Showing 7 results for Evaporation
A Masjedi, A Shokohfar, M Alavi Fazel,
Volume 12, Issue 46 (1-2009)
Abstract
The increasing cultivation of corn in Ahwaz and the direct relation between the increase of the summer corn yield and its perfect irrigation in sowing period all together have made the research regarding this crop necessary. Deciding over the suitable irrigation scheduling of corn (hybrid SC.704) in summer by utilization of class A evaporation pan is the focal point of this research. Accordingly, a project was conducted in the form of stadistical perfect accidendal block in four repetitions and four treatments in 1383 on Ahwaz Azad university research land situated in Choneibeh. The irrigation treatment had four levels of T1,T2,T3 and T4 in class A evaporation pan containing of four levels of 50,75,100 and 150 mm, carried out in split plot. The suitable irrigation period was chosen according to the best treatment performance and its components, and the total amount of water in the taking period defines the depth of irrigation. The soil texture is clay lomy silty and the internal soil is silty clay. According to the amount of the accumulated evaporation from class A evaporation pan and taking the plant coefficient (Kc) into consideration, the amount of needed evapotrans piration was calculated and the amount of needed water for plot was measured by water counter. Then a comparison between the means by the use of Donken multi domains test was made and in this way the superior treatment was selected. Accordingly, the most suitable time for irrigation of summer corn in Ahwaz was after 50 mm of accumulated evaporation from class A evaporation pan which equals ten irrigation in the growing period. So in order to acquire 12 tons of seed yield in each hectare, at least 9600 m^3 of water for every hectar is needed. However, given the equal amount of water, with 3 times decrease in irrigation in treatment T2 in comparison with T1, a performance near 11 tons and with five times decrease in irrigation and ten tons in treatment T3 a performance near 10 tons can be attained.
M. Shadmani, S. Marofi,
Volume 15, Issue 55 (4-2011)
Abstract
In this research, based on the observed data of Class A pan evaporation and application of non-linear regression (NLR), artificial neural network (ANN), neuro-fuzzy (NF) as well as Stephens-Stewart (SS) methods daily evaporation of Kerman region was evaluated. In the cases of NLR, ANN and NF methods, the input variables were air temperature (T), air pressure, relative humidity (RH), solar radiation (SR) and wind speed (U2) which were used in various combinations to estimate daily pan evaporation (Ep) defined as output variable. Performance of the methods was evaluated by comparing the observed and estimated data, using determination coefficient (R2), root mean square error (RMSE) and mean absolute error (MAE). Based on the observed data at Kerman meteorological station, the monthly and annual average evaporation values of the region were 272 and 3263 mm, respectively. The results of this study indicated that NF method is the most suitable method to estimate daily Class A pan evaporation. The statistics criteria of this model which is constituted based on the 5 input parameters were R2 = 0.85, RMSE=1.61 and MAE= 1.24 mm day-1. The sensitivity analysis of NF model revealed that the estimated EP is more sensitive to T and U2 (as the input variables), respectively. Due to weak accuracy of SS method, a new modification step of the model was also developed based on the SR and T in order to have a more exact daily evaporation estimation of the region. However, the result of the modified model was not acceptable
S. Dodangeh, J. Abedi Koupai, S. A. Gohari,
Volume 16, Issue 59 (4-2012)
Abstract
Due to the important role of climatic parameters such as radiation, temperature, precipitation and evaporation rate in water resources management, this study employed time series modeling to forecast climatic parameters. After normality test of the parameters, nonparametric Mann-Kendall test was used in order to do trend analysis of data at P-value<0.05. Relative humidity and evaporation (with significant trend, -0.348 and -0.42 cm, respectively), as well as air temperature, wind speed, and sunshine were selected for time series modeling. Considering the Autocorrelation function (ACF) and Partial Autocorrelation function (PACF) and trend of data, appropriate models were fitted. The significance of the parameters of the selected models was examined by SE and t statistics, and both stationarity and invertibility conditions of Autoregressive (AR) and Moving average (MA) were also tested. Then, model calibration was carried out using Kolmogorov-Smirnov, Anderson- Darling and Rayan-Joiner. The selected ARIMA models are ARIMA(0,0,11)*(0,0,1), ARIMA(2,0,4)*(1,1,0), ARIMA(4,0,0)*(0,1,1), ARIMA (1,0,1)*(0,1,1), ARIMA (1,0,0)*(0,1,1) for relative humidity, evaporation, air temperature, wind speed and sunshine, respectively. The fitted models were then used to forecast the parameters. Finally, trend analysis of forecasted data was done in order to investigate the climate change. This study emphasizes efficiency of time series modeling in water resources studies in order to forecast climatic parameters.
