Wind Drift And Evaporation Losses Research Articles

Estimation of wind drift and evaporation losses of sprinkler irrigation systems using dimensional analysis

Wind Drift and Evaporation Losses (WDEL) critically determine the application efficiency of sprinkler irrigation systems. In specific conditions, even half of the irrigation water can evaporate or drift out of the irrigated area. The purpose of this study was to develop a WDEL estimation equation based on dimensional analysis (Buckingham's π method), considering a wide set of independent variables. An equation was sought that could be used for various sprinkler technologies and meteorological conditions in semiarid areas. Our research used experimental data from the literature, obtained in northeastern Spain and northwestern Iran. The complete data set consisted of 153 WDEL observations obtained at different operating pressures, nozzle diameters, irrigation durations, day and night irrigations, elevations from the soil surface and meteorological conditions. The experiments involved solid-sets and moving laterals, impact sprinklers, gear driven sprinklers and rotating spray plate sprinklers. The equation developed in this research included four technical independent variables (main nozzle diameter, auxiliary nozzle diameter, operating pressure and nozzle elevation) and four meteorological independent variables (air temperature and relative humidity, wind speed and solar radiation). The equation resulted in improved estimation respect to the equations previously derived from part of the experimental data set. The proposed equation was calibrated using 70% of the experimental data and validated using 30% of the experimental data. When the proposed equation was applied to the complete experimental data set, the determination coefficient was 0.81 and the root mean square error was 3.49%. The proposed equation represents a clear improvement respect to the equations reported in the literature in terms of the number and range of the independent variables and the predictive capacity.

Employing Data Mining Algorithms and Mathematical Empirical Models for Predicting Wind Drift and Evaporation Losses of a Sprinkler Irrigation Method

The advantage of a sprinkler irrigation method is that it saves up to 50% of water consumption during the application of water, as compared to any other surface irrigation system. To assess the behavior of a sprinkler irrigation method, wind drift and evaporation losses (WDEL) are often employed as important parameters. The predictive capacities of four previous mathematical empirical models and two data mining algorithms, namely, reduced-error pruning tree (REPTree) and artificial neural network (ANN) models, were employed to evaluate the impact of the operating parameters of a sprinkler irrigation method on WDEL. The inputs to the REPTree and ANN models were the working pressure, vapor pressure deficit, air temperature, wind speed, nozzle diameter, and air relative humidity. In the experimental field, for data collection, a solid set of sprinklers and collectors positioned per ASAE standards was employed. Promising results showed remarkable performance for one of the mathematical empirical models tested, with a confidence index value of 0.829. Meanwhile, the REPTree and ANN models presented smaller errors for testing data set and are qualified for use given their confidence index values of 0.956 and 0.964, respectively. The REPTree and ANN algorithms were classified as optimal models, indicating that the use of mathematical experimental models alone is inadequate in operational situations involving the nozzle diameter, working pressure, and other variables.

Machine learning and regression-based techniques for predicting sprinkler irrigation's wind drift and evaporation losses

Wind drift and evaporation losses (WDEL), which can occur as a result of operational and meteorological factors, are two of the most significant sprinkler-irrigation losses that can occur even in a well-managed irrigation system. A proper understanding of factors that influence WDEL in sprinkle irrigation is critical for developing water conservation strategies that significantly impact the quality and return on investment of irrigation projects. The specific objective of this research was to determine the predictive ability of five soft computing approaches (artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), multivariate adaptive regression spline (MARS), probabilistic linear regression (PLR), and support vector regression (SVR)) for predicting WDEL on a sprinkler irrigation system under design, operational, and meteorological conditions. Datasets were collected from previously published studies conducted under a variety of conditions. The results showed that the five approaches yielded statistically different WDEL predictions. The ANN model produced the most accurate WDEL predictions compared to the other models with the training and testing dataset. The ANFIS, MARS, PLR, and SVR models' performance ranks were found to be inconsistent across a variety of statistical performance criteria. Hence, Shannon's entropy-based decision theory was used to rank these models. The MARS model was ranked second (0.896), followed by the ANFIS model (0.865), the PLR model (0.833), and the SVR model (0.794). The design variable “auxiliary nozzle diameter” and climate variable “wind speed” both had high contribution ratios (17.5% and 12.19%, respectively) in WDEL modeling to produce a robust predictive model. In general, the developed models, particularly the ANN model, demonstrated a high degree of accuracy in estimating the WDEL of sprinkler irrigation systems.

