1. Introduction
The Mediterranean region is one of the world’s climate change hot spots [
1]. Numerous studies concerning the Mediterranean region have found that droughts and water scarcity associated with climate change constitutes a major threat to current and future water supplies (e.g., [
2,
3]). In Greece, climate change has already contributed to decreasing precipitation since the 1990s [
4,
5,
6], while rising temperatures have simultaneously led to increasing reference evapotranspiration [
7]. Because of these climatic trends, dramatic changes in runoff volume relative to historical conditions should be expected by the middle of the upcoming century [
8,
9]. In this context, a robust assessment of the uncertain changes in freshwater availability is essential for current and future water resource management in Greece [
10].
An essential prerequisite for the effective management of water resources is the reliable characterisation of historical time series of hydrological processes, comprising non-stationarity [
11]. Water balance models can provide the broad data basis necessary for such studies. Hydrological modelling in semiarid areas, and especially in the Mediterranean region, is marked by high complexity [
12] and strong non-linearity associated with the significant seasonal fluctuations in precipitation and temperature. For this reason, the overall objective of this study is to establish a fully distributed high-resolution water balance model for the Pinios River Basin (PRB) in central Greece using the mGROWA model [
13] and analyse the results.
The mGROWA model was developed to provide high-resolution, ready for use estimates for the water balance components of large catchments or administrative areas, originally for the federal states Lower Saxony and North Rhine-Westphalia in Germany [
13,
14]. The federal states require estimates of renewable water resources and allocate water rights based on the mGROWA model outputs of the spatiotemporal distributions of groundwater recharge. Because the simulated soil moisture pattern is an important pre-condition for irrigation modelling, mGROWA was further developed through the integration of an irrigation module to study the impact of irrigation practices on the regional water balance in the Hamburg Metropolitan Region (Germany) [
15]. Due to the flexible parameterisation options of the model, mGROWA has been adapted and applied to Mediterranean conditions, e.g., for areas in France, Italy, and Turkey [
16,
17,
18]. As the methodology implemented in mGROWA allows the modelling of the impacts of climate change according to the rating system described by Refsgaard et al. [
11], the model has also been applied in climate impact studies in Germany [
13] and the Mediterranean [
16,
17].
The PRB presents a hydrological regime within a complex geomorphological environment and high seasonal and interannual variability of water balance components [
19], while also being used for intensive irrigated agriculture. A sub optimal organisation of irrigation systems [
20,
21] and unsustainable water resources management practices [
22] have deteriorated the already disturbed water balance and accelerated the degradation of water resources in previous decades. This study additionally aims to: (a) supplement and add to the existing diverse assessment studies and data provided by model implementations in the whole PRB, its sub-catchments, groundwater bodies, and other administrative sub-areas, e.g., as described in [
23,
24,
25,
26,
27,
28]; and (b) facilitate the implementation of sustainable water resources management practices.
In particular, the spatiotemporal distribution of groundwater recharge in the PRB is not adequately addressed by the aforementioned studies. One of the key objectives in our study is therefore to reduce the uncertainty concerning the characterisation of site conditions that control groundwater recharge and to quantify its potential range over time and space. Considering the above, as well as the necessity to develop effective water management plans within the context of the Water Framework Directive (2000/60/EC), this study aims to:
describe the implementation of the fully distributed water balance model mGROWA (
Section 3) in the PRB (
Section 2),
identify the implementation difficulties of such a hydrological model in a highly complex yet data-scarce Mediterranean basin (
Section 4),
provide insights into the hydrological processes of the PRB, (
Section 5),
provide qualitative and quantitative water balance assessments of the PRB (
Section 5) and their evaluation (
Section 6),
demonstrate the potential usability of this model as a water resources management tool in Greece (
Section 6 &
Section 7), and
provide a robust basis for further studies of climate change impacts on water resources in the PRB (
Section 7).
We modelled the hydrologic period 1971–2000 due to limited climate data availability for more recent time periods and because this period is used as the historical control period of the EURO-CORDEX RCM ensemble [
29]. We have set up the mGROWA model in the PRB on a 100 m grid and it is simulating water balance in daily resolution.
