Identifying potential effects of climate change on the development of water resources in Pinios River Basin, Central Greece

Identifying potential effects of climate change on the development of water resources in Pinios... The aim of the present study is to assess the future spatial and temporal distribution of precipitation and temperature, and relate the corresponding change to water resources’ quantitative status in Pinios River Basin (PRB), Thessaly, Greece. For this purpose, data from four Regional Climate Models (RCMs) for the periods 2021–2100 driven by several General Circula- tion Models (GCMs) were collected and bias-correction was performed based on linear scaling method. The bias-correction was made based on monthly precipitation and temperature data collected for the period 1981–2000 from 57 meteorological stations in total. The results indicate a general trend according to which precipitation is decreasing whilst temperature is increasing to an extent that varies depending on each particular RCM–GCM output. On the average, annual precipitation change for the period 2021–2100 was about − 80 mm, ranging between − 149 and + 35 mm, while the corresponding change for temperature was 2.81 °C, ranging between 1.48 and 3.72 °C. The investigation of potential impacts to the water resources demonstrates that water availability is expected to be significantly decreased in the already water-stressed PRB. The water stresses identified are related to the potential decreasing trend in groundwater recharge and the increasing trend in irrigation demand, which constitutes the major water consumer in PRB. Keywords Climate change · Water resource regional climate models · Precipitation · Temperature · Pinios River Basin Introduction spring. In terms of precipitation, significant decrease of up to 30% was indicated on an annual basis for the south Medi- Mediterranean has been identified as the most vulner- terranean area, which was presented to be even higher in its able European region in terms of climate change impacts westernmost and easternmost parts. Similar trends are pre- (Schröter et al. 2005; Navarra and Tubiana 2013). According sented by Giorgi and Lionello (2008). Jacobeit et al. (2014) to Giorgi (2006), Mediterranean region constitutes the plan- reviewed a wide number of studies which investigated et’s hot spot in terms of climate change effects. This is justi - projected climate change trends in Mediterranean region fied by the significant temperature increase and precipitation by applying statistical downscaling techniques in model’s decrease with fewer wet days and drier summers as pre- climate data. In terms of temperature, seasonal variation in sented in several studies. More specifically, Dubrovsky et al. future projections indicates the best agreement. With regard (2014) investigated the future trends of precipitation and to precipitation, a decreasing trend can be considered for temperature variation based on the results of 16 GCM runs. autumn, spring and summer values for the whole Mediter- Their results indicate significant increase in temperature for ranean region, while winter precipitation indicates signifi - the period 2070–2099 compared to the period 1961–1990, cant variability and cannot be characterized as increasing which is higher during summer and lower during winter and or decreasing in general. Concerning Greece, the results of the analysis performed in precipitation and temperature data of 22 RCMs by Tolika et al. (2012) indicated an increasing * G. Arampatzis trend in future temperature variation by all models, while in arampgeo@gmail.com terms of precipitation, most of the models, but not all, pre- Soil and Water Resources Institute, Hellenic Agricultural sented decrement in future precipitation amount and wet day Organization-Demeter, 57400 Sindos, Greece occurrence. Precipitation is also presented to be decreased Forschungzentrum Juelich GmbH, Agrosphere Institute by Chenoweth et al. (2011), according to which a decrement (IBG-3), 52425 Juelich, Germany Vol.:(0123456789) 1 3 51 Page 2 of 17 Applied Water Science (2018) 8:51 by 18 and 22% is indicated for precipitation in Greece by the spatio-temporal distribution. Against this background, the midcentury and the end of century, respectively. Moreover, aims of this study are: extreme precipitation events such as frequency and mag- nitude are expected to be increased in Greece, especially • To assess the temporal and spatial future trends in pre- during winter (Tolika et al. 2008). cipitation and temperature variation in the largest fully The above-described changes in precipitation and tem- developed basin in Greece (Pinios River Basin, PRB) perature variation patterns during the twenty-first century and, are expected to significantly affect water resource availabil - • To relate those changes to potential impacts in future ity in Mediterranean region, while there are studies which water resources availability. are indicating that water yields in Mediterranean region have already been decreased, as a consequence of climate change Given the fact that agriculture is the dominant water con- (García-Ruiz et al. 2011; Ludwig et al. 2011). According to sumer in PRB accounting for over 90% of water use (Hel- European Environment Agency (2009), several studies have lenic Ministry for the Environment, Energy and Climate been conducted which aim to assess the potential effects of Change-Special Secretariat for Water, 2014), precipitation climate change in water resources in Mediterranean region and temperature evolution are expected to significantly affect and their common conclusion is that water resource avail- water resource availability in the form of effective precipita- ability is expected to decrease. Milano et al. (2013) inves- tion and crop water demands and indirect availability in the tigated the effects of climate change in water resources in form of groundwater recharge and surface runoff. Mediterranean region and their results indicated that by 2050 a significant decrease in freshwater availability is expected which ranges between 30 and 50%. Local studies of climate change impacts in water resources are also indicating sig- Materials and methods nificant stresses for water resources in Greece. More specifi- cally, Pisinaras (2016) investigated potential climate change Study area description effects in an aquifer located in northeastern Greece and the results indicated a significant decrease in groundwater level, PRB is located in Central Greece and covers an area of about 11,000 km . It is characterized by highly diversified geo- as a result of decreased groundwater recharge and increased groundwater abstractions for irrigation. A significant reduc- logical, hydrological and hydrogeological conditions and marked by the systematic exploitation of water resources tion in future water resource availability was also presented by Koutroulis et al. (2016) for Crete island (south Greece), since early 1960s. From the water administration point of view, PRB belongs to the Thessaly water district (EL08) while significant decrease in surface runoff was suggested for the next 50 years by Kalogeropoulos and Chalkias (2013) and covers the major part of this district (85%). Two climate types are identified in PRB: continental climate conditions for a catchment located in Andros island. Several hydrological modelling studies have already been are dominant at the central and western part of PRB, while typical Mediterranean climate conditions are met at the east- performed in Pinios River Basin to assess the impacts of climate change on water resources, e.g. Mimikou and Baltas ern part. For the period 1981–2000, the minimum average annual precipitation was 392 mm at the southeastern plain (2013), Varanou et al. (2002), indicating decreasing runoff levels and a need to adapt regional water resources manage- part of the basin, while the corresponding maximum value was 1705 mm at the western mountainous part. The aver- ment to climate change. Panagopoulos et al. (2016) applied the grid-based empirical model GROWA to assess the cli- age annual precipitation for the aforementioned period was 700 mm. mate change impact for the forecasting period 2020–2080. Despite the fact that the implemented code provides a spa- The agriculturally used plains covering 45% of PRB belong to the most intensively cultivated and productive tially distributed but temporally averaged result, the fore- casted impact of climate change was pronounced as the agricultural areas of Greece. Accordingly, agriculture con- stitutes the major water consumer for Pinios river basin, availability of renewable water resources, i.e. the mean total runoff, was forecasted to decrease by 22–62%, depending on since about 93% of total water consumption (1292 hm ) is allocated to irrigation followed by domestic water sup- the examined climate change scenario. Taking into account all the above, as well as the neces- ply (5.5%), livestock (1%) and industry (0.5%). According to Loukas (2010), a wide variety of crops are cultivated in sity to develop climate change impact assessment studies on the local scale, to construct sustainable development PRB, including cotton, wheat, alfalfa and maize in the plain area, whereas apple, apricot, cherry, olive trees and grapes plans (Milano et al. 2013), careful evaluation of climate change data sets seems to be indispensable to comprehend are cultivated at the foothills of the eastern mountains. climate change impact on water resources availability and 1 3 Applied Water Science (2018) 8:51 Page 3 of 17 51 Permeable geological formations are dominating in PRB, Mitchell 2009). These regional simulations are driven by since they cover about 44% of the total basin area. Imperme- ERA40 reanalysis data for the control period and by several able geological formations and karstic aquifers cover about GCMs under SRES A1B socio-economic scenario. Among 40 and 16% of the total basin area, respectively. With regard the various models of ENSEMBLES project, data for the to the hydrogeological conditions presented in PRB, the periods 1981–2000 and 2021–2100 were used from the fol- aquifers developed in quaternary depositions are indicating lowing four RCMs: (a) HIRHAM5 (Christensen et al. 2006) significant water abstraction potential followed by karstic driven by ARPEGE GCM (hereafter referred as HA), (b) aquifers found mainly around the plain parts of PRB. Since RACMO2 (van Meijgaard et al. 2008) driven by ECHAM5 about 65% of total water consumption is satisfied by local GCM (hereafter referred as RAE), (c) REMO (Jacob 2001) aquifers, groundwater constitutes a vital water source for driven by ECHAM5 GCM (hereafter referred as REE) and PRB. (d) RCA (Kjellström et al. 2005) driven by HadCM3 GCM In the framework of implementing EU-Water Framework (hereafter referred as RH). These models were found to have Directive (EU-WFD, 2000), 27 groundwater bodies have suc ffi ient performance in representing precipitation and tem - been delineated in PRB, from which 3 display bad qualita- perature in several Mediterranean basins when compared to tive status because of high N O concentrations attributed observed data (Deidda et al. 2013). to agricultural activities. 