54 resultados para localized irrigation


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A self-consistent relativistic two-fluid model is proposed for electron-ion plasma dynamics. A one-dimensional geometry is adopted. Electrons are treated as a relativistically degenerate fluid, governed by an appropriate equation of state. The ion fluid is also allowed to be relativistic, but is cold, nondegenerate, and subject only to an electrostatic potential. Exact stationary-profile solutions are sought, at the ionic scale, via the Sagdeev pseudopotential method. The analysis provides the pulse existence region, in terms of characteristic relativistic parameters, associated with the (ultrahigh) particle density.

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A study was undertaken to determine the effects of different concentrations of arsenic (As) in irrigation water on Boro (dry-season) rice (Oryza sativa) and their residual effects on the following Aman (wet-season) rice. There were six treatments, with 0, 0.1, 0.25, 0.5, 1, and 2 mg As L-1 applied as disodium hydrogen arsenate. All the growth and yield parameters of Boro rice responded positively at lower concentrations of up to 0.25 mg As L-1 in irrigation water but decreased sharply at concentrations more than 0.5 mg As L-1. Arsenic concentrations in grain and straw of Boro rice increased significantly with increasing concentration of As in irrigation water. The grain As concentration was in the range of 0.25 to 0.97 μg g-1 and its concentration in rice straw varied from 2.4 to 9.6 μg g-1 over the treatments. Residual As from previous Boro rice showed a very similar pattern in the following Aman rice, although As concentration in Aman rice grain and straw over the treatments was almost half of the As levels in Boro rice grain. Arsenic concentrations in both grain and straw of Boro and Aman rice were found to correlate with iron and be antagonistic with phosphorus. Copyright © Taylor & Francis Group, LLC.

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The last decade has witnessed an unprecedented growth in availability of data having spatio-temporal characteristics. Given the scale and richness of such data, finding spatio-temporal patterns that demonstrate significantly different behavior from their neighbors could be of interest for various application scenarios such as – weather modeling, analyzing spread of disease outbreaks, monitoring traffic congestions, and so on. In this paper, we propose an automated approach of exploring and discovering such anomalous patterns irrespective of the underlying domain from which the data is recovered. Our approach differs significantly from traditional methods of spatial outlier detection, and employs two phases – i) discovering homogeneous regions, and ii) evaluating these regions as anomalies based on their statistical difference from a generalized neighborhood. We evaluate the quality of our approach and distinguish it from existing techniques via an extensive experimental evaluation.

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In this paper we compare conceptualising single factor technical and allocative efficiency as indicators of a single latent variable, or as separate observed variables. In the former case, the impacts on both efficiency types are analysed by means of structural equation modeling (SEM), in the latter by seemingly unrelated regression (SUR). We compare estimation results of the two approaches based on a dataset on single factor irrigation water use efficiency obtained from a survey of 360 farmers in the Guanzhong Plain, China. The main methodological findings are that SEM allows identification of the most important dimension of irrigation water efficiency (technical efficiency) via comparison of their factor scores and reliability. Moreover, it reduces multicollinearity and attenuation bias. It thus is preferable to SUR. The SEM estimates show that perception of water scarcity is the most important positive determinant of both types of efficiency, followed by irrigation infrastructure, income and water price. Furthermore, there is a strong negative reverse effect from efficiency on perception.

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In this paper, an automatic Smart Irrigation Decision Support System, SIDSS, is proposed to manage irrigation in agriculture. Our system estimates the weekly irrigations needs of a plantation, on the basis of both soil measurements and climatic variables gathered by several autonomous nodes deployed in field. This enables a closed loop control scheme to adapt the decision support system to local perturbations and estimation errors. Two machine learning techniques, PLSR and ANFIS, are proposed as reasoning engine of our SIDSS. Our approach is validated on three commercial plantations of citrus trees located in the South-East of Spain. Performance is tested against decisions taken by a human expert.

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This article analyses adoption of farm-based irrigation water saving techniques, based on a cross-sectional data set of 357 farmers in the Guanzhong Plain, China. Approximately 83% of the farmers use at least one farm-based water-saving technique. However, the traditional, inefficient techniques border and furrow irrigation are still prevalent whereas the use of advanced, more efficient techniques is still rather rare. We develop and estimate an adoption model consisting of two stages: awareness of water scarcity and intensity of adoption. We find that awareness of water scarcity and financial status enhance adoption of more advanced techniques whereas access to better community-based irrigation infrastructure discourages it. We furthermore find both community-based irrigation infrastructure and farm-based irrigation water-saving techniques have mitigating effects on production risk. From the results it follows that adoption can be stimulated via financial support and via extension aimed at enhancing awareness of water scarcity.

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In this work, the general framework in which fits our investigation is that of modeling the dynamics of dust grains therein dusty plasma (complex plasma) in the presence of electromagnetic fields. The generalized discrete complex Ginzburg-Landau equation (DCGLE) is thus obtained to model discrete dynamical structure in dusty plasma with Epstein friction. In the collisionless limit, the equation reduces to the modified discrete nonlinear Schrödinger equation (MDNLSE). The modulational instability phenomenon is studied and we present the criterion of instability in both cases and it is shown that high values of damping extend the instability region. Equations thus obtained highlight the presence of soliton-like excitation in dusty plasma. We studied the generation of soliton in a dusty plasma taking in account the effects of interaction between dust grains and theirs neighbours. Numerical simulations are carried out to show the validity of analytical approach.

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Raman analysis of dilute aqueous solutions is normally prevented by their low signal levels. A very general method to increase the concentration to detectable levels is to evaporate droplets of the sample to dryness, creating solid deposits which are then Raman probed. Here, superhydrophobic (SHP) wires with hydrophilic tips have been used as supports for drying droplets, which have the advantage that the residue is automatically deposited at the tip. The SHP wires were readily prepared in minutes using electroless galvanic deposition of Ag onto copper wires followed by modification with a polyfluorothiol (3,3,4,4,5,5,6,6,7,7,8,8,9,9,10,10,10-heptadecafluoro-1-decanethiol, HDFT). Cutting the coated wires with a scalpel revealed hydrophilic tips which could support droplets whose maximum size was determined by the wire diameter. Typically, 230 μm wires were used to support 0.6 μL droplets. Evaporation of dilute melamine droplets gave solid deposits which could be observed by scanning electron microscopy (SEM) and Raman spectroscopy. The limit of detection for melamine using a two stage evaporation procedure was 1 × 10-6 mol dm-3. The physical appearance of dried droplets of sucrose and glucose showed that the samples retained significant amounts of water, even under high vacuum. Nonetheless, the Raman detection limits of sucrose and glucose were 5 × 10-4 and 2.5 × 10-3 mol dm-3, respectively, which is similar to the sensitivity reported for surface-enhanced Raman spectroscopy (SERS) detection of glucose. It was also possible to quantify the two sugars in mixtures at concentrations which were similar to those found in human blood through multivariate analysis.