Abstract

Lakes Volvi and Koronia are located in the Mygdonia basin and constitute the second and fifth largest natural lakes in Greece, respectively. The lakes along with the Mygdonia basin aquifer have undergone severe quantitative and qualitative degradation, while Lake Koronia has been totally depleted in recent years. In this study, a fully integrated hydrological analysis of the Mygdonia basin for historical and future periods is carried out. Future climatic data were derived and analyzed from a Regional Climate Model, while the implications of climate change on the water balance of both lakes and the Mygdonia basin aquifer until 2100 were projected by developing a modelling system which includes coupled hydrological and hydraulic models, such as UTHBAL, MIKE SHE, MIKE HYDRO River and the MIKE HYDRO Basin. The results indicated that the precipitation is expected to decrease by 17%, the temperature to increase by 2.90 °C and as a result, the surface runoff is projected to decrease by 21% and the groundwater recharge to decrease by 38% in the Mygdonia basin at the end of the century. The above changes would have a direct negative impact on the Lakes Koronia and Volvi and the Mygdonia basin aquifer future water balance necessitating adaptation measures.

INTRODUCTION

Climate change is anticipated to have a direct and negative impact on the water availability in many Mediterranean countries by exacerbating freshwater scarcity (Andrew & Sauquet 2017). Precipitation and temperature constitute the main climatic drivers that directly and indirectly control surface water and groundwater resources availability. Precipitation tends to decrease in subtropical latitudes including the Mediterranean region, while the temperature tends to increase in the wider Mediterranean area (Basharin et al. 2016). The streamflow is expected to decrease in southern Europe (Candela et al. 2016), and it is generally consistent with the regional magnitude and seasonal distribution primarily of precipitation and also of temperature and evaporation. Regarding the behaviour of lakes, their water level is significantly affected by the precipitation and air temperature changes (Azgin & Dadaser-Celik 2015). The groundwater recharge mainly depends on precipitation; however, there is great uncertainty in recharge estimation and, in particular, areas with different soil characteristics under uniform precipitation changes can yield different groundwater responses (Earman & Dettinger 2011). According to the IPCC AR5 (Jiménez Cisneros et al. 2014), the extent to which climate change affects groundwater withdrawals is not known because of the limited number of relevant studies.

The Mediterranean region constitutes one of the ‘hotspot’ areas in the world in terms of climate change. Future precipitation and temperature changes in the Mediterranean area are expected to create uncertainty in water delivery, timing and availability, which in turn affects freshwater systems (Kolokytha et al. 2017). According to Brouziyne et al. (2018), the impacts of climate change on the natural resources of the Mediterranean region may be very dramatic. Therefore, the climate change impact studies on water resources availability in the Mediterranean area are of considerable importance. Bucak et al. (2017) studied the impacts of climate change and land uses change on the future water availability in Lake Beyşehir in Turkey and concluded that the shallow Mediterranean lakes are in danger of drying out in the near future. Pulido-Velazquez et al. (2018) investigated the impacts of climate change on the groundwater recharge in Spain and found that an average decrease by 12% of the net aquifer recharge over continental Spain is expected until 2045.

In the face of the future water scarcity in the Mediterranean region, there is an urgent need for an accurate projection of the impacts of climate change on future water resources availability through an integrated study of both surface water and groundwater. However, the vast majority of the research studies focus on the implications of climate change solely on surface water, groundwater or the surface water − groundwater exchanges, while the studies regarding the climate change impacts on both surface water and groundwater (Tzabiras et al. 2016) are still limited in the literature.

Apart from climate change, freshwater availability is largely attributable to additional influences such as water abstractions. Agriculture constitutes the major water consumer in Greece, accounting of about 84% of the total freshwater abstractions (EUROSTAT 2019), which is even higher than the relevant percentage of the whole Mediterranean area, estimated as equal to 80% (Ferragina & Canitano 2015). Water abstractions for irrigation in Greece are expected to increase in the future due to the expected increase of crop water requirements. The great significance of estimating the impact of climate change on water resources availability in Greece is reflected by the number of relevant studies (Loukas et al. 2015; Tzabiras et al. 2016).

The Mygdonia basin is one of the agricultural basins with significant water deficit in the Mediterranean area. The extensive cultivation of water intensive crops led to a remarkable water demand increase, which was satisfied by the unsustainable over-exploitation of surface water and groundwater resources resulting in a significant water-level decrease of groundwater table as well as a decrease of the water volume of Lakes Koronia and Volvi. The research on the water availability in the Mygdonia basin is still very limited, focusing mainly on Lake Koronia and its sub-catchment without considering the future climate conditions.

The Mygdonia water basin is anticipated to face the negative impacts of climate change in a more intense way compared with other locations in the country for two reasons. First, the temperature increase is expected to be higher in central and northern Greece (Tolika et al. 2012), and secondly, agriculture plays a major role in the pressure put on the water systems of the Mygdonia basin since irrigation is currently the largest water consumer, accounting for about 95% of the total water needs (Bobori et al. 2016).

The main objectives of this study are to present the development of a fully integrated hydrological modelling system for the coupled simulation of surface water and groundwater in the Mygdonia basin and to estimate the future water balances of the basin (including Lakes Koronia and Volvi and the Mygdonia basin aquifer) for the first time. This analysis has been applied for historical and future periods, 2010–2040, 2040–2070 and 2070–2100. The starting year for the future climate and hydraulic study was selected to be the year 2010. The reasons for this selection are the illegal water abstractions from Lakes Koronia and Volvi that were carried out until the year 2010 and whose quantities are not known and the limited meteorological data for the period is 2000–2010.

