Evaporation Losses from Sprinkler Irrigation Systems under Various Operating Conditions

Bavi, A.; Kashkuli, Heydar Ali; Boroomand, S.; Naseri, Abd Ali; Albaji, Mohammad

doi:10.3923/jas.2009.597.600

Cited by 26 publications

(18 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Several authors (Basahi et al 1998;Bautista et al 2009;Bavi et al 2009;Eigel and Moore 1983;Kincaid et al 1996;Kohl and DeBoer 1985;Li et al 1994;Montero et al 2003;Salvador et al 2009;Sudheer and Panda 2000) have experimentally confirmed this behavior in sprinkler irrigation systems. Figure 6 depicts the cumulative drop diameter frequency (Fig.…”

Section: Distribution Of Drop Diametersmentioning

confidence: 88%

“…These losses are commonly estimated from the difference between the amount of water discharged by the sprinkler and the amount of water collected at catch cans distributed along the field. WDEL directly depend on climatic and operational conditions (Bavi et al 2009), including drop diameter. Additionally, a number of papers have focused on the effect of drops' impact on soil properties (Seginer 1965;Kohl et al 1985;Thompson and James 1985;Kincaid 1996;Basahi et al 1998;Bautista et al 2012).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A particle tracking velocimetry technique for drop characterization in agricultural sprinklers

et al. 2014

View full text Add to dashboard Cite

A variety of techniques have been proposed in the literature for sprinkler drop characterization. An optical Particle Tracking Velocimetry (PTV) technique is proposed in this paper to determine drop velocity, diameter and angle. The technique has been applied to the drops emitted by an isolated impact sprinkler equipped with two nozzles (diameters 3.20 mm and 4.37 mm) operating at a pressure of 175 kPa. PTV has been previously used to determine the velocity vector of different types of particles. In this research, PTV was used to photograph sprinkler drops over a region illuminated with laser light. Photographs were taken at four horizontal distances from the sprinkler, which was located at an elevation of 1.65 m over the soil surface. Drop angle and velocity were derived from the displacement of the drop centroid in two images separated by a short time step. Centrality and dispersion parameters were obtained for each drop variable and observation point. Results derive from the analysis of 2,360 images. Only 37.5% of them (884 images) contained drops which could be processed by the PTV algorithm, resulting in

show abstract

Section: Distribution Of Drop Diametersmentioning

confidence: 88%

Section: Introductionmentioning

confidence: 99%

A particle tracking velocimetry technique for drop characterization in agricultural sprinklers

et al. 2014

View full text Add to dashboard Cite

show abstract

“…Bavi et al . () and McLean et al . () reported that it is necessary to accurately determine the relationship between losses and the parameters of influence.…”

Section: Introductionmentioning

confidence: 94%

Estimation of Wind Drift and Evaporation Losses from Sprinkler Irrigation systemS by Different Data‐Driven Methods

Maroufpoor

Hadi

Emamgholizadeh

et al. 2017

Irrigation and Drainage

View full text Add to dashboard Cite

An accurate estimation of losses created by wind drift and evaporation is necessary for water management in sprinkler irrigation systems. In the current study, three artificial intelligence (AI) methods, namely artificial neural network (ANN), adaptive neuro‐fuzzy inference system (ANFIS) and gene expression programming (GEP), were used to estimate the wind drift and evaporation losses (WDEL) based on influential variables such as operating pressure (P), wind speed (W), nozzle diameter (D) and vapour pressure deficit (es − ea). Field measurements data were applied to training and testing of ANN, ANFIS and GEP models. The results of these AI models were also compared with previous studies. Three statistical metrics, namely coefficient of determination (R2), root mean square error (RMSE) and mean absolute error (MAE), were utilized to assess the performance of the models. The results indicate that the AI models (i.e. ANFIS, ANN and GEP) predict the WDEL more accurately than in previous studies. Moreover, the results show that the GEP model (with RMSE = 1.19% and R2 = 0.97) provides a better estimation of WDEL compared to the ANN model (with RMSE = 2.56% and R2 = 0.87) and ANFIS model (with RMSE = 1.64% and R2 = 0.94). Copyright © 2017 John Wiley & Sons, Ltd.

show abstract

“…Catch-can based studies have been conducted in the past to measure the WAE of pressurised irrigation systems (Abo-Ghobar, 1992;Bavi, Kashkuli, Boroomand, Naseri, & Albaji, 2009;Christiansen, 1942;Faci, Salvador, Play an, & Sourell, 2001;Frost & Schwalen, 1955;George, 1955;King, Dungan, & Bjorneberg, 2012;Kohl, Kohl, & DeBoer, 1987;Kraus, 1966;McLean, Ranjan, & Klassen, 2000;Musick et al, 1988;Ocampo, Thomas, Hook, & Harrison, 2003;Ortiz et al, 2009;Play an et al, 2005;Robinson, 1973;Seginer, Kantz, & Nir, 1991;Silva, 2006;Sternburg, 1967;Tarjuelo, Montero, Carrion, Honrubia, & Calvo, 1999;Yazar, 1984). The testing usually involved the placement of multiple catch cans in a networked pattern and estimating the amount of water being delivered to the cans (assuming spatial independence of the measurements, Loescher, Powers, & Oberbauer, 2002).…”

Section: Introductionmentioning

confidence: 99%

Novel approach to evaluate the dynamic variation of wind drift and evaporation losses under moving irrigation systems

Sadeghi

Peters

Amini

et al. 2015

Biosystems Engineering

View full text Add to dashboard Cite

Evaporation lossCenter pivot Catch can testWater application efficiency Strip testThe increased need for water and food security requires the development of new approaches to save water through irrigation management strategies, particularly for center pivot irrigation. To do so entails monitoring of the dynamic variation in wind drift and evaporation losses (WDELs) of irrigation systems under different weather conditions and for relatively long time periods. The historical catch can method has limited our ability to address this goal. Here, a new and easy-to implement methodology, called the strip test, was developed and validated against the catch can technique. Our results showed strong agreement between the catch can method and the strip test for determining the average water application efficiency (WAE z 1-WDEL). Because the strip test method was measured for shorter intervals compared to the catch can method, the variables influencing WAE were able to be compared during each test. WAE had a large variance over time, which was controlled, in part, by wind speed (>4 m s À1 ). Site-specific characterisation of WDEL is needed to apply this technique. Once applied, it can provide a better understanding of WAE behaviour over the time, and enhance the capability of predicting results for the optimising water use in sprinkler irrigation.

show abstract

Evaporation Losses from Sprinkler Irrigation Systems under Various Operating Conditions

Cited by 26 publications

References 8 publications

A particle tracking velocimetry technique for drop characterization in agricultural sprinklers

A particle tracking velocimetry technique for drop characterization in agricultural sprinklers

Estimation of Wind Drift and Evaporation Losses from Sprinkler Irrigation systemS by Different Data‐Driven Methods

Novel approach to evaluate the dynamic variation of wind drift and evaporation losses under moving irrigation systems

Contact Info

Product

Resources

About