Towards improving the global water application uniformity of centre pivots through lateral speed adjustment

An initial step is made towards improving the global water application uniformity of centre pivots by adjusting the lateral speed based on diurnal changes of wind drift and evaporation losses (WDEL). A large WDEL dataset was used to construct an artificial neural network (ANN) model capable of predicting the above ground application efficiency (AGAE ≈ 1- WDEL) from input weather data. Given its reasonably good accuracy (RMSE = 1.5%), the ANN model was then applied in heuristic, simple and dynamic algorithms that used forecasted or real-time weather parameters corresponding to the hourly time intervals of the pivot's revolution time. For each timing interval, the final output of the algorithms is a coefficient ( λ ), that when multiplied by the lateral speed, can ensure a more consistent water delivery depth across the field. The proposed algorithms were theoretically tested for extremely hot, dry, humid, and windy days. These efforts indicated that under the climatic conditions of the study, λ could potentially vary between 0.92% and 1.06% if the revolution time is about 24 h. The λ coefficient typically increased from 1:00 AM to 9:00 AM, then decreased until the sunset, between 19:00 to 21:00, and then increased again until midnight. This general trend for λ could however, be disrupted by sudden changes in the wind speed. Future studies should conduct extensive field work to test the efficacy of the proposed algorithms and quantify the improvement of centre pivot global water application uniformity through the lateral speed adjustment. • Centre pivot lateral speed can be adjusted to account for a changing application efficiency. • Two theoretical algorithms were developed to improve the global water application uniformity. • The first algorithm uses forecasted weather data while the second uses real time data. • The lateral speed adjustment factor varied within ±6% during a 24-hr cycle. • Centre pivot lateral speed adjustment is easy to implement.

Wind Drift Evaporation Loss and Soil Moisture Distribution under Sprinkler Irrigated Blackgram (Vigna mungo L.)

An experiment was conducted during March–June 2018 with the sprinkler irrigation system covered in an area of 39×42 m2. Proper design and management of sprinkler irrigation systems improves the uniformity of moisture distribution and reduces wind drift and evaporation losses (WDEL) for effective crop growth. Uniformity coefficient, wind drift and evaporation loss of the sprinkler system at a different pressure head of 2 kg cm-2, 2.5 kg cm-2 and 3 kg cm-2 were studied. Wind speed was observed by using handheld anemometer. The wind speed ranged between 0.9 to 4.5 m s-1. The highest uniformity coefficient of 88.19% and wind drift and evaporation loss of 3.5% were obtained at the pressure head of 3 kg cm-2 and the wind speed of 0.9 m s-1. Soil samples were collected at different depths of 0–10 cm, 10–20 cm, 20–30 cm and at a radial distance from 0 m, 3 m, 6 m, 9 m, 12 m respectively to determine the soil moisture distribution pattern. The soil moisture content values were plotted by using the computer software, surfer 10 of the windows version and contour maps were drawn. The moisture content was found to be more at 0–10 cm depth, as compared to 10–20 cm and 20–30 cm depth. The percentage of moisture was found to be highest at a 6 m distance, which was due to overlapping of the sprinkler system.