2. Materials and Methods
Located in central Greece, the PRB covers an area of about 11,000 km
2, and is the 2nd largest fully developed basin in Greece (
Figure 1). The PRB covers about 85% of the Thessaly Water District [
30], which according to the 2021 census, had a population of about 687,500. The PRB constitutes a highly diversified geologic, hydrological, and geomorphological environment and is surrounded by a rugged relief reaching altitudes of over 2000 m.
Figure 2 shows the location of major geomorphological and geographical features in the PRB.
The PRB is subdivided into two major sub-basins, namely the Eastern and Western Thessaly basins (
Figure 2A,B), which exhibit significantly different geologic and hydroclimatic characteristics. A low-lying hill area (
Figure 2C) comprising of karstified carbonate rocks [
31,
32] divides the two sub-basins. Along the riverine zone of Pinios River and in its delta (
Figure 2D), alluvial and recent deposits are prevalent, followed by Neogene formations (conglomerates, sandstones, clays, marls, and terrestrial-lacustrine deposits). Aquifers of medium to high water abstraction potential have developed within these formations. In the mountain ranges (
Figure 2E–I) around the two plains, Mesozoic and Paleozoic solid rock formations (mainly crystalline limestones, marbles, gneisses, and schists) dominate [
32]. Due to the high degree of karstification in some parts of the basin, the corresponding aquifers display high water abstraction potential and are strongly influencing the groundwater budget of the PRB through springs and lateral crossflows recharging the alluvial aquifers of the plain [
26].
The PRB is characterised by continental and Mediterranean climate conditions with dry and warm to hot summers, and precipitation concentrated in the winter months. According to Beck et al. [
33], the Köppen–Geiger climate classification indicates BSk (arid, steppe, cold) in the Eastern Thessaly plain, Csa (temperate, dry and hot summer) in the Western Thessaly plain and both Csb and Dsb (temperate, dry and warm summer; cold, dry and warm summer) in the mountain ranges. The basin-averaged annual precipitation for the period 1981–2000 was estimated as 700 mm [
34].
The PRB is one of the most intensively cultivated and productive agricultural areas in Greece, with agriculture corresponding to about 45% of the total basin area. Annual crops such as cotton, wheat, and corn are most common in the plains, while orchards (mainly apples, cherries, and vine) are located at the foothills of the mountain ranges. Hills and mountain ranges are forested with sclerophyllous and coniferous vegetation or covered by Mediterranean scrubland.
Almost 94% of the total water abstraction in the PRB is allocated to irrigation [
35]. Since the 1980s, the increasing water demand for irrigation requirements accompanied by irrational water management practices have resulted in significant overexploitation of groundwater resources. Currently, more than 65% of the total water consumption is served by groundwater, emphasising the importance of groundwater for the sustainability of the area. According to the most recent regional water management plan [
35], nine of the 27 groundwater bodies recognised in the PRB have been designated as of bad quantity [
31]. They are subject to recurring quantitative groundwater stress [
36]. In addition, the reservoirs in the region of the former Lake Karla (
Figure 2K) play an important role in supplying the Eastern Thessaly plain with irrigation water [
37]. The former Lake Karla was fully drained by 1962. Its reconstruction started in 1999 and was finalised in 2018. Nowadays the re-constructed reservoir is designed to store water originating from the southern mountains, as well as redirected winter runoff from the Pinios River, provided by a water diversion and a network of channels and ditches [
38,
39].
3. mGROWA Model Description
The water balance model mGROWA [
13] has been developed for assessing the water balance over large areas (river basins, states, etc.) under present and possible future climate conditions. mGROWA constitutes a new generation of the water balance model GROWA [
40], which has been used in numerous water balance studies in Germany and the Mediterranean region since the beginning of the 2000s, as presented in the section of Introduction. For a detailed description of the GROWA/mGROWA modelling approach, the reader is referred to the corresponding literature. Here, we briefly introduce the basic concepts and modules of most importance for modelling the PRB.
