A critical review of water resources in Greece: The key role of agricultural adaptation to climate-water effects

Coupling SWAT and DPSIR models for groundwater management in Mediterranean catchments

Groundwater is an essential natural resource and has a significant role in human and environmental health as well as in the economy. Management of subsurface storage remains an important option to meet the combined demands of humans and ecosystems. The increasing need to find multi-purpose solutions to address water scarcity is a global challenge. Thus, the interactions leading to surface runoff and groundwater recharge have received particular attention over the last decades. Additionally, new methods are developed to incorporate the spatial-temporal variation of recharge in groundwater modeling. In this study, groundwater recharge was spatiotemporally quantified using the Soil and Water Assessment Tool (SWAT) in the Upper Volturno-Calore hydrological basin in Italy and the results were compared with other two basins in Greece (Anthemountas and Mouriki). SWAT model was applied in actual and future projections (2022-2040) using the Representative Concentration Pathway (RCP) 4.5 emissions scenario to evaluate changes in precipitation and assess the future hydrologic conditions, along with, the Driving Force-Pressure-State-Impact-Response (DPSIR) framework that was applied in all the basins as a low-cost analysis of integrated physical, social, natural, and economic factors. According to the results, no significant variations in runoff are predicted in the Upper Volturno-Calore basin for the period 2020-2040 while the potential evapotranspiration percentage varies from 50.1% to 74.3% and infiltration around 5%. The limited primary data constitutes the main pressure in all sites and exaggerates the uncertainty of future projections.

Coastal Water Quality Modelling Using E. coli, Meteorological Parameters and Machine Learning Algorithms

In this study, machine learning models were implemented to predict the classification of coastal waters in the region of Eastern Macedonia and Thrace (EMT) concerning Escherichia coli (E. coli) concentration and weather variables in the framework of the Directive 2006/7/EC. Six sampling stations of EMT, located on beaches of the regional units of Kavala, Xanthi, Rhodopi, Evros, Thasos and Samothraki, were selected. All 1039 samples were collected from May to September within a 14-year follow-up period (2009-2021). The weather parameters were acquired from nearby meteorological stations. The samples were analysed according to the ISO 9308-1 for the detection and the enumeration of E. coli. The vast majority of the samples fall into category 1 (Excellent), which is a mark of the high quality of the coastal waters of EMT. The experimental results disclose, additionally, that two-class classifiers, namely Decision Forest, Decision Jungle and Boosted Decision Tree, achieved high Accuracy scores over 99%. In addition, comparing our performance metrics with those of other researchers, diversity is observed in using algorithms for water quality prediction, with algorithms such as Decision Tree, Artificial Neural Networks and Bayesian Belief Networks demonstrating satisfactory results. Machine learning approaches can provide critical information about the dynamic of E. coli contamination and, concurrently, consider the meteorological parameters for coastal waters classification.

Prediction of monthly precipitation using various artificial models and comparison with mathematical models

Precipitation (PP) prediction is an interesting topic in the meteorology or hydrology field since it is directly related to agriculture, the management of water resources in hydrologic basins, and water scarcity. Selecting the right model to predict precipitation has always been a challenge because it could help researchers to use the proper model for their purposes. Accordingly, the performance of five artificial models (feed-forward neural network, cascade forward neural network, Elman neural network, multi-layer perceptron neural network, and radial basis neural network) and three mathematical models (Poisson regression model (PRM), quadratic model, and multiple linear regression) were evaluated for their ability to predict the monthly precipitation in Mediterranean coastal cities located in Eastern part of Mediterranean Sea for the first time. Twenty-seven Mediterranean coastal cities are considered case studies. For this aim, scenario 1 and scenario 2 with various input variables are proposed. Scenario 1 is developed using the number of months (MN), maximum temperature (Tmax), minimum temperature (Tmin), downward radiation (DR), wind speed (WS), vapor pressure (VP), and actual evapotranspiration (AE). Scenario 2 is developed by adding geographical coordinates (latitude, longitude, and altitude) to the global meteorological data to see the impact of geographical coordinates on the accuracy of the prediction of monthly precipitation. This study utilized the monthly data, which were obtained from TerraClimate for the period from 2010 to 2021. Based on the performance indexes, the PRM model performed best for the prediction of monthly precipitation in all selected locations compared to other models. Moreover, the results indicate that scenario 2 ([Formula: see text]) has shown higher prediction accuracy compared to scenario 1 ([Formula: see text]). In conclusion, PRM with the combination of [[Formula: see text]] had RMSE value that was lower by 12% relative to PRM with the combination of [[Formula: see text]]. Consequently, the PRM model can be recommended for modeling the complexity of interactions for precipitation-climate conditions-geographical coordinates and predicting precipitation.