Accurate measurement of wind drift and evaporation losses could improve water application efficiency of sprinkler irrigation systems − A comparison of measuring techniques

Wind drift and evaporation losses (WDEL) are some of the major sprinkler-irrigation losses which exist even in a well-managed irrigation system. Several research studies found a wide range of WDEL under different and nearly similar configurations of sprinkler irrigation systems under similar weather conditions but using different methodologies to measure the WDEL. The specific objective of this research was to evaluate the three most commonly used measuring techniques (standard catch-can tests (CC), an electrical conductivity method (EC), and a physical-based mathematical approach (PM)) for WDEL on a common sprinkler irrigation system under the same climatic conditions. We conducted 33 experiments from May to September of 2018 near Prosser, Washington. Twenty-two of these experiments were during the daylight hours, and 11 were during the night. We used catch-cans of 29.3 cm diameter and rain gauges (diameter of 10 cm) to collect water to measure the irrigation water's electrical conductivity. Mass and heat transfer approaches were used in the PM technique. The results showed that the three techniques yielded statistically different mean WDEL. The highest WDELs were in CC (22.8%), followed by EC (17.5%) and PM (6.8%) techniques. The CC WDELs were better correlated with PM than the EC approach. The mean nighttime WDEL for the EC and CC methods were not statistically different (p > 0.05). The CC WDELs were more closely related to wind speed than the vapor pressure deficit. The EC and PM approaches have a higher correlation to the vapor pressure deficit. The overall conclusion disclosed that the more we use indirect measurement methods, the more the chances of erroneous numbers. The EC and PM approaches are likely limited to measuring droplet evaporation as the latter includes several assumptions. The CC approach is a direct measurement of the WDEL.

COMPARISON OF CLASSICAL SPRINKLER AND WHEEL MOVE IRRIGATION SYSTEMS IN DEHGOLAN PLAIN, NORTH‐WEST IRAN†

AbstractThe performance and efficiency of classical fixed sprinkler and wheel move irrigation systems were compared in the Dehgolan Plain, north‐west Iran. The field and laboratory experiments were conducted with 10 classical fixed and 10 wheel move systems. Christensen coefficient of uniformity (CU), distribution uniformity (DU), potential application efficiency of low quarter (PELQ) and application efficiency of the lower quarter (AELQ) were used for the purpose of this assessment. The results showed a low efficiency due to improper design and management of classical fixed systems. Also, the results indicated that the wheel move systems used in the Dehgolan Plain performed well. The average mean values of the above coefficients (i.e. 12.6, 19.8, 21.5 and 14.5%) were higher in wheel move systems in comparison to those of classical fixed systems. Additionally, the average mean value of wind drift and evaporation losses (WDEL) and percolation losses (DP) were 0.45 and 1.17% lower in the wheel move systems, respectively, in comparison to those of classical fixed systems. The adequacy of irrigation (ADirr) of the wheel move systems was 16.3% higher than that of classical fixed systems. Generally, the results showed that wheel move systems in the Dehgolan Plain have a substantially higher efficiency than the classical fixed systems. © 2020 John Wiley & Sons, Ltd.

Linear mixed modeling and artificial neural network techniques for predicting wind drift and evaporation losses under moving sprinkler irrigation systems

Pressurized irrigation systems, center pivots, and linear moves are used worldwide on a large scale. Accurate predictions of wind drift and evaporation losses (WDEL) could help in improving the system’s uniformity and efficiency. The current study evaluates data analysis techniques for accurately estimating WDEL under moving sprinkler irrigation systems. A total of 72 experiments (2015–2017) were conducted at the research and extension center in Prosser, WA, under a wide variety of climate conditions. Two data analysis techniques, namely linear mixed modeling (LMM) and artificial neural networks (ANN), were used to identify the significant drivers of WDEL from the given weather-related inputs. Four published datasets were also used to check the generalization capabilities of the developed models. The results revealed an average of ~ 20% WDEL under Prosser, WA, conditions. Vapor pressure deficit and wind speed were the only significant weather variables at a 0.05 level of significance. Both in training and in testing, the ANN models (root mean squared error (RMSE = 2%)) worked better than the LMM (RMSE = 5%). Testing results revealed the high generalization and predictive power of ANN models with a RMSE of 1% for the (Yazar 1984) datasets. The best LMM model was with the Sanchez et al. (2011) dataset with a RMSE of 14%. The above results showed that ANN models can be used to accurately predict WDEL. This should help in further research for efficiency improvements in sprinkler irrigation systems.

