Vassilis Z. Antonopoulos

Simulation of water temperature and dissolved oxygen distribution in Lake Vegoritis, Greece

Changes in lake water temperature and temperature stratification dynamics can have a profound effect on lake biological and chemical processes. A one-dimensional temperature stratification and oxygen prediction model was developed to simulate the seasonal temperature cycle and oxygen distribution for Lake Vegoritis in Northern Greece. The submodel of heat transport is based on the non-linear heat transfer equation using daily weather parameters as input data. The dissolved oxygen (D.O.) submodel is based on the unsteady diffusion equation with the oxygen fluxes through the free surface and bottom of lake as boundary conditions, and photosynthetic oxygen production, biochemical oxygen demand and plant respiration as internal sources and sinks. The solution of these equations uses the finite element method. The model was calibrated and verified by using data from Lake Vegoritis from two different years (1981 and 1993). The model results showed that there was good agreement between the simulated and the measured values of water temperature and D.O. at different depths in the lake and on different days of the year.

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.

A Decision Support System Approach for Rivers Monitoring and Sustainable Management

This paper presents a Decision Support System (DSS) approach developed in the context of the Copernicus project entitled System for Water Monitoring and Sustainable Management based on Ground Stations and Satellite Images (WATERMAN). The main objective of WATERMAN is the monitoring and management of the Strymon River in the Southern Balkans. The specific DSS integrates the main components of WATERMAN and helps the decision maker to monitor the Strymon region; to control and forecast the quantity and quality of the river water; as well as to make objective decisions about the state of the water based on data provided by radio computers, earth stations and satellite images processed by mathematical and statistical models and Geographical Information Systems (GIS).

Simulation of soil moisture dynamics on irrigated cotton in semi-arid climates

Abstract A simulation study of the soil moisture under cotton was carried out in two areas of Central and North Greece during the 1990 and 1994 growing periods. The soil moisture dynamics were evaluated using a one-dimensional model based on the Galerkin finite element method. The model was applied to simulate the state of a cotton crop-soil system under dynamic environmental conditions and irrigation schedules in the two areas. Three different cases of maximum extraction rate were examined. The simulated results were compared with available measurements of water content at different depths in the soil. The qualitative and quantitative procedures for model evaluation showed that there was a good agreement between the simulated and the measured values of water content at different depths of soil.

Simulation of water and nitrogen dynamics in soils during wastewater applications by using a finite-element model

A mathematical model was developed to simulate water movement, mass transport, and nitrogen transformations in soils during wastewater applications. The model is one-dimensional and based on the Galerkin finite-element method. The submodel of mass transport of nitrogen incorporates the convection-dispersion processes of ammonium and nitrate nitrogen, nitrification, denitrification, ammonium exchange and uptake of ammonium and nitrate ions. The accuracy and validity of the proposed model was examined by comparison with an explicit-implicit finite-difference model results. The model was used for simulation of water and nitrogen dynamics during wastewater application in homogeneous and multi-layered soils under different N concentration, rate, duration and scheduling of application.

Dispersion Coefficient Prediction Using Empirical Models and ANNs

The concentration of a conservative pollutant is changed along a river, as a result of transport processes. The dispersion coefficient is the most important parameter of mass transport in rivers. In this paper, the dispersion coefficient was estimated in a section of Axios River, with the analytical procedure of Fischer method, under different hydrological and hydrodynamic conditions. An empirical equation and a model of artificial neural networks (ANNs) for dispersion coefficient were proposed, based on the data estimated with analytical Fischer method. The dispersion coefficients predicted by the proposed models and other empirical equations reported in earlier studies were compared to the coefficients obtained in the present study. The most accurate equations for dispersion coefficient were used to predict the concentration of conservative toxic pollutants released instantaneously in Axios River upstream of the border of Greece-Former Yugoslav Republic of Macedonia (FYROM).

Solutions of one-dimensional water flow and mass transport equations in variably saturated porous media by the finite element method.