9 groundwater bodies display bad To improve local climate variability representation on quantitative status, i.e. declining groundwater tables, due to regional and local assessment of climate change effects, over-abstraction of groundwater for satisfying the agricul- further bias-correction in RCM output may be applied. A tural irrigation needs. wide range of bias-correction methods are proposed in the The average long-term annual water discharge of PRB scientific community, out of which the simple methods have comprises 3300 hm . For assessing and documenting the the advantage of altering the RCMs’ results as little as possi- status of surface waters of PRB, 73 river water bodies have ble (Graham et al. 2007). The advantages and disadvantages been identified. As Pinios River surface waters are only used of the most widely applied simple bias-correction methods, locally for feeding irrigation needs, 57 are characterized by namely the delta change and linear scaling, are presented by low river water abstraction, 7 by medium water abstraction Teutschbein and Seibert (2013). Linear scaling was applied and only 9 by high water abstraction. In terms of pollution, for the purposes of this study, which has been previously Pinios river water quality is stressed by the discharge of used in several studies for the assessment of climate change treated and untreated domestic and industrial effluent and impacts at river basin scale (Bosshard et al. 2013; Fiseha agricultural return flows (Loukas 2010). According to the et al. 2014). recently revised water management plan, in terms of nitro- With regard to precipitation, a scaling factor was calcu- gen loads and BOD, inputs from non-point (diffuse) sources lated for each calendar month, RCM and meteorological sta- are dominating (70 and 82% of the total loads, respectively), tion as the ratio between the average observed and average while concerning P, 32% of the total loads are attributed to simulated monthly precipitation for the period 1981–2000. non-point sources. Those scaling factors were subsequently multiplied by monthly precipitation data for the period 2021–2100 Climate data–bias‑correction (2021–2099 for RH) for each calendar month. Monthly temperature was similarly corrected except that addition of Monthly precipitation data were collected from 57 mete- a scaling factor to projected monthly average temperature orological stations located in the wider PRB area covering was used, rather than multiplication. the period 1981–2000 (control period). For 17 of the 57 The ordinary Kriging algorithm was applied to develop meteorological stations, average monthly temperature for the spatial distribution of precipitation and temperature the control period was also available. The location of the data in PRB. The period 2021–2100 was divided into four meteorological stations is illustrated in Fig. 1. sub-periods of 20 years each to assess future trends in pre- Despite the fact that output of GCMs has been widely cipitation temporal variation. The results were analyzed on applied in climate change assessment studies, the complex- monthly, seasonal and annual basis for the four periods and ity of climate characteristics of Greece and its controlling compared to the corresponding precipitation and tempera- factors cannot be adequately represented by GCMs (Tolika ture data of the period 1981–2000, which will be referred to et al. 2012) and, therefore, the application of RCMs which as historical period. are based on finer grid resolutions are thought more appro- To assess RCM performance on representing precipi- priate. Consequently, precipitation and temperature data tation and temperature variation patterns, as well as the were extracted from the ENSEMBLES project, in which performance of bias-correction, Taylor diagrams (Taylor state-of-the-art RCMs were used to produce regional simu- 2001) were compiled, since they provide an efficient graphi- lations at a 25 or 50  km resolution (van der Linden and cal method to present how well simulated patterns match 1 3 51 Page 4 of 17 Applied Water Science (2018) 8:51 Fig. 1 Location map of the study area the observed ones. Taylor diagrams are incorporating cor- higher correlation indicate better representation of observed relation coefficient, centered root mean square difference patterns. With regard to raw RCM precipitation data, corre- (cRMSD) and standard deviation into a single diagram lation coefficient ranged between 0.21 (REE) and 0.37 (RH), and, therefore, they provide a clear overview of similarity while standard deviation ranged between 1.35 (REE) and between simulated and observed data. 2.02 mm/day (HA). The corresponding range for cRMSD was 2.26 mm/day (RH) to 2.53 mm/day (HA). Better per- formance is presented by RH and HA, since the first RCM Results indicates the highest correlation coefficient value and the latter indicates standard deviation closer to the observed one. Future trends in precipitation variation All RCMs were found to underestimate standard deviation and, therefore, they indicate lower precipitation variation The Taylor diagram compiled by raw and bias-corrected compared to the observed. The bias-correction procedure RCM precipitation data for the period 1981–2000 is improved correlation coefficient since it was found to be presented in Fig.  2. Points that are found closer to the increased by more than 0.1 units for all RCMs (0.39–0.5), “observed” quadrant of standard deviation and demonstrate while significant improvement was also observed for 1 3 Applied Water Science (2018) 8:51 Page 5 of 17 51 3 3 Taylor Diagram hm ), followed by RAE (113 mm or 1.250 h m ) and REE (− 91 mm or 1007 hm ), while RH results indicate a small increase in average total annual precipitation for the period 2021–2099 (35 mm or 391 hm ). Increased precipitation for 3 the period 2011–2100 is also indicated by RH for Vosvozis 2.5 REE-BC river basin located in northeastern Greece (Pisinaras et al. 2.5 HA-BC 2014). RAE-BC HA-R 2 When comparing the temporal change of annual pre- RH-BC 2 cipitation for each RCM–GCM model combination, differ - RAE-R ent trends are indicated. HA demonstrates a very signifi- 1.5 1.5 REE-R cant decrease during 2021–2040, which becomes milder RH-R but still significant during 2041–2060. In contrast, RAE demonstrates a very small precipitation decrease during 2021–2040, while for the period 2041–2060 precipitation decrease is much more significant and almost equal to pre- 0.5 cipitation decrease for the period 2061–2080. REE tem- 0.5 poral variation is similar to RAE except from the period Observed 2081–2100, during which precipitation decrease is lower 1.0 when compared to precipitation decrease for the periods 0 0.5 1 1.5 22.5 3 Standard Deviaon (mm/d) 2041–2060 and 2061–2080. The increased precipitation indicated by RH in the present study has been also indi- Fig. 2 Taylor diagram of raw (R) and bias-corrected (BC) RCM pre- cated by Tolika et al. (2012) for precipitation projection with cipitation data for the period 1981–20 RCA-ECHAM4. The spatial distribution change of annual total precipita- standard deviation for all RCMs. RH and RAE RCMs indi- tion for the period 2021-2100 for each RCM–GCM combi- cate better performance after bias-correction application. nation is presented in Fig. 4. Similar trends of precipitation Annual precipitation temporal variation was assessed spatial distribution change are presented for HA, RAE and for the four sub-periods and compared to the median total REE, as higher precipitation decrease is deduced for the annual precipitation of historical period (1981–2000), which mountainous parts of the PRB and especially for its eastern is 682 mm (or 7500 hm ) and the results are illustrated in part. In contrast, RH indicates increased precipitation in the Fig. 3. A wide range of annual precipitation change is indi- mountainous parts of PRB and decreased precipitation in cated for all RCM–GCM combinations and all periods. The the central plain part. general point of the results illustrated in Fig. 3 is that pre- To identify temporal trends in precipitation variation on cipitation is expected to be significantly decreased, espe- seasonal basis, box-plots of seasonal total precipitation were cially during the period 2041–2060. Climate change signal created for all sub-periods and RCM–GCM combinations, for the period 2021–2040 is not very clear as highly contro- which are presented in Fig. 5. In general, there are some versial estimates are generated; HA indicates a very signifi- clear variation trends identified when the seasonal precipi- cant decrease of precipitation by 166 mm on the median, tation for the period 2021–2100 is compared to the histori- while RAE also indicates annual precipitation decrement cal period, but seasonal precipitation variation within the by 52 mm. REE and RH present annual precipitation incre- four sub-periods appears complex, as there is no continu- ment by 6 and 82 mm on the median, respectively. Accord- ous and stable trend observed for each model. For example, ing to RH results, precipitation is also increased for the according to HA results, median autumn precipitation is pre- period 2041–2060 by 97 mm on the median, while the other sented to be 166 mm for the period 2021–2040, increases RCM–GCM combinations indicate significant decrease to 177  mm during the period 2041–2060, decreases to in precipitation ranging between −  136  mm (RAE) and 166 mm during the period 2061–2080 and finally increases −  116  mm (HA). For HA, RAE and REE precipitations to 183 mm during the period 2081–2100. are further decreased during the period 2061–2080 (− 197 Concerning the autumn season, there is a general trend to − 131 mm), while for RH, precipitation was found to observed which indicates wider seasonal precipitation vari- be increased by 15 mm. Finally, for the period 2081–2100 ation range and subsequently increment in precipitation (2099 for RH) precipitation decreases for all models and extremes, either low or high. The high autumn precipita- the decrement ranges between − 261 and − 68 mm. On the tion extremes are increasing the potential negative impact average, the highest annual precipitation decrease for the on agricultural production for crops such as cotton, which is period 2021–2100 is demonstrated by HA (149 mm or 1647 the dominant crop for PRB and its cultivation period usually 1 3 Standard Deviation (mm/d) 0.0 51 Page 6 of 17 Applied Water Science (2018) 8:51 Fig. 3 Box-plots of total annual precipitation variation according to results from the four RCM–GCM combinations for the periods 2021–2040, 2041–2060, 2061–2080 and 2081–2100 ends between end of October and middle November. RAE all the sub-periods, with the overall strongest decreasing and REE indicate increased autumn precipitation by 20 and trend indicated by HA ranging between 16 mm (sub-period 30 mm, respectively, during the period 2021–2040, signifi- 2041–2060) and 80 mm (sub-period 2061–2080). RH pre- cantly decreased values during the periods 2041–2060 and sents decreased winter precipitation only for the period 2061–2080, and slightly increased precipitation values dur- 2081–2100 and increased winter precipitation for the other ing the period 2081–2100, compared to the corresponding three sub-periods. Similarly to autumn season, there is a precipitation values for the historical period. HA and RH general trend according to which winter precipitation varia- indicate decreased autumn precipitation compared to the tion range is wider compared to the corresponding variation historical period for all the sub-periods, while the highest range of the historical period, thus indicating increment in autumn precipitation decrement is presented by RH for the precipitation extremes, either low or high, for most of the period 2081–2100 and it is equal to 69 mm. examined model combinations and sub-periods. Except from RH, the other three RCM–GCM combina- Concerning spring precipitation variation and similarly to tions indicate a decreasing trend in winter precipitation for autumn precipitation, HA, RAE and REE models indicate 1 3 Applied Water Science (2018) 8:51 Page 7 of 17 51 Fig. 4 Spatial distribution of average annual total pre- cipitation change for the period 2021–2100 for each RCM– GCM combination decreasing trend for all sub-periods, with the overall strong- cumulative frequency diagrams for the four sub-periods and est decreasing trend indicated by HA ranging on the median for each RCM–GCM combination are presented in Fig. 6. between 66 mm (period 2041–2060) and 99 mm (period These diagrams indicate that at least one RCM–GCM com- 2081–2100). For the periods 2021–2040 and 2041–2060, bination indicates maximum monthly precipitation greater spring season precipitation according to RH model is pre- than the corresponding maximum of the historical period sented slightly increased by 6 and 2 mm, respectively, while and, therefore, increment in monthly precipitation extremes for the periods 2061–2080 and 2081–2100 is presented as is presented by most of the RCM–GCM combinations. This decreased by 19 and 10 mm, respectively, compared to the is also proved from the fact that for cumulative frequency spring precipitation of the historical period. In contrast to values > 90%, higher precipitation values are indicated autumn and winter, the variation and inter-quartile range for most RCM–GCM combinations and sub-periods. For presented by the RCM–GCM combinations during the sev- cumulative frequency values < 90%, HA, RAE and REE eral sub-periods are similar to the