Solar photovoltaic systems have become one of the most popular topics in the water management industry. Moreover, irrigation networks are water- and energy-hungry, and utility managers are likely to adapt water consumption (and consequently energy demand) to the hours in which there is energy availability. In countries such as Spain (with high irradiance values), solar energy is an available green alternative characterised by zero electricity costs and significantly lower environmental impact. In this work, several types of irrigation scheduled programmes (according to different irrigation sectors) that minimise the number of photovoltaic solar panels to be installed are studied; moreover, the effects of the variable costs linked to energy (energy and emissions costs) are presented. Finally, the effect of incorporating batteries for storing energy to protect the system against emergencies, such as unfavourable weather, is proposed. The irrigation hours available to satisfy water demands are limited by sunlight; they are also limited by the condition that the irrigation schedule type has to be rigid (predetermined rotation) and that the pressure at any node has to be above minimum pressure required by standards. A real case study is performed, and the results obtained demonstrate that there is no universal solution; this is because the portfolio of alternatives is based on investments for purchasing equipment at present and also on future energy savings (revenues). Apart from these two values, there is an economic value (equivalent discontinuous discount rate), which also influences the final results.

Agro-hydrological models are considered an economic and simple tool for quantifying crop water requirements. In the last two decades, agro-hydrological physically based models have been developed to simulate mass and energy exchange processes in the soil-plant-atmosphere system. Although very reliable, because of the high number of required variables, simplified models have been proposed to quantify crop water consumes. The main aim of this paper is to propose an amendment of the Food and Agricultural Organization (FAO) of the United Nations FAO-56 spreadsheet program to introduce a more realistic shape of the stress function, valid for mature olive orchards (Olea europaea L.). The modified model is successively validated by means of the comparison between measured and simulated soil water contents and actual transpiration fluxes. These outputs are finally compared with those obtained with the original version of the model. Experiments also allowed assessing the ability of simulated crop water stress coefficients to explain the actual water stress conditions evaluated on the basis of measured relative transpirations and midday stem water potentials. The results show that the modified model significantly improves the estimation of actual crop transpiration fluxes and soil water contents under soil water deficit conditions, according to the RMSEs associated with the revised model, resulting in significantly higher than the corresponding values obtained with the original version

This paper describes the application of artificial neural networks (ANNs) for estimating reference evapotranspiration ( ETo ) as a function of local maximum and minimum air temperatures as well as exogenous relative humidity and reference evapotranspiration in different continental contexts of the autonomous Valencia region, on the Spanish Mediterranean coast. The development of new and more precise models for ETo prediction from minimum climatic data is required, since the application of existing methods that provide acceptable results is limited to those places where large amounts of reliable climatic data are available. The Penman-Monteith model for ETo prediction, proposed by the FAO as the sole standard method for ETo estimation, was used to provide the ANN targets for the training and testing processes. Concerning models which demand scant climatic inputs, the proposed model provides performances with lower associated errors than the currently existing temperature-based models, which only consider l...

Due to the fact that irrigation networks are water and energy hungry and that both resources are scarce, many strategies have been developed to reduce this consumption. Solar energy sources have emerged as a green alternative with lower energy costs and, consequently, lower environmental impacts. In this work, a new methodology is proposed to select a scheduled program for irrigation which minimizes the number of photovoltaic solar panels to be installed and which better fits energy consumption (calculated for discrete potential combinations, assisted by programming software) to available energy obtained by panels without any power conditioning unit. Thus, the irrigation hours available to satisfy the water demands are limited by sunlight, the schedule type of irrigation has to be rigid (rotation predetermined), and the pressure at any node has to be above the minimum pressure required by standards. A case study was undertaken and, after running the software 10⁵ times, the best result was an irrigation schedule which satisfied all the requirements, involving the installation of 651 solar panels and energy consumption of 428.74 kWh per day, to deliver water to orchards of different varieties of citrus fruit spread over 167.7 ha.