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Good water quality status in rivers and lakes is vital for both human well-being and biodiversity conservation and requires efficient monitoring and restoration strategies. This is reflected in an increasing number of International and National legislations which enforce water resources management and monitoring at a basin scale.For this purpose, state-of-the-art monitoring schemes have been developed by using low-cost, technologically advanced sensors and Internet of Things (IoT) infrastructure. Remote sensing offers also a good water monitoring alternative but is more appropriate for medium to large water bodies with less dynamic character in comparison to small scale, temporary rivers.Recent technological advances in sensors technology, energy supply, telecommunication protocols and data handling, facilitate the use of automated monitoring stations, but still, deployment of extended networks with readily available data remains far from common practice. Installation and operational costs for the development of such monitoring networks are among the most commonly faced challenges.The main aim of this effort is to present the development of a network of automatic monitoring stations that measure in near real time water level and physicochemical parameters in several Greek rivers. This infrastructure has been developed under the project “Open ELIoT” (Open Internet of Things infrastructure for online environmental services - https://www.openeliot.com/en/), which was funded by the Greek National Structural Funds. It includes a low cost and easy to produce hardware node, coupled with commercial sensors of industrial specifications, as well as an IoT data platform, elaborating and presenting data, based on open technologies.During its initial operation phase, the system has been deployed in sites with different hydrological regimes and various pressures to water quality, including (a) an urban Mediterranean stream (Pikrodafni stream), and (b) the urban part of a continental river running through an agricultural area (Lithaios stream).Preliminary data on the continuous monitoring of sites (a) and (b) are presented here, reflecting the differences in pressures to the respective water bodies. Pikrodafni stream which is located close to the center of Athens – Greece and receives a lot of pressure from urban waste, illustrates Dissolved Oxygen (DO) concentration with a heavily skewed distribution towards low values (mean value: 2.15 mg/l and median: 0.93 mg/l). On the contrary, in Lithaios stream, which is more affected by agricultural runoff, dissolved oxygen data approach a normal distribution (mean value: 6.93 mg/l and median: 7.03 mg/l). The 25th and 75th percentiles in Pikrodafni stream are: 0.1 mg/l and 3.47 mg/l respectively while in Lithaios stream are: 5.6 mg/l and 8.45 mg/l. The average water temperature is similar to both streams (18.8 oC in Pikrodafni and 16.2 oC in Lithaios). Therefore, the significant differences in DO concentrations between the two streams indicate the need for continuous monitoring of data that facilitates the identification of pressures and enables stakeholders to respond to pollution events in time.

The atmospheric blocking over eastern Europe and western Russia that prevailed during July and August of 2010 led to the development of a devastating Russian heat wave. Therefore the question of whether the event was predictable or not is highly important. The principal aim of this study is to examine the predictability of this high-impact atmospheric event on a seasonal timescale. To this end, a set of dynamical seasonal simulations have been carried out using an atmospheric global circulation model (AGCM). The impact of various model initializations on the predictability of this large-scale event and its sensitivity to the initial conditions has been also investigated. The ensemble seasonal simulations are based on a modified version of the lagged-average forecast method using different lead-time initializations of the model. The results indicated that only a few individual members reproduced the main features of the blocking system 3 months ahead. Most members missed the phase space and the propagation of the system, setting limitations in the predictability of the event.

The POSEIDON weather forecasting system became operational at the Hellenic Centre for Marine Research (HCMR) in October 1999. The system with its nesting capability provided 72-h forecasts in two different model domains, i.e. 25- and 10-km grid spacing. The lower-resolution domain covered an extended area that included most of Europe, Mediterranean Sea and N. Africa, while the higher resolution domain focused on the Eastern Mediterranean. A major upgrade of the system was recently implemented in the framework of the POSEIDON-II project (2005–2008). The aim was to enhance the forecasting skill of the system through improved model parameterization schemes and advanced numerical techniques for assimilating available observations to produce high resolution analysis fields. The configuration of the new system is applied on a horizontal resolution of 1/20°×1/20° (~5 km) covering the Mediterranean basin, Black Sea and part of North Atlantic providing up to 5-day forecasts. This paper reviews and compares the current with the previous weather forecasting systems at HCMR presenting quantitative verification statistics from the pre-operational period (from mid-November 2007 to October 2008). The statistics are based on verification against surface observations from the World Meteorological Organization (WMO) network across the Eastern Mediterranean region. The results indicate that the use of the new system can significantly improve the weather forecasts.