New Approach to Modelling the Impact of Heavy Metals on the European Union's Water Resources

The present research aims to address the highly topical issue of heavy metal water pollution from an integrated European perspective, i.e., to quantify through modelling a general model of water pollution reduction in the EU. The objectives of the study are mainly aimed at identifying effective solutions to reduce heavy metal water pollution and providing supranational decision-makers with public policy directions in the field. The research methods consist of the foundation of working hypotheses based on the study of the literature, the consolidation of official statistical databases in the field, econometric modelling and the conceptualisation of a general model and its testing and validation by statistical methods. The results of the analysis consist of the following marginal contributions: the identification of a general model for combating heavy metal pollution; the calculation of the degree of contribution of regional policies to the general model; and the identification of effective solutions to improve the combating of heavy metal water pollution in Europe. The main conclusion of the analysis shows that significant progress has been achieved at the EU level in the field of combating heavy metal water pollution. However, the level of disparity and poor policy coordination are real vulnerabilities for the EU.

A web-based GIS platform supporting innovative irrigation management techniques at farm-scale for the Mediterranean island of Crete

The aim of this paper is the creation of an integrated and free-access web platform for parcel irrigation water management on a large spatial scale (Water District of Crete, in Greece) in order to: a) accurately determine the irrigation needs of the main crops for Crete such as olives, citrus, avocados and vineyards, b) design strategies, for optimal adaptation of the agricultural sector in the context of climate change, and c) incorporate the dynamic integration of the above information through the creation of a digital platform. In the proposed decision-making system, essential factors are taken into account, such as real-time meteorological data, information about the type and spatial distribution of the agricultural parcels in Crete, algorithms for calculation crop evapotranspiration per development stage and age of the crops, satellite remote sensing techniques in combination with field surveys to depict accurate soil texture map for the whole island of Crete as well as sustainable cultivation practices for saving water per crop and parcel geomorphology. Based on the proposed decision-making system, users will have the opportunity in any specific location/farm in Crete to know the irrigation needs of the crops in real-time and obtain information about proper climate-water adaptation practices. The main novelty points of the proposed platform include the derivation of parcel-level soil texture data from Sentinel-2 satellite imagery and field samples, the comprehensiveness of the irrigation management information, the relatively low data requirements and the application interface simplicity provided to the end-user.

Study of the Interaction between Yellow River Water and Groundwater in Henan Province, China

Determining the interaction between surface water and groundwater is crucial for the protection of groundwater resources. Based on the data of natural geography, geological and hydrogeological conditions, environmental isotopes, and groundwater hydrochemical components, we investigated the interaction between Yellow River water and groundwater in Henan Province, China. The recharge range and interaction amount of the groundwater aquifer from the Yellow River lateral seepage were also analysed, and the influence of the lateral seepage of the Yellow River on groundwater hydrochemical type was studied. The results showed that, firstly the transverse seepage range of the north bank of the Yellow River was larger (approximately 20 km) than that of the south bank (approximately 10 km). The main groundwater recharge sources were atmospheric precipitation and the Yellow River, of which the latter accounted for 50.1%. Secondly, in Sections 1–4, the lateral seepage amounts in the north bank were 1476.94, 505.89, 40.88, and 65.7 m3/a·m, respectively. The single-width permeability of typical Section 2 was larger upstream than downstream and larger in the north than in the south. Thirdly, the lateral seepage of the Yellow River significantly influenced the hydrochemical types of groundwater. From upstream to downstream and from proximal to distal location from the Yellow River, the hydrochemical types changed from single to complex and the salinity increased gradually. Fourthly, the annual average lateral seepage groundwater recharge quantity of the Yellow River was 25,114.36 × 104 m3/a between 2001–2019.