Abstract The Galerkin finite element method is used to solve problems of one-dimensional, vertical flow of water and mass transport of conservative solutes in variably saturated porous media. The method is applied to solve the original equation of mass transport, where Greens theorem is used to remove the second derivatives, either of the total mass flux (convection and dispersion) term or of the flux due only to dispersion. The method is also applied to solve a modified mass transport equation. In all cases, linear one-dimensional elements are used. The resulting computational schemes are applied to (a) a clay loam soil, where the flow conditions lead to small Peclet numbers ranging from 0.5 to 2.4, (b) a sandy soil, where the Peclet numbers ranged from 7.5 to 32.7, and (c) another sandy soil, where the Peclet numbers are large and ranged from 24 to 50. The modified mass transport equation gives better results than does the original equation. Comparison of the solutions obtained by the application of the original equation shows that the results obtained by removing the second derivatives of the dispersion term are close to those obtained by the modified equation.

Modeling of water and nitrogen balance in the ponded water of rice fields

A water and nitrogen balance model for the surface ponded water compartment of rice fields was developed. The model estimates the daily ponded water depth and the daily losses and the uses of NH4–N and NO3–N in their transformation processes. The model was applied with data obtained from two rice fields during 2005 at Thessaloniki plain in northern Greece. Significant amounts of applied irrigation water were lost with the surface runoff and deep percolation to groundwater. The gaseous losses of nitrogen (volatilization and denitrification) and nitrogen uptake by algae were the main processes of nitrogen reduction in the ponded water of rice fields. The study showed that the system of a rice field is a natural system where an important amount of influent nitrogen applied by irrigation water can be reduced. These processes decrease the possibilities of water resources contamination.

Daily reference evapotranspiration estimates by artificial neural networks technique and empirical equations using limited input climate variables

Empirical equations of ETo compared to Penman-Monteith method.ANNs model based on daily meteorological data estimate accurate ETo.ANNs models estimate with slightly lower accuracy ETo with less input variables.Different years training datasets give different testing results of ETo. The artificial neural networks (ANN) and the empirical methods of Priestley-Taylor, Makkink, Hargreaves and mass transfer were used to estimate the reference evapotranspiration with daily meteorological data. These datasets consisted of daily meteorological measurements from a station in northern Greece, covering a period of five years (20092013). The daily values of the reference evapotranspiration were calculated using the Penman-Monteith equation. Those datasets were used for training and testing the ANN. The algorithm that was used is of the multi-layer feed forward artificial neural networks and of the back-propagation for optimization. The architecture that was finally chosen has the 4-6-1 structure, with 4 neurons in the input layer, 6 neurons in the hidden layer and 1 neuron in the output layer which corresponds to the reference evapotranspiration, using a sigmoid transfer function. The ANNs models estimate ETo with an accuracy of a root mean square error (RMSE) ranged from 0.574 to 1.33mmd1, and correlation coefficient (r) from 0.955 to 0.986. Using limited input variables (3 or 2) for training the ANNs result in ETo values with slightly lower accuracy. The RMSE ranged from 0.598 to 0.954mmd1 and r ranged from 0.952 to 0.978 when 3 inputs variables were used, and RMSE of 0.846 to 1.326mmd1 and r of 0.910 to 0.956 when 2 input variables were used. The Priestley-Taylor and Makkink methods correlated very well with the Penman-Monteith method followed by the Hargreaves method which overestimates the higher values of ETo. The mass transfer method also correlated satisfactorily but it underestimated the ETo values.

Modelling of soil water dynamics in an irrigated corn field using direct and pedotransfer functions for hydraulic properties.

A simulation study of the soil waterdynamics in a corn field was carried out inan area of Northern Greece during the 1996growing period. The soil water dynamicswere evaluated using a one-dimensionalmodel based on the Galerkin finite elementmethod. The simulations were carried out ontwo plots in the field which differed as tothe amount and timing of nitrogenfertilizer application. The irrigationwater was applied to the field ininadequate quantities, which resulted inlow water availability. Two procedures forobtaining soil hydraulic properties weretested with regard to the application inthe simulations. The pedotransfer functionsdeveloped by Vereecken et al. (1989,1990) were used to determine the parametersof the soil hydraulic functions, which werethen used in the model to simulate the soilwater dynamics. The simulated results werecompared with available measurements ofwater content at different depths in thesoil during the growing period. Thequalitative and quantitative procedures formodel evaluation showed that there was goodagreement between the simulated and themeasured values of water content atdifferent depths of soil. Results show thatsimulations based on pedotransfer functionspredict the water content reasonably wellcompared to results with the directedestimated hydraulic functions.