variation and inter-quartile are presenting lower monthly precipitation for all the sub- range of the historical period. periods, while the strongest decreasing precipitation signal Finally, summer precipitation variation follows the gen- is presented for the sub-period 2081–2100. RH indicates eral trends observed for winter and spring, however, exhib- significantly different variation patterns, as for cumulative iting wider seasonal variation range. Hence, it decreases frequency values < 80% it presents monthly precipitation for all sub-periods and RCM–GCM combinations, except values which are close to or greater than the corresponding from RH. The summer precipitation decrement ranges on values of the historical period. the median between: (a) 21.6 and 48.5 mm for the period 2021–2040, (b) 20.9 and 46.5 mm for the period 2041–2060, Future trends in temperature variation (c) 27.3 and 55.3 mm for the period 2061–2080 and (d) 37.6 and 56.2 for the period 2081–2100. For RH, median value The Taylor diagram compiled by the raw and bias-cor- of summer precipitation is increased compared to that of the rected RCMs temperature data for the period 1981–2000 historical period. Moreover, compared to autumn and winter, is presented in Fig.  7. Points that are found closer to the summer precipitation indicates increased seasonal precipita- “observed” quadrant of standard deviation and demon- tion variation range, while total dry summer periods are also strate higher correlation indicate better representation of demonstrated by the models HA, RAE and REE. observed patterns. With regard to raw RCM temperature In complement to annual and seasonal precipitation vari- data, correlation coefficient ranged between 0.962 (REE) ation, monthly precipitation variation was also assessed. The and 0.972 (RAE), while standard deviation ranged between 1 3 51 Page 8 of 17 Applied Water Science (2018) 8:51 Fig. 5 Box-plots of seasonal total precipitation variation according to results from the four RCM–GCM combinations for the periods 2021– 2040, 2041–2060, 2061–2080 and 2081–2100 7.96 (HA) and 8.53 °C (REE). The corresponding range for standard deviation for all RCMs. After bias-correction, all cRMSD was 2.05 °C (RH) to 2.3 °C (REE). Since correla- RCM performance was found to be similar. tion coefficient values of all RCMs raw temperature data Average annual temperature variation for the four sub- are similar, the best performance is presented by RH since periods is presented in Fig.  8. Despite the fact that all it indicates standard deviation closer to the observed one. RCM–GCM combinations are indicating temperature All RCMs were found to slightly overestimate standard increase during the period 2021–2100, the variation range deviation and, therefore, they indicate higher temperature of temperature increase produced by each RCM–GCM is variation compared to the observed. The bias-correction large. Still, clearer trends are depicted for all tested models procedure improved correlation coefficient since it was combinations, compared to the afore-discussed precipitation found to be increased by more than 0.02 units for all RCMs trends. Depending on the period, the highest temperature (0.983–0.987), while improvement was also observed for increment is indicated by a different model. For the periods 1 3 Applied Water Science (2018) 8:51 Page 9 of 17 51 Fig. 6 Cumulative frequency diagrams of monthly precipitation for the historical period (1981–2000) and all RCM–GCM combinations at the four sub-periods 2021–2040 and 2041–2060, the highest temperature increase temporal change of temperature for each RCM–GCM mod- is indicated by HA, while for the periods 2061–2080 and els combination indicates almost linear temperature incre- 2081–2100 the highest temperature increase is presented by ment for RAE, REE and RH, while for HA, temperature RAE. The lowest temperature increase is demonstrated for increase for the period 2041–2060 is almost equal to the the whole projection period by RH model. For the period temperature increase for the period 2061–2080. 2021–2040, the temperature increase ranges between 0.2 °C Moreover, similarly to temperature variation for most sea- (RH) and 3.3 °C (HA), while the corresponding range for the sons, it is worth mentioning that especially for HA, RAE period 2041–2060 is 1.3 °C (RH) and 3.7 °C (HA). For all and REE the minimum average annual temperature is higher RCMs–GCMs, temperature is projected to further increase than the maximum average annual temperature observed during the period 2061–2080 [2 (RH) to 4 °C (RAE)], while during the historical period, thus indicating significant dif- the highest temperature increase is presented for all models ference in annual temperature variation pattern. Even for RH during the period 2081–2100 (2081–2099 for RH) ranging results which indicate the weakest climate change signal, between 2.6 (RH) and 5.1 °C (RAE). The comparison of the inter-quartile ranges of annual temperature variation for 1 3 51 Page 10 of 17 Applied Water Science (2018) 8:51 Taylor Diagram indicating significant difference in autumn temperature vari- ation pattern. This is also indicated by RAE and REE results, according to which their inter-quartile range does not even partially overlap with the corresponding inter-quartile range of the historical period. Significantly different variation pat- tern is presented by RH results, for which autumn tempera- ture illustrates milder increment ranging between 0.6 (sub- 6 period 2041–2060) and 1.8 °C (sub-period 2081–2100). In terms of winter temperature variation, the overall 5 strongest climate change signal is indicated by RAE model, which illustrates, on the median, temperature increment that ranges between 2.5 (sub-period 2021–2040) and 5.4 °C (sub- period 2081–2100). Significant winter temperature increase is also presented by HA (3.1–4.2 °C) and REE (1.7–4.4 °C). REE-R RAE-R RH-R 2 2 The lowest winter temperature increase is illustrated by RH HA-R RAE-BC REE-BC and ranges between 0.7 (sub-period 2041–2060) and 2.1 °C HA-BC 1 RH-BC (sub-period 2081–2100), while wider temperature varia- Observed tion ranges are demonstrated for all periods. Similarly to 0 1.0 autumn temperature, the inter-quartile variation ranges for 0246 8 Standard Deviaon ( C) the models HA, RAE and REE, and the whole 2010–2100 period does not overlap with the corresponding range of Fig. 7 Taylor diagram of raw (R) and bias-corrected (BC) RCM tem- the historical period, thus indicating significant difference perature data for the period 1981–2000 in winter precipitation patterns. Compared to autumn and winter, spring average temperature indicates lower but sig- the periods 2041–2060, 2061–2080 and 2081–2100 do not nificant increase compared to the historical period. Spring overlap with the corresponding inter-quartile range of the temperature is constantly increasing during the period historical period. 2021–2100 and the corresponding increment ranges for The spatial distribution of average annual temperature the four RCM–GCM combinations are 2.3–3.2 °C (HA), change for the period 2021–2100 for each RCM–GCM com- 1.8–4.4 °C (RAE), 0.3–3.2 °C (REE) and 0.6–2.5 °C (RH). bination is illustrated in Fig. 9, in which significant differ - Considering that PRB is dominated by summer crops, ences are illustrated. HA and RAE present a smooth spatial any changes in summer temperature variation can poten- distribution of temperature gradient, which is higher in the tially affect agricultural production. Among the four seasons, mountainous part of the basin, while REE demonstrates summer presents the strongest climate change signal with a highly contrasting spatial distribution with significantly temperature increment on the median by up to 5.9 °C. More higher temperature gradient in the mountainous part of PRB. specifically, the overall higher temperature increment is pre- In contrast, RH demonstrates lower temperature increase in sented by HA (3.8–5.5 °C) followed by RAE (2.1–5.9 °C) the mountainous part than temperature increase in the plain and REE (1.4–4.9 °C), while the lowest temperature incre- part. ment is presented by RH (0.8–3.4 °C). Similarly to spring, With regards to seasonal average temperature varia- summer temperature is steadily increasing during the period tion, box-plots for the results of all RCM–GCM combina- 2021–2100 for all RCM–GCM combinations, while the tions and the four sub-periods were created and compared significant differences in variation range and inter-quartile to the results of historical period (Fig.  10). Except from ranges indicate the important differences in temperature RH autumn temperature for the period 2021–2040 which variation patterns. is estimated to be decreased compared to the historical Similarly to precipitation, cumulative frequency diagrams period, all the other models demonstrate increased seasonal of average monthly temperature for the four sub-periods and temperature for all periods and all seasons. Concerning for each RCM–GCM combination are presented in Fig. 11. autumn, the overall strongest climate change signal is on Concerning the sub-period 2021–2040, the widest monthly the median presented by HA with temperature increment temperature variation range is presented by RH, according ranging between 3.2 (sub-period 2021–2040) and 4.5 °C to which minimum monthly temperature expected to be (sub-period 2081–2100). Moreover, it is interesting to men- observed during the period 2021–2040 is much lower than tion that according to HA results, minimum median autumn the corresponding temperature observed during the histori- temperature is higher than the maximum median autumn cal period. The other three models demonstrate higher mini- temperature observed during the historical period, thus mum monthly temperatures. The strongest climate change 1 3 Standard Deviation ( C) 0.0 Applied Water Science (2018) 8:51 Page 11 of 17 51 Fig. 8 Box-plots of average annual temperature variation according to results from the four RCM–GCM combinations for the periods 2021– 2040, 2041–2060, 2061–2080 and 2081–2100 signal is presented by HA due to the fact that monthly tem- frequency values < 0.4 during the period 2081–2100 there perature is higher for the whole range of cumulative fre- are noticeable differences between the cumulative frequency quency curve, followed by RAE. The lowest climate change curves, for cumulative frequency values > 0.4 the differ - signal is demonstrated by RH, as the cumulative frequency ences are smoother; hence lower inter-model variability is curve for RH is very close to the corresponding curve of presented for low monthly temperatures compared to high the historical period, except from cumulative frequency val- temperatures. ues > 0.9 for which significantly higher monthly tempera- ture values are indicated by RH compared to the historical period. The cumulative frequency curves for the other three Discussion sub-periods presented in Fig. 11 are shifting steadily to the right, thus indicating further increment in average monthly Clearly, precipitation and temperature are crucial param- temperature compared to the historical period. Moreover, eters in shaping water budget, especially so under climate it is worth noting that despite the fact that for cumulative change conditions in an intensively cultivated basin, such 1 3 51 Page 12 of 17 Applied Water Science (2018) 8:51 Fig. 9 Spatial distribution of average annual temperature change for the period 2021– 2100 for each RCM–GCM combination as PRB. Hence, the presented results of the estimated shift the partial diversion of the Acheloos River, located in cen- in precipitation and temperature patterns are expected to tral–western Greece, into PRB will be able to account for considerably affect future water resource availability and the negative water balance during dry hydrological years. status. PRB has been found to be severely stressed in terms Since RCMs have been found to partially reproduce of its water resources, since the last few decades (Koutsoy- climate pattern in Europe (Jacob et al. 2007; Christensen iannis and Mimikou 1996; Loukas et al. 2007). The major and Christensen 2010) and taking into account the regional responsibility for water resource stress developed in PRB character of our study, we decided to include in our study is the agricultural sector, as irrigation water consumption RCMs that have been