S. A. Banimahd, D. Khalili, A. A. Kamgar-Haghighi, Sh. Zand-Parsa,
Volume 18, Issue 70 (3-2015)
Abstract
In the present research, the performances of six empirical models, i.e., simple threshold exceedance, fixed proportion exceedance, quadratic function of storage, power function of storage, cubic function of storage, and exponential function of storage were investigated for estimation of groundwater potential recharge in a semi-arid region. First, the FAO Dual Crop procedure was used to calibrate evaporation from bare soil during the occurrence of potential recharge period. Then, the empirical models were calibrated utilizing soil moisture and potential recharge data. For validation of empirical models, soil moisture and potential recharge were simultaneously estimated for an independent event. Results indicated that 5 of the six models (except for the simple threshold exceedance model) were able to estimate potential recharge with a reasonable accuracy, showing the maximum computed value of NRMSE (Normalized Root Mean Square Errors) of 24.4 percent. According to validation results, exponential, cubic, and power function models provided better estimation of potential recharge in comparison with the linear models. Also, all of the applied empirical models were able to simulate soil moisture during the recharge period with an acceptable accuracy. Finally, the exponential model with minimum NRMSE value for soil water simulation and also acceptable performance of potential recharge estimation was recommended for estimation of potential recharge in the study area.
R. Ziaee, M. Moghaddasi, S. Paimozd, M. H. Bagher,
Volume 22, Issue 4 (3-2019)
Abstract
Evaporation is one of the important components in water body’s management, leading to changes in the water level and water balance. Also, its accurate estimation is faced with certain difficulties and complexities. Because of the limitations of physical and empirical methods based on the meteorological data, remote sensing technology can be widely used for evaporation calculation due to its capabilities for spatial data estimation and minimization of the meteorological data application. Many models have been developed to estimate evapotranspiration using remote sensing technology. Regarding the use of these algorithms for estimating evaporation from water surface, a few studies have been done; however, there is yet no comparison between them to estimate evaporation from the water surface. For this purpose, in this study, the output from two models estimating spatially distributed evaporation of water surfaces from remotely sensed imagery is compared. In order to implement these models, Terra/MODIS Images for four months including June, July, August and September in of 2006, 2007, 2008 and 2009 were prepared. Comparisons were made using pan data from Urmia synoptic station. In general, there was a reasonable agreement between the evaporation outputs from both models versus a pan data observation. The statistical analysis also showed that the SEBS algorithm (by applying the salinity factor), despite being simple in its implementation, has higher accuracy than the SEBAL algorithm.
M. Karim Zadeh, J. Zahiri, V. Nobakht,
Volume 26, Issue 4 (3-2023)
Abstract
Reservoir dams have had problems despite all the benefits for humans. one of the most important issues is exposing a large amount of water in contact with the air causing a large amount of water to evaporate. Using chemical methods including heavy alcohols is one of the evaporation suppression methods. In this study, three emulsions of octadecanol, hexadecanol, and a combination of octadecanol, and hexadecanol along with Brij-35 and two physical methods of the canopy and floating balls were used to evaluate the performance of different emulsions. A one-way analysis of variance was applied to compare the mean of evaporation in different chemical and physical methods and a two-way analysis of variance was performed to investigate the main and interaction effects of different meteorological parameters on the value of evaporation. The mean comparison of the evaporation in different methods showed that the two physical methods of the canopy and floating balls had better performance than the chemical methods, and the octadecanol was more efficient than the two other chemical methods. The results of one-way ANOVA showed that among the chemical methods, the octadecanol had no significant difference with floating balls at a 99% probability level (P <0.01). Two-way ANOVA indicated that air temperature and relative humidity had the greatest effect on evaporation. Examination of the effect of different levels of meteorological parameters on the performance of evaporation reduction methods showed that at low temperatures, octadecanol had poor performance than the two physical methods but with increasing temperature, its performance improved. In addition, this monolayer had a suitable performance at low wind speeds compared to physical methods. By increasing wind speed, its performance is severely affected and its efficiency decreases. So, at temperatures above 37° C, an increase in wind speed from 3.5 m/s to above 8.7 m/s has increased evaporation by more than 50%. The effects of monolayers and other evaporation suppression methods on the quality characteristics of the water including dissolved oxygen are significant and should be investigated in future research.
H. R. Ghazvinian, H. Karami, Y. Dadrasajirlou,
Volume 28, Issue 2 (8-2024)
Abstract
One method used to estimate the evaporation rate involves employing various types of evaporation pans, including the standard Colorado Sunken and Class A evaporation pans. This study aimed to investigate and compare the evaporation rates from two pans, Class A and Colorado Sunken, in Semnan City. The Colorado Sunken evaporation pan was utilized as the test pan, and the test was conducted in an open space near the Faculty of Civil Engineering at Semnan University, located in Semnan City. Evaporation measurements were recorded daily for 123 days, from June 1, 2017, to September 31, 2017. The evaporation amount from the Class A pan was obtained from the synoptic station of Semnan city, situated 2.39 km away from the test site, and was subsequently analyzed. Meteorological data, including maximum and minimum temperature, maximum and minimum relative humidity, wind speed, sunshine hours, and air pressure, were also collected from the Semnan synoptic station and compared with the experimental evaporation data. The results indicated no significant difference in the daily evaporation amount between the Class A pan and the Colorado Sunken pan during the tested periods. The best statistical distribution, based on Kolmogorov–Smirnov test, for the Class A evaporation pan and the buried Colorado pan, were selected as Error with (k-s=0.05019) and Gamma with (k-s=0.05552). The coefficient of determination between the two pans was estimated to be approximately 93%. Further analysis revealed that the rate of evaporation is most closely associated with the maximum daily temperature. Pearson's correlation coefficient for the maximum temperature with the Class A evaporation