Five different water resource management scenarios are examined on eight dry islands of the Aegean Sea in Greece, pitting the current practice of water hauling via ship against alternative water supply schemes in delivering a sustainable solution for meeting water demand. The first scenario employs current water supply practices along with the operation of domestic rainwater harvesting systems. Desalinated water, provided through the operation of wind-powered desalination plants, is considered the main source of potable water in the rest of scenarios. Wind-powered desalination may be combined with rainwater harvesting as a supplementary source of water and/or seawater pumping and an additional source of energy that is supplied to the system. All different alternatives are evaluated for a 30-year lifespan, and an optimal solution is proposed for each island, based on a life cycle cost (LCC) analysis. The performance of this solution is then assessed under six climate change (CC) scenarios in terms of the rate of on-grid versus off-grid renewable energy that is required in order to achieve a certain reliability level. Overall, the examined scenarios show a decreasing performance in terms of reliability under CC for the eight islands.

Reference evapotranspiration (ETo) estimation is essential for water resources management. The present research compares four different ETo estimators based on reanalysis data (ERA5-Land) and in situ observations from three different cultivation sites in Greece. ETo based on FAO56-Penman–Monteith (FAO-PM) is compared to ETo calculated from the empirical methods of Copais, Valiantzas and Hargreaves-Samani using both reanalysis and in situ data. The daily and monthly biases of each method are calculated against the FAO56-PM method. ERA5-Land data are also compared to ground-truth observations. Additionally, a sensitivity analysis is conducted on each site for different cultivation periods. The present research finds that the use of ERA5-Land data underestimates ground-truth-based ETo by 35%, approximately, when using the FAO56-PM method. Additionally, the use of other methodologies also shows underestimation of ETo when calculated with ERA5-Land data. On the contrary, the use of the Valiantzas and Copais methodologies with in situ observations shows overestimation of ETo when compared to FAO56-PM, in the ranges of 32–62% and 24–56%, respectively. The sensitivity analysis concludes that solar radiation and relative humidity are the most sensitive variables of the Copais and Valiantzas methodologies. Overall, the Hargreaves-Samani methodology was found to be the most efficient tool for ETo estimation. Finally, the evaluation of the ERA5-Land data showed that only air temperature inputs can be utilized with high levels of confidence.

In weather radar applications, the Z-R relationship is considered one of the most crucial factors for providing quality quantitative precipitation estimates. However, the relationship’s parameters vary in time and space, making the derivation of an optimal relationship for a specific weather radar system challenging. This research focused on the analysis of the spatiotemporal variability of the parameters for a newly installed X-Band weather radar in Athens, Greece, by performing correlation and optimization analyses between high temporal resolution weather radar and rain gauge datasets. The correlation analysis was performed to assess the available datasets and provide the base of quality control. Multiple Z-R relationships were then derived for the following three optimization procedures; event-based relationships, station-based relationships, and a single area-based relationship. The results highlighted the region’s spatial variability regarding the Z-R relationship and the correlation between the station location and its parameter values. Moreover, it was found that stations near the coast and the front end of precipitation systems featured parameter values typical of convective type events. Finally, a single Z-R relationship was determined under a calibration and validation scheme, Z = 321R^1.53,, which was validated with good agreement.

Inland water resources are facing increasing quantitative and qualitative pressures, deriving from anthropogenic causes and the ongoing climate change. The monitoring of reservoirs is essential for sustainable management and preparation against water scarcity and extreme events, such as droughts. This research, relying on the Sentinel-2 and 3 missions, attempts to demonstrate the efficiency of combining remotely sensed water level and water area estimations, in order to estimate the water storage variation of Yliki reservoir. The case study is conducted in one of the few sufficiently monitored reservoirs in Greece, enabling a direct comparison of the proposed methodology results with in situ observations. Moreover, this research work proposes a weekly time interval for pairing level and area estimations, instead of shorter time intervals. The results strongly demonstrate the efficiency of remote sensing in the production of empirical level–area–storage (L–A–S) curves. Correlation to in situ monitored storage- and satellite-derived water level, area stand for 98.81% and 99.27% respectively. Water storage variation is estimated and compared to the observed time series, resulting in an RMSE of 1.28% of the reservoir capacity and a correlation of 96.14%. The empirical L–S relationship underestimates storage, while the A–S relationship overestimates storage when compared to the existing L–A–S curve.