proved in the literature to reproduce accounts approximately for 95% of the total water consump- satisfactorily climate patterns in Mediterranean conditions. tion (Koutsoyiannis and Mimikou 1996; Alexandridis et al. The four RCMs selected in the context of the present study 2014). Although there are studies which indicate that the have been found to sufficiently represent precipitation and annual water availability is higher than the corresponding temperature variation in several Mediterranean basins when water needs (Koutsoyiannis and Mimikou 1996), the high compared to observed data (Deidda et al. 2013), while they demand for irrigation water during the summer cultivation are also introducing a significant degree of variation both for period leads to groundwater over-exploitation, as surface precipitation and temperature. water availability during this period is low. Therefore, about Overall, the strongest signal taken from projected climate 80% of irrigation water needs are covered by groundwa- data is precipitation decrease and temperature increase, since ter abstracted mainly from aquifers developed in the plain annual precipitation change for the period 2021–2100 was areas of PRB. The huge number of productive wells in PRB, on the average about − 80 mm (or − 11.7%, 883 hm ), rang- which is estimated to exceed 30,000 (Hellenic Ministry for ing between − 149 (or − 21.8%, 1644 hm ) and + 35 mm (or the Environment, Energy and Climate Change-Special Sec- 5%, 386 hm ), while the corresponding change for tempera- retariat for Water 2014), is indicative of the groundwater ture was 2.81 °C, ranging between 1.48 and 3.72 °C. Despite over-exploitation conditions developed in the basin. Pana- the different periods examined, the aforementioned trends gopoulos et al. (2012) indicate that water-deficient budget are similar to previous studies for PRB and central–east- conditions have already been established in several water ern Greece. Zanis et al. (2009) assessed the projected future systems of the studied basin. According to Loukas et al. precipitation and temperature change (2071–2100) using (2007), some proposed surface water storage projects would the PRUDENCE dataset consisting of nine RCMs and they significantly contribute to the reduction of PRB water deficit estimated for central–eastern Greece an annual precipita- without being able to satisfy total water needs. Not even tion decrease by 15.5% and an average annual temperature 1 3 Applied Water Science (2018) 8:51 Page 13 of 17 51 Fig. 10 Box-plots of seasonal average temperature variation according to results from the four RCM–GCM combinations for the periods 2021– 2040, 2041–2060, 2061–2080 and 2081–2100 increase by 4.0 °C. According to Vasiliades et al. (2009), precipitation variation, while temperature increase was sug- an average annual precipitation reduction of about 3.9 and gested for all scenarios and models. Compared to these stud- 3.4% for period 2020–2050, and of about 13.5 and 8.5% ies, the here presented trends have been evaluated based on for period 2070–2100 for SRES A2 and SRES B2, respec- RCM data, indicating higher resolution than GCMs, which tively, was estimated based on downscaled precipitation was further bias-corrected, thus representing a higher local data from CGCMa2 model. According to Mimikou et al. representativeness. (2000), precipitation decrease and temperature increase were When aggregating precipitation data from the four RCMs indicated by two GCMs used to quantify the effects of cli- for the four future periods and comparing to the period mate change in a sub-basin of PRB (Ali Efenti). Varanou 1981–2000, winter precipitation decrease ranges between et al. (2002) used precipitation and temperature data from 7.2% (period 2041–2060) and 14.0% (period 2081–2100) four GCMs concluding that decreasing trend is dominant in and temperature increase ranges between 2.06 (period 1 3 51 Page 14 of 17 Applied Water Science (2018) 8:51 Fig. 11 Cumulative frequency diagrams of average monthly temperature for the historical period (1981–2000) and all RCM–GCM combinations at the four sub-periods 2021–2040) and 3.80 °C (period 2081–2100). The corre- evapotranspiration not only for non-cultivated areas but also sponding changes for central–eastern Greece presented by for winter crops, and consequently increased water needs. Zanis et al. (2009) based on PRUDENCE dataset consist- Finally, the increased variation and inter-quartile range pre- ing of nine RCMs for winter of period 2071–2100 and A2 sented for most of the future periods and RCMs constitute scenario are − 20.4% for precipitation and 3.70 °C for tem- an indicator of increment in precipitation extremes, either perature. Taking into account that the winter season is the low or high, and therefore increased risk for effective water wettest period for PRB with the lowest evapotranspiration resources management due to increased flooding poten- amounts, it is significantly contributing to the replenishment tial (in case of high extremes) or droughts (in case of low of water consumed during the irrigation period through extremes). groundwater recharge or through the collection of surface The corresponding precipitation decrease for spring runoff in the dams. Moreover, rainfed crops such as wheat, during the period 2021–2100 ranges between 14.6 (period which cover significant parts of PRB, are cultivated dur - 2021–2040) and 36.1% (period 2081–2100), while tem- ing winter. Therefore, the decrement of winter precipitation perature increase ranges between 2.1 (period 2021–2040) and the corresponding increment in potential evapotranspi- and 3.8 °C (period 2081–2100). Similarly to winter, early ration is expected to significantly stress the availability of spring is a period of significant precipitation contribution to water resources during winter in two ways: (a) decrement groundwater recharge and, therefore, precipitation decrement in groundwater recharge and (b) increment in potential is expected to result in groundwater recharge decrement. 1 3 Applied Water Science (2018) 8:51 Page 15 of 17 51 Moreover, spring period is very significant for the devel- from surface water bodies, thus magnifying the water-defi- opment of rainfed winter crops, the cultivation period of cient budget conditions that have already been established which usually ends at early summer and combined to poten- in PRB, as described above. Moreover, as deduced from tial evapotranspiration increase as a result of the increased the presented results, during the wet seasons and especially temperature, the water stress of winter crops is expected to during winter, a high precipitation intensity variability is be increased. Moreover, spring season constitutes the sow- anticipated along with overall decrease in total precipita- ing period for summer crops in PRB. Taking into account tion heights that could potentially lead to: (a) increased flash the elevated water needs indicated by temperature increase, flood events, (b) soil clogging effects, (c) decreased natu- in combination with reduced water availability as a result of ral recharge of groundwater bodies. All three phenomena precipitation decrease, the water stress indicated by summer may trigger extensive soil erosion leading to desertification, crops during the spring period is significant. magnification of existing or triggering of new groundwater Since agricultural activities and especially summer crops depletion conditions (that may eventually lead to mining) are dominating water consumption in PRB, summer precipi- and fresh water reserves pollution. tation is of high importance and the demonstrated decreasing trend ranging between 22.7 (period 2041–2060) and 45.9% (period 2081–2100) reflects the necessity for increased irri - Conclusions and outlook gation to satisfy water demand of the summer crops. Water demand is expected to further increase in response to tem- This study aimed to quantify the temporal and spatial vari- perature increase which ranges between 2.0 and 4.9 °C, as ation in precipitation and temperature in PRB using bias- a result of the increased potential evapotranspiration. The corrected data from four RCMs, driven by different GCMs corresponding changes for central–eastern Greece presented for the emissions scenario A1B and relate this variation to by Zanis et al. (2009) based on PRUDENCE dataset consist- potential impacts in water resources status and availabil- ing of nine RCMs for summer of period 2071–2100 and ity. Results of the study are in agreement with other studies A2 scenario are − 54.2% for precipitation and 5.00 °C for in Mediterranean region that indicate decreasing trend in temperature. It has to be mentioned that crops that are not precipitation and increasing trend in temperature, despite tolerant to the temperature increase will suffer from tempera- the considerable differences in the spatial and temporal dis- ture stress, leading to decreased agricultural production, thus tribution of both parameters. The above-mentioned trends posing another risk except from water resource availability are expected to significantly affect the water availability in reduction. Concerning the autumn season, precipitation data PRB in several ways, including mainly reduction in ground- aggregation from the four RCMs indicates that seasonal pre- water recharge and increase in irrigation demands. Taking cipitation change may vary on average from − 19.0 (period into account that water balance in PRB is deficient already 2061–2080) to 0.4% (period 2021–2040), while correspond- since 1990′s, the water stress signal becomes more intense ing temperature increase ranges between 1.4 and 3.6 °C. Due and climate change adaptation becomes more difficult. to the fact that for the most significant crops cultivated in This fact highlights the necessity of investigating climate PRB, cultivation period extends to autumn, the significant change effects on the local scale to incorporate the specific change in autumn temperature variation can potentially and particular water resource management conditions. It increase water demand during early autumn and affect crop would appear that crop patterns, irrigation methods and growth behavior. overall water management approaches need to be carefully Based on the overall results produced by the examined considered and appropriately adapted to address forthcom- model combinations and taking into account that the refer- ing climate change effects. The expected climate changes ence period (1981–2000) includes a severe drought period effects call for optimal use and sufficient protection of water (Loukas and Vasiliades 2004) which significantly affected resources to endure impacts and ensure adequate volumes the water balance of PRB, the anticipated effects of climate of sufficient quality. change in water resources availability and management The careful data evaluation as shown in this paper is are expected to be severe. The aforementioned trends are indispensable to comprehend climate change impact on expected to lead to an acute water-deficit condition, since water resource availability and spatio-temporal distribu- potential evapotranspiration shall increase (both for winter tion. Application of the presented climate change data shall and summer crops) with parallel decrease of precipitation be used in setting up mGROWA (Herrmann et al. 2015), a share to irrigation, and obviously effective precipitation for hydrologic model of high temporal and spatial resolution to natural groundwater replenishment is expected to further assess the impact of climate change on development of water decrease or even vanish over specific years and/or periods. availability and the inner-annual shift of runoff generation Consequently, water demands will need to be catered for by periods for the entire basin. 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Identifying potential effects of climate change on the development of water resources in Pinios River Basin, Central Greece

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Abstract