STUDY AREA AND DATA BASE

Study area

The Mygdonia basin is situated between 22°54′03″–23°42′57″E longitude and 40°27′41″–41°00′07″N latitude in northern Greece, and it covers an area of about 2.061 km2. Lakes Koronia and Volvi are located at the lowest parts of the Mygdonia basin, and, in particular, Lake Koronia lies at the western and Lake Volvi at the eastern part of the basin (Figure 1). Six and 13 streams outflow to Lakes Koronia and Volvi, respectively. The overflow of Lake Koronia drains to Lake Volvi through the Derveni ditch, and the overflow of Lake Volvi drains to the Strymonikos gulf through the Richios stream.

Figure 1

(a) The 19 sub-catchments of the Mygdonia catchment and (b) the seven aquifers of the Mygdonia basin.

Figure 1

(a) The 19 sub-catchments of the Mygdonia catchment and (b) the seven aquifers of the Mygdonia basin.

During the last decades, Lakes Volvi and Koronia, which constitute the second and fifth largest natural lakes in Greece, respectively, along with the Mygdonia basin aquifer, have undergone a severe quantitative degradation. In particular, the water depth of Lake Koronia has progressively decreased since 1970, and the lake was totally depleted in the summer of 2008. Lake Volvi experienced a smaller reduction of its depth. Also, the limited recharge to the Mygdonia basin aquifer and the over-pumping for irrigation caused a significant drawdown of the groundwater table.

The water quantitative problem of the Mygdonia basin has not been recognized before 1998 when the ‘Master Plan for the restoration of Lake Koronia’ was carried out. In 2004, a ‘Revised Plan for the restoration of Lake Koronia in the Prefecture of Thessaloniki’ was carried out, revising the Master Plan and proposing measures to confront the water deficit of Lake Koronia. The Master Plan and the Revised Plan are so far the only official documents regarding the restoration of the Mygdonia water bodies. The water quantitative measures that were proposed in the Revised Plan and have been implemented are: (a) the diversion of 15% of Sxolari stream flow and the total diversion of Lagkadikia stream to Lake Koronia; (b) the improvement in the hydraulic characteristics of the Derveni ditch which carries the overflow of Lake Koronia to Lake Volvi; (c) the promotion of the replacement of sprinkler irrigation by drip irrigation; (d) the excavation of the bottom of the eastern part of the Lake Koronia at about 1 m; and (e) the construction of an embankment at the western part of Lake Koronia.

Nowadays, Lakes Koronia and Volvi have been partially recovered because of the water management measures that have been implemented along with the prohibition of illegal abstractions from the lakes and the high precipitation amounts during recent years. However, the main stressors that caused the water quantitative problems have not been effectively confronted yet according to the Management Body of Lakes Koronia and Volvi.

Geographical, hydrological and meteorological data

Geographical, hydrological and meteorological data were collected in the current study; an extensively difficult task, since all the required data were extremely fragmented and were collected from many different sources. These data have been evaluated and processed before their input to climatic and hydrological models. A Geographic Information System (GIS) database containing all the necessary spatial information of the Mygdonia basin was developed using the ArcGIS v.10.3 software.

The surface of the study area was represented by the Aster Global Digital Elevation Map v.2 (ASTER GDEM v.2). The DEM was used in the preliminary surface hydrological analysis which includes the surface water flow direction, flow accumulation and natural drainage network simulation resulting in the delineation of the boundaries of 19 sub-catchments (Figure 1(a)). The main geographical characteristics (e.g. area, average elevation and average slope) were calculated for each sub-catchment.

The original precipitation and temperature measurements were collected from the Hellenic National Meteorological Service and regional water resources agencies. The time series measurements were checked for errors, homogenized and their missing data filled. Processed monthly precipitation and temperature data from 15 and 9 meteorological stations (MS), respectively, within and in the vicinity of the Mygdonia basin for the period October 1970 to September 2000, were available (Figure 1(a)). The period from October 2000 until September 2010 was not taken into consideration in the current study due to the unavailability of measured meteorological data; in particular, all the MSs located inside the Mygdonia basin were shut down at the end of 2000, after the completion of the Master Plan study. The operation cessation of the MSs is attributed to the completion of the Master Plan study in 1998 which proposed technical rehabilitation measures for the quantitative and qualitative restoration of Lake Koronia. From 2000 until today, only 3 out of 15 precipitation stations and only 3 out of 9 temperature stations are in operation. These stations are located in the vicinity of the Mygdonia basin and not within the basin. For this reason, they were not considered in the current study. The future period 2010–2100 that is taken into account in the current research is a common period applied to several climatic and hydraulic studies. In the current study, the mean areal precipitation of the whole Mygdonia basin was estimated equal to 518.69 mm/year for the period 1970–2000 using the Thiessen polygon method modified by the precipitation gradient method. The mean annual temperature of the Mygdonia basin was calculated equal to 13.27 °C for the period 1970–2000 using the temperature gradient method. Finally, the mean areal potential evapotranspiration was estimated equal to 777.83 mm/year for the period 1970–2000 using the Thornthwaite method.

The Mygdonia basin is divided into 25 municipalities or 79 municipal units at a primary or secondary administrative level, respectively. The boundaries of all the municipal units and villages laying within the Mygdonia basin were digitized in ArcGIS.

