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The aim of this work is the determination of the parameters of Earth’s triaxiality through a geometric fitting of a triaxial ellipsoid to a set of given points in space, as they are derived from a geoid model. Starting from a Cartesian equation of an ellipsoid in an arbitrary reference system, we develop a transformation of its coefficients into the coordinates of the ellipsoid center, of the three rotation angles and the three ellipsoid semi-axes. Furthermore, we present different mathematical models for some special and degenerate cases of the triaxial ellipsoid. We also present the required mathematical background of the theory of least-squares, under the condition of minimization of the sum of squares of geoid heights. Also, we describe a method for the determination of the foot points of the set of given space points. Then, we prepare suitable data sets and we derive results for various geoid models, which were proposed in the last fifty years. Among the results, we report the semi-axes of the triaxial ellipsoid of geometric fitting with four unknowns to be 6378171.92 m, 6378102.06 m and 6356752.17 m and the equatorial longitude of the major semi-axis –14.9367 degrees. Also, the parameters of Earth’s triaxiality are directly estimated from the spherical harmonic coefficients of degree and order two. Finally, the results indicate that the geoid heights with reference to the triaxial ellipsoid are smaller than those with reference to the oblate spheroid and the improvement in the corresponding rms value is about 20 per cent.

This study presents the provisional, regulating and cultural ecosystem services that can be delivered by the newly constructed multi-purpose reservoir of Lake Karla located in a water-scarce agricultural area in central Greece. The present short paper takes advantage of literature data and outputs produced from a dynamic GIS hydrologic and management model of the study area with SWAT that simulated hydrology, reservoir operation, irrigation practices and crop production. The paper highlights the net provisional services that the local agricultural society can gain from the full operation of Karla and the additional benefits arising, such as flood control, biodiversity maintenance, aesthetic improvement and touristic opportunities.

Due to the fact of water resource deterioration from human activities and increased demand over the last few decades, optimization of management practices and policies is required, for which more reliable data are necessary. Cost and time are always of importance; therefore, methods that can provide low-cost data in a short period of time have been developed. In this study, the ability of an artificial neural network (ANN) and a multiple linear regression (MLR) model to predict the electrical conductivity of groundwater samples in the GallikosRiver basin, northern Greece, was examined. A total of 233 samples were collected over the years 2004–2005 from 89 sampling points. Descriptive statistics, Pearson correlation matrix, and factor analysis were applied to select the inputs of the water quality parameters. Input data to the ANN and MLR were Ca, Mg, Na, and Cl. The best results regarding the ANN were provided by a model that included one hidden layer of three neurons. The mean absolute percentage error, modeling efficiency, and root mean square error were used to evaluate the performances of the methods and to compare the prediction capabilities of the ANN and MLR. We concluded that the ANN and MLR models were valid and had similar accuracy (using the same inputs) with a large number of samples, but in the case of a smaller data set, the MLR showed a better performance.

The sustainable management of lakes and reservoirs requires the determination of their minimum environmental water level. Even though the assessment of minimum water level depends on a number of biotic and abiotic factors of the lake ecosystem, in many cases these factors are not entirely known and, furthermore, their evaluation is usually a challenging and laborious task. On the other hand, the lakes/reservoirs may comprise an important water resource to meet the requirements arising from economic activities. In this paper, the morphological and hydrological features of four lakes of northern Greece were analysed in order to assess their minimum environmental water level. The hydromorphological analysis was based on the relationship of the lake surface area and volume with water level as well as the water inflow from the lake’s hydrological catchment area, considering as the lake’s critical volume storage, the annual water volume flowing into a lake from its hydrological catchment area with a probability of exceedance 50% of a long time series of hydrological years. By combining morphological and hydrological features, the proposed methodology aimed to extend the analysis based solely on morphological features, and assess more comprehensively the minimum environmental water level in the four lakes, ensuring also the rising from the minimum level to the maximum (overflow) level for most of the hydrological years.

Water stress in one of the most important abiotic stresses that affects the productivity of many crop species worldwide. In addition, the climate change creates new challenges for crop adaptation especially as water resources become limited and the increase in water stress becomes more pronounced even in areas where there is adequate water supply. The objective of the present study was to determine the effect of water stress on physiological characteristics of five cultivars of basil under field conditions. Water stress affected leaf temperature, dry herb yield, leaf water potential, assimilation rate and gas exchange parameters, quantum yield, instantaneous water use efficiency (WUE), and essential oil content. From the physiological characteristics water potential and assimilation rate can be used for the selection of basil cultivars tolerant to water stress. In addition, essential oil content was lower under water stress indicating that essential oil content is correlated with water availability. From the present study it is obvious that there are tolerant basil cultivars to water stress and can be found using physiological traits such as water potential and assimilation rate and can be used to save and use water more sustainable and also conserve the water resources.

Drought is one of the major yield constraints of crop productivity for many crops. In addition, nowadays, climate change creates new challenges for crop adaptation in stressful environments. The objective of the present study was to determine the effect of water stress on five cultivars of basil (Mrs Burns, Cinnamon, Sweet, Red Rubin, Thai) and whether water use efficiency (WUE) can be increased by using the appropriate cultivar. Water stress affected the fresh and dry weight and also the partitioning of dry matter to leaves, flowers, and stems. Also, there are cultivars, such as Mrs Burns and Sweet, which were not affected by the limited amount of water and continued to produce a high amount of dry matter and also showed high essential oil yield. Essential oil content was not affected by the irrigation; however, essential oil yield was affected by the irrigation, and the highest values were found at Mrs Burns. The water use efficiency was affected by the cultivar and irrigation level, and the highest was found at Mrs Burns. The results show that using appropriate cultivars basil can achieve higher WUE and allow saving water resources and utilizing fields in areas with limited water resources for irrigation.

Water quality is a worldwide problem which affects human beings lives fundamentally. Water scarcity is intensified in result of quality deterioration. Different factors such as population increase, economic development and water pollution could be considered as the origins of the problem. The study and forecasting of water quality is necessary to prevent serious water quality deteriorations in future. Different methodologies have been used to predict and estimate the quality of water. In present study using time series modeling, the quality of Hor Rood River is studied at Kakareza station using time series analysis. 9 parameters of water quality are studied such as: TDS, EC, HCO3-, SO42-, Mg2+, Ca2+, Na+, pH and SAR. Investigation of observed time series show that there is an increasing trend for all parameters unless Na+, pH and SAR. The order of model for each parameter was determined using auto correlation function (ACF) and partial auto correlation function (PACF) of time series. ARIMA (autoregressive, integrated, moving average) model was found suitable to generate and forecast the quality of river water. AIC, R2, RMSE and VE % criteria were used for evaluating the generation and forecasting results. Results show that time series modeling is quite capable of water quality forecasting. For all generated and forecasted parameters the value of R2 was greater than 0.66 Except for SO42-. The value of R2 for generated SO42- was 0.48 and this value was 0.43 for forecasting this parameter. Also the study show that the quality of water is deteriorating based on an increasing trend for the majority of parameters and needs serious managerial actions.