The aim of the present study is to assess the future spatial and temporal distribution of precipitation and temperature, and relate the corresponding change to water resources’ quantitative status in Pinios River Basin (PRB), Thessaly, Greece. For this purpose, data from four Regional Climate Models (RCMs) for the periods 2021–2100 driven by several General Circula- tion Models (GCMs) were collected and bias-correction was performed based on linear scaling method. The bias-correction was made based on monthly precipitation and temperature data collected for the period 1981–2000 from 57 meteorological stations in total. The results indicate a general trend according to which precipitation is decreasing whilst temperature is increasing to an extent that varies depending on each particular RCM–GCM output. On the average, annual precipitation change for the period 2021–2100 was about − 80 mm, ranging between − 149 and + 35 mm, while the corresponding change for temperature was 2.81 °C, ranging between 1.48 and 3.72 °C. The investigation of potential impacts to the water resources demonstrates that water availability is expected to be significantly decreased in the already water-stressed PRB. The water stresses identified are related to the potential decreasing trend in groundwater recharge and the increasing trend in irrigation demand, which constitutes the major water consumer in PRB. Keywords Climate change · Water resource regional climate models · Precipitation · Temperature · Pinios River Basin Introduction spring. In terms of precipitation, significant decrease of up to 30% was indicated on an annual basis for the south Medi- Mediterranean has been identified as the most vulner- terranean area, which was presented to be even higher in its able European region in terms of climate change impacts westernmost and easternmost parts. Similar trends are pre- (Schröter et al. 2005; Navarra and Tubiana 2013). According sented by Giorgi and Lionello (2008). Jacobeit et al. (2014) to Giorgi (2006), Mediterranean region constitutes the plan- reviewed a wide number of studies which investigated et’s hot spot in terms of climate change effects. This is justi - projected climate change trends in Mediterranean region fied by the significant temperature increase and precipitation by applying statistical downscaling techniques in model’s decrease with fewer wet days and drier summers as pre- climate data. In terms of temperature, seasonal variation in sented in several studies. More specifically, Dubrovsky et al. future projections indicates the best agreement. With regard (2014) investigated the future trends of precipitation and to precipitation, a decreasing trend can be considered for temperature variation based on the results of 16 GCM runs. autumn, spring and summer values for the whole Mediter- Their results indicate significant increase in temperature for ranean region, while winter precipitation indicates signifi - the period 2070–2099 compared to the period 1961–1990, cant variability and cannot be characterized as increasing which is higher during summer and lower during winter and or decreasing in general. Concerning Greece, the results of the analysis performed in precipitation and temperature data of 22 RCMs by Tolika et al. (2012) indicated an increasing * G. Arampatzis trend in future temperature variation by all models, while in arampgeo@gmail.com terms of precipitation, most of the models, but not all, pre- Soil and Water Resources Institute, Hellenic Agricultural sented decrement in future precipitation amount and wet day Organization-Demeter, 57400 Sindos, Greece occurrence. Precipitation is also presented to be decreased Forschungzentrum Juelich GmbH, Agrosphere Institute by Chenoweth et al. (2011), according to which a decrement (IBG-3), 52425 Juelich, Germany Vol.:(0123456789) 1 3 51 Page 2 of 17 Applied Water Science (2018) 8:51 by 18 and 22% is indicated for precipitation in Greece by the spatio-temporal distribution. Against this background, the midcentury and the end of century, respectively. Moreover, aims of this study are: extreme precipitation events such as frequency and mag- nitude are expected to be increased in Greece, especially • To assess the temporal and spatial future trends in pre- during winter (Tolika et al. 2008). cipitation and temperature variation in the largest fully The above-described changes in precipitation and tem- developed basin in Greece (Pinios River Basin, PRB) perature variation patterns during the twenty-first century and, are expected to significantly affect water resource availabil - • To relate those changes to potential impacts in future ity in Mediterranean region, while there are studies which water resources availability. are indicating that water yields in Mediterranean region have already been decreased, as a consequence of climate change Given the fact that agriculture is the dominant water con- (García-Ruiz et al. 2011; Ludwig et al. 2011). According to sumer in PRB accounting for over 90% of water use (Hel- European Environment Agency (2009), several studies have lenic Ministry for the Environment, Energy and Climate been conducted which aim to assess the potential effects of Change-Special Secretariat for Water, 2014), precipitation climate change in water resources in Mediterranean region and temperature evolution are expected to significantly affect and their common conclusion is that water resource avail- water resource availability in the form of effective precipita- ability is expected to decrease. Milano et al. (2013) inves- tion and crop water demands and indirect availability in the tigated the effects of climate change in water resources in form of groundwater recharge and surface runoff. Mediterranean region and their results indicated that by 2050 a significant decrease in freshwater availability is expected which ranges between 30 and 50%. Local studies of climate change impacts in water resources are also indicating sig- Materials and methods nificant stresses for water resources in Greece. More specifi- cally, Pisinaras (2016) investigated potential climate change Study area description effects in an aquifer located in northeastern Greece and the results indicated a significant decrease in groundwater level, PRB is located in Central Greece and covers an area of about 11,000 km . It is characterized by highly diversified geo- as a result of decreased groundwater recharge and increased groundwater abstractions for irrigation. A significant reduc- logical, hydrological and hydrogeological conditions and marked by the systematic exploitation of water resources tion in future water resource availability was also presented by Koutroulis et al. (2016) for Crete island (south Greece), since early 1960s. From the water administration point of view, PRB belongs to the Thessaly water district (EL08) while significant decrease in surface runoff was suggested for the next 50 years by Kalogeropoulos and Chalkias (2013) and covers the major part of this district (85%). Two climate types are identified in PRB: continental climate conditions for a catchment located in Andros island. Several hydrological modelling studies have already been are dominant at the central and western part of PRB, while typical Mediterranean climate conditions are met at the east- performed in Pinios River Basin to assess the impacts of climate change on water resources, e.g. Mimikou and Baltas ern part. For the period 1981–2000, the minimum average annual precipitation was 392 mm at the southeastern plain (2013), Varanou et al. (2002), indicating decreasing runoff levels and a need to adapt regional water resources manage- part of the basin, while the corresponding maximum value was 1705 mm at the western mountainous part. The aver- ment to climate change. Panagopoulos et al. (2016) applied the grid-based empirical model GROWA to assess the cli- age annual precipitation for the aforementioned period was 700 mm. mate change impact for the forecasting period 2020–2080. Despite the fact that the implemented code provides a spa- The agriculturally used plains covering 45% of PRB belong to the most intensively cultivated and productive tially distributed but temporally averaged result, the fore- casted impact of climate change was pronounced as the agricultural areas of Greece. Accordingly, agriculture con- stitutes the major water consumer for Pinios river basin, availability of renewable water resources, i.e. the mean total runoff, was forecasted to decrease by 22–62%, depending on since about 93% of total water consumption (1292 hm ) is allocated to irrigation followed by domestic water sup- the examined climate change scenario. Taking into account all the above, as well as the neces- ply (5.5%), livestock (1%) and industry (0.5%). According to Loukas (2010), a wide variety of crops are cultivated in sity to develop climate change impact assessment studies on the local scale, to construct sustainable development PRB, including cotton, wheat, alfalfa and maize in the plain area, whereas apple, apricot, cherry, olive trees and grapes plans (Milano et al. 2013), careful evaluation of climate change data sets seems to be indispensable to comprehend are cultivated at the foothills of the eastern mountains. climate change impact on water resources availability and 1 3 Applied Water Science (2018) 8:51 Page 3 of 17 51 Permeable geological formations are dominating in PRB, Mitchell 2009). These regional simulations are driven by since they cover about 44% of the total basin area. Imperme- ERA40 reanalysis data for the control period and by several able geological formations and karstic aquifers cover about GCMs under SRES A1B socio-economic scenario. Among 40 and 16% of the total basin area, respectively. With regard the various models of ENSEMBLES project, data for the to the hydrogeological conditions presented in PRB, the periods 1981–2000 and 2021–2100 were used from the fol- aquifers developed in quaternary depositions are indicating lowing four RCMs: (a) HIRHAM5 (Christensen et al. 2006) significant water abstraction potential followed by karstic driven by ARPEGE GCM (hereafter referred as HA), (b) aquifers found mainly around the plain parts of PRB. Since RACMO2 (van Meijgaard et al. 2008) driven by ECHAM5 about 65% of total water consumption is satisfied by local GCM (hereafter referred as RAE), (c) REMO (Jacob 2001) aquifers, groundwater constitutes a vital water source for driven by ECHAM5 GCM (hereafter referred as REE) and PRB. (d) RCA (Kjellström et al. 2005) driven by HadCM3 GCM In the framework of implementing EU-Water Framework (hereafter referred as RH). These models were found to have Directive (EU-WFD, 2000), 27 groundwater bodies have suc ffi ient performance in representing precipitation and tem - been delineated in PRB, from which 3 display bad qualita- perature in several Mediterranean basins when compared to tive status because of high N O concentrations attributed observed data (Deidda et al. 2013). to agricultural activities. 