The total water amount supplied to agriculture in the Mygdonia basin is not known because of the large number of illegal pumping wells. Therefore, the irrigation water demand is estimated based on the area of each cultivated crop within the study area. The cultivated area of each crop was collected for each one of the 25 municipalities and 79 municipal units lying within the Mygdonia basin for the years 2000 and 2010 from Exarchou Nikolopoulos Bensasson S.A. (ENM) et al. (2007), Greek Ministry of Environment Energy and Climate Change (2013) and the Regional Administration of Central Macedonia. The cultivated area was then transferred to each one of the 19 sub-catchments and slightly corrected using the Corine Land Cover 2000 and 2012 raster data which were produced by the European Union Copernicus Land Monitoring Service (https://land.copernicus.eu/). The irrigation water demand in the study area is fulfilled by both the Mygdonia basin aquifer and Lake Volvi. In particular, local land reclamation organizations of Askos, Mikri Volvi and Nymfopetra pumped a total water amount of 5.23 hm3/year from Lake Volvi since 1997 for the irrigation needs of the adjacent agricultural fields. In the early years of the 21st century, the organization of Nymfopetra was shut down and the remaining organizations pump a total water amount of 2.40 hm3/year from Lake Volvi.

The Mygdonia basin aquifer was divided into seven groundwater sub-catchments including the Lake Koronia sub-catchment (Figure 1(b)) during the preparation of the River Basin Management Plans in Greece and imported into the GIS database that was created in the current study. The total number of pumping wells in the Mygdonia basin is estimated to be more than 2,300, from which only 361 are legal and therefore their location is known. The coordinates of all the known wells were collected from the Greek Institute of Geology and Mineral Exploration and digitized in ArcGIS in the current study.

METHODOLOGY

Historical and future precipitation and temperature time series along with geographical and hydrological data were used in a modelling system. The modelling system consists of four coupled hydrological and water resources models: (a) the UTHBAL (University of THessaly water BALance) model for the surface hydrological processes simulation; (b) the MIKE SHE (Danish Hydraulic Institute, DHI) model for the simulation of groundwater flow; (c) the MIKE HYDRO River (DHI) model for the simulation of water exchange between the lakes and the Mygdonia basin aquifer; and (d) the MIKE HYDRO Basin (DHI) model for the water balance calculation of Lakes Koronia and Volvi. The flow diagram of the developed modelling system in the case of the Mygdonia basin is depicted in Figure 2 and presented in the following sections.

Figure 2

The developed integrated modelling system applied in the Mygdonia basin.

Figure 2

The developed integrated modelling system applied in the Mygdonia basin.

The developed integrated hydrological modelling system is a suite of coupled mathematical models employed to accomplish the objectives of the study within the framework of the integrated water resources management. The surface hydrological model UTHBAL calculates the groundwater recharge and the discharge to Lakes Koronia and Volvi, which are then imported to the MIKE SHE groundwater model and the MIKE HYDRO River lake–aquifer simulation model. The MIKE SHE and MIKE HYDRO River models receipt also precipitation and evaporation of the lakes, pumping from the lakes, pumping from groundwater and return flows of the pumped water for irrigation use and calculate water exchange volumes between the Mygdonia basin aquifer and the neighbouring aquifer and also water exchange volumes between the lakes and the Mygdonia basin aquifer. The lakes–aquifer water exchange along with precipitation, evaporation and pumping from the lakes are imported into the MIKE HYDRO Basin model which calculates the water level, the surface area and the stored water volume of the Lakes Koronia and Volvi.

MIKE SHE is a deterministic, physically based, distributed model which covers the whole processes in the hydrological cycle and allows each process to be simulated at different spatial and temporal resolutions and complexity depending on the data availability and the model purpose. In particular, a MIKE SHE model is able to simulate stream flow taking into account topographical, meteorological and vegetation data (Danish Hydraulic Institute (DHI) 2017). However, a MIKE SHE model requires many and detailed data which are not available in the study basin. On the other hand, a UTHBAL model is a monthly water balance model and has five parameters which can be calibrated with the limited available monthly discharge data. The UTHBAL model requires only monthly times series of precipitation and potential evapotranspiration. Furthermore, the UTHBAL model has been successfully applied to watersheds in Cyprus (Loukas et al. 2003), Crete (Christodoulaki et al. 2003, 2004), Thessaly (Loukas et al. 2007; Sidiropoulos et al. 2013; Sidiropoulos et al. 2016; Tzabiras et al. 2016) and the transboundary Nestos/Mesta River basin (Kampragou 2006).

The hydrological modelling system contains parameters that are categorized into three types, namely exogenous inputs, endogenous variables and output variables with some output variables of a model acting as inputs to another model, as shown in Figure 2. In particular, precipitation, temperature, potential evapotranspiration and measured discharges constitute the exogenous inputs of the UTHBAL model, while the recharge to groundwater and the discharge to Lakes Koronia and Volvi are the outputs of the model. Also, the groundwater recharge along with precipitation to the lakes, evaporation from the lakes, pumping from the lakes, pumping from the Mygdonia basin aquifer for irrigation, industrial, livestock, touristic and household needs, and return flows of the pumped water for irrigation use constitute the exogenous inputs to the MIKE SHE and MIKE HYDRO River models, while the water exchange between the Mygdonia basin aquifer and the neighbouring aquifer along with the water exchange between the lakes and the Mygdonia basin aquifer constitute the outputs of the models. The latter along with precipitation to the lakes, evaporation from the lakes, pumping from the lakes and the discharge to the lakes are inputs to the MIKE HYDRO Basin model, while the water level, the surface area and the stored volume of the Lakes Koronia and Volvi are the outputs of the model.

