scholarly journals Modeling wind drift and evaporation losses during sprinkler irrigation in arid areas (case of Touggourt - Algeria)

2022 ◽  
Author(s):  
Sofiane Gheriani ◽  
Noureddine MEZA ◽  
Djamel BOUTOUTAOU
Keyword(s):  
Mean Squared Error ◽  
Sprinkler Irrigation ◽  
Weather Conditions ◽  
Climatic Conditions ◽  
Coefficient Of Determination ◽  
Irrigation Performance ◽  
Water Losses ◽  
Wind Drift ◽  
Evaporation Losses ◽  
Complex Indicators

Abstract In recent years, agriculture development in South-eastern Algeria progressed rapidly which increased the demand for agricultural products. Given that this region is characterized by hard agro-climatic conditions, irrigation seems to be a necessary factor for ensuring optimal development and high agricultural production. Like many irrigation technics widely used, sprinkler irrigation performance was considerably affected by these conditions, mainly evaporation, which causes water losses. This study aims to propose an adequate mathematical model predicting wind drift and evaporation losses under different weather conditions resume by the complex indicator of climatic intensity (ɸ). Results showed that complex indicators of climatic intensity, were significant factors affecting the wind drift and evaporation losses, puissance relationship between wind drift and evaporation losses, and complex indicators of climatic intensity, obtained model are adopted can be useful tools in the determination of the overall losses in terms of environmental conditions (air temperature, relative humidity, and wind speed). Totally 25 measure samples were used for training the model, and 15 measure samples for testing and validation of the model. The developed model for the WDEL modeling shows high good performance with a coefficient of determination (R2) = 0.808, mean squared error (RMSE) = 3.39%, and Mean Absolute Error MAE = 8.41%.

scholarly journals Evaluation of Sprinkler Irrigation Evaporation Losses in Ilaro, Ogun State, South Western Nigeria

2021 ◽  
Vol 2 (1) ◽  
pp. 47-59
Author(s):  
Samuel Dare OLUWAGBAYIDE ◽  
Olugbenga FASANU ◽  
Ajayi Johnson OLORUNTADE
Keyword(s):  
Wind Velocity ◽  
Air Temperature ◽  
Climatic Factors ◽  
Sprinkler Irrigation ◽  
Climatic Conditions ◽  
Operating Pressure ◽  
Ogun State ◽  
Evaporation Losses ◽  
Pressure Medium ◽  
Rate Of Evaporation

Under the prevailing climate change the world is currently facing, efficient irrigation water management is essential to ensure food security, especially in countries with similar climate to Nigeria. Hence, this study was undertaken at the Research Farm of Federal Polytechnic, Ilaro, Ogun State, Nigeria to evaluate evaporation losses during sprinkler irrigation between March and July 2019. Experiments were performed using 360 rotating sprinkler and single nozzle of diameter 3 mm, while due cognizance was taken of the prevailing climatic conditions. Three operating pressures, namely, 50 kPa, 100 kPa and 150 kPa, representing low pressure, medium pressure and high pressure, respectively, were used. The results showed that operating pressures influence droplet sizes, droplet heights and flow rate during the experiment. In addition, it was observed that at operating pressures of 50 kPa, 100 kPa and 150 kPa, mean percentage of evaporation losses were 8.88%, 13.21% and 16.46%, respectively, indicating that evaporation losses increased with increasing operating pressure. Further analysis showed that percentage evaporation losses increased at higher relative humidity, thereby emphasizing the predominance of air temperature and wind velocity as climatic variable influencing sprinkler evaporation losses. The relationship between wind velocity (Vw ) and air temperature (Ta) and to predict evaporation losses (E ) was a function of E = 7.968Vw + 0.393Ta – 19.977. Therefore, it was concluded that, both climatic factors and operating pressures influence the rate of evaporation losses during sprinkler irrigation, adequate attention should be paid to variation of climatic variables since sprinklers are sold with their specified operating pressures.