9 groundwater bodies display bad To improve local climate variability representation on quantitative status, i.e. declining groundwater tables, due to regional and local assessment of climate change effects, over-abstraction of groundwater for satisfying the agricul- further bias-correction in RCM output may be applied. A tural irrigation needs. wide range of bias-correction methods are proposed in the The average long-term annual water discharge of PRB scientific community, out of which the simple methods have comprises 3300 hm . For assessing and documenting the the advantage of altering the RCMs’ results as little as possi- status of surface waters of PRB, 73 river water bodies have ble (Graham et al. 2007). The advantages and disadvantages been identified. As Pinios River surface waters are only used of the most widely applied simple bias-correction methods, locally for feeding irrigation needs, 57 are characterized by namely the delta change and linear scaling, are presented by low river water abstraction, 7 by medium water abstraction Teutschbein and Seibert (2013). Linear scaling was applied and only 9 by high water abstraction. In terms of pollution, for the purposes of this study, which has been previously Pinios river water quality is stressed by the discharge of used in several studies for the assessment of climate change treated and untreated domestic and industrial effluent and impacts at river basin scale (Bosshard et al. 2013; Fiseha agricultural return flows (Loukas 2010). According to the et al. 2014). recently revised water management plan, in terms of nitro- With regard to precipitation, a scaling factor was calcu- gen loads and BOD, inputs from non-point (diffuse) sources lated for each calendar month, RCM and meteorological sta- are dominating (70 and 82% of the total loads, respectively), tion as the ratio between the average observed and average while concerning P, 32% of the total loads are attributed to simulated monthly precipitation for the period 1981–2000. non-point sources. Those scaling factors were subsequently multiplied by monthly precipitation data for the period 2021–2100 Climate data–bias‑correction (2021–2099 for RH) for each calendar month. Monthly temperature was similarly corrected except that addition of Monthly precipitation data were collected from 57 mete- a scaling factor to projected monthly average temperature orological stations located in the wider PRB area covering was used, rather than multiplication. the period 1981–2000 (control period). For 17 of the 57 The ordinary Kriging algorithm was applied to develop meteorological stations, average monthly temperature for the spatial distribution of precipitation and temperature the control period was also available. The location of the data in PRB. The period 2021–2100 was divided into four meteorological stations is illustrated in Fig. 1. sub-periods of 20 years each to assess future trends in pre- Despite the fact that output of GCMs has been widely cipitation temporal variation. The results were analyzed on applied in climate change assessment studies, the complex- monthly, seasonal and annual basis for the four periods and ity of climate characteristics of Greece and its controlling compared to the corresponding precipitation and tempera- factors cannot be adequately represented by GCMs (Tolika ture data of the period 1981–2000, which will be referred to et al. 2012) and, therefore, the application of RCMs which as historical period. are based on finer grid resolutions are thought more appro- To assess RCM performance on representing precipi- priate. Consequently, precipitation and temperature data tation and temperature variation patterns, as well as the were extracted from the ENSEMBLES project, in which performance of bias-correction, Taylor diagrams (Taylor state-of-the-art RCMs were used to produce regional simu- 2001) were compiled, since they provide an efficient graphi- lations at a 25 or 50  km resolution (van der Linden and cal method to present how well simulated patterns match 1 3 51 Page 4 of 17 Applied Water Science (2018) 8:51 Fig. 1 Location map of the study area the observed ones. Taylor diagrams are incorporating cor- higher correlation indicate better representation of observed relation coefficient, centered root mean square difference patterns. With regard to raw RCM precipitation data, corre- (cRMSD) and standard deviation into a single diagram lation coefficient ranged between 0.21 (REE) and 0.37 (RH), and, therefore, they provide a clear overview of similarity while standard deviation ranged between 1.35 (REE) and between simulated and observed data. 2.02 mm/day (HA). The corresponding range for cRMSD was 2.26 mm/day (RH) to 2.53 mm/day (HA). Better per- formance is presented by RH and HA, since the first RCM Results indicates the highest correlation coefficient value and the latter indicates standard deviation closer to the observed one. Future trends in precipitation variation All RCMs were found to underestimate standard deviation and, therefore, they indicate lower precipitation variation The Taylor diagram compiled by raw and bias-corrected compared to the observed. The bias-correction procedure RCM precipitation data for the period 1981–2000 is improved correlation coefficient since it was found to be presented in Fig.  2. Points that are found closer to the increased by more than 0.1 units for all RCMs (0.39–0.5), “observed” quadrant of standard deviation and demonstrate while significant improvement was also observed for 1 3 Applied Water Science (2018) 8:51 Page 5 of 17 51 3 3 Taylor Diagram hm ), followed by RAE (113 mm or 1.250 h m ) and REE (− 91 mm or 1007 hm ), while RH results indicate a small increase in average total annual precipitation for the period 2021–2099 (35 mm or 391 hm ). Increased precipitation for 3 the period 2011–2100 is also indicated by RH for Vosvozis 2.5 REE-BC river basin located in northeastern Greece (Pisinaras et al. 2.5 HA-BC 2014). RAE-BC HA-R 2 When comparing the temporal change of annual pre- RH-BC 2 cipitation for each RCM–GCM model combination, differ - RAE-R ent trends are indicated. HA demonstrates a very signifi- 1.5 1.5 REE-R cant decrease during 2021–2040, which becomes milder RH-R but still significant during 2041–2060. In contrast, RAE demonstrates a very small precipitation decrease during 2021–2040, while for the period 2041–2060 precipitation decrease is much more significant and almost equal to pre- 0.5 cipitation decrease for the period 2061–2080. REE tem- 0.5 poral variation is similar to RAE except from the period Observed 2081–2100, during which precipitation decrease is lower 1.0 when compared to precipitation decrease for the periods 0 0.5 1 1.5 22.5 3 Standard Deviaon (mm/d) 2041–2060 and 2061–2080. The increased precipitation indicated by RH in the present study has been also indi- Fig. 2 Taylor diagram of raw (R) and bias-corrected (BC) RCM pre- cated by Tolika et al. (2012) for precipitation projection with cipitation data for the period 1981–20 RCA-ECHAM4. The spatial distribution change of annual total precipita- standard deviation for all RCMs. RH and RAE RCMs indi- tion for the period 2021-2100 for each RCM–GCM combi- cate better performance after bias-correction application. nation is presented in Fig. 4. Similar trends of precipitation Annual precipitation temporal variation was assessed spatial distribution change are presented for HA, RAE and for the four sub-periods and compared to the median total REE, as higher precipitation decrease is deduced for the annual precipitation of historical period (1981–2000), which mountainous parts of the PRB and especially for its eastern is 682 mm (or 7500 hm ) and the results are illustrated in part. In contrast, RH indicates increased precipitation in the Fig. 3. A wide range of annual precipitation change is indi- mountainous parts of PRB and decreased precipitation in cated for all RCM–GCM combinations and all periods. The the central plain part. general point of the results illustrated in Fig. 3 is that pre- To identify temporal trends in precipitation variation on cipitation is expected to be significantly decreased, espe- seasonal basis, box-plots of seasonal total precipitation were cially during the period 2041–2060. Climate change signal created for all sub-periods and RCM–GCM combinations, for the period 2021–2040 is not very clear as highly contro- which are presented in Fig. 5. In general, there are some versial estimates are generated; HA indicates a very signifi- clear variation trends identified when the seasonal precipi- cant decrease of precipitation by 166 mm on the median, tation for the period 2021–2100 is compared to the histori- while RAE also indicates annual precipitation decrement cal period, but seasonal precipitation variation within the by 52 mm. REE and RH present annual precipitation incre- four sub-periods appears complex, as there is no continu- ment by 6 and 82 mm on the median, respectively. Accord- ous and stable trend observed for each model. For example, ing to RH results, precipitation is also increased for the according to HA results, median autumn precipitation is pre- period 2041–2060 by 97 mm on the median, while the other sented to be 166 mm for the period 2021–2040, increases RCM–GCM combinations indicate significant decrease to 177  mm during the period 2041–2060, decreases to in precipitation ranging between −  136  mm (RAE) and 166 mm during the period 2061–2080 and finally increases −  116  mm (HA). For HA, RAE and REE precipitations to 183 mm during the period 2081–2100. are further decreased during the period 2061–2080 (− 197 Concerning the autumn season, there is a general trend to − 131 mm), while for RH, precipitation was found to observed which indicates wider seasonal precipitation vari- be increased by 15 mm. Finally, for the period 2081–2100 ation range and subsequently increment in precipitation (2099 for RH) precipitation decreases for all models and extremes, either low or high. The high autumn precipita- the decrement ranges between − 261 and − 68 mm. On the tion extremes are increasing the potential negative impact average, the highest annual precipitation decrease for the on agricultural production for crops such as cotton, which is period 2021–2100 is demonstrated by HA (149 mm or 1647 the dominant crop for PRB and its cultivation period usually 1 3 Standard Deviation (mm/d) 0.0 51 Page 6 of 17 Applied Water Science (2018) 8:51 Fig. 3 Box-plots of total annual precipitation variation according to results from the four RCM–GCM combinations for the periods 2021–2040, 2041–2060, 2061–2080 and 2081–2100 ends between end of October and middle November. RAE all the sub-periods, with the overall strongest decreasing and REE indicate increased autumn precipitation by 20 and trend indicated by HA ranging between 16 mm (sub-period 30 mm, respectively, during the period 2021–2040, signifi- 2041–2060) and 80 mm (sub-period 2061–2080). RH pre- cantly decreased values during the periods 2041–2060 and sents decreased winter precipitation only for the period 2061–2080, and slightly increased precipitation values dur- 2081–2100 and increased winter precipitation for the other ing the period 2081–2100, compared to the corresponding three sub-periods. Similarly to autumn season, there is a precipitation values for the historical period. HA and RH general trend according to which winter precipitation varia- indicate decreased autumn precipitation compared to the tion range is wider compared to the corresponding variation historical period for all the sub-periods, while the highest range of the historical period, thus indicating increment in autumn precipitation decrement is presented by RH for the precipitation extremes, either low or high, for most of the period 2081–2100 and it is equal to 69 mm. examined model combinations and sub-periods. Except from RH, the other three RCM–GCM combina- Concerning spring precipitation variation and similarly to tions indicate a decreasing trend in winter precipitation for autumn precipitation, HA, RAE and REE models indicate 1 3 Applied Water Science (2018) 8:51 Page 7 of 17 51 Fig. 4 Spatial distribution of average annual total pre- cipitation change for the period 2021–2100 for each RCM– GCM combination decreasing trend for all sub-periods, with the overall strong- cumulative frequency diagrams for the four sub-periods and est decreasing trend indicated by HA ranging on the median for each RCM–GCM combination are presented in Fig. 6. between 66 mm (period 2041–2060) and 99 mm (period These diagrams indicate that at least one RCM–GCM com- 2081–2100). For the periods 2021–2040 and 2041–2060, bination indicates maximum monthly precipitation greater spring season precipitation according to RH model is pre- than the corresponding maximum of the historical period sented slightly increased by 6 and 2 mm, respectively, while and, therefore, increment in monthly precipitation extremes for the periods 2061–2080 and 2081–2100 is presented as is presented by most of the RCM–GCM combinations. This decreased by 19 and 10 mm, respectively, compared to the is also proved from the fact that for cumulative frequency spring precipitation of the historical period. In contrast to values > 90%, higher precipitation values are indicated autumn and winter, the variation and inter-quartile range for most RCM–GCM combinations and sub-periods. For presented by the RCM–GCM combinations during the sev- cumulative frequency values < 90%, HA, RAE and REE eral sub-periods are similar to the variation and inter-quartile are presenting lower monthly precipitation for all the sub- range of the historical period. periods, while the strongest decreasing precipitation signal Finally, summer precipitation variation follows the gen- is presented for the sub-period 2081–2100. RH indicates eral trends observed for winter and spring, however, exhib- significantly different variation patterns, as for cumulative iting wider seasonal variation range. Hence, it decreases frequency values < 80% it presents monthly precipitation for all sub-periods and RCM–GCM