Ido Seginer

Aerodynamic roughness of vegetated surfaces

Available experimental results indicate that as the density of roughness elements over a horizontally homogeneous surface is varied, the roughness length, z0, varies in a manner that exhibits a maximum at intermediate density values. In an attempt to explain this behaviour, the available analytical solutions for the wind profile inside dense homogeneous canopies were reviewed. The review indicated that the variation of z0 with density depends on the interrelationship between the leaf density, a, and the mixing length, l. In view of this finding, a numerical model was devised based on a simple rule for constructing mixing-length profiles in the canopy. The rule states that the actual value of l is the maximum possible under the two constraints: l ⩽ li and ¦dl/dz¦ ⩽ k, where k is the von Karman constant and the intrinsic mixing length, li, is a function of the local internal structure of the canopy. The model which ensures a smooth transition from dense to thin canopy, was used to reproduce the observed maximum of z0. The model is also capable of handling vertically non-homogeneous canopies.

Gully development and sediment yield

Abstract Several methods are presented which may be helpful in quantitative gully erosion studies. Advancement rate of gully heads is related to watershed area, and sediment yield of a gully system is calculated and compared with trapped sediments. A model of gully system development is suggested and the discrepancies between various results are discussed.

Some artificial neural network applications to greenhouse environmental control

Abstract A review is presented of several potentially useful applications of artificial neural networks (NN) to greenhouse climate control. Subjects covered are: Quasi-steady-state modelling, reduction (compression) of input and state vectors, NNs used as difference equations and replacing controllers (algorithms or humans) with NNs. In this context the strength of NNs is their flexibility to adapt to non-linear and non-physical data. Their main disadvantage is that their proper training requires large multi-dimensional sets of data to reduce the risk of extrapolation. Therefore, minimizing the dimensionality of the problem (both input and state vectors) becomes of paramount importance. Bottleneck NNs may be used for this purpose.

A Note on the Economic Significance of Uniform Water Application

SummaryIt is shown how a yield vs water application diagram, with uniformity of water-distribution and price of water as parameters, can be used to determine the optimum water application and the expected income for a certain crop. The diagram can further be used to explore the possible outcome of changing water uniformity and/or price. The diagram is based on simplified forms of the yield and water-distribution functions.

Optimal CO2 control in a greenhouse modeled with neural networks

Abstract CO2 enrichment in warm climates requires a delicate balance between the need to ventilate and the desire to enrich. Model-based optimization can achieve this balance, but requires reliable models of the greenhouse environment and of the crop response. This study assumes that the crop response is known, and focuses on the greenhouse model. Neural network greenhouse models were trained using data collected over two summer months in a small greenhouse. The models were reduced to minimum size, by predicting separately the temperature and CO2 concentration, and by eliminating any unessential input. The resulting models not only fit the data well, they also seem qualitatively correct, and produce reasonable optimization results. Using these models, the effect of evaporative cooling on extending the enrichment duration is demonstrated.

The distortion by wind of the distribution patterns of single sprinklers

Abstract The distribution patterns of sprinklers are modified, under field conditions, by drift, evaporation and distortion, caused by wind and evaporative demand of the air. To evaluate experimentally spray loss (evaporation plus drift), collector evaporation must be suppressed or corrected for. Here an approximate correction, based on the measured evaporation from peripheral collectors, was applied to the data. It was further assumed that spray loss is distributed over the pattern in proportion to the local rate of water application. Based on experimental results, a set of wind distorted patterns for wind speeds of 0, 2, 4, 6 and 8 m/s was obtained. These can be used for simulation under conditions similar to those encountered during the experiment. The patterns can be interpolated for any desired wind-speed, rotated to the required direction and then corrected for the spray-loss appropriate to the environmental conditions.

Atmospheric-stability effect on windbreak shelter and drag

Wind speed was measured near the surface, along a line normal to a single, 50% porous windbreak, to determine its wind-reducing effect. Simultaneously, undisturbed wind and temperature profiles were measured to obtain the atmospheric stability. In some of the runs, the drag on a section of the windbreak was also measured.A systematic and significant effect of the atmospheric stability was found. The relative wind speed at any distance from the windbreak could be expressed for unstable conditions as an empirical function of the Richardson number. As an extreme example, the reduction of the surface shear, at a downwind distance 7.5 times the height of the windbreak, was 86 % in adiabatic conditions, and only 62 % when the gradient Richardson number at the windbreak height was −1.0. The minimum relative effect was found in the neighborhood of the windbreak, where the windbreak-induced turbulence was dominant. The maximum absolute effect was found at a downwind distance of about ten times the height of the windbreak.The drag coefficient of the windbreak was found to becd=0.77 in a neutral atmosphere, increasing slightly with instability. This trend is contrary to the trend of the surface-shear-reduction coefficient, which decreases significantly with instability.

Calculation of velocity skewness in real and artificial plant canopies

Wind velocities within a plant canopy are much more strongly skewed than those of the air flow above. We have examined the governing Eulerian equations for the velocity products u′i, u′j u′k using data from a wind tunnel study with an artificial canopy consisting of an array of 5 cm lengths of monofilament fishing line, and from measurements in corn (Zea mays L).Simple parameterizations for pressure-velocity correlations, and for the quadruple velocity products allowed reasonably accurate calculations of the third moments using measured profiles of the mean velocity, variance and covariance fields. Comparisons of individual terms in the rate equations for ovu′i, u′ju′krevealed that diffusion (from above) and mean shear were most important in creating large skewness in the canopy. A drag term also contributed but was of lesser importance. These terms were balanced by return-to-isotropy and a turbulence interaction term. A quasi-Gaussian approximation considerably underestimated the magnitude of the fourth moments within the canopy.

Optimal temperature regimes for a greenhouse crop with a carbohydrate pool: A modelling study

Abstract A simple crop model with two state variables, namely structural biomass and carbohydrate pool, was used to explore the effect of alternative temperature regimes on greenhouse crop production. Assuming a repeated environmental cycle, certain qualitative predictions could be made. (1) The smaller the plants and the higher the light integral and CO2 enrichment, the higher are the temperatures which lead to maximum production. (2) Day temperatures higher than night temperatures usually lead to higher production. On winter days, however, an inverse temperature regime may result in energy saving without loss of production. (3) Temperature variations may often be tolerated, provided that the mean temperature (temperature integral) is maintained at the level appropriate for maximum production. A limited amount of published experimental data was used to fit the model, leading to a satisfactory agreement.

Optimal temperature setpoints for greenhouse lettuce

A two state-variable greenhouse lettuce model is formulated and used to optimize dynamically the daytime temperature setpoint of the greenhouse. Pontryagins Maximum Principle is used to solve the problem numerically. The resulting control strategy recommends that initially leaf area expansion should be promoted, while later on, when the canopy fully covers the soil, the emphasis should be shifted to dry matter accumulation. This is reflected in a decreasing temperature setpoint during the growing period. Day-to-day fluctuations in response to the changing weather are superimposed on the general trend. While this result is consistent with the physiology of the modelled crop, the projected economic gain, compared with the results for the best constant temperature setpoint, was found to be small.