Wind drift and evaporation losses of a mechanical lateral-move irrigation system: Oscillating plate versus fixed spray plate sprinklers

The mechanical lateral-move irrigation system has the capacity to achieve high irrigation efficiency when handled properly; however, during irrigation, wind drift and evaporation losses (WDEL) can occur that are caused by operational and meteorological factors. Thus, the objectives of this study were: to determine the WDEL of a mechanical lateral-move irrigation system fully equipped with oscillating plate sprinklers (I-Wob) under different meteorological conditions; to evaluate the predictive capacity of eight published WDEL models that were compared with field data of the full length mechanical lateral-move irrigation system; to develop a model for estimating the WDEL of a mechanical lateral-move irrigation system equipped with an oscillating plate; and to compare the WDEL and Christiansen Uniformity coefficient for fixed-spray plate (Superspray) and I-Wob under field conditions. The study was conducted using 65 in-field tests that were divided into two groups; the first group of 35 in-field tests used a full-length lateral-move irrigation system equipped with I-Wob sprinklers, and the second group consisted of 30 in-field tests that used only the span 2 (Superspray) and the span 4 I-Wob sprinklers. The WDEL for the full-length lateral-move systems ranged from 4.4 to 25.2%, with an average of 11.6%. A Pearson’s correlation test found that wind speed was significant at a 5% significance level. The proposed model performed better than the eight published models. A comparison of the I-Wob and Superspray sprinklers installed in the mechanical lateral-move irrigation systems indicated that I-WOB performed better and had higher Christiansen’s Uniformity coefficient values and lower wind drift and evaporation losses.

Evaluating water application efficiency of low and mid elevation spray application under changing weather conditions

Over half of the irrigated land in the US, 11.5 million ha, is irrigated with center pivot and linear move systems. Because of this, minor changes in the operation efficiency of these systems can have large impact on overall water conservation. The objective of this study was to evaluate the water application efficiency (WAE) of low and of mid elevation spray application (LESA and MESA) using catch can test and drainage lysimeters, and develop governing equations based on the weather variables. A three-year (2015–2017) field study was conducted at the Washington State University Research and Extension Center, near Prosser. Catch cans were used to collect the fraction of total irrigation-water applied that reached the ground surface as WAE and drainage lysimeters to measure the overall water loss (OAWL) and wind drift and evaporation losses (WDEL), (WDEL = 100-WAE). Air temperature (Ta), relative humidity (RH), short-wave global irradiance (Rg), wind speed (WS), and calculated vapor pressure deficit (VPD) were used as the input weather variables to mixed modeling technique. Results showed that on average 21% more irrigation-water reached the ground with LESA than with MESA systems. Lysimetric measurements showed on average a 16% efficiency difference between MESA and LESA. The monthly WAE differences between MESA and LESA increased from 12 to 30% during the hot summer months and thereafter decreased, from 30 to 9%. The warmer and drier year of 2015 had the highest annual average values of WDEL of 17% for LESA and 19% for MESA. Results indicated a relatively constant WAE for LESA regardless of weather conditions. Mixed modelling showed that VPD was the only significant predictor (P < 0.05) of WAE for LESA, while VPD and WS for MESA. Our results might be used to adjust center pivot travel speed (% settings) to compensate for variations in WAE as the weather changes.