The distributed grid-based mGROWA model uses a two-step calculation process. Firstly, the water balance and runoff formation at the ground surface layer, which includes the root zone of the soil, is simulated using a physically based approach. Building on that, an empirical approach is used to provide a mass-separation of the total formed runoff into in-situ groundwater recharge and other diffuse water fluxes occurring near-surface in the unsaturated zone, accumulated as direct runoff. Sets of distributed gridded parameters are required, which characterise the in-situ processes in a generalised way. Thus, the spatial accuracy of mGROWA simulations is highly dependent on the quality and resolution of these input parameters.
3.1. Simulation of the Total Water Balance
The underlying formula for the first part of the simulation constitutes the generic water balance equation, with its climatic, runoff and storage terms given as:
where
p represents the precipitation,
irr the irrigation,
eta the actual evapotranspiration,
qt the total runoff,
s the amount of water stored in a grid cell, and
t the time. All values represent a vertical water height in mm. For grid cells with vegetation or bare soils,
s corresponds to the soil moisture (
θ), whereas for artificially sealed surfaces (e.g., buildings, paved roads, etc.),
s represents the water stored on these impervious surfaces. For grid cells partially covered by impervious surfaces (
PI refers to the percentage imperviousness), the simulation is executed in the two independent modes
soil with vegetation (SWV-mode) and
sealed ground surface (SGS-mode), and afterwards merged.
In the mGROWA model, special attention has been paid to the calculation of actual evapotranspiration and the associated storage functions:
The grass reference evapotranspiration
et0 is commonly determined based on the Penman–Monteith equation, as given in [
41] or alternative equations depending on the available climate data (see
Section 4.4).
kc is a land use and vegetation (or crop) specific evapotranspiration factor (also known as crop coefficient).
f(
SI,
SA) represents a topography function that accounts for slope (
SI) and aspect (
SA) (details in [
40]).
f(
s) is a storage function which considers the water available for evapotranspiration. In the SWV-mode,
f(
s) is solved by a multi-layer soil module (MLSM). In the PRB model domain, we simulated the vertical soil moisture dynamics using five soil layers of 3 dm thickness each. In each layer, the total soil water storage is characterised by the plant available field capacity
θa (details in
Section 4.2) and the rooting depth
RD. The functional dependence of evapotranspiration on soil moisture is given by the Disse-function [
42]:
where
e is the Euler number,
r is a vegetation-specific factor,
θpwp the soil moisture at the permanent wilting point,
θa the plant available soil moisture of the soil at field capacity (i.e., the difference between the soil moisture at field capacity
θfc and
θpwp), and
θ the actual soil moisture. The Disse-function provides values in the range of 0 to 1. When the soil moisture decreases to the permanent wilting point, actual evapotranspiration becomes 0. When the soil water storage reaches the field capacity, actual evapotranspiration is not diminished, i.e., the level of potential evapotranspiration is reached.
Because of the intensive irrigation of most field crops in the PRB, irrigation-triggered evaporation fluxes must be incorporated into basin-wide water balance assessments. For this purpose, mGROWA provides an irrigation module (IM) that indirectly includes this flux by estimating the spatial variation of the irrigation requirements of field crops on a daily basis and linking irrigation water inputs to the MLSM. Irrigation of field crops commonly follows specific rules which are intended to ensure economically justified expenses and soil water content values at a plant-physiological level that promise optimal yields. The IM utilises the simulated soil moisture status of the MLSM and crop-specific sets of rules, which reflect the common irrigation management practices of farmers, in order to determine irrigation sequences and water quantities. The following rules and constraints are implemented (details in [
15]), and the corresponding parameters are introduced in
Section 4.2:
irrigation-relevant root zone,
soil water content that initiates irrigation,
soil water content at which irrigation stops,
maximum irrigation level per day,
period of the year with potential irrigation application,
minimum precipitation level per day for which no irrigation is applied,
total water budget available for irrigation in a predefined period (according to water usage rights allocated to a farmer or field plot).