All the exogenous inputs are imported into the modelling system in a monthly time scale and are considered as the stressors of the surface water and the groundwater. The cultivated area of each crop and the levels of the rest economic activities are assumed not to be changed in the future; an assumption that is reasonable and in accordance with the Greek Joint Ministerial Decision 6919/2004 that has established pumped water volume limitation in the Mygdonia basin.

The endogenous variables of the modelling system are related to the mathematical equations of each hydrological model. In particular, the UTHBAL model runs in a lumped mode, while a detailed description of the model is presented in Loukas et al. (2007). The groundwater flow in the Mygdonia basin was simulated using the fully distributed MIKE SHE model in which the spatial and temporal variations of the hydraulic head are described by the three-dimensional saturated flow in saturated porous media Darcy equation. The exchange flow between the lakes and the Mygdonia basin aquifer was calculated equal to the conductance multiplied by their head difference using the MIKE SHE model coupled with the MIKE HYDRO River model. The water balance simulation of the Lakes Koronia and Volvi was carried out in the MIKE HYDRO Basin model using the water level–surface area–stored water volume curves of the lakes as collected from Exarchou Nikolopoulos Bensasson S.A. (ENM) et al. (2007).

The final outputs of the modelling system include the future water balance of the Mygdonia basin aquifer and the Lakes Koronia and Volvi as well as the piezometric surface and the water level, surface area and stored volume of the lakes until 2100.

Climate data analysis and downscaling technique

Monthly precipitation and temperature projections were collected from the ENSEMBLES European project database (http://ensemblesrt3.dmi.dk/). The climatic data derived from the SMHIRCA GCM-RCM (Regional Climate Model; RCA RCM driven by the ECHAM5-r3 GCM) which has a spatial resolution of almost 25 km. The future climatic projections concern the period from October 2010 until September 2100 under the IPCC Emission Scenario A1B. The SRES (Special Report on Emissions Scenarios) A1B constitutes a good mid-line scenario for socio-economic changes and corresponds to RCP (Representative Concentration Pathway) 6.0 (Van Vuuren & Carter 2014). At the time of research implementation, the ENSEMBLES data were the most up to date climatic data and they are nowadays applied in a wide range of research studies (Knežević et al. 2018; Paparrizos et al. 2018). SRES and RCPs are equally plausible representations of future emissions, and no liking or disliking is attached to the SRES or RCPs; therefore, future precipitation and temperature under both groups of scenarios, i.e. SRES or RCPs, can be used to study the impacts of climate change (Alotaibi et al. 2018).

The meteorological measurements of the historical reference period 1970–2000 were compared with the historical data of the climate model for the same period. Because of the biased raw precipitation and temperature climatic data, the Bias Correction Quantile Mapping (BCQM) method was applied to correct RCM projections. The BCQM method was implemented in the R programming language using the qmap package (Gudmundsson 2016). The exponential tendency to an asymptote transformation function was used to fit the quantile–quantile relation of observed and modelled precipitation and temperature values, and it is described by the following equation (Gudmundsson 2016):
formula
(1)
where is the observed variable, is the modelled variable, and a, b, x and are parameters.

The transformation function was then applied to the future climatic projections to correct their bias. In order to carry out a detailed climate analysis, the future period 2010–2100 was subdivided into three 30-year time periods, i.e. 2010–2040 (short-term projection), 2040–2070 (mid-term projection) and 2070–2100 (long-term projection). The mean annual precipitation and mean annual temperature and their standard deviation, estimated using the BCQM method, are presented for the historical and future time periods in Table 1.

Table 1

Historical data and future projections of precipitation and temperature

Precipitation (mm/year)
Temperature (°C)
Mean annualStandard deviationMean annualStandard deviation
Observations (1970–2000) 518.69 82.69 13.27 7.24 
Raw climatic data (1970–2000) 575.03 158.75 13.24 6.85 
Downscaled climatic data (1970–2000) 517.95 119.05 13.26 7.23 
Climatic projections (2010–2040) 515.47 85.97 14.14 7.42 
Climatic projections (2040–2070) 449.56 101.45 15.17 7.36 
Climatic projections (2070–2100) 432.93 107.30 16.17 7.48 
Precipitation (mm/year)
Temperature (°C)
Mean annualStandard deviationMean annualStandard deviation
Observations (1970–2000) 518.69 82.69 13.27 7.24 
Raw climatic data (1970–2000) 575.03 158.75 13.24 6.85 
Downscaled climatic data (1970–2000) 517.95 119.05 13.26 7.23 
Climatic projections (2010–2040) 515.47 85.97 14.14 7.42 
Climatic projections (2040–2070) 449.56 101.45 15.17 7.36 
Climatic projections (2070–2100) 432.93 107.30 16.17 7.48 

According to Table 1, the mean annual precipitation is projected to continuously decrease and the average monthly temperature to continuously increase in the Mygdonia basin until 2100.

The distributions of precipitation and temperature in the wet and cold period (from October to March), dry and hot period (April to September) and the whole hydrological year in the Mygdonia basin are presented in Figure 3(a) and 3(b), respectively.

Figure 3

Box-and-whisker diagrams of (a) precipitation and (b) temperature in the wet and cold period, dry and hot periods, and the whole hydrological year in the Mygdonia catchment.

Figure 3

Box-and-whisker diagrams of (a) precipitation and (b) temperature in the wet and cold period, dry and hot periods, and the whole hydrological year in the Mygdonia catchment.