Estimation of wind drift and evaporation losses in sprinkler irrigation of urban green spaces

The wind drift and evaporation losses (WDEL) are high in arid, semi-arid and windward areas, and reduce the efficiency of the sprinkler irrigation system; therefore, this study was carried out in order to achieve a practical criterion and provide a relationship for accurate estimation of the wind drift and evaporation losses in different atmospheric conditions. The experiments were done at the Meteorological Station of the Faculty of Agriculture of Ferdowsi University of Mashhad using a line-source sprinkler irrigation system based on the single sprinkler installation method. To achieve the objectives of this plan, factorial experiment was performed on PGP sprinkler with regard to the two factors, the pressure of the sprinkler function (with three levels 1.6, 2.5 and 3.4 bar) and the diameter of the nozzle (with three levels of 4, 5 and 6 mm) with three replications (morning, noon and night). Assessing the result of the data variance analysis showed that the effects of pressure, aperture diameter, and time on the wind drift and evaporation losses are not significant. Investigating the main effects of these factors showed that the effect of aperture diameter on irrigation losses is significant at the level of the 1%. In order to further investigate, the comparison of mean losses data in three aperture diameter was done using Duncan′s test. The results indicated that aperture 4 with the losses of 44% had a significant difference with other diameters. This result suggests an increase in losses for smaller diameters due to the small droplets and the increase in wind drift. Also, the comparison of the mean losses data in three times showed that irrigation at noon with the losses of 44% had a significant difference compared to other times due to a significant increase in temperature and radiation of the sun and saturation vapor pressure deficit, and there is no significant difference between morning and evening irrigation. Also, analysis of variance showed that the effect of water pressure change between 1.6 and 4.3 bar does not have a significant effect on the WDEL in this sprinkler. In general, the results showed that increasing wind speed increases the losses of evaporation and wind. Also, this study suggested that changing the irrigation time in areas with hot and dry days, from day to night in summer, leads to a significant reduction of the wind drift and evaporation losses.

Prediction of wind drift and evaporation losses of a sprinkler irrigation system using principal component analysis and artificial neural network technique

Principal component analysis was merged with the artificial neural network (ANN) technique to predict wind drift and evaporation losses (WDEL) from a sprinkler irrigation system. For this purpose, field experiments were conducted to determine WDEL under different conditions. Data from field experiments and previous studies were used as sample data to train the ANN model. Three models were developed to predict WDEL. In the first model (ANN1), 9 neurons (riser height, main nozzle diameter, auxiliary nozzle diameter, discharge rate of the main nozzle, discharge rate of the auxiliary nozzle, operating pressure, wind speed, air temperature and relative humidity) were used as the input layer. In the second model (ANN2), 7 neurons (riser height, operating pressure, wind speed, air temperature and relative humidity, diameter ratio and discharge ratio) were used as the input layer. The third model (ANN3) used a multivariate technique (PC1, PC2, and PC3). Results revealed that the ANN3 model had the highest coefficient of determination (R2 = 0.8349). The R2 values for the ANN1 and ANN2 models were 0.7792 and 0.4807, respectively. It can be concluded that the ANN3 model has the highest predictive capacity.

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

AbstractAn 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 &amp; Sons, Ltd.

Prediction of wind drift and evaporation losses from sprinkler irrigation using neural network and multiple regression techniques