An Estimation of the Discharge Exponent of a Drip Irrigation Emitter by Response Surface Methodology and Machine Learning

The discharge exponent is a general index used to evaluate the hydraulic performance of emitters, which is affected by emitters’ structural parameters. Accurately estimating the effect of change in structural parameters on the discharge exponent is critical for the design and optimization of emitters. In this research, the response surface methodology (RSM) and two machine learning models, the artificial neural network (ANN) and support vector regression (SVR), are used to predict the discharge exponent of tooth-shaped labyrinth channel emitters. The input parameters consist of the number of channel units (N), channel depth (D), tooth angle (α), tooth height (H) and channel width (W). The applied models are assessed through the coefficient of determination (R2), root-mean-square error (RMSE) and mean absolute error (MAE). The analysis of variance shows that tooth height had the greatest effect on the discharge exponent. Statistical criteria indicate that among the three models, the SVR model has the highest prediction accuracy and the best robustness with an average R2 of 0.9696, an average RMSE of 0.0037 and an average MAE of 0.0031. The SVR model can quickly and accurately simulate the discharge exponent of emitters, which is conducive to the rapid design of the emitter.

Assessing Lake Response to Extreme Climate Change Using the Coupled MIKE SHE/MIKE 11 Model: Case Study of Lake Zazari in Greece

Lakes, either artificial or natural, are greatly important as a component in their catchments’ hydrology, but also as ecosystem service providers. However, due to climate change, they have begun to face numerous problems with their water quality and quantity. Furthermore, general circulation models (GCMs) show future climate change with a reduction in rainfall and increase in temperature. The aim of the current study is to present an application where GCMs and state-of-the-art hydrological modelling system MIKE SHE/MIKE 11 are combined for assessing the response of a Greek lake in terms of its water balance and water level under climate change. Four general circulation models (GCMs; GFDL-CM3, MIROC-ESM-CHEM, MIROC-ESM, IPSL-CM5A-LR) for the extreme climate change scenario of RCP8.5 were used in the basin of Lake Zazari in Greece as a case study. Results showed that, by keeping the irrigated demands (the main water user) unchanged in the future, the lake exhibited a lower water level for all GCMs, fluctuating from −0.70 to −1.8 m for the mean (min) water level and from −0.30 to −1.20 m for the mean (max) water level. Instead of the above and by preserving the amount of withdraw water n from the lake at a certain percentage of inflows, the irrigated area should be reduced from 54.1% to 64.05% depending on the circulation model.

Identifying Degraded and Sensitive to Desertification Agricultural Soils in Thessaly, Greece, under Simulated Future Climate Scenarios

The impact of simulated future climate change on land degradation was assessed in three representative study sites of Thessaly, Greece, one of the country’s most important agronomic zones. Two possible scenarios were used for estimation of future climatic conditions, which were based on greenhouse gas emissions (RCP4.5 and RCP8.5). Three time periods were selected: the reference past period 1981–2000 for comparison, and the future periods 2041–2060 and 2081–2100. Based on soil characteristics, past and future climate conditions, type of land uses, and land management prevailing in the study area, the Environmentally Sensitive to desertification Areas (ESAs) were assessed for each period using the MEDALUS-ESAI index. Soil losses derived by water and tillage erosion were also assessed for the future periods using existing empirical equations. Furthermore, primary soil salinization risk was assessed using an algorithm of individual indicators related to the natural environment or socio-economic characteristics. The obtained data by both climatic scenarios predicted increases in mean maximum and mean minimum air temperature. Concerning annual precipitation, reductions are generally expected for the three study sites. Desertification risk in the future is expected to increase in comparison to the reference period. Soil losses are estimated to be more important in sloping areas, due especially to tillage erosion in at least one study site. Primary salinization risk is expected to be higher in one study site and in soils under poorly drainage conditions.