combinations, except values which are close to or greater than the corresponding from RH. The summer precipitation decrement ranges on values of the historical period. the median between: (a) 21.6 and 48.5 mm for the period 2021–2040, (b) 20.9 and 46.5 mm for the period 2041–2060, Future trends in temperature variation (c) 27.3 and 55.3 mm for the period 2061–2080 and (d) 37.6 and 56.2 for the period 2081–2100. For RH, median value The Taylor diagram compiled by the raw and bias-cor- of summer precipitation is increased compared to that of the rected RCMs temperature data for the period 1981–2000 historical period. Moreover, compared to autumn and winter, is presented in Fig.  7. Points that are found closer to the summer precipitation indicates increased seasonal precipita- “observed” quadrant of standard deviation and demon- tion variation range, while total dry summer periods are also strate higher correlation indicate better representation of demonstrated by the models HA, RAE and REE. observed patterns. With regard to raw RCM temperature In complement to annual and seasonal precipitation vari- data, correlation coefficient ranged between 0.962 (REE) ation, monthly precipitation variation was also assessed. The and 0.972 (RAE), while standard deviation ranged between 1 3 51 Page 8 of 17 Applied Water Science (2018) 8:51 Fig. 5 Box-plots of seasonal total precipitation variation according to results from the four RCM–GCM combinations for the periods 2021– 2040, 2041–2060, 2061–2080 and 2081–2100 7.96 (HA) and 8.53 °C (REE). The corresponding range for standard deviation for all RCMs. After bias-correction, all cRMSD was 2.05 °C (RH) to 2.3 °C (REE). Since correla- RCM performance was found to be similar. tion coefficient values of all RCMs raw temperature data Average annual temperature variation for the four sub- are similar, the best performance is presented by RH since periods is presented in Fig.  8. Despite the fact that all it indicates standard deviation closer to the observed one. RCM–GCM combinations are indicating temperature All RCMs were found to slightly overestimate standard increase during the period 2021–2100, the variation range deviation and, therefore, they indicate higher temperature of temperature increase produced by each RCM–GCM is variation compared to the observed. The bias-correction large. Still, clearer trends are depicted for all tested models procedure improved correlation coefficient since it was combinations, compared to the afore-discussed precipitation found to be increased by more than 0.02 units for all RCMs trends. Depending on the period, the highest temperature (0.983–0.987), while improvement was also observed for increment is indicated by a different model. For the periods 1 3 Applied Water Science (2018) 8:51 Page 9 of 17 51 Fig. 6 Cumulative frequency diagrams of monthly precipitation for the historical period (1981–2000) and all RCM–GCM combinations at the four sub-periods 2021–2040 and 2041–2060, the highest temperature increase temporal change of temperature for each RCM–GCM mod- is indicated by HA, while for the periods 2061–2080 and els combination indicates almost linear temperature incre- 2081–2100 the highest temperature increase is presented by ment for RAE, REE and RH, while for HA, temperature RAE. The lowest temperature increase is demonstrated for increase for the period 2041–2060 is almost equal to the the whole projection period by RH model. For the period temperature increase for the period 2061–2080. 2021–2040, the temperature increase ranges between 0.2 °C Moreover, similarly to temperature variation for most sea- (RH) and 3.3 °C (HA), while the corresponding range for the sons, it is worth mentioning that especially for HA, RAE period 2041–2060 is 1.3 °C (RH) and 3.7 °C (HA). For all and REE the minimum average annual temperature is higher RCMs–GCMs, temperature is projected to further increase than the maximum average annual temperature observed during the period 2061–2080 [2 (RH) to 4 °C (RAE)], while during the historical period, thus indicating significant dif- the highest temperature increase is presented for all models ference in annual temperature variation pattern. Even for RH during the period 2081–2100 (2081–2099 for RH) ranging results which indicate the weakest climate change signal, between 2.6 (RH) and 5.1 °C (RAE). The comparison of the inter-quartile ranges of annual temperature variation for 1 3 51 Page 10 of 17 Applied Water Science (2018) 8:51 Taylor Diagram indicating significant difference in autumn temperature vari- ation pattern. This is also indicated by RAE and REE results, according to which their inter-quartile range does not even partially overlap with the corresponding inter-quartile range of the historical period. Significantly different variation pat- tern is presented by RH results, for which autumn tempera- ture illustrates milder increment ranging between 0.6 (sub- 6 period 2041–2060) and 1.8 °C (sub-period 2081–2100). In terms of winter temperature variation, the overall 5 strongest climate change signal is indicated by RAE model, which illustrates, on the median, temperature increment that ranges between 2.5 (sub-period 2021–2040) and 5.4 °C (sub- period 2081–2100). Significant winter temperature increase is also presented by HA (3.1–4.2 °C) and REE (1.7–4.4 °C). REE-R RAE-R RH-R 2 2 The lowest winter temperature increase is illustrated by RH HA-R RAE-BC REE-BC and ranges between 0.7 (sub-period 2041–2060) and 2.1 °C HA-BC 1 RH-BC (sub-period 2081–2100), while wider temperature varia- Observed tion ranges are demonstrated for all periods. Similarly to 0 1.0 autumn temperature, the inter-quartile variation ranges for 0246 8 Standard Deviaon ( C) the models HA, RAE and REE, and the whole 2010–2100 period does not overlap with the corresponding range of Fig. 7 Taylor diagram of raw (R) and bias-corrected (BC) RCM tem- the historical period, thus indicating significant difference perature data for the period 1981–2000 in winter precipitation patterns. Compared to autumn and winter, spring average temperature indicates lower but sig- the periods 2041–2060, 2061–2080 and 2081–2100 do not nificant increase compared to the historical period. Spring overlap with the corresponding inter-quartile range of the temperature is constantly increasing during the period historical period. 2021–2100 and the corresponding increment ranges for The spatial distribution of average annual temperature the four RCM–GCM combinations are 2.3–3.2 °C (HA), change for the period 2021–2100 for each RCM–GCM com- 1.8–4.4 °C (RAE), 0.3–3.2 °C (REE) and 0.6–2.5 °C (RH). bination is illustrated in Fig. 9, in which significant differ - Considering that PRB is dominated by summer crops, ences are illustrated. HA and RAE present a smooth spatial any changes in summer temperature variation can poten- distribution of temperature gradient, which is higher in the tially affect agricultural production. Among the four seasons, mountainous part of the basin, while REE demonstrates summer presents the strongest climate change signal with a highly contrasting spatial distribution with significantly temperature increment on the median by up to 5.9 °C. More higher temperature gradient in the mountainous part of PRB. specifically, the overall higher temperature increment is pre- In contrast, RH demonstrates lower temperature increase in sented by HA (3.8–5.5 °C) followed by RAE (2.1–5.9 °C) the mountainous part than temperature increase in the plain and REE (1.4–4.9 °C), while the lowest temperature incre- part. ment is presented by RH (0.8–3.4 °C). Similarly to spring, With regards to seasonal average temperature varia- summer temperature is steadily increasing during the period tion, box-plots for the results of all RCM–GCM combina- 2021–2100 for all RCM–GCM combinations, while the tions and the four sub-periods were created and compared significant differences in variation range and inter-quartile to the results of historical period (Fig.  10). Except from ranges indicate the important differences in temperature RH autumn temperature for the period 2021–2040 which variation patterns. is estimated to be decreased compared to the historical Similarly to precipitation, cumulative frequency diagrams period, all the other models demonstrate increased seasonal of average monthly temperature for the four sub-periods and temperature for all periods and all seasons. Concerning for each RCM–GCM combination are presented in Fig. 11. autumn, the overall strongest climate change signal is on Concerning the sub-period 2021–2040, the widest monthly the median presented by HA with temperature increment temperature variation range is presented by RH, according ranging between 3.2 (sub-period 2021–2040) and 4.5 °C to which minimum monthly temperature expected to be (sub-period 2081–2100). Moreover, it is interesting to men- observed during the period 2021–2040 is much lower than tion that according to HA results, minimum median autumn the corresponding temperature observed during the histori- temperature is higher than the maximum median autumn cal period. The other three models demonstrate higher mini- temperature observed during the historical period, thus mum monthly temperatures. The strongest climate change 1 3 Standard Deviation ( C) 0.0 Applied Water Science (2018) 8:51 Page 11 of 17 51 Fig. 8 Box-plots of average annual temperature variation according to results from the four RCM–GCM combinations for the periods 2021– 2040, 2041–2060, 2061–2080 and 2081–2100 signal is presented by HA due to the fact that monthly tem- frequency values < 0.4 during the period 2081–2100 there perature is higher for the whole range of cumulative fre- are noticeable differences between the cumulative frequency quency curve, followed by RAE. The lowest climate change curves, for cumulative frequency values > 0.4 the differ - signal is demonstrated by RH, as the cumulative frequency ences are smoother; hence lower inter-model variability is curve for RH is very close to the corresponding curve of presented for low monthly temperatures compared to high the historical period, except from cumulative frequency val- temperatures. ues > 0.9 for which significantly higher monthly tempera- ture values are indicated by RH compared to the historical period. The cumulative frequency curves for the other three Discussion sub-periods presented in Fig. 11 are shifting steadily to the right, thus indicating further increment in average monthly Clearly, precipitation and temperature are crucial param- temperature compared to the historical period. Moreover, eters in shaping water budget, especially so under climate it is worth noting that despite the fact that for cumulative change conditions in an intensively cultivated basin, such 1 3 51 Page 12 of 17 Applied Water Science (2018) 8:51 Fig. 9 Spatial distribution of average annual temperature change for the period 2021– 2100 for each RCM–GCM combination as PRB. Hence, the presented results of the estimated shift the partial diversion of the Acheloos River, located in cen- in precipitation and temperature patterns are expected to tral–western Greece, into PRB will be able to account for considerably affect future water resource availability and the negative water balance during dry hydrological years. status. PRB has been found to be severely stressed in terms Since RCMs have been found to partially reproduce of its water resources, since the last few decades (Koutsoy- climate pattern in Europe (Jacob et al. 2007; Christensen iannis and Mimikou 1996; Loukas et al. 2007). The major and Christensen 2010) and taking into account the regional responsibility for water resource stress developed in PRB character of our study, we decided to include in our study is the agricultural sector, as irrigation water consumption RCMs that have been proved in the literature to reproduce accounts approximately for 95% of the total water consump- satisfactorily climate patterns in Mediterranean conditions. tion (Koutsoyiannis and Mimikou 1996; Alexandridis et al. The four RCMs selected in the context of the present study 2014). Although there are studies which indicate that the have been found to sufficiently represent precipitation and annual water availability is higher than the corresponding temperature variation in several Mediterranean basins when water needs (Koutsoyiannis and Mimikou 1996), the