According to Equation (1), total runoff is calculated as the surplus water that cannot be stored in the root zone of soil against gravity or on an impervious surface due to its limited water storage capacity. The daily surplus water is then separated into groundwater recharge and direct runoff (incorporating quick runoff components) within the subsequent empirical part of the simulation.
3.2. Runoff Separation
For the overall water balance simulation, runoff separation is also split into two modes depending on the presence of artificially sealed surfaces (SGS-mode). For impervious shares of grid cells, the surplus water that cannot be stored on the surface is balanced as quick urban direct runoff and attributed to the direct runoff (
qd). The runoff characteristics of grid cells (or shares) without ground surface sealing (SWV-mode) are assigned using empirically derived distributed
BFI values (base flow indices) which describe groundwater recharge (
qr) as a constant portion of total runoff:
The
BFI values depend on natural site conditions (details in
Section 4.3) and can be regarded as constant in the long-term. Because groundwater recharge equals base flow in the long-term (under the assumption of hydrological stationarity),
BFIs derived from discharge hydrographs can be regionalised and correlated with spatially distributed site conditions (e.g., soil or geologic properties) and resulting distributed
BFI values can thus be utilised to estimate area-differentiated in-situ groundwater recharge [
40,
43]. In the mGROWA model,
qd is the residual of such calculations (see Equation (4)) and comprises the fast and moderate-fast runoff components, such as overland flow and interflow, however, without separating them into these individual components.
5. Results
Maps of the long-term annual water balance quantities for water resources management purposes in the PRB were calculated by temporal aggregation of mGROWA’s grid-based simulation results.
Figure 13 displays the spatial patterns of simulated mean annual actual evapotranspiration, total runoff, direct runoff, and groundwater recharge. Because actual evapotranspiration strongly depends on the water available in soil and impervious surface storages, the low water storage capacity of the ground surface and soil in urban areas, in combination with the number of rain days per year, is the reason for the low levels below 300 mm/a in these environments. In contrast, the high plant available field capacity of soils and irrigation application raise evapotranspiration significantly above the level of 650 mm/a over large areas of the agricultural plains. Forested areas in low and moderate slopes reach levels above 600 mm/a, whereas Mediterranean shrublands covering moderate to steep slopes as well as flat low-water-capacity soils exhibit mean evapotranspiration values in the range 400 to 550 mm/a.
Precipitation water that does not leave the basin as evapotranspiration is modelled as total runoff in mGROWA in the long-term. High total runoff occurs in mountainous terrain (>500 mm/a) and a general east-west gradient can be observed in the plains, with an increase from 100 to 300 mm/a. These quantities of water runoff follow different flow paths, according to the
BFI values introduced in
Figure 7 and
Figure 8. Quick runoff (interflow, overland flow; considered as direct runoff) dominates in mountainous terrain, except in karstic areas. Direct runoff feeds the river systems in the PRB mainly during the hydrological winter half-year and is the main cause of the intermittent character of smaller creeks. Along the fringes of the mountain ranges, direct runoff seeps laterally into unconsolidated aquifers of the basins and acts as lateral aquifer recharge. The portion of the direct runoff that likely infiltrates into groundwater bodies via the streambeds has not been considered; however, major contributions to aquifer recharge originate from in-situ groundwater recharge, as shown in
Figure 13.
The spatial distribution of groundwater recharge is governed by geologic properties, but also by the patterns of climatic quantities (mainly precipitation). The lowest recharge rates occur in the southern parts of the Eastern Thessaly plain, with values below 50 mm/a. In the north-western unconsolidated and highly permeable parts of the Western Thessaly plain, recharge levels can exceed 300 mm/a. Significant groundwater recharge also takes place in the karstic rock formations, with levels of 300 mm/a and higher.
Figure 14 illustrates the temporal patterns of in-situ groundwater recharge aggregated for the whole PRB. As expected, recharge frequently occurs during the hydrologic winter half-year, with no simulated recharge occurring for the majority of the summer months. The interannual variability generally follows the precipitation patterns. The long-term catchment-averaged annual groundwater recharge amounts to approximately 120 mm/a. Monthly precipitation quantities that are close to the mean climatological level during winter half-year typically cause a low level of groundwater recharge of less than 20 mm/month. High groundwater recharge at the level of 50 mm/month and above occurs only when precipitation exceeds 150 mm/month, i.e., during above-average wet months and occasionally associated with extreme rain events. These events regularly lift the annual groundwater recharge above the long-term annual average, whereas more uniform temporal distributions of winter precipitation rarely lead to above-average levels.
