A rational water resources exploitation and management is associated with determination of water balance, hence modelling in this scientific field is always topic of high interest. Although water balance modelling is in silico attainable, combination of hydrological processes that are extremely challenging to be simulated together with inadequacy of observations, result in inherent incertitudes. This study focuses on incorporating structural and parametric uncertainties by tuning the parameters of modified - with a snowmelt subroutine - GR2M hydrological model, using simulated annealing optimization method within fuzzy logic environment. Therefore, model parameters are expressed as fuzzy numbers, leading to the formulation of a sub-optimization problem for estimating the a-cut boundary values of the predicted outflow. Analytical description of the proposed hybrid method is presented, along with a case study evaluating efficiency performances of the modified model. Results reveal that the implementation of fuzzy parameters in modified GR2M embodies these uncertainties including vast majority of observed outflows into fuzzy bands of simulated flows.

Drought as an extreme weather phenomenon has recently become more frequent with significant impacts on water resources, such as reduced infiltration and surface runoff. To assess the vulnerability of water resources to drought, the Standardized Drought Vulnerability Index (SDVI) was applied to the hydrological basin of Lake Karla in Thessaly, Central Greece. The Lake Karla basin has a semi-arid climate and is an agricultural basin in which water-demanding crops are cultivated. The SDVI is a composite index that integrates all types of droughts and, with its holistic approach, can be used as a monitoring tool to provide knowledge for the delineation of vulnerable areas.

Extreme rainfall analysis is essential for accurate flood hazard assessment. Traditional approaches, such as the use of annual maxima, may overlook seasonal variations and lead to underestimated precipitation extremes, compromising effective flood risk management strategies. This study applies a point process model to uninterrupted daily rainfall records (1901–2023) from the National Observatory of Athens meteorological station in Thiseion. This method analyzes both the frequency of exceedances above a given threshold and the values of those exceedances, incorporating seasonality into the modeling process. Preliminary analysis using annual maxima revealed no statistically significant trend but indicated clear monthly seasonality in precipitation extremes. By incorporating seasonality, the point process method yielded estimates up to 22% higher than those obtained using traditional annual maxima approaches, such as those employed in Greece's National Flood Risk Management Plans. These findings highlight the need for a revision of current methodologies, which could significantly impact flood risk assessments and management strategies.

This study analyses polarimetric weather radar data to explore their potential for comprehensive and reliable precipitation and thus, drought monitoring in Cyprus. For this purpose, we compare reflectivity measurements from the two ground-based X-band dual-polarization radars of the Department of Meteorology of the Republic of Cyprus with measurements obtained from the Dual-Frequency Precipitation Radar (DPR) onboard NASA’s Global Precipitation Measurement (GPM) mission. The comparison considers six years (2017–2023) of observations. It is implemented using the volume-matching method proposed by Schwaller and Morris (2011), as extended by Crisologo et al (2018) to take into account the beam blockage fraction as the basis of a quality index. To further enhance the consistency and precision of the calibration bias, we introduce path-integrated attenuation as an additional filter in the quality index. The path-integrated attenuation of the ground radars is estimated using a forward gate-by-gate attenuation correction method based on an iterative approach with scalable constraints. The level of path-integrated attenuation of the GPM Dual-Frequency Precipitation Radar is evaluated based on the GPM 2AKu variable piaFinal. Acknowledgements The authors acknowledge the ‘EXCELSIOR’: ERATOSTHENES: EΧcellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The ‘EXCELSIOR’ project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology. The authors also acknowledge the Department of Meteorology of the Republic of Cyprus for providing the X-band radar data.