high compared to observed data (Deidda et al. 2013), while they demand for irrigation water during the summer cultivation are also introducing a significant degree of variation both for period leads to groundwater over-exploitation, as surface precipitation and temperature. water availability during this period is low. Therefore, about Overall, the strongest signal taken from projected climate 80% of irrigation water needs are covered by groundwa- data is precipitation decrease and temperature increase, since ter abstracted mainly from aquifers developed in the plain annual precipitation change for the period 2021–2100 was areas of PRB. The huge number of productive wells in PRB, on the average about − 80 mm (or − 11.7%, 883 hm ), rang- which is estimated to exceed 30,000 (Hellenic Ministry for ing between − 149 (or − 21.8%, 1644 hm ) and + 35 mm (or the Environment, Energy and Climate Change-Special Sec- 5%, 386 hm ), while the corresponding change for tempera- retariat for Water 2014), is indicative of the groundwater ture was 2.81 °C, ranging between 1.48 and 3.72 °C. Despite over-exploitation conditions developed in the basin. Pana- the different periods examined, the aforementioned trends gopoulos et al. (2012) indicate that water-deficient budget are similar to previous studies for PRB and central–east- conditions have already been established in several water ern Greece. Zanis et al. (2009) assessed the projected future systems of the studied basin. According to Loukas et al. precipitation and temperature change (2071–2100) using (2007), some proposed surface water storage projects would the PRUDENCE dataset consisting of nine RCMs and they significantly contribute to the reduction of PRB water deficit estimated for central–eastern Greece an annual precipita- without being able to satisfy total water needs. Not even tion decrease by 15.5% and an average annual temperature 1 3 Applied Water Science (2018) 8:51 Page 13 of 17 51 Fig. 10 Box-plots of seasonal average temperature variation according to results from the four RCM–GCM combinations for the periods 2021– 2040, 2041–2060, 2061–2080 and 2081–2100 increase by 4.0 °C. According to Vasiliades et al. (2009), precipitation variation, while temperature increase was sug- an average annual precipitation reduction of about 3.9 and gested for all scenarios and models. Compared to these stud- 3.4% for period 2020–2050, and of about 13.5 and 8.5% ies, the here presented trends have been evaluated based on for period 2070–2100 for SRES A2 and SRES B2, respec- RCM data, indicating higher resolution than GCMs, which tively, was estimated based on downscaled precipitation was further bias-corrected, thus representing a higher local data from CGCMa2 model. According to Mimikou et al. representativeness. (2000), precipitation decrease and temperature increase were When aggregating precipitation data from the four RCMs indicated by two GCMs used to quantify the effects of cli- for the four future periods and comparing to the period mate change in a sub-basin of PRB (Ali Efenti). Varanou 1981–2000, winter precipitation decrease ranges between et al. (2002) used precipitation and temperature data from 7.2% (period 2041–2060) and 14.0% (period 2081–2100) four GCMs concluding that decreasing trend is dominant in and temperature increase ranges between 2.06 (period 1 3 51 Page 14 of 17 Applied Water Science (2018) 8:51 Fig. 11 Cumulative frequency diagrams of average monthly temperature for the historical period (1981–2000) and all RCM–GCM combinations at the four sub-periods 2021–2040) and 3.80 °C (period 2081–2100). The corre- evapotranspiration not only for non-cultivated areas but also sponding changes for central–eastern Greece presented by for winter crops, and consequently increased water needs. Zanis et al. (2009) based on PRUDENCE dataset consist- Finally, the increased variation and inter-quartile range pre- ing of nine RCMs for winter of period 2071–2100 and A2 sented for most of the future periods and RCMs constitute scenario are − 20.4% for precipitation and 3.70 °C for tem- an indicator of increment in precipitation extremes, either perature. Taking into account that the winter season is the low or high, and therefore increased risk for effective water wettest period for PRB with the lowest evapotranspiration resources management due to increased flooding poten- amounts, it is significantly contributing to the replenishment tial (in case of high extremes) or droughts (in case of low of water consumed during the irrigation period through extremes). groundwater recharge or through the collection of surface The corresponding precipitation decrease for spring runoff in the dams. Moreover, rainfed crops such as wheat, during the period 2021–2100 ranges between 14.6 (period which cover significant parts of PRB, are cultivated dur - 2021–2040) and 36.1% (period 2081–2100), while tem- ing winter. Therefore, the decrement of winter precipitation perature increase ranges between 2.1 (period 2021–2040) and the corresponding increment in potential evapotranspi- and 3.8 °C (period 2081–2100). Similarly to winter, early ration is expected to significantly stress the availability of spring is a period of significant precipitation contribution to water resources during winter in two ways: (a) decrement groundwater recharge and, therefore, precipitation decrement in groundwater recharge and (b) increment in potential is expected to result in groundwater recharge decrement. 1 3 Applied Water Science (2018) 8:51 Page 15 of 17 51 Moreover, spring period is very significant for the devel- from surface water bodies, thus magnifying the water-defi- opment of rainfed winter crops, the cultivation period of cient budget conditions that have already been established which usually ends at early summer and combined to poten- in PRB, as described above. Moreover, as deduced from tial evapotranspiration increase as a result of the increased the presented results, during the wet seasons and especially temperature, the water stress of winter crops is expected to during winter, a high precipitation intensity variability is be increased. Moreover, spring season constitutes the sow- anticipated along with overall decrease in total precipita- ing period for summer crops in PRB. Taking into account tion heights that could potentially lead to: (a) increased flash the elevated water needs indicated by temperature increase, flood events, (b) soil clogging effects, (c) decreased natu- in combination with reduced water availability as a result of ral recharge of groundwater bodies. All three phenomena precipitation decrease, the water stress indicated by summer may trigger extensive soil erosion leading to desertification, crops during the spring period is significant. magnification of existing or triggering of new groundwater Since agricultural activities and especially summer crops depletion conditions (that may eventually lead to mining) are dominating water consumption in PRB, summer precipi- and fresh water reserves pollution. tation is of high importance and the demonstrated decreasing trend ranging between 22.7 (period 2041–2060) and 45.9% (period 2081–2100) reflects the necessity for increased irri - Conclusions and outlook gation to satisfy water demand of the summer crops. Water demand is expected to further increase in response to tem- This study aimed to quantify the temporal and spatial vari- perature increase which ranges between 2.0 and 4.9 °C, as ation in precipitation and temperature in PRB using bias- a result of the increased potential evapotranspiration. The corrected data from four RCMs, driven by different GCMs corresponding changes for central–eastern Greece presented for the emissions scenario A1B and relate this variation to by Zanis et al. (2009) based on PRUDENCE dataset consist- potential impacts in water resources status and availabil- ing of nine RCMs for summer of period 2071–2100 and ity. Results of the study are in agreement with other studies A2 scenario are − 54.2% for precipitation and 5.00 °C for in Mediterranean region that indicate decreasing trend in temperature. It has to be mentioned that crops that are not precipitation and increasing trend in temperature, despite tolerant to the temperature increase will suffer from tempera- the considerable differences in the spatial and temporal dis- ture stress, leading to decreased agricultural production, thus tribution of both parameters. The above-mentioned trends posing another risk except from water resource availability are expected to significantly affect the water availability in reduction. Concerning the autumn season, precipitation data PRB in several ways, including mainly reduction in ground- aggregation from the four RCMs indicates that seasonal pre- water recharge and increase in irrigation demands. Taking cipitation change may vary on average from − 19.0 (period into account that water balance in PRB is deficient already 2061–2080) to 0.4% (period 2021–2040), while correspond- since 1990′s, the water stress signal becomes more intense ing temperature increase ranges between 1.4 and 3.6 °C. Due and climate change adaptation becomes more difficult. to the fact that for the most significant crops cultivated in This fact highlights the necessity of investigating climate PRB, cultivation period extends to autumn, the significant change effects on the local scale to incorporate the specific change in autumn temperature variation can potentially and particular water resource management conditions. It increase water demand during early autumn and affect crop would appear that crop patterns, irrigation methods and growth behavior. overall water management approaches need to be carefully Based on the overall results produced by the examined considered and appropriately adapted to address forthcom- model combinations and taking into account that the refer- ing climate change effects. The expected climate changes ence period (1981–2000) includes a severe drought period effects call for optimal use and sufficient protection of water (Loukas and Vasiliades 2004) which significantly affected resources to endure impacts and ensure adequate volumes the water balance of PRB, the anticipated effects of climate of sufficient quality. change in water resources availability and management The careful data evaluation as shown in this paper is are expected to be severe. The aforementioned trends are indispensable to comprehend climate change impact on expected to lead to an acute water-deficit condition, since water resource availability and spatio-temporal distribu- potential evapotranspiration shall increase (both for winter tion. Application of the presented climate change data shall and summer crops) with parallel decrease of precipitation be used in setting up mGROWA (Herrmann et al. 2015), a share to irrigation, and obviously effective precipitation for hydrologic model of high temporal and spatial resolution to natural groundwater replenishment is expected to further assess the impact of climate change on development of water decrease or even vanish over specific years and/or periods. availability and the inner-annual shift of runoff generation Consequently, water demands will need to be catered for by periods for the entire basin. The results of such a model are either groundwater abstractions and/or further abstractions deemed essential in developing an applicable and realistic 1 3 51 Page 16 of 17 Applied Water Science (2018) 8:51 Graham LP, Andréasson J, Carlsson B (2007) Assessing climate change strategic management tool for water resources in the sensi- impacts on hydrology from an ensemble of regional climate mod- tive and complex environment of the Pinios River Basin. els, model scales and linking methods—a case study on the Lule River basin. Clim Change 81(S1):293–307 Acknowledgements The authors thank and gratefully acknowledge Hellenic Ministry for the Environment, Energy and Climate Change- the ENSEMBLES project, funded by the European Commission’s 6th Special Secretariat for Water (2014) Compilation of management Framework Programme through contract GOCE-CT-2003-505539 for plan for the river basins of Thessaly water district (GR08)-man- providing RCM climate data. 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Applied Water ScienceSpringer Journals

Published: Mar 16, 2018

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