Dimitris Papamichail

Ecosystem approach to water resources management using the MIKE 11 modeling system in the Strymonas River and Lake Kerkini.

The ability to apply an ecosystem approach to the Strymonas River catchment was investigated using the MIKE 11 modeling system for the simulation of surface water. The Strymonas River catchment is shared mainly between Bulgaria and Greece. The river feeds the artificial Lake Kerkini, a significant wetland ecosystem, and further downstream it outflows to the Gulf of Strymonikos, whose estuary ecosystem is very important for fisheries, biodiversity and tourism. MIKE 11-NAM was used for the simulation of rainfall-runoff process in the Strymonas River catchment and MIKE 11-HD was used to simulate the unsteady flow of the Strymonas River and to apply management rules based on the water level of Lake Kerkini. Two water level management scenarios were investigated. The first scenario referred to the mean daily-observed water level of Lake Kerkini between 1986 and 2006, and the second scenario represented adjustments necessary to fulfill the lakes ecosystem requirements. Under the current water level management practices (Scenario 1), the Strymonas River-Lake Kerkini system has enough water to fulfill its Irrigation Water Requirements (IWR) in normal and wet years while a slight deficit is appeared in dry years; however, both Lake Kerkini and the Strymonas River estuary ecosystems are subject to pressures, since reduction of the forest area has been recorded. Applying the ecosystem approach (Scenario 2), the protection of the riparian forest of Lake Kerkini is achieved while in normal and wet years the IWR are fulfilled and the deficit of the IWR is increased in dry years. Compared to Scenario 1, the pressure of the Strymonas River estuary ecosystem is slightly increased.

Geostatistical analysis of spatial variability of rainfall and optimal design of a rain gauge network

Kriging is a geostatistical estimation technique for regionalized variables that exhibit an autocorrelation structure. Such a structure can be described by a semivariogram of the observed data. The punctual-kriging estimate at any point is a weighted average of the data, where the weights are determined by using the semivariogram and an assumed drift, or lack of drift, in the data. The kriging algorithm, based on unbiased and minimum-variance estimates, involves a linear system of equations to calculate the weights. Kriging is applied in an attempt to describe the spatial variability of rainfall data over a geographical region in northern Greece. Monthly rainfall data of January and June 1987 have been taken from 20 measurement stations throughout the above area. The rainfall data are used to compute semivariograms for each month. The resulting semivariograms are anisotropic and fitted by linear and spherical models. Kriging estimates of rainfall and standard deviation were made at 90 locations covering the study area in a rectangular grid and the results used to plot contour maps of rainfall and contour maps of kriging standard deviation. Verification of the kriging estimates of rainfall are made by removing known data points and kriging an estimate at the same location. This verification is known as the jacknifing technique. Kriging errors, a by-product of the calculations, can then be used to give confidence intervals of the resulting estimates. The acceptable results of the verification procedure demonstrated that geostatistics can be used to describe the spatial variability of rainfall. Finally, it is shown how the property of kriging variance depends on the structure and the geometric configuration of the data points and the point to be estimated can also be used for the optimal design of the rain gauge network in an area.

The use of a Neural Network technique for the prediction of water quality parameters

This paper is concerned with the use of Neural Network models for the prediction of water quality parameters in rivers. The procedure that should be followed in the development of such models is outlined. Artificial Neural Networks (ANNs) were developed for the prediction of the monthly values of three water quality parameters of the Strymon river at a station located in Sidirokastro Bridge near the Greek — Bulgarian borders by using the monthly values of the other existing water quality parameters as input variables. The monthly data of thirteen parameters and the discharge, at the Sidirokastro station, for the time period 1980–1990 were selected for this analysis. The results demonstrate the ability of the appropriate ANN models for the prediction of water quality parameters. This provides a very useful tool for filling the missing values that is a very serious problem in most of the Greek monitoring stations.

Interventions to increase seasonal influenza vaccine coverage in healthcare workers: A systematic review and meta-regression analysis

ABSTRACT Influenza vaccination is recommended for healthcare workers (HCWs), but coverage is often low. We reviewed studies evaluating interventions to increase seasonal influenza vaccination coverage in HCWs, including a meta-regression analysis to quantify the effect of each component. Fourty-six eligible studies were identified. Domains conferring a high risk of bias were identified in most studies. Mandatory vaccination was the most effective intervention component (Risk Ratio of being unvaccinated [RRunvacc] = 0.18, 95% CI: 0.08–0.45), followed by “soft” mandates such as declination statements (RRunvacc = 0.64, 95% CI: 0.45–0.92), increased awareness (RRunvacc = 0.83, 95% CI: 0.71–0.97) and increased access (RRunvacc = 0.88, 95% CI: 0.78–1.00). For incentives the difference was not significant, while for education no effect was observed. Heterogeneity was substantial (τ2 = 0.083). These results indicate that effective alternatives to mandatory HCWs influenza vaccination do exist, and need to be further explored in future studies.

Population Seroprevalence Study after a West Nile Virus Lineage 2 Epidemic, Greece, 2010

Introduction During summer 2010, 262 human cases including 35 deaths from West Nile virus (WNV) infection were reported from Central Macedonia, Greece. Evidence from mosquitoes, birds and blood donors demonstrated that the epidemic was caused by WNV lineage 2, which until recently was considered of low virulence. We conducted a household seroprevalence study to estimate the spread of infection in the population during the epidemic, ascertain the relationship of infection to clinical disease, and identify risk factors for infection. Methods We used a two-stage cluster design to select a random sample of residents aged ≥18 years in the outbreak epicentre. We collected demographic, medical, and risk factor data using standard questionnaires and environmental checklists, and tested serum samples for presence of WNV IgG and IgM antibodies using ELISA. Results Overall, 723 individuals participated in the study, and 644 blood samples were available. Weighted seropositivity for IgG antibodies was 5.8% (95% CI: 3.8–8.6; n=41). We estimated that about 1 in 130 (1:141 to 1:124) infected individuals developed WNV neuroinvasive disease, and approximately 18% had clinical manifestations attributable to their infection. Risk factors for infection reflected high exposure to mosquitoes; rural residents were particularly at risk (prevalence ratio: 8.2, 95% CI: 1.1–58.7). Discussion This study adds to the evidence that WNV lineage 2 strains can cause significant illness, demonstrating ratios of infection to clinical disease similar to those found previously for WNV lineage 1.