The study aims to analyze the effects of climate change, irrigation and nitrogen fertilization practices and water reserve strategies, on water resources, aimed at nitrogen use efficiency, groundwater nitrate pollution, groundwater budget, and seawater intrusion. Intensive groundwater abstraction for irrigation and nitrogen fertilization has led to a substantial water deficit, rising nitrate pollution, and seawater intrusion in the Almyros aquifer system. The analysis employs an Integrated Modelling System (IMS) to simulate coastal water resources, incorporating models for surface hydrology (UTHBAL), reservoir operations (UTHRL), groundwater hydrology (MODFLOW), nitrate leaching/crop growth (REPIC), nitrate pollution (MT3DMS), and seawater intrusion (SEAWAT) to capture the complex interactions between climate, hydrology, and agricultural practices. Climate projections for Representative Concentration Pathway 8.5 (RCP 8.5) from the Med-CORDEX (Mediterranean Coordinated Regional Downscaling Experiment) database for precipitation and temperature are bias-corrected with Empirical Quantile Mapping and used to estimate the effects of climate change. Irrigation scenarios, including base irrigation and deficit irrigation, as well as reduced nitrogen fertilization, are evaluated to determine their effects on water resources management and sustainability. The study’s results highlight a significant decline in water availability across climate models, with reduced runoff and groundwater recharge projected for the Almyros Basin. Increasing nitrate concentrations and chloride levels suggest worsening water quality, posing risks of seawater intrusion and nutrient pollution. The Nitrogen Use Efficiency index (NUE) improves under reduced nitrogen fertilization, supporting more efficient nutrient use and reducing excess nitrogen losses. The findings highlight critical water quality and quantity challenges, aligning mainly with Sustainable Development Goal 6, and following SDGs 9, 12, and 13 by promoting efficient resource use, pollution reduction, and climate resilience, guiding adaptation strategies for mitigating water scarcity under climate change.

The Almyros groundwater system in Magnesia, Greece, is experiencing significant nitrate contamination, exacerbated by intensive agricultural activities, particularly in rural and coastal zones. This study aims to identify nitrate-vulnerable areas by applying and comparing three vulnerability assessment models: DRASTIC, Canter, and modified models incorporating land use factors alongside the Analytic Hierarchy Process (AHP). The analysis spans three timeframes 1992–1997, 2004–2009, and 2010–2015 to capture temporal changes in nitrate vulnerability. Results show that coastal zones consistently exhibit high nitrate vulnerability across all models and study periods. Approximately 40

Floods are among the most devastating water-related hazards and are primarily responsible for the loss of human life and destruction of the natural and man-made environment. This study addresses the estimation and mapping of flood hazard in small mountain watersheds with urban areas at the lowlands and the related uncertainty. Specifically, this research studies the flood hazard for the Metropolitan city of Volos in Central Greece, which is frequently affected by intense storms that cause flash floods. The above study area is crossed by three (3) streams.The methodology used in the study is divided into three stages. At first the 24-hour design storm hydrographs were constructed for the three sub-basins of the study area with using the mean IDF parameters and the relevant confidence limits. The Alternating Block Method was used for the design hyetographs for return periods, T = 50-year, T=100-year and T=1000-year (worst-case scenario). The second stage concerns the hydrological analysis using a rainfall-runoff model. Firstly, the net rainfall was estimated by using the U.S. Soil Conservation Service (SCS-CN) method for three (3) soil's Antecedent Moisture Conditions (AMC) for dry-average-wet conditions. Then, the net rainfall was transformed by using the Instantaneous Unit Clark hydrograph into discharge and the flood hydrographs for each return period were estimated. At the final stage, the flood hydrograph estimated for each watershed was routed through the hydrographic network using the HEC-RAS 2D hydraulic-hydrodynamic simulation (2D) model. For the flow routing, Manning’s n was estimated for various cross sections by visual inspection and corresponding values reported in international reports. The “upper” and “lower” boundaries of Manning’s n were estimated as the -50% and +50% of the average Manning’s n values, respectively. In this simulation approach, flood hazard maps for three return periods, T=50, T=100 and T=1000 years considering three different soil moisture conditions and three different values of Manning’s n have been estimated. The values of Manning’s n in the flood plain were estimated by using land cover/land use data. The flow routing with in the urban areas was simulated by the block rising method. In total twenty-seven (27) flood scenarios have been simulated for each watershed. The results were validated with the flooded areas during a specific historical flood event using the Critical Success Index (CSI) method and reports and photographs of the historical flood event. The results of hydrological analysis and hydraulic simulation were also compared with the results of the Greek Flood Hazard Management Plans.

The Available Information contained in a hydrological dataset represents the meaningful information per timestep that enters a rainfall-runoff model. To estimate this quantity, Independent Component Analysis (ICA) must be performed to transform the original observations into statistically independent signals. However, ICA algorithms may detect many sets of nearly independent signals suitable for this transformation, posing the question of which set is the optimal one. In the present paper, it is proposed that the components of the optimal set must share the least total pairwise mutual information among all sets since the mutual information of a pair of components is a measure of their statistical independence. This novel approach of estimating the available information of a dataset is applied to five basins in Thessaly, Greece and it is compared to the standard approach of taking the average value occurring from multiple ICA runs. It is illustrated that discarding ICA solutions with high total pairwise mutual information shared between their components stabilizes the estimator of Available Information and increases its precision. This comes with the cost of additional computation time since multiple evaluations of bivariate mutual information are needed.

