardanas river watershed gave
The model reacted positively on certain key hydro- annual values between 0.2 and 0.45 (CP, 1993). For
logical years. Namely in 1989 to 1990, 1991 to 1992, and Rhodes, the model produced a value of 0.20, which is close
992 to 1993, the years of the severe consecutive droughts, enough to the value of 0.159 that the UNEP (1996) study
it produced minimum runoff as it was recorded on the has estimated applying another modeling approach. How-
available databases. ever, using the original data of the UNEP study (Table 6)
1
The estimated average annual runoff coefficients show the model gave a runoff coefficient value of 0.14. Such a
a range from 0.08 to 0.58. Such variability may be prima- value is practically the same with the value of the UNEP
rily attributed to the geology of each area, if it would be study and may add towards the validity of the whole ef-
considered that the rainfall and the evapotranspiration ex- fort, as it produced similar results with another indepen-
hibit such a variability to a lesser degree. Thus, the aver- dent approach. Finally for Ierapetra (lower watershed)
age annual runoff coefficients for the cases that aquifers the model produced a value of 0.213, while measurements
have not been present in the watersheds, were plotted in the upper watersheds of rivers Myrtos and
against the corresponding rainfall of each area and a Kalamaukianos have values of 0.173 and 0.255 (MECPPW,
trendline is calculated. The trendline was found to be a 1993). Thus, it seems that the model consistently arrives
2
logarithmic curve, with an R of 0.8801. Such a result for- at an acceptable approximation. If flow measurements are
tifies the initial premise and may be considered as an ad- also carried out in the other islands (an effort that would
vantage of the overall methodology. The pertinent effort require time and resources considering the current state
is presented in Figure 4. It is also pointed out, that such of the organizational, political, and institutional environ-
areas with impermeable strata are usually the prime can- ment), it may be possible to arrive to a more accurate
didates for any future surface water resources develoment model development. Nevertheless at this stage, it seems
schemes. Finally, the extreme variability of the runoff co- that the model may well serve as a decision support tool,
efficients for the cases where aquifers were present was an aide in estimating the approximate magnitude of the
prohibitive for the pertinent plot, fortifying the strong geo- various water balance parameters.
logical bond of the results.
Overall, it may be pointed out that the model reacts
Conclusions and Recommendations
well to the choice of parameters (Table 6) and the hydro-
In a fast changing era, any present or future oriented
water resources development and management scheme
should be also able to cope with the larger aims of social
y = 0,402Ln(x) - 2,2937
2
and economic dimensions. In this dynamic environment
one should incorporate both “structural” and “non-struc-
tural” mechanisms as vital components of an integrated
water resources planning and management policy. At the
same time, supply augmentation and demand reduction
measures are both influencing the rate and the extent of
change in the environment. Underlying all such consider-
ations is the centrality of sustainability and equitable shar-
ing of water resources.
R
= 0,8801
0.7
0.6
0.5
0.4
0.3
0.2
0.1
The key point to be made is that ecological values and
the quest for sustainable development require a balanced
combination of data and judgement. The recently adopted
Water Framework Directive (WFD, 2000) in the Euro-
0
0
200
400
600
800
1000
1200
1400
1600
Rainfall in mm
Figure 4. Average annual rainfall (x) vs. average annual runoff coeffi- pean Union emphasizes the protection of quantity and qual-
cients (y) and trendline with impermeable strata in the watersheds.
ity of surface and groundwater, introduction of water pricing
IWRA, Water International, Volume 27, Number 2, June 2002

Estimation of the Water Resources Potential in the Island System
of the Aegean Archipelago, Greece
253
policies, integrated watershed management, and the
About the Authors
strengthening of public participation. In this regard, it be-
comes more than necessary that decision making should
move beyond considerations of only economic tradeoffs
and traditional methodologies into considering underlying
water resources development goals and strategies, as well
as shared societal visions. Thus, alternative water resources
policy options (e.g., reservoir storage, conservation, re-
use, desalination, transport of water from other areas;
conjunctive water use with withdrawals from aquifers, etc.)
emerge as results of the application of an integrated water
resources planning and management methodology.
Christos A. Karavitis has a Ph.D degree in Civil
Engineering, Water Resources Planning and Management,
and a M.Sc. degree in Agricultural Engineering, Ground-
water Management. He is Faculty Affiliate in Water Re-
sources Planning and Management, Department of Civil
Engineering, Colorado State University, Fort Collins, Colo-
rado, USA, and visiting Lecturer and researcher at the
National Technical University of Athens and the Agricul-
tural University of Athens, Greece. He is an Evaluator
and Expert for the Research projects of the European
Union, DG XII, European Commission. Dr. Karavitis has
participated in many research projects both in Europe and
in the United States, and is involved in Water Resources
Planning and Management, Environmental Impact Assess-
ments Methodologies, and Transboundary River Basin
Problems. He is a member of the International Water
Resources Association (IWRA) and of the American So-
ciety of Civil Engineers (ASCE). Email: chrisk@hol.gr.
Petros Kerkides is a Professor, Soil Physics, De-
partment of Natural Resources and Agricultural Engineer-
ing, Agricultural University of Athens, Athens, Greece.
Given such considerations, the approach suggested in
the present work seems to address more completely the
challenges associated with the surface water resources
potential in an island environment. The effort resulted in
estimating the annual surface runoff coefficients, poten-
tial and actual evapotranspration, using the developed and
described simulation model. The various premises and es-
timates were presented. Summarizing, key aspects of the
final output may be delineated in the following:
•
The precipitation and the majority of surface runoff
takes place in the winter months, creating a strong tem-
poral water deficit in the dry summer season, where
most of the activities are concentrated;
Discussions open until December 1, 2002.
•
The estimated average annual runoff coefficients rep-
resent a range from 0.08 to 0.58. Such variability may
be primarily attributed to the geology of each area, if it
would be considered that the rainfall and the evapo-
transpiration exhibit a similar variability to a lesser de-
gree. Both are generally decreasing from north to south
and such a trend may also be demarcated in the aver-
age annual runoff coefficients values.
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