scholarly journals Evaluation of Random Forest for short-term daily streamflow forecast in rainfall and snowmelt driven watersheds

2020 ◽  
Author(s):  
Leo T. Pham ◽  
Lifeng Luo ◽  
Andrew O. Finley
Keyword(s):  
Random Forest ◽  
Mean Squared Error ◽  
Absolute Error ◽  
Climatic Conditions ◽  
Coefficient Of Determination ◽  
Streamflow Forecasting ◽  
Short Term ◽  
Streamflow Forecast ◽  
Daily Streamflow ◽  
Rf Performance

Abstract. In the past decades, data-driven Machine Learning (ML) models have emerged as promising tools for short-term streamflow forecasts. Among other qualities, the popularity of ML for such applications is due to the methods' competitive performance compared with alternative approaches, ease of application, and relative lack of strict distributional assumptions. Despite the encouraging results, most applications of ML for streamflow forecast have been limited to watersheds where rainfall is the major source of runoff. In this study, we evaluate the potential of Random Forest (RF), a popular ML method, to make streamflow forecast at 1-day lead time at 86 watersheds in the Pacific Northwest. These watersheds span climatic conditions and physiographic settings and exhibit varied contributions of rainfall and snowmelt to their streamflow. Watersheds are classified into three hydrologic regimes: rainfall-dominated, transisent, and snowmelt-dominated based on the timing of center of annual flow volume. RF performance is benchmarked against Naive and multiple linear regression (MLR) models, and evaluated using four metrics Coefficient of determination, Root mean squared error, Mean absolute error, and Kling-Gupta efficiency. Model evaluation metrics suggest RF performs better in snowmelt-driven watersheds. Largest improvement in forecasts, compared to benchmark models, are found among rainfall-driven watersheds. We obtain Kling–Gupta Efficiency (KGE) scores in the range of 0.62–0.99. RF performance deteriorates with increase in catchment slope and increase in soil sandiness. We note disagreement between two popular measures of RF variable importance and recommend jointly considering these measures with the physical processes under study. These and other results presented provide new insights for effective application of RF-based streamflow forecasting.

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

Water SA ◽  
2018 ◽  
Vol 44 (3 July) ◽  
Author(s):  
Samy A Marey ◽  
Mohamed SA El Marazky ◽  
Abdulwahed M Aboukarima
Keyword(s):  
Field Experiments ◽  
Irrigation System ◽  
Discharge Rate ◽  
Principal Component ◽  
Sprinkler Irrigation ◽  
Operating Pressure ◽  
Wind Drift ◽  
Evaporation Losses ◽  
Input Layer ◽  
Riser Height

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

2017 ◽  
Vol 67 (2) ◽  
pp. 222-232 ◽  
Author(s):  
E. Maroufpoor ◽  
H. Sanikhani ◽  
S. Emamgholizadeh ◽  
Ö. Kişi
Keyword(s):  
Sprinkler Irrigation ◽  
Data Driven ◽  
Irrigation Systems ◽  
Wind Drift ◽  
Evaporation Losses

scholarly journals Evaluation of random forests for short-term daily streamflow forecasting in rainfall- and snowmelt-driven watersheds

2021 ◽  
Vol 25 (6) ◽  
pp. 2997-3015
Author(s):  
Leo Triet Pham ◽  
Lifeng Luo ◽  
Andrew Finley
Keyword(s):  
Random Forests ◽  
Mean Squared Error ◽  
Predictive Performance ◽  
Absolute Error ◽  
Climatic Conditions ◽  
Coefficient Of Determination ◽  
Streamflow Forecasting ◽  
Short Term ◽  
Daily Streamflow ◽  
Rf Performance