This study presents the projected future evolution of water resource balance and nitrate pollution under various climate change scenarios and climatic models using a holistic approach. The study area is Almyros Basin and its aquifer system, located in Central Greece, Thessaly, Greece. Almyros Basin is a coastal agricultural basin and faces the exacerbation of water deficit and groundwater nitrate pollution. Using an Integrated Modeling System (IMS), which consists of the surface hydrology model (UTHBAL), the nitrate leachate model (REPIC, an R-ArcGIS-based EPIC model), the groundwater hydrology model (MODFLOW), and the nitrates’ advection, dispersion, and transport model (MT3MDS), the projected values of the variables of water quantity and quality are simulated. Nineteen climatic models from the Med-CORDEX database were bias-corrected with the Quantile Empirical Mapping method and employed to capture the variability in the simulated surface and groundwater water balance and nitrate dynamics. The findings indicate that future precipitation, runoff, and groundwater recharge will decrease while temperature and potential evapotranspiration will increase. Climate change will lead to reduced nitrogen leaching, lower groundwater levels, and persistent nitrate pollution; however, it will be accompanied by high variability and uncertainty, as simulations of IMS under multiple climatic models indicate.

The study examines the impacts of climate change and sea level rise on coastal aquifers, focusing on the influence of the components of the water cycle on seawater intrusion, and the evolution of the phenomenon in the future. The simulation of coastal water resources was performed using an integrated modeling system (IMS), designed for agricultural coastal watersheds, which consists of inter-connected models of surface hydrology (UTHBAL), groundwater hydrology (MODFLOW), and seawater intrusion (SEAWAT). Climatic models for the adverse impact scenario (RCP8.5) and the medium impact scenario (RCP4.5) of climate change were used. Transient boundary head conditions were set to the coastal boundary, to dynamically represent the rise in sea level due to climate change. The response of groundwater in the coastal Almyros Basin, located in central Greece, was simulated from 1991 to 2100. The findings indicate that seawater intrusion will be advanced in the future, in both climate change scenarios. The models show varying patterns in groundwater recharge, with varying uncertainty projected into the future, and sensitivity to time in the fluctuation of the components of the water cycle.

The aim of this paper is the spatial and temporal analysis of droughts in a typical water limited Mediterranean basin, Pinios River Basin in Thessaly, Greece using satellite data and compare this analysis with the spatio-temporal analysis of droughts using ground station data. To achieve this, time series analysis with geoinformatics techniques and the calculation of drought indices is applied. The drought assessment methodology was developed for the determination of spatio-temporal drought analysis using ground and remote sensing data. The analysis was carried out for the common period from October 1981 to September 2002. The methodology was developed by estimating the meteorological drought indices, Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) for various time scales, but also comparing them with the Surface Runoff Index (hydrological drought index). Initially, the station monthly precipitation and temperature data were spatially distributed by using an MLR interpolation method. Thus, a canvas of 487 pixels was created for the entire basin area. Correlation analysis was performed to validate the results of the spatial distribution of monthly precipitation and temperature. Precipitation satellite data by Climate Hazards Infrared Precipitation with Stations (CHIRPS) have been used. These global precipitation data have a spatial resolution of 0.05° (5 x 5 km), from 1981. The monthly temperature was estimated by the ERA5 reanalysis data at the same spatial resolution. The Thornthwaite method was used for the estimation of potential evapotranspiration for both ground and satellite data. The values of the drought indices (SPI and SPEI) estimated using ground and remote sensing data have been compared for the whole period of analysis (1981-2002) and the results were deemed satisfactory. The Pinios River Basin experienced severe, extreme, and persistent droughts during the period from the late 1980s to the early 1990s and in early 2000s and the results of the analysis have been compared for these specific drought events. Furthermore, the drought indices of various time scales were compared for an unregulated sub-basin of Pinios River with the SRI index and the results indicated that a meteorological drought index (SPI and/or SPEI) at 6-month time scale correlates well with the SRI. Overall, the results of the analysis showed that the satellite data could be used for the estimation of drought indices with reasonable accuracy for the analysis of droughts in areas were ground meteorological data are not available. Keywords: Droughts; Standardized Precipitation Index, SPI; Standardized Precipitation Evapotranspiration Index, SPEI; Surface Runoff Index, SRI; CHIRPS; ERA5; Pinios River Basin