Estimation of Leaf Area Index and Foliage Area Index of Rice using an Indirect Gravimetric Method

The aim of this study was to present a gravimetric method for the estimation of leaf area index (LAI) and foliage area index (FAI) of rice. The method estimates indirectly the LAI-FAI variation during the growing season using simple measurements during harvest, based on a module of predetermined relations among agronomic parameters. The method confronts the limitations of other methods under specific conditions, such as (a) high plant densities and high LAI-FAI values, where indirect optical methods are restricted and (b) experiments related to crop modeling applications where direct destructive methods are not allowed because they alter the initial design of the experimental setup. The method was applied for the high-yield cultivar (Oryza sativa L. ssp. indica, cv. Thaibonnet) during 2-year evapotranspiration experiments in lysimeters. The method identified the differences between the replicate lysimeters, and LAI-FAI estimations were significantly correlated with the final grain yields and the crop factors obtained from evapotranspiration measurements.

Water allocation under deficit irrigation using MIKE BASIN model for the mitigation of climate change

Irrigated agriculture is likely to be affected by the changes in temperature and precipitation patterns due to climate change. Particularly in Greece, on account of higher temperatures and reduced precipitation, the irrigation water management is essential to the viability of agriculture in areas already facing water scarcity. In this paper, two deficit distribution methods, the equal shortage (ES) and the yield stress (YS), are evaluated for the mitigation of climate change in the irrigation networks of Nestos River, Greece. The two methods were applied in the irrigation module of the MIKE BASIN model to analyze the effect of water deficit on crop yield and net profit for the periods 1980–2000, 2030–2050 and 2080–2100. In comparison with the ES method, the YS method, in which the water is by priority distributed to the crop that is more sensitive to water shortage, increases the yield in most of the crops, estimates higher net profit to farmers and secures more water for the downstream ecosystems.

Assessment of rural and highly seasonal tourist activity plus drought effects on reservoir operation in a semi-arid region of Greece using the WEAP model

The WEAP (Water Evaluation and Planning) model was used to estimate the effects of drought in addition to rural and tourist activity on the operation of two multi-purpose reservoirs in the Chalkidiki region of Greece. In scenarios based on historical data from 1975–2005, the fully effective months exceeded 85% of the total simulation period, while short-term droughts (less than two years’ duration) made the reservoirs ineffective to cover summer water demand. The results show that short-term droughts, in combination with high competition for water supply during summer between tourist and rural activities, may have environmental and social implications in semi-arid environments.

Terrain Segmentation of Greece Using the Spatial and Seasonal Variation of Reference Crop Evapotranspiration

The study presents a combination of techniques for integrated analysis of reference crop evapotranspiration () in GIS environment. The analysis is performed for Greece and includes the use of (a) ASCE-standardized Penman-Monteith method for the estimation of 50-year mean monthly , (b) cross-correlation and principal components analysis for the analysis of the spatiotemporal variability of , (c) -means clustering for terrain segmentation to regions with similar temporal variability of , and (d) general linear models for the description of based on clusters attributes. Cross-correlation revealed a negative correlation of with both elevation and latitude and a week positive correlation with longitude. The correlation between and elevation was maximized during the warm season, while the correlation with latitude was maximized during winter. The first two principal components accounted for the 97.9% of total variance of mean monthly . -means segmented Greece to 11 regions/clusters. The categorical factor of cluster number together with the parameters of elevation, latitude, and longitude described satisfactorily the through general linear models verifying the robustness of the cluster analysis. This research effort can contribute to hydroclimatic studies and to environmental decision support in relation to water resources management in agriculture.

Low vaccination coverage of Greek Roma children amid economic crisis: national survey using stratified cluster sampling

Abstract Background: Research on Roma health is fragmentary as major methodological obstacles often exist. Reliable estimates on vaccination coverage of Roma children at a national level and identification of risk factors for low coverage could play an instrumental role in developing evidence-based policies to promote vaccination in this marginalized population group. Methods: We carried out a national vaccination coverage survey of Roma children. Thirty Roma settlements, stratified by geographical region and settlement type, were included; 7–10 children aged 24–77 months were selected from each settlement using systematic sampling. Information on children’s vaccination coverage was collected from multiple sources. In the analysis we applied weights for each stratum, identified through a consensus process. Results: A total of 251 Roma children participated in the study. A vaccination document was presented for the large majority (86%). We found very low vaccination coverage for all vaccines. In 35–39% of children ‘minimum vaccination’ (DTP3 and IPV2 and MMR1) was administered, while 34–38% had received HepB3 and 31–35% Hib3; no child was vaccinated against tuberculosis in the first year of life. Better living conditions and primary care services close to Roma settlements were associated with higher vaccination indices. Conclusions: Our study showed inadequate vaccination coverage of Roma children in Greece, much lower than that of the non-minority child population. This serious public health challenge should be systematically addressed, or, amid continuing economic recession, the gap may widen. Valid national estimates on important characteristics of the Roma population can contribute to planning inclusion policies.