Pantazis Georgiou

Optimization model of an irrigation reservoir for water allocation and crop planning under various weather conditions

This paper develops a non-linear programming optimization model with an integrated soil water balance, to determine the optimal reservoir release policies, the irrigation allocation to multiple crops and the optimal cropping pattern in irrigated agriculture. Decision variables are the cultivated area and the water allocated to each crop. The objective function of the model maximizes the total farm income, which is based on crop–water production functions, production cost and crop prices. The proposed model is solved using the simulated annealing (SA) global optimization stochastic search algorithm in combination with the stochastic gradient descent algorithm. The rainfall, evapotranspiration and inflow are considered to be stochastic and the model is run for expected values of the above parameters corresponding to different probability of exceedence. By combining various probability levels of rainfall, evapotranspiration and inflow, four weather conditions are distinguished. The model takes into account an irrigation time interval in each growth stage and gives the optimal distribution of area, the water to each crop and the total farm income. The outputs of this model were compared with the results obtained from the model in which the only decision variables are cultivated areas. The model was applied on data from a planned reservoir on the Havrias River in Northern Greece, is sufficiently general and has great potential to be applicable as a decision support tool for cropping patterns of an irrigated area and irrigation scheduling.

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.

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).

Calibration equations for two capacitance water content probes

Calibration equations for two capacitance water content probes This paper presents the calibration equations of two capacitance probes for monitoring the soil water content in a lysimeter field. Capacitance probes provide readings at desired depths and time intervals. The calibration equations are derived by regression analysis between measurements of scaled frequency and volumetric soil water content. The calibration equations are compared with the manufacturer default equations to estimate the irrigation water depth. The accuracy of capacitance probes in monitoring soil water content increased by using the site-specific calibration equations rather than the manufacturer default equation.

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.

Evapotranspiration and simulation of soil water movement in small area vegetation

Abstract In Greece, crops are frequently cultivated in small isolated areas in close proximity to roads and bare soils and therefore evapotranspiration is affected by local advection. Under these circumstances, oasis effect conditions are present and evapotranspiration is higher than what is expected. In this paper, the evapotranspiration and soil water dynamics of a cotton crop cultivated in small areas under the oasis effect is studied. To this end, two isolated free-drainage lysimeters cultivated with cotton in the year 2007 were used. Soil moisture of the soil profile of both the lysimeters was monitored with two capacitance water content probes. The soil water balance method was used to estimate crop evapotranspiration and corresponding crop coefficients in one of the two lysimeters. These coefficients were 75% larger than the FAO-56 crop coefficients at the mid-season stage. The FAO-56 and the derived crop coefficients were used for the simulation of the water dynamics in the second lysimeter by the SWBACROS model. The derived crop coefficients for these conditions produced much better results than the FAO-56 crop coefficients. The results were improved when crop coefficient value equal to 2.5 was used for the mid-season stage.

Application of stochastic models to rational management of water resources at the Damasi Titanos karstic aquifer in Thessaly Greece

Several stochastic models, known as Box and Jenkins or SARIMA (Seasonal Autoregressive Integrated Moving Average) have been used in the past for forecasting hydrological time series in general and stream flow or spring discharge time series in particular. SARIMA models became very popular because of their simple mathematical structure, convenient representation of data in terms of a relatively small number of parameters and their applicability to stationary as well as nonstationary process. The application of SARIMA model to the Mati spring’s monthly discharge time series for the period 1974-2007 at Damasi Titanos karst system yielded the following results. The stationary is obtained by logarithmic transformation and the suitable model (2,0,0)(0,1,1)12 is selected by different criteria. This type of model is suitable for the Damasi Titanos karst aquifer simulation and can be utilised as a tool to forecast monthly discharge values at Mati spring for at least a 4 year period. SARIMA model seem to be capable of simulating both runoff and groundwater flow conditions on a karst system and also easily adapt to their natural conditions.

Evaluating three different model setups in the MIKE 11 NAM model

In this paper, the NAM model was applied in the Strymonas River catchment to simulate the daily discharge that ends up into the Lake Kerkini. In the NAM model, the catchment is represented by four reservoirs, each one representing different physical elements of the catchment. The model uses precipitation, potential evapotranspiration and temperature as driving forces in the simulation of snow accumulation and melting, interception, actual evapotranspiration, overland flow, interflow, groundwater recharge and baseflow. Optimal calibration of the model parameters was obtained for three different model setups by using meteorological and discharge data. The model was also validated against discharge data. The NAM model was used to estimate the continuous Strymonas River mean daily discharge and the results show that the estimation accuracy is depended by the model setup.