In the present article, the Theory of Information is applied to hydrological time series to quantify their informational content. Uncertainty is defined as the gap between available and required knowledge. This approach is more intuitive than the traditional treatment of uncertainty as confidence intervals. Moreover, a theoretical framework is developed, in which the components of total uncertainty are explicitly defined and a novel method of splitting epistemic uncertainty into its structural and parametric components is applied. The extensive computations to detangle these components are compacted into a single methodology, which is applied to two hydrological basins, to evaluate various methods of aerial integration of rainfall point data. Five lumped monthly models are utilized to simulate the runoff. For each model, a characteristic curve can be drawn which can be used to select the appropriate model depending on the available information of the data set.

The increasing global demand for high-quality agricultural products poses significant challenges for water resource management while the traditional irrigation methods, reliant on open canal systems, are inefficient and environmentally detrimental, necessitating a shift to more efficient pressurized irrigation networks. However, designing these systems is complex and costly, primarily due to the high expenses associated with pipe materials. This research introduces a novel pipe length splitting (PLS) method which optimizes the pipe diameters and lengths by allowing a strategic splitting of the pipes under certain constraints (e.g. flow velocity, head losses etc.) aiming to reduce costs without sacrificing the network efficiency. In this work the proposed PLS method combined with the existing computationally efficient Simplified optimization method (SOM) offers a robust solution for cost minimization while it is very flexible and compatible also with various existing optimization methods (e.g. linear and dynamic programming). In this work the network under study was the existing open canal irrigation network of Limnochori in North Greece which was studied as a pressurized irrigation network. Applying the SOM in conjunction with the PLS, the comparative study shows a total cost reduction of 21,930€ while PLS affected 45

This paper analyses polarimetric weather radar data to explore their potential for comprehensive and reliable precipitation and thus, drought monitoring in Cyprus. Reflectivity measurements from the two ground-based X-band dual-polarization radars of the Department of Meteorology of the Republic of Cyprus are compared with measurements obtained from the Dual-Frequency Precipitation Radar (DPR) onboard NASA’s Global Precipitation Measurement (GPM) mission in order to calibrate the ground-based reflectivity. The comparison is done using a volume matching method that allows us to associate the datasets both in space and time. To correct the attenuation, we examine a Z-A relationship approach and the forward gate-by-gate attenuation correction based on an iterative approach with scalable constraints. Preliminary results show a significant underestimation of the ground-based reflectivity, as well as a notable impact of attenuation that leads to a major source of error for rainfall estimation.

This authoritative Encyclopedia provides an innovative approach to theory, reviews, applications and examples relevant to the basic concepts of water science and water management issues in order to facilitate better interdisciplinary cooperation.

In this paper, the effects of climate change on the phenology of cotton and maize are studied applying the Agricultural Policy/Environmental eXtender (APEX) simulation model. Cotton and maize are two dominant irrigated crops in Lake Karla Watershed (Central Greece). The phenology of maize and cotton is examined considering the mild climate scenario (RCP 4.5) with results from 5 climate models for the 2080 – 2100 period. The 5 climate models selected for this study are CNRM, HADLEY, ICHEC, IPSL and MPI. The scenario based on the HADLEY climate model predicts the highest values of average minimum and average maximum temperature while the ICHEC model predicts the lowest average minimum and average maximum temperature. In terms of precipitations, the MPI model predicts the lowest average precipitation while the highest average precipitation is predicted by the CNRM climate model. The APEX model simulates plant development using the heat units approach and the heat units index (HUI), calculated as ratio between accumulated heat units and the total heat units needed to reach maturity, can be used as indicator of plant phenology. According to this approach, HUI = 1 indicates the physiological maturity. For all climate models the HUI shows that the cotton and maize reach maturity too early in the season as a result of which they also record lower yields, with the HADLEY climate scenario giving the lowest crop yield. According to the results provided by the APEX model for the two crops considered here, cotton will be affected the most by the predicted future climate.