Simulation of the surface hydrological processes

The hydrological model UTHBAL was used for the surface hydrology component estimation in the Mygdonia basin. The model could run in a fully distributed, semi-distributed and lumped mode, and it has been applied in various regions of Greece and Cyprus. The distributed simulation of the hydrological balance of the Mygdonia basin requires spatially distributed hydrometeorological data in grids as an input to the model. However, the historical discharge values that are used for the calibration and validation of the model were only available at a specific location, and, therefore, only the lumped version of the UTHBAL model can be used. Essentially, the model has been applied in a semi-lumped mode for each of the sub-watersheds. Furthermore, it has proved that the level of the spatial discretization of the UTHBAL model does not largely affect the quality of the hydrological simulation (Loukas et al. 2006). The UTHBAL model requires time series of precipitation, temperature, potential evapotranspiration and measured discharge values at a monthly time scale, and it produces time series of actual snow water equivalent, actual evapotranspiration, actual soil moisture, total surface runoff and groundwater recharge. In this study, the hydrological analysis was performed separately for each one of the 19 sub-catchments of the Mygdonia basin using the five-parameter lumped UTHBAL model. The monthly areal precipitation was calculated using the Thiessen polygon method modified by the precipitation gradient method. The monthly temperature was calculated using the temperature gradient method. Also, the mean areal potential evapotranspiration was calculated using the Thornthwaite method. The UTHBAL model was calibrated and validated with the monthly discharge values of the Gerakarou stream at its outfall point to Lake Koronia measured for the period October 1995–September 2000 (Veranis & Katirtzoglou 2001). The first 4 years of the measured discharge values and the last one were used for the calibration and the validation of the model, respectively. The Nash–Sutcliffe Model Efficiency (Eff) was used as the objective function during the optimization of the model. Apart from the Eff, the coefficient of determination (R2) was used as a measure of the quality of simulation. These goodness-of-fit statistics are considered satisfactory for the calibration (Eff = 0.510, R2 = 0.538) and validation (Eff = 0.494, R2 = 0.534) periods taking into account the short period of calibration and the low quality of the available hydrometric and meteorological data. The calibrated parameters of the UTHBAL model for the Gerakarou sub-catchment were used for the simulation of the other sub-catchments of the Mygdonia basin, because there are no flow measurements in the other sub-catchments to allow the calibration of the UTHBAL model. It is reasonable to assume that the hydrological response of the other sub-catchments is similar to that of the Gerakarou sub-catchment since they have similar geomorphological, soil and land-cover characteristics.

The calculated monthly surface runoff of the sub-catchments, which are inflows to Lakes Koronia and Volvi, were, then, imported into the MIKE HYDRO River and MIKE HYDRO Basin models to simulate the water balance of the lakes (Figure 2). The monthly groundwater recharge of the sub-catchments was imported into the MIKE SHE model for the simulation of groundwater as is presented in the next paragraphs (Figure 2).

Simulation of the groundwater flow and lakes–aquifer interaction

Monthly agricultural, industrial, livestock, household and tourist water demand time series as well as monthly groundwater recharge time series were imported into the MIKE SHE model for each one of the 19 sub-catchments of the Mygdonia basin.

In particular, the monthly irrigation water demand per crop in each sub-catchment was estimated using the Net Irrigation Requirements parameter which is equal to the difference between the crop-specific potential evapotranspiration and the effective precipitation (Smith 1992; United States Department of Agriculture (USDA) 1997). The crop-specific potential evapotranspiration of each crop was estimated by multiplying the crop coefficient with the potential evapotranspiration (Döll 2002) which was calculated using the Thornthwaite method. The monthly effective precipitation, WST-EM19304eq22, was calculated as:
formula
(2)

where P is the monthly precipitation at each sub-catchment.

The monthly agricultural water demand per crop in each sub-catchment was then estimated by multiplying the cultivation area of each crop with its Net Irrigation Requirements divided with the efficiency of its irrigation system. Then, the total agricultural water demand in the whole Mygdonia basin was estimated for the historical and future periods. A water amount of 15% of the total irrigation water, which represents the water loss during its transfer to the field, is treated as return flow to the groundwater.

Monthly industrial, livestock, household and tourist water demand data for each one of the 25 municipalities within the Mygdonia catchment were collected from Exarchou Nikolopoulos Bensasson S.A. (ENM) et al. (2007) and estimated to each sub-catchment of the Mygdonia basin. The vast majority of the industries, now, are not in operation due to the limitations in the pumped water policy. The decrease of the industrial water demand is now more than about 90% according to the Management Body of Lakes Koronia and Volvi. All the water demands for industrial, livestock, household and tourist water uses are covered by groundwater pumping. The total agricultural, industrial, livestock, household and tourist water withdrawals from the Mygdonia basin aquifer are simulated to be pumped through the 361 known wells whose location was imported into the MIKE SHE model.