Wind drift and evaporation losses (WDEL) play a significant role in the development of water conservation strategies in sprinkler irrigation. In this study, artificial neural network (ANN) and multiple linear regression (MLR) models were developed by taking data collected from published studies on predicted WDEL for several design, operational, and meteorological conditions of variables in sprinkler irrigation. Five combinations of input variables, including riser height, operating pressure, main nozzle diameter, auxiliary nozzle diameter (da), water discharge by main nozzle, water discharge by auxiliary nozzles, wind speed (WS), air temperature, and relative humidity were used to create prediction models for WDEL. The ANN and MLR models were trained and tested on 70% and 30% of the data points, respectively. The accuracy of the models was assessed by the coefficients of correlation (r), overall indices of model performance (OI), root mean square errors (RMSE), and mean absolute errors (MAE). Statistical results showed that the ANN and MLR models with all input variables had the best predicting capabilities. When comparing the results of different ANN and MLR models, it was seen that the ANN models had more success in predicting WDEL. The ANN models gave higher r (0.843–0.956) and OI (0.794–0.909) values, and lower RMSE (2.662%–4.886%) and MAE (2.197%–3.729%) values compared to the MLR models in the training stage. The MLR models’ r values ranged from 0.794 to 0.864, OI values ranged from 0.747 to 0.816, RMSE values ranged from 4.562% to 5.514%, and MAE values ranged from 3.513% to 4.414%. Furthermore, a contribution analysis found that the design parameter da and the climatic parameter WS were considered to obtain the most robust estimation model. It can be stated that the ANN model is a more suitable tool than the MLR model for the prediction of WDEL from sprinkler-irrigation.

Continuous variation of wind drift and evaporation losses under a linear move irrigation system

The traditional catch-can technique for measuring water depth application under sprinkler irrigation systems has the limitation of being unable to monitor the continuous variation of wind drift and evaporation losses (WDEL) under changing weather conditions. Such information is essential to better manage the agricultural water by improving the global water application uniformity under moving irrigation machines. Three parallel, long, impermeable water collection strips were constructed underneath a stationary linear move irrigation system to address this issue. The sprinkler discharge efficiency (SDE≈1- WDEL) was monitored over 5-min intervals (SDE5min) during Apr-Aug of 2014-on a bare experimental plot. Experiments were conducted on a discrete basis for about 1040h total in order to collect more than 11,600 SDE5min data points. It was found that the SDE5min is very dynamic and can experience abrupt changes up to 16.5% as a result of sudden changes in wind speed and direction. The maximum and minimum observed SDE5min during the study period were 97.5 and 73.6%, respectively. The difference between maximum and minimum SDE5min during a day/night cycle was controlled by solar radiation and maximum wind speed. The average hourly SDE (SDEhr) for data collected at predawn, morning, afternoon, and evening were 89.5, 87.7, 86.9 and 88.8%, respectively. Overall, the daily SDE was mainly controlled by air temperature and varied between 81.8 and 91.8%, indicating that ∼8–18% of the daily applied water was lost on average. A multiple linear regression model was developed to help predict the SDEhr as a function of weather parameters. The model indicated wind speed, temperature and relative humidity as the best explanatory variables and predicted the SDEhr with an absolute error just over 4%. Because the difference between maximum and minimum SDEhr over a full experimental day could be as high as 22%, this magnitude of error was considered to be acceptable for wind drift and evaporation loss estimation.

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

The 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 ≈ 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−1). 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.

Performance of new agricultural impact sprinkler fitted with plastic nozzles

The radial water distribution and irrigation performance of an agricultural sprinkler with plastic nozzles were analysed. Twenty-six tests with an isolated sprinkler corresponding to different combinations of three working pressure (p, 200, 300 and 400 kPa) and three nozzle diameters of the main nozzle (4.0, 4.5 and 5.0 mm) were performed to evaluate the radial water distribution curves, All the tests were performed under calm wind (≤1 m s−1) under open air conditions. Fifty tests corresponding to six combinations of nozzle diameter and pressure with the same sprinkler model were performed under a wide range of meteorological conditions in a rectangular solid-set system at 18 m × 18 m sprinkler spacing to evaluate the Christiansen's Uniformity Coefficient (CUC) and wind drift and evaporation losses (WDEL). The resulting radial water distribution curves were compared with those from impact sprinklers with brass nozzles. Sprinkler model had an important effect on the radial water distribution, even under similar operational conditions, and these differences were shown in the first 2.5–6 m from the sprinkler. The CUC and WDEL of a solid-set sprinkler system were compared with simulated values from the “Ador-Sprinkler” model. The results of this analysis showed that the type of sprinkler had a moderate influence on sprinkler irrigation uniformity. The analysis presented in this study may serve to develop a decision tool to choose the most suitable combinations of sprinkler model, nozzle diameter and working pressure to optimise the uniformity and efficiency of sprinkler irrigation.