Energy Transition on Sifnos: An Approach to Economic and Social Transition and Development

This article aims to present the potential of energy transition in insular systems for social and economic transition and development, when planned and implemented appropriately, with the active involvement of local communities. To this end, the example of Sifnos Energy Community is examined and presented as a pilot case. It proves that energy transition, apart from its obvious energy conservation and climate necessity, can provide a strong contribution to the development of remote areas and the remedying of crucial issues, especially in insular communities, such as unemployment, low standards of living, isolation and energy supply security. Energy transition on Sifnos has been undertaken by the Sifnos Energy Community (SEC), with the target to achieve 100% energy independency through effective and rational projects. The major project is a centralized hybrid power plant consisting of a wind park and a pumped hydro storage system. It was designed to fully cover the current electricity demand and the anticipated forthcoming load due to the overall transition to e-mobility for the transportation sector on the island. Through the exploitation of the excess electricity production with the production of potable water and hydrogen, energy transition can facilitate the development of new professional activities on the island and reduce the local economy’s dependence on tourism. Additionally, a daily link to the neighboring larger Cyclades islands can be established with a hydrogen powered-passenger vessel, ensuring the secure and cheap overseas transportation connection of Sifnos throughout the whole year. The overall energy transition process is executed with the active involvement of the Sifnos citizens, ensuring wide public acceptance and the minimization of the projects’ impacts on the natural and human environment. At the same time, the anticipated benefits for the insular communities are maximized, highlighting the energy transition process on Sifnos as a new sustainable development pattern. For all this effort and the already achieved results, Sifnos has been declared as one of the six pilot islands of the European Community’s initiative “Clean Energy for EU Islands”.

Adaptation: A Vital Priority for Sustainable Water Resources Management

Sustainability in terms of water management implies the study of all interrelated parameters (social, environmental, economic, engineering and political) in a comprehensive way. Although Greece is presented in the international rankings as a water-rich country, it has significant water problems due to its high temporal and spatial distribution of water resources and its unsustainable management practices characterized by a fragmented and sector-oriented water management system. This problem has been significantly improved by the adoption of the EU WFD and the development of management plans at the river basin scale. Nevertheless, because of the climate change effects, there is still a long way to go, and radical changes are needed in order to reach sustainability. Adaptation is a vital response toward sustainability. The Mygdonia agricultural basin is a case study of a highly negative water balance system that highlights the shortcomings of both water management and adaptation in Greece. Analysis of the hydrology of the basin, as well as the climate projections until 2100, revealed the urgent need for concerted action. A set of different development adaptation strategies was applied and assessed concerning their effectiveness. According to the outputs of this research, integrated watershed management is a prerequisite for a successful adaptation policy. Radical reform is needed in the agricultural sector by decreasing the agricultural land and changing crops. Demand management is the solution rather than focusing on supply options.

Spatiotemporal Evaluation of Water Quality and Hazardous Substances in Small Coastal Streams According to Watershed Characteristics

In this study, spatial and temporal changes of eight water quality indicators and 30 types of hazardous substances including volatile organic compounds (VOCs), semi-volatile organic compounds (SVOCs), pesticides, and inorganic matters for the small coastal streams along the West Coast of South Korea were investigated. In coastal streams with clear seasonal changes in water quality, larger watershed areas led to greater contamination by particulate matter (i.e., suspended solids, r = 0.89), and smaller watershed areas led to greater contamination by organic matter (i.e., BOD, r = −0.78). The concentration of VOCs and pesticides was higher in agricultural areas, and those of SVOCs and metals were often higher in urban areas. According to the principal component analysis (PCA), during the wet season, the fluctuation in the water quality of coastal streams was higher in urban areas than in agricultural areas. Furthermore, coastal streams in residential areas exhibited higher levels of SVOCs, and those in industrial areas exhibited higher levels of metallic substances. Based on these results, the spatial and temporal trends of water quality and hazardous substances were obtained according to watershed characteristics, thereby clarifying the pollution characteristics of small-scale coastal streams and the major influencing factors.