Geometrical and hydraulic groundwater parameters, namely upper level, lower level, horizontal hydraulic conductivity, vertical hydraulic conductivity, specific yield and storage coefficient, were imported into the MIKE SHE model for each layer of each one of the seven groundwater sub-catchments. The parameter values were collected by Mylopoulos et al. (2002), Veranis et al. (2009), Veranis (2010a, 2010b) and Kalousi & Pratanopoulos (2010) or estimated using lithological cross-sections including in these studies. Τhe whole Mygdonia groundwater catchment was considered as an endorheic basin, in hydrogeological terms, apart from a small region at the eastern part of the catchment, in particular at the outflow area of the Richios stream to the neighbouring sub-catchment (Veranis 2010a). The calibration of the groundwater model was based on 45 hydraulic head observations of the Mygdonia basin aquifer measured by Mylopoulos et al. (2002) at the area surrounding Lake Koronia in the dry period of the years 1997 and 2000. These were the only available hydraulic head observations in the study area for the historical reference period, and thus, only a calibration process of the groundwater model for the 3-year period 1997–2000 was carried out. The horizontal and vertical hydraulic conductivity of the Koronia aquifer was calibrated using a trial-and-error procedure. Several simulations were performed in order to maximize the Eff parameter between simulated and observed hydraulic head values. Except from the Eff, the R2 parameter was also used to measure the quality of simulation. These goodness-of-fit statistics were improved between the initial (Eff = 0.622, R2 = 0.720) and final run (Eff = 0.805, R2 = 0.838) and can be characterized as very good considering the uncertainties in the Mygdonia basin aquifer simulation, including the low number of the known pumping wells, which affects the simulated hydraulic gradients of the Mygdonia basin aquifer.

Surface runoff to Lakes Koronia and Volvi, direct precipitation, evaporation from the surface of the lakes and water abstraction from Lake Volvi for irrigation time series at a monthly time scale were imported into the MIKE HYDRO River model for the accurate simulation of the water table of the lakes at each simulation time step. In particular, the surface runoff to lakes was calculated at a previous step using the UTHBAL model. The monthly direct precipitation to Lakes Koronia and Volvi was calculated using the Thiessen polygon method modified by the precipitation gradient method. The evaporation from the lakes was estimated using measured monthly evaporation data for the period November 1980–September 2000 by Exarchou Nikolopoulos Bensasson S.A. (ENM) et al. (2007). A strong correlation (R2 = 0.879) was found between the measured monthly evaporation from the lakes and the measured monthly temperature at the area of the lakes, and then the monthly evaporation data were estimated for the whole extent of the historical period as well as for the future periods based on the temperature data and the developed regression equation. The monthly time series of water abstraction from Lake Volvi by the local land reclamation organizations was also imported into the MIKE HYDRO River model.

The outputs of the coupled MIKE HYDRO River and MIKE SHE models are monthly time series of groundwater outflow to the neighbouring groundwater catchment and monthly time series of water exchange between the lakes and the aquifer. Afterwards, the monthly lakes–aquifer water exchange time series were imported into the MIKE HYDRO Basin model.

Simulation of Lakes Koronia and Volvi

Runoff to Lake Koronia, direct precipitation and evaporation time series at a monthly time scale were imported into the MIKE HYDRO Basin model for the water balance simulation of Lake Koronia. Also, runoff to Lake Volvi, direct precipitation, inflow from the Derveni stream, inflow from the aquifer, outflow to the aquifer, water abstraction and evaporation time series were imported into the MIKE HYDRO Basin model for the simulation of Lake Volvi. The runoff to the lakes was calculated using the UTHBAL model, the direct precipitation to lakes was calculated using the Thiessen polygon method modified by the precipitation gradient method and the evaporation was calculated using the relation between temperature and evaporation. Moreover, the inflow from the aquifer and the outflow to the aquifer were calculated using the coupled MIKE HYDRO River and MIKE SHE models.

The quality of simulation of the lakes was measured using 104 and 102 observations of the water table of Lakes Koronia and Volvi, respectively, collected from Exarchou Nikolopoulos Bensasson S.A. (ENM) et al. (2007). The observations refer to the discontinuous periods from July 1986 to October 1996 and from January 1985 to August 1994 in the case of Lakes Koronia and Volvi, respectively. The Eff and R2 goodness-of-fit indices are found to be very good for Lake Koronia (Eff = 0.711, R2 = 0.925) and good for Lake Volvi (Eff = 0.555, R2 = 0.757), taking into account the uncertainties related to the lakes model input parameters.

The outputs of the MIKE HYDRO Basin model are monthly time series of the outflow of Lake Koronia to the Derveni stream, the outflow of Lake Volvi to the Richios stream and evaporation losses based on the actual water surface of the lakes at each time step.

RESULTS AND DISCUSSION

Simulation of surface water and groundwater resources

The simulation of the surface hydrological processes was carried out with a monthly time step for the historical and future periods using the UTHBAL model. The average () and standard deviation () monthly and annual values of precipitation (P), temperature (T), potential evapotranspiration (PET), surface runoff and the recharge to groundwater in the whole Mygdonia catchment for the historical and future periods are presented in Table 2.

Table 2

Average and standard deviation values of the water balance parameters of the Mygdonia catchment for the historical and future periods