Abstract. In the past decades, data-driven machine-learning (ML) models have emerged as promising tools for short-term streamflow forecasting. Among other qualities, the popularity of ML models for such applications is due to their relative ease in implementation, less strict distributional assumption, and competitive computational and predictive performance. Despite the encouraging results, most applications of ML for streamflow forecasting have been limited to watersheds in which rainfall is the major source of runoff. In this study, we evaluate the potential of random forests (RFs), a popular ML method, to make streamflow forecasts at 1 d of lead time at 86 watersheds in the Pacific Northwest. These watersheds cover diverse climatic conditions and physiographic settings and exhibit varied contributions of rainfall and snowmelt to their streamflow. Watersheds are classified into three hydrologic regimes based on the timing of center-of-annual flow volume: rainfall-dominated, transient, and snowmelt-dominated. RF performance is benchmarked against naïve and multiple linear regression (MLR) models and evaluated using four criteria: coefficient of determination, root mean squared error, mean absolute error, and Kling–Gupta efficiency (KGE). Model evaluation scores suggest that the RF performs better in snowmelt-driven watersheds compared to rainfall-driven watersheds. The largest improvements in forecasts compared to benchmark models are found among rainfall-driven watersheds. RF performance deteriorates with increases in catchment slope and soil sandiness. We note disagreement between two popular measures of RF variable importance and recommend jointly considering these measures with the physical processes under study. These and other results presented provide new insights for effective application of RF-based streamflow forecasting.

scholarly journals PERDAS DE ÁGUA POR EVAPORAÇÃO E ARRASTE NA IRRIGAÇÃO POR ASPERSÃO NAS CONDIÇÕES CLIMÁTICAS DE LAVRAS-MG, UTILIZANDO ASPERSORES DE TAMANHO MÉDIO

Irriga ◽  
2008 ◽  
Vol 13 (1) ◽  
pp. 113-127
Author(s):  
Samuel Beskow ◽  
Alberto Colombo ◽  
Geraldo Magela Pereira ◽  
José Henrique da Silva Taveira ◽  
Célio Moreira Ricardo
Keyword(s):  
Sprinkler Irrigation ◽  
Field Trials ◽  
Climatic Conditions ◽  
Irrigation Efficiency ◽  
Considerable Influence ◽  
Wind Drift ◽  
Nozzle Size ◽  
1 Samuel

PERDAS DE ÁGUA POR EVAPORAÇÃO E ARRASTE NA IRRIGAÇÃO POR ASPERSÃO NAS CONDIÇÕES CLIMÁTICAS DE LAVRAS-MG, UTILIZANDO ASPERSORES DE TAMANHO MÉDIO[1]  Samuel Beskow; Alberto Colombo; Geraldo Magela Pereira; José Henrique da Silva Taveira; Célio Moreira RicardoDepartamento de Engenharia, Universidade Federal de Lavras, Lavras, MG, [email protected]  1 RESUMO             O objetivo deste trabalho foi determinar as perdas de água por evaporação e arraste durante ensaios de campo com um único aspersor e também com laterais de aspersores, sob várias condições climáticas, usando quatro modelos de aspersores, operando em três níveis de pressão. Quatro diferentes modelos de aspersores, representando diferentes combinações de diâmetro de bocal e ângulo de jato, foram usados: 1 - Agropolo NY-7 (4,6 mm x 4 mm e 7º); 2 - Agropolo NY-12 (3,5 mm e 12º); 3 - Naan (3,0 mm e 12º); e 4 - Agropolo NY-25 (2,8 mm x 2,5 mm e 25º). Testes de campo mostraram que as perdas observadas em ensaios com um único aspersor (valores médios de 8,5, 36,5, 40,3 e 39,8% para, respectivamente, aspersor 1, 2, 3 e 4) foram maiores do que as perdas observadas em ensaios com laterais de aspersores (valores médios de 4,7, 13,6, 20,2 e 18,9% para, respectivamente, aspersor 1, 2, 3 e 4), e que o diâmetro do bocal exerce grande influência no valor de perdas de água por evaporação e arraste. UNITERMOS: eficiência de irrigação, avaliação de aspersores.  BESKOW, S.; COLOMBO, A.; PEREIRA, G. M.; TAVEIRA, J. H. S.; RICARDO, C. M. EVAPORATION AND WIND DRIFT LOSSES IN SPRINKLER IRRIGATION UNDER THE CLIMATIC CONDITIONS OF LAVRAS-MG, USING MEDIUM-SIZED SPRINKLERS  2 ABSTRACT             The objective of this work was to determine evaporation and drift losses during single-sprinkler and block irrigation outdoor tests held at several climatic conditions, by using four sprinkler models operating at different pressure levels. Four different sprinkler models, representing different combinations of nozzle sizes and jet angles, were used: 1 – Agropolo NY-7 (4.6 x 4 mm and 7º); 2 – Agropolo NY-12 (3.5 mm and 12º); 3 – Naan-12 (3.0 mm and 12º), and 4 – Agropolo NY-25 (2.8 mm x 2.5 mm and 25º). Field trials showed that observed losses at single tests (average values of 8.5, 36.5, 40.3, and 39.8% for, respectively, sprinkler 1, 2, 3, and 4) are greater than the ones observed on block irrigation tests (average values of 4.7, 13.6, 20.2, and 18.9% for, respectively, model 1, 2 , 3, and 4), and that nozzle size has considerable influence on evaporation and wind drift losses.KEY WORDS: sprinkler evaluation, irrigation efficiency. 