Sprinkler evaporation losses in alfalfa during solid-set sprinkler irrigation in semiarid areas

Gross sprinkler evaporation losses (SELg) can be large and decrease irrigation application efficiency. However, it is not universally established how much of the SELg contributes to decrease the crop evapotranspiration during the sprinkler irrigation and how much are the net sprinkler losses (SELn). The components of SEL were the wind drift and evaporation losses (WDEL) and the water intercepted by the crop (IL). The gross WDEL (WDELg) and evapotranspiration (ET) were measured simultaneously in two alfalfa (Medicago sativa L.) plots, one being irrigated (moist, MT) and the other one not being irrigated (dry, DT). Catch can measurements, mass gains, and losses in the lysimeters and micrometeorological measurements were performed to establish net WDEL (WDELn) during the irrigation and net IL (ILn) after the irrigation as the difference between ETMT and ETDT. Also, equations to estimate ILn and net sprinkler evaporation losses (SELn) were developed. ILn was strongly related to vapor pressure deficit (VPD). SELn were 8.3 % of the total applied water. During daytime irrigations, SELn was 9.8 % of the irrigation water and slightly less than WDELg (10.9 %). During nighttime irrigations, SELn were slightly greater than WDELg (5.4 and 3.7 %, respectively). SELn was mainly a function of wind speed.

Assessing Sprinkler Irrigation Performance Using Field Evaluations at the Medjerda Lower Valley of Tunisia

Irrigation uniformity and wind drift and evaporation losses (WDEL) are major concerns for the design and management of sprinkler irrigation systems under arid or semi-arid conditions. Field trials were carried out to assess irrigation uniformity and WDEL under various wind velocities, sprinkler spacings and operating pressure heads. Based on experimental data, a frequency analysis was performed to infer the occurrence probability of a given uniformity coefficient (UC). In addition, statistical regressions were used to model WDEL as a function of different climatic variables. Increasing the operating pressure head improved uniformity at low wind speeds. It was shown that UC has been severely impaired at wind speeds above 4 m/s. In the prevailing wind conditions, the frequency analysis showed that a sprinkler spacing of 12 m × 12 m provided the best uniformity. In the local conditions, it is recommended to stop irrigation when wind velocity exceeds 4 m/s. Moreover, it was shown that wind speed and relative humidity were the main significant variables influencing WDEL.

The effects of pressure, nozzle diameter and meteorological conditions on the performance of agricultural impact sprinklers

Abstract This study evaluates agricultural impact sprinklers under different combinations of pressure (p), nozzle diameter (D) and meteorological conditions. The radial curve (Rad) of an isolated sprinkler, i.e., the water distribution along the wetted radius, was evaluated through 25 tests. Christiansen's uniformity coefficient (CUC) and the wind drift and evaporation losses (WDEL) were evaluated for a solid-set system using 52 tests. The Rad constitutes the footprint of a sprinkler. The CUC is intimately connected to the Rad. The Rad must be characterized under calm conditions. Very low winds, especially prevailing winds, significantly distort the water distribution. The vector average of the wind velocity (V’) is recommended as a better explanatory variable than the more popular arithmetic average (V). We recommend characterizing the Rad under indoor conditions or under conditions that meet V’ The Rad was mostly affected by the sprinkler model. V’ was the main explanatory variable for the CUC; p was significant as well. V was the main variable explaining the WDEL; the air temperature (T) was significant, too. Sprinkler irrigation simulators simplify the selection of a solid-set system for farmers, designers and advisors. However, the quality of the simulations greatly depends on the characterization of the Rad. This work provides useful recommendations in this area.