P (mm)T (°C)PET (mm)Runoff (mm)Groundwater recharge (mm)
Historical reference period 1970–2000 
October  = 47.96  = 13.45  = 51.93  = 0.15  = 0.04 
= 24.39  = 1.48  = 7.59  = 0.19  = 0.20 
November  = 61.45  = 8.67  = 23.37  = 0.68  = 2.40 
= 41.04  = 1.63  = 5.85  = 0.50  = 5.84 
December  = 54.43  = 5.03  = 10.84  = 1.54  = 7.77 
= 30.18  = 1.19  = 3.47  = 0.90  = 11.17 
January  = 35.01  = 3.82  = 7.73  = 2.27  = 10.39 
= 18.16  = 1.18  = 2.89  = 1.02  = 13.34 
February  = 46.36  = 4.92  = 10.11  = 2.68  = 22.49 
= 25.86  = 1.75  = 4.21  = 0.98  = 25.82 
March  = 43.25  = 7.22  = 23.70  = 3.21  = 15.68 
= 18.51  = 2.42  = 8.43  = 1.25  = 15.87 
April  = 42.92  = 11.81  = 48.12  = 2.84  = 7.65 
= 21.65  = 1.25  = 6.49  = 0.99  = 14.32 
May  = 50.73  = 16.90  = 92.84  = 2.02  = 0.16 
= 19.78  = 0.72  = 5.39  = 0.87  = 0.38 
June  = 42.37  = 21.32  = 126.18  = 0.84  = 0.00 
= 12.85  = 1.02  = 7.80  = 0.36  = 0.00 
July  = 36.82  = 23.49  = 151.92  = 0.15  = 0.00 
= 19.30  = 0.89  = 7.80  = 0.13  = 0.00 
August  = 27.65  = 23.15  = 138.95  = 0.00  = 0.00 
= 14.19 σ = 1.08  = 8.62 σ = 0.01 σ = 0.00 
September  = 29.74  = 19.48  = 92.14  = 0.00  = 0.00 
= 14.78  = 1.00  = 6.48  = 0.01  = 0.00 
Year = 518.69 = 13.27 = 777.83 = 16.38 = 66.58 
= 260.68 = 1.30 = 75.02 = 7.21 = 86.93 
2010–2040 period 
October  = 68.94  = 14.45  = 55.93  = 0.22  = 0.21 
= 34.59  = 2.98  = 12.41  = 0.26  = 1.16 
November  = 74.10  = 9.10  = 22.90  = 0.94  = 3.62 
= 39.81  = 1.38  = 5.92  = 0.64  = 10.79 
December  = 57.70  = 5.83  = 11.63  = 1.85  = 14.95 
= 26.49  = 1.15  = 2.62  = 0.90  = 23.52 
January  = 38.99  = 4.30  = 7.69  = 2.61  = 16.20 
= 21.32  = 0.86  = 1.75  = 1.05  = 16.98 
February  = 35.82  = 5.90  = 11.31  = 2.81  = 18.83 
= 29.72  = 2.15  = 5.31  = 0.75  = 21.70 
March  = 31.76  = 8.95  = 30.80  = 2.84  = 9.22 
= 18.51  = 4.60  = 30.53  = 0.93  = 11.13 
April  = 33.64  = 12.66  = 51.16  = 2.33  = 2.04 
= 23.63  = 3.32  = 23.40  = 0.73  = 4.89 
May  = 48.74  = 17.45  = 93.65  = 1.60  = 0.18 
= 24.25  = 1.12  = 5.89  = 0.60  = 0.70 
June  = 44.81  = 21.90  = 128.41  = 0.74  = 0.41 
= 24.80  = 1.24  = 10.19  = 0.43  = 2.26 
July  = 39.13  = 24.20  = 156.58  = 0.17  = 0.00 
= 23.10  = 0.84  = 7.27  = 0.25  = 0.00 
August  = 21.76  = 23.98  = 144.22  = 0.01  = 0.00 
= 17.70  = 1.13  = 9.21  = 0.05  = 0.00 
September  = 20.08  = 21.00  = 100.23  = 0.00  = 0.00 
= 11.54  = 1.11  = 7.16  = 0.00  = 0.00 
Year = 515.47 = 14.14 = 814.51 = 16.12 = 65.66 
= 295.44 = 1.82 = 121.67 = 6.58 = 93.14 
2040–2070 period 
October  = 50.17  = 16.03  = 60.13  = 0.12  = 0.49 
= 35.95  = 1.14  = 6.22  = 0.26  = 2.66 
November  = 50.90  = 10.25  = 24.81  = 0.56  = 1.49 
= 38.97  = 1.83  = 6.52  = 0.63  = 5.82 
December  = 60.41  = 6.34  = 11.49  = 1.35  = 7.00 
= 30.38  = 1.09  = 3.11  = 0.87  = 17.82 
January  = 37.47  = 4.83  = 7.78  = 2.20  = 9.58 
= 24.53  = 0.84  = 2.32  = 1.12  = 15.16 
February  = 31.25  = 6.68  = 11.68  = 2.54  = 15.51 
= 31.91  = 1.12  = 3.01  = 1.07  = 24.41 
March  = 35.21  = 10.33  = 32.09  = 2.70  = 5.76 
= 19.93  = 1.81  = 8.13  = 1.35  = 7.57 
April  = 37.14  = 13.66  = 52.03  = 2.15  = 3.62 
= 24.75  = 1.41  = 7.95  = 0.94  = 14.70 
May  = 39.33  = 18.27  = 95.92  = 1.45  = 1.12 
= 27.67  = 0.80  = 5.41  = 1.00  = 6.03 
June  = 44.46  = 23.31  = 138.30  = 0.58  = 0.71 
= 25.20  = 1.23  = 10.61  = 0.65  = 3.61 
July  = 20.24  = 25.48  = 167.38  = 0.12  = 0.00 
= 17.94  = 0.72  = 7.08  = 0.30  = 0.00 
