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The designer of irrigation systems must consider a complex combination of emitter type, emitter uniformity, hydraulics, topography, desired water distribution, crop salt tolerance, water requirements, water quality, fertilizer injection, soil salinity, cultural practices, and other site-specific conditions. In contrast to the approaches applied for the hydraulic design of irrigation installations, there is not a clear, general and consolidated design criterion for calculating the number required emitters per plant. In most cases, given the wide spectrum of possible scenarios, only guideline recommendations can be found, and the final decision is often based on the subjective experience of the designer or grower. This paper aims at revising, clarifying and refining the existing published guidelines and methodologies for estimating the required emitters per plant in drip irrigation, focussing on the Montalvo approach. The agronomic design should satisfy, among others, two specific conditions: (i) the emitters should wet at least a minimum threshold of the soil area (or volume) corresponding to the plant for ensuring a proper development of the roots; (ii) overlapping between emitter bulbs is required for merging wetted volumes and avoiding salt concentration near the root zone. Relying on this basis, a thorough theoretical geometric analysis of the overlapping between wet bulbs of contiguous emitters is carried out. As a result, Montalvo's overlapping coefficients are deduced here. This author assumes an identical net wetted area for all emitters in the laterals, but it can be stated that the overlapping areas between emitters differ in extreme emitters and interior emitters, as well as in configurations with one lateral per plant row and two laterals per plant row. Therefore, this study proposes new formulations for the computation of the overlapping coefficient, which need to incorporate the number of emitters as an additional variable, as well as to distinguish between the presence of one or two laterals per plant row, and between grouped and non-grouped emitters. In one lateral per plant row, the original overlapping coefficient underestimates the net wetted area by one emitter and thus overestimates the theoretical number of required emitters. In the case of two laterals per plant row, the original overlapping coefficient overestimates the net wetted area in the interior emitters, and thus underestimates the theoretical number of required emitters per plant. The presented formulations are applied in different practical examples covering a wide range of scenarios. The results allow a general overview of the influence of the soil type, the emitter flow rate, and the selected overlapping ratio in the number of required emitters per plant. The revision of guidelines and methods presented here, complemented with other experimental results and models of soil water dynamics under drip irrigation, might contribute to a better decision making of designers and field engineers. [ABSTRACT FROM AUTHOR]

The presence of emitters along the lateral, as well as of connectors along the manifold, causes additional local head losses other than friction losses. An accurate estimation of local losses is of crucial importance for a correct design of microirrigation systems. This paper presents a procedure to assess local head losses caused by 6 lateral start connectors of 32- and 40-mm nominal diameter each under actual hydraulic working conditions based on artificial neural networks (ANN) and gene expression programming (GEP) modelling approaches. Different input–output combinations and data partitions were assessed to analyse the hydraulic performance of the system and the optimum training strategy of the models, respectively. The range of the head losses in the manifold (hsM) is considerable lower than in the lateral (hsL). hsM increases with the protrusion ratio (s/S). hsL does not decrease for a decreasing s/S. There is a correlation between hsL and the Reynolds number in the lateral (ReL). However, this correlation might also be dependent on the flow conditions in the manifold before the derivation. The value of the head loss component due to the protrusion might be influenced by the flow derivation. DN32 connectors and hsM present more accurate estimates. Crucial input parameters are flow velocity and protrusion ratio. The inclusion of friction head loss as input also improves the estimating accuracy of the models. The range of the indicators is considerably worse for DN40 than for DN32. The models trained with all patterns lead to more accurate estimations in connectors 7 to 12 than the models trained exclusively with DN40 patterns. On the other hand, including DN40 patterns in the training process did not involve any improvement for estimating the head losses of DN32 connectors. ANN were more accurate than GEP in DN32. In DN40 ANN were less accurate than GEP for hsM, but they were more accurate than GEP for hsL, while both presented a similar performance for hscombined. Different equations were obtained using GEP to easily estimate the two components of the local loss. The equation that should be used in practice depends on the availability of inputs. [ABSTRACT FROM AUTHOR]

The article discusses the article "Hydraulic and Statistical Analyses of Design Emission Uniformity of Trickle Irrigation Systems," by Jafar Safaa Noori and Hayder A. Al Thamiry that was published in a September 2012 issue of the "Journal of Irrigation & Drainage Engineering." Topics discussed include the validity of a formula on trickle irrigation, the design criterion for a drip irrigation, and flow rates. Also mentioned are manufacturing uniformity and hydraulic emission uniformity.

Highlights: [•] Accurate estimation of outlet dissolved oxygen allows to improve the management of sand filters. [•] ANN, GEP and MLR based models were evaluated for estimating dissolved oxygen at sand filter outlet through k-fold testing. [•] GEP tended to provide the most accurate estimations. [•] New GEP based expression for estimating DOo is provided. [•] At least k-fold testing should be considered for a suitable model performance evaluation. [Copyright &y& Elsevier]

This paper describes an application of artificial neural networks (ANNs) to the prediction of local losses from integrated emitters. First, the optimum input-output combination was determined. Then, the mapping capability of ANNs and regression models was compared. Afterwards, a five-input ANN model, which considers pipe and emitter internal diameter, emitter length, emitter spacing, and pipe discharge, was used to develop a local losses predicting tool which was obtained from different training strategies while taking into account a completely independent test set. Finally, a performance index was evaluated for the test emitter models studied. Emitter data with low reliability were removed from the process. Performance indexes over 80% were obtained for the remaining test emitters. [ABSTRACT FROM AUTHOR]