Figure 15 displays the spatial distribution of mean annual potential irrigation requirements (1971–2000) simulated using mGROWA, and
Table 5 provides the corresponding spatial statistics. Olives do not require extensive irrigation, whereas the other crops need multiple applications of irrigation per season, which result in long-term means ranging from 300 to more than 460 mm/a. The spatial patterns of the irrigation requirements are controlled by a combination of influencing factors; primarily by precipitation, plant available field capacity, and the irrigation rules.
Figure 16 displays the simulated mean longitudinal river discharge for the period 1971–2000 under the assumptions of congruent surface and sub-surface catchments of the plotted river segments and largely natural discharge behaviour, i.e., no withdrawals for irrigation purposes, bypasses, wastewater inflows, etc. The approach implemented to calculate longitudinal river discharge profiles uses the total runoff pattern shown in
Figure 13 and flow directions derived from the DEM (
Figure 4). The flow accumulation is calculated using the fast algorithm proposed by Zhou et al. [
84]. According to this approach, the Pinios River has a long-term mean discharge (1971–2000) of 89.9 m
3/s at the outlet to the Aegean Sea.
Bringing together the simulated irrigation requirements, which represent the potential irrigation requirements, and total runoff or groundwater recharge in practical indices allows insights into spatial patterns of water availability for agricultural purposes [
15].
Figure 17 shows the spatial distribution of the ratio of potential irrigation to total runoff (
PIQT ratio) and to groundwater recharge (
PIQR ratio). These indices are calculated by applying the flow accumulation approach to the simulated variables, and then using the accumulated values at each grid cell to calculate the ratios. The ratios therefore depict the overall situation at each grid cell, including the situation topographically upstream. Values close to zero indicate zero or negligible water consumption by agriculture. Within the range 0 to 1, irrigation water consumption in the upstream areas can theoretically be supplied by the runoff or groundwater recharge formed upstream. However, in practice values around 0.7 seem to be thresholds in this context. The higher the values above 1 (or 0.7), the more water has to be transferred from other parts of the PRB to supply irrigation requirements. In the case of irrigated agriculture in the Pinios delta, the major part of required water quantities are extracted from the Pinios River [
85] and were previously formed as discharge somewhere else in the headwaters of the river system.
The PIQT and PIQR also indirectly indicate the pressure on farmers to compete for water for irrigation. The hotspot of this competition for water resources is clearly the Eastern Thessaly basin. This is one of the main reasons for which the Lake Karla reservoir, in the southern part of the Eastern Thessaly basin (see
Figure 2), was re-established [
22]. The small mountain fringe around the Karla reservoir provides significant quantities of direct runoff which is used to counterbalance some of the water gap caused by the very low level of in-situ groundwater recharge observed there.
Additionally, from a water management perspective, the long-term groundwater recharge to precipitation ratio (QRP ratio) constitutes a useful indicator, as it provides spatial information about the percentage of precipitation that becomes groundwater recharge in years of average climate conditions. The QRP ratio was calculated based on the mGROWA simulation results and is shown in
Figure 18. The highest ratios (>0.5) are attained in the Western Thessaly basin, whereas the Eastern Thessaly basin again shows low values, in particular at the south-eastern edge. Most of the mountain ranges also exhibit low ratios frequently below 0.1 (except the karstic units), because rock formations are of low permeability and cannot accommodate high amounts of groundwater recharge. As described above, interflow is the dominant runoff component at these sites.