August  = 19.81  = 25.20  = 153.36  = 0.01  = 0.00 
= 12.81  = 0.76  = 7.24  = 0.02  = 0.00 
September  = 23.17  = 21.60  = 101.78  = 0.00  = 0.00 
= 16.15  = 0.97  = 6.51  = 0.01  = 0.00 
Year = 449.56 = 15.17 = 856.75 = 13.78 = 45.28 
= 306.20 = 1.14 = 74.10 = 8.24 = 97.77 
2070–2100 period 
October  = 55.89  = 17.01  = 62.44  = 0.18  = 0.31 
= 40.34  = 1.51  = 8.03  = 0.27  = 1.71 
November  = 47.63  = 11.67  = 27.71  = 0.58  = 3.02 
= 42.68  = 1.96  = 6.92  = 0.64  = 11.24 
December  = 56.62  = 7.26  = 12.32  = 1.31  = 5.32 
= 27.85  = 1.15  = 3.08  = 1.03  = 11.62 
January  = 38.85  = 5.42  = 7.81  = 2.05  = 7.66 
= 19.29  = 0.88  = 2.02  = 0.99  = 10.25 
February  = 43.36  = 7.52  = 12.31  = 2.52  = 19.16 
= 31.73  = 1.33  = 3.40  = 0.89  = 25.04 
March  = 26.97  = 11.57  = 35.02  = 2.83  = 4.28 
= 18.36  = 2.12  = 9.82  = 1.27  = 7.77 
April  = 29.17  = 14.57  = 53.40  = 1.92  = 1.58 
= 24.10  = 1.19  = 6.19  = 0.84  = 5.41 
May  = 31.26  = 18.77  = 95.34  = 1.13  = 0.20 
= 22.69  = 0.80  = 6.70  = 0.79  = 1.09 
June  = 42.76  = 24.36  = 144.94  = 0.36  = 0.00 
= 19.55  = 1.15  = 10.43  = 0.42  = 0.00 
July  = 17.42  = 26.63  = 177.50  = 0.04  = 0.00 
= 13.00  = 0.88  = 9.67  = 0.09  = 0.00 
August  = 16.21  = 26.51  = 164.08  = 0.00  = 0.00 
= 14.16  = 0.92  = 9.39  = 0.00  = 0.00 
September  = 26.79  = 22.80  = 107.86  = 0.00  = 0.00 
= 17.57  = 1.08  = 8.48  = 0.00  = 0.00 
Year = 432.93 = 16.17 = 900.73 = 12.92 = 41.53 
= 291.31 = 1.25 = 84.13 = 7.23 = 74.13 
P (mm)T (°C)PET (mm)Runoff (mm)Groundwater recharge (mm)
Historical reference period 1970–2000 
October  = 47.96  = 13.45  = 51.93  = 0.15  = 0.04 
= 24.39  = 1.48  = 7.59  = 0.19  = 0.20 
November  = 61.45  = 8.67  = 23.37  = 0.68  = 2.40 
= 41.04  = 1.63  = 5.85  = 0.50  = 5.84 
December  = 54.43  = 5.03  = 10.84  = 1.54  = 7.77 
= 30.18  = 1.19  = 3.47  = 0.90  = 11.17 
January  = 35.01  = 3.82  = 7.73  = 2.27  = 10.39 
= 18.16  = 1.18  = 2.89  = 1.02  = 13.34 
February  = 46.36  = 4.92  = 10.11  = 2.68  = 22.49 
= 25.86  = 1.75  = 4.21  = 0.98  = 25.82 
March  = 43.25  = 7.22  = 23.70  = 3.21  = 15.68 
= 18.51  = 2.42  = 8.43  = 1.25  = 15.87 
April  = 42.92  = 11.81  = 48.12  = 2.84  = 7.65 
= 21.65  = 1.25  = 6.49  = 0.99  = 14.32 
May  = 50.73  = 16.90  = 92.84  = 2.02  = 0.16 
= 19.78  = 0.72  = 5.39  = 0.87  = 0.38 
June  = 42.37  = 21.32  = 126.18  = 0.84  = 0.00 
= 12.85  = 1.02  = 7.80  = 0.36  = 0.00 
July  = 36.82  = 23.49  = 151.92  = 0.15  = 0.00 
= 19.30  = 0.89  = 7.80  = 0.13  = 0.00 
August  = 27.65  = 23.15  = 138.95  = 0.00  = 0.00 
= 14.19 σ = 1.08  = 8.62 σ = 0.01 σ = 0.00 
September  = 29.74  = 19.48  = 92.14  = 0.00  = 0.00 
= 14.78  = 1.00  = 6.48  = 0.01  = 0.00 
Year = 518.69 = 13.27 = 777.83 = 16.38 = 66.58 
= 260.68 = 1.30 = 75.02 = 7.21 = 86.93 
2010–2040 period 
October  = 68.94  = 14.45  = 55.93  = 0.22  = 0.21 
= 34.59  = 2.98  = 12.41  = 0.26  = 1.16 
November  = 74.10  = 9.10  = 22.90  = 0.94  = 3.62 
= 39.81  = 1.38  = 5.92  = 0.64  = 10.79 
December  = 57.70  = 5.83  = 11.63  = 1.85  = 14.95 
= 26.49  = 1.15  = 2.62  = 0.90  = 23.52 
January  = 38.99  = 4.30  = 7.69  = 2.61  = 16.20 
= 21.32  = 0.86  = 1.75  = 1.05  = 16.98 
February  = 35.82  = 5.90  = 11.31  = 2.81  = 18.83 
= 29.72  = 2.15  = 5.31  = 0.75  = 21.70 
March  = 31.76  = 8.95  = 30.80  = 2.84  = 9.22 
= 18.51  = 4.60  = 30.53  = 0.93  = 11.13 
April  = 33.64  = 12.66  = 51.16  = 2.33  = 2.04 
= 23.63  = 3.32  = 23.40