Pablo González-Altozano

Reference evapotranspiration estimation without local climatic data

The Penman–Monteith equation for reference evapotranspiration (ETo) estimation cannot be applied in many situations, because climatic records are totally or partially not available or reliable. In these cases, empirical equations that rely on few climatic variables are necessary. Nevertheless, the uncertainty associated with empirical model estimations is often high. Thus, the improvement of methods relying on few climatic inputs as well as the development of emergency estimation tools that demand no local climatic records turns into a task of great relevance. The present study describes different approaches based on multiple linear regression, simple regression and artificial neural networks (ANNs) to deal with ETo estimation exclusively from exogenous records from secondary stations. This cross-station approach is based on a continental characterization of the study region, which enables the selection and hierarchization of the most suitable ancillary data supplier stations. This procedure is compared with different traditional and cross-station approaches, including methodologies that also consider local temperature inputs. The proposed methods are also evaluated as gap infilling procedures and compared with a simple methodology, the window averaging. The artificial neural network and the multiple linear regression approaches present very similar performance accuracies, considerably higher than simple regression and traditional temperature-based approaches. The proposed input combinations allow similar performance accuracies as ANN models relying on exogenous ETo records and local temperature measurements. The cross-station multiple linear regression procedure is recommended due to its higher simplicity.

Three-Dimensional Modeling and Geometrical Influence on the Hydraulic Performance of a Control Valve

The ability to understand and manage the performance of hydraulic control valves is important in many automatic and manual industrial processes. The use of computational fluid dynamics (CFD) aids in the design of such valves by inexpensively providing insight into flow patterns, potential noise sources, and cavitation. Applications of CFD to study the performance of complex three-dimensional (3D) valves, such as poppet, spool, and butterfly valves, are becoming more common. Still, validation and accuracy remain an issue. The Reynolds-averaged Navier-Stokes equations were solved numerically using the commercial CFD package FLUENT V6.2 to assess the effect of geometry on the performance of a 3D control valve. The influence of the turbulence model and of a cavitation model was also investigated. Comparisons were made to experimental data when available. The 3D model of the valve was constructed by decomposing the valve into several subdomains. Agreement between the numerical predictions and measurements of flow pressure was less than 6% for all cases studied. Passive flow control, designed to minimize vortical structures at the piston exit and reduce potential cavitation, noise, and vibrations, was achieved by geometric smoothing. In addition, these changes helped to increase C υ and reduce the area affected by cavitation as it is related to the jet shape originated at the valve throat. The importance of accounting for full 3D geometry effects in modeling and optimizing control valve performance was demonstrated via CFD. This is particularly important in the vicinity of the piston. It is worth noting that the original geometry resulted in a lower C υ with higher velocity magnitude within the valve, whereas after smoothing C υ increased and served to delay cavitation inception.

Mathematical Model for Predicting and Estimating Evapotranspiration in Valencia Region, Spain

The Potential Evapotranspiration (ETo) is a powerful and useful tool in order to estimate and manage the amount of water that it is necessary for irrigating crops and trees. Several equations can be used for calculating ETo, although Penman-Monteith equation is the most accurate equation, function of the temperature, relative humidity, wind velocity and net radiation. Moreover, ETo is currently obtained from sparsely located weather stations around different zones or states. These values are often extrapolated for calculating the requirements within a zone or it is directly taken into account the nearest station from the crop. However, the limitations in the number of stations make sometimes that this procedure does not fit perfectly with the real water requirements of the plants. On the other hand, meteorology mathematical models for predicting weather behaviour have been developed over the last years based on basic fluid dynamics equations (Conservation of the mass, momentum and energy equations). Its usage has been validated in many studies for environmental and climatology studies. In the present paper, the authors have been used a mathematical model, RAMS, for evaluating the ETo around a wide zone, using the standard and homogeneous data in the Region of Valencia, Spain. The results show that this tool is a very powerful way to calculate ETo from sparsely stations. This ETo map has been obtained from a mathematical model, instead of extrapolating empirical values from the stations around a zone.