6. Model Evaluation Strategy and Discussion
The evaluation of long-term water balance simulations covering a non-recent hydrologic period is challenging, particularly when river discharge gauges were not permanently installed and maintained in a basin. As in many regions, long, reliable, and continuous discharge hydrographs are rare for the PRB and hydrologic observation networks were downsized during the last decades. Furthermore, discharge values from the published literature do not necessarily match the hydrologic period modelled in this study. For example, Therianos [
86] provided an average discharge of 80.92 m
3/s (published in Foutrakis et al. [
87]) in the Pinios estuary area, which was probably derived for below-average dry years in the 1960s. However, this value compares well to the long-term average (1971–2000) of 89.9 m
3/s produced by mGROWA. Moreover, Migiros et al. [
32] state that the mean annual total discharge is 3500 × 10
6 m
3 (equivalent to 111 m
3/s), without naming sources, which appears to correspond to wet year conditions.
The common method to evaluate mGROWA simulations is to compare long-term mean observed discharge with simulated total runoff in a set of sub-catchments of a larger basin. For this purpose, observed discharge is converted from m
3/s to catchment-averaged mm/a.
Table 6 lists the set of gauges (sub-catchments shown in
Figure 19, right) that were selected from the results of research in the studies of HYDROMET [
88], Zarris et al. [
89], and Koutsogiannis et al. [
90]. A quality flag describing the reliability of the streamflow data is also included in the
Table 6, determined based on the detailed description of gauges included in the study of Zarris et al. [
89]. Within the evaluation procedure, only periods with complete observed data were considered, except from only a very few cases in which filled data with double linear regression were obtained from the study of Koutsogiannis et al. [
90].
This evaluation procedure is additionally impeded by the fact that water abstraction quantities from rivers and groundwater for irrigation purposes are unknown. Although the observed discharge implicitly accounts for water abstractions, the spatially distributed total runoff simulated in mGROWA does not in the same way, because a part of the simulated total runoff is transferred to irrigation internally within the sub-catchments. To therefore correct these simulated runoff values and derive discharge values for a sub-catchment, a fraction (considered as a correction factor) of the simulated potential irrigation requirement (
Figure 15) should be subtracted from the total simulated runoff. The values of the correction factors are catchment-specific and are unfortunately unknown. For this reason, we show the whole range of the possible influence of the correction factors in the scatter plot of results shown in
Figure 19 (left), in which unfilled circles represent uncorrected simulated total runoff while filled circles represent 100% correction by simulated potential irrigation.
The results presented in
Figure 19 suggest a tendency for the mGROWA model to overestimate the total runoff in smaller mountainous headwater sub-catchments such as
Gavros,
Skopia,
Sarakina,
Kedros, and
Ampelia, where irrigation water consumption is generally lower than in the plains. The smaller range resulting from the correction process indicates these lower irrigation requirements. We hypothesise that one reason for this finding could be that the orographic gradients applied (see
Section 4.4) could overestimate precipitation quantities in high altitudes; however, this would also influence the model performance at the downstream gauges. The large sub-catchments corresponding to the gauges
Larissa (as the sum of Alkazar and Giannouli gauges),
Piniada, and
Amigdalia reveal a good agreement of the simulation and observation. This is indicated by the position of these points close to the 1:1-line and their linking lines (dotted) that intersect it. The knowledge of the true amount of irrigation water abstraction would likely lead to a very good model performance after application of the relevant correction factor. Consequently, we conclude that mGROWA has been proved to provide a reliable spatially distributed water balance of the PRB.
In contrast to the total runoff, the evaluation of groundwater recharge is even more challenging. In general, groundwater recharge in a basin can be equated with base flow over a long period. Behind this approach is the assumption that the inflow (recharge) and outflow (base flow) from an aquifer must be constant in the long-term if the level in the aquifer also remains constant. In practice, the base flow can be determined by filtering the hydrograph, however, this process requires daily streamflow data which were available only for the gauges in
Larissa. The implementation of Arnold’s filtering method [
91] in daily streamflow data from Larissa yielded a base-flow fraction of 0.54 in total discharge. This compares well with the value of 0.46 that can be derived from our mGROWA setup for the
Larissa sub-catchment.
7. Summary and Future Research
The components of the water balance, most importantly the crop-specific potential irrigation requirements, actual evapotranspiration, total runoff, direct runoff, and groundwater recharge, were simulated using mGROWA for the PRB for 1971–2000. The established model setup comprises comprehensive observed climatic input data and spatially distributed parameters from national and European datasets. The derivation of reliable geomorphologically plausible parameter distributions (BFI values, plant available field capacity, etc.) posed a key challenge in the study.
A trend of increasing reference evapotranspiration in the range of 1050 to 1200 mm/a has been observed in the PRB in the period 1971–2000, while the precipitation time series shows an extended dry period from 1988 until 1993, but without a noticeable long-term trend. The long-term catchment-averaged annual potential irrigation requirements of the major crops cultivated in the PRB varies from 300 to more than 460 mm/a. Comparing to other studies, our results are reasonable for the major crops of the PRB. More in detail, Tsakmakis et al. [
92] presented that irrigation water requirements calculated with crop growth modelling and applied in cotton fields located in North Greece ranged between 227 mm (deficit irrigation applied with drip system) and 400 mm (regular irrigation applied with sprinkler system). Stamatiadis et al. [
93] reported that intermediate irrigation was 300 and 335 mm for cotton fields located in the PRB (near Larissa) for years 2008 and 2009, respectively. For a corn cultivation field located in the Pinios River Basin, Tsakmakis et al. [
94] indicated irrigation requirements of 350 mm based on crop growth modelling. Nevertheless, according to the water district management plan [
35], cotton irrigation requirements were found to range between 427 and 445 mm. These requirements are significantly higher than the average cotton irrigation requirements presented in
Table 5. This discrepancy is mainly attributed to the different approach in calculating crop irrigation requirements. Irrigation water requirements reported in the water district management plan [
35] are calculated according to the Greek Ministerial Decision No. Φ.16/6631 (JoG issue B’ 428 2/6/1989) “Estimation of the minimum and maximum necessary volumes for the rational use of water in irrigation”, which is based on the Blaney–Criddle formula [
95]. According to Tegos et al. [
96], this formula was found to overestimate the potential evapotranspiration by 30% in Greece, while for stations located far from the sea, such as Larissa, the deviation was found to exceed 50%. Moreover, cotton irrigation requirements reported in the water district management plan imply full irrigation, while our approach is based on moderate deficit irrigation of cotton. Similar or higher discrepancies in irrigation water requirements are also presented for the other crops. These differences are partially reflected at the basin scale, since the 814 hm
3 of average annual potential irrigation water demand simulated with mGROWA for the irrigated agricultural land of the PRB is substantially less than the 1202.5 hm
3 reported in the water district management plan [
35]. Aside from the different irrigation water requirement calculation methodologies, this difference can be also attributed to the following factors: (1) our calculations do not incorporate the efficiency of irrigation systems and losses of water distribution, meaning that they can be considered to be close to the optimal and (2) for cotton and complex cultivation patterns, moderate deficit irrigation is applied with mGROWA, which reduces the irrigation water requirements on the basin scale.
The extraction of these water volumes from the ground and surface waters places substantial stress on the water resources of the basin. The groundwater resources of the basin are recharged at a mean rate of approximately 120 mm/a. In line with the long-term temporal patterns of precipitation, there was no obvious temporal trend in groundwater recharge in the PRB from 1971 to 2000, but groundwater recharge declined corresponding to the extended dry period from 1988 until 1993. The mGROWA simulation provides additional data for further analyses and comprehensive statistics in terms of water resources management, e.g., the PIQT and PIQR ratios. The procedure applied to evaluate the total runoff simulated by mGROWA revealed the uncertainties associated with modelling in data-scarce basins, such as the PRB. There are several starting points to improve, proceed and extend the water balance modelling in the PRB in addition to the findings achieved so far, some of which are briefly discussed in the following paragraphs.