scholarly journals Modelling daily net radiation of open water surfaces using land-based meteorological data

Water SA ◽  
2021 ◽  
Vol 47 (4 October) ◽  
Author(s):  
L Myeni ◽  
MJ Savage ◽  
AD Clulow
Keyword(s):  
Meteorological Data ◽  
Model Performance ◽  
Open Water ◽  
Weather Conditions ◽  
Equilibrium Temperature ◽  
Climatic Conditions ◽  
Coefficient Of Determination ◽  
Water Evaporation ◽  
Average Wind Speed ◽  
Wide Range

Accurate quantification of net irradiance of open water (Rn water) is of paramount importance for the estimation of open water evaporation, which is critical for the efficient management of water resources. Alternatively, model estimates of Rn water are often used when quality measurements of Rn water are not readily available for the water storage of interest. A Daily Penman, Monteith, Equilibrium Temperature Hargreaves-Samani (DPMETHS) model has been developed for the estimation of Rn water using land-based meteorological data. The DPMETHS model is a spreadsheet-based iterative procedure that computes Rn water using daily land-based meteorological measurements of solar irradiance (Rs land), minimum and maximum air temperatures (Tmin and Tmax), minimum and maximum relative humidity (RHmin and RHmax) and average wind speed (Uland). In this study, the DPMETHS model was evaluated using daily Rn water in-situ measurements acquired from 5 sites in both hemispheres, representing very different climatic conditions. Results showed reasonable model performance at all 5 sites, with the coefficient of determination (r2) values greater than 0.85 and root mean square error (RMSE) values ranging from 0.60 MJ∙m-2 for Stratus Ocean (East Pacific Ocean) to 1.89 MJ∙m-2 for Midmar Dam (South Africa). The results of this study suggested that the DPMETHS model can be reliably used to estimate Rn water for a wide range of climatic conditions. The performance of the DPMETHS model depends on the representativeness of the land-based meteorological data to the weather conditions above the open water surface. The DPMETHS model is user-friendly with minimal computational and data requirements that allows easy data handling and visual inspection.

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

2018 ◽  
Vol 14 (1) ◽  
pp. 77-96
Author(s):  
M. Naderianfar ◽  
A. Faryabi ◽  
H. Dehghan
Keyword(s):  
Irrigation System ◽  
Water Pressure ◽  
Sprinkler Irrigation ◽  
Accurate Estimation ◽  
Atmospheric Conditions ◽  
Wind Drift ◽  
Aperture Diameter ◽  
Urban Green Spaces ◽  
Significant Difference ◽  
Evaporation Losses

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.

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