Due to the grid-based 1-D nature of the mGROWA model, simulation results require some post-processing in a GIS-system or numerical groundwater model to derive final key parameters for decisions in water resources management (e.g., to derive the sustainably usable groundwater supply in a groundwater body). In the case of the PRB, interflow as a component of direct runoff seeps laterally into unconsolidated aquifers of the basins along the fringes of mountain ranges and acts as lateral recharge of the main aquifer. Thus, the total aquifer recharge of the main aquifers in the two Thessaly plains consists of this lateral component, in-situ groundwater recharge in the plains and other difficult to estimate influxes over various boundaries. In practice, the water volumes and rates calculated using mGROWA can serve as boundary conditions in more specific groundwater modelling studies, as described in Herrmann et al. [
97]. Nevertheless, simulation results from mGROWA have been proven to provide reliable decision support for water resources management at the regional scale, e.g., recently in the federal state of Lower Saxony (Germany) [
14] and the Ergene River Basin (Turkey) [
18].
In addition to the application of mGROWA to provide data on total water fluxes for water resources management, the model has been established in a model chain together with a regional-scale nutrient model (mGROWA-DENUZ) In the Thessaly Water District, nitrates constitute a diffuse pollution from agricultural activities that should be controlled and mitigated [
98]. The ongoing implementation of the already established action plans in Thessaly would benefit from results of the model chain mGROWA-DENUZ.
In the context of the present study, we provide a comprehensive description of parameterisation workflow, adapted to the data availability situation in Greece. This workflow can be used as a guidance for the implementation of fully distributed water balance models in European data-scarce regions, since the data used are usually available under public domain. Nevertheless, and as described in this article, further improvements to the input datasets are needed to advance the model’s reliability. It is widely known that the Mediterranean region is prone to severe observation data scarcity. For this reason, the Pinios Hydrologic Observatory (PHO) [
99] was established to improve data availability in the eastern part of the PRB and to support the improvement of parameter estimations, which are of fundamental importance for water balance modelling in the Mediterranean region [
49]. In the PHO, for example, several observation sites at the southern slopes of the Mount Ossa massif have been equipped with various meteorological and soil moisture sensors. They almost completely cover the range of elevation levels in the region and can support, among other things, increased accuracy in the calculation of the orographic gradients of precipitation and reference evapotranspiration described in
Section 4.4.
To complement the model performance evaluation presented in our study, we propose additional methods for evaluation in future studies. Model performance evaluation will continue to be an issue in forthcoming studies. We plan to evaluate simulated soil moisture time series (mGROWA MLSM) by comparing simulated soil moisture time series with the advanced remote sensing products described in El Hajj et al. [
100] and Bazzi et al. [
101], using an approach similar to Herrmann et al. [
17]. Additionally, for the evaluation of simulated total runoff and baseflow, improvements in model evaluation might be difficult to achieve, since the current river flow monitoring network is not able to support such a task. Nevertheless, analysing reconstructed historical hydrographs in combination with a modern powerful hydrograph filter (e.g., described in Pelletier and Andréassian [
102]) can provide information to support the suitability of the BFI values chosen for this study.
A major obstacle to the efficient water resources management in the PRB is the non-existence of short-term retrospective and forecasting water balance simulations, which could quantify, for example, the severity and impacts of water scarcity events. The meteorological observation network in the PRB has shrunk over the previous decades and the gridded E-OBS data (ENSEMBLES daily gridded observational dataset for precipitation, temperature and sea level pressure in Europe [
103,
104]) show many gaps over the PRB model domain. A possible approach to accurately characterise the spatiotemporal patterns of meteorological data from 2000 onwards seems to be the use of reanalysis data (e.g., COSMO-REA6 [
105]) in a model chain with mGROWA. As a mid-term goal, the full operational mode of mGROWA is intended to encompass the coupling with numerical weather forecast models.
Numerous studies have stated that irrigation water requirements are expected to increase [
106] and available freshwater resources to decrease [
107] in the Mediterranean region due to climate change. A reduction in mean annual precipitation in the PRB of 80 mm/a is expected by 2100 [
34]. Several studies have already demonstrated the suitability of implementing mGROWA for climate change impact studies [
15,
17,
108]. Consequently, such a study using mGROWA in a chain with the EURO-CORDEX RCM ensemble [
29] is the next reasonable step towards providing the data basis for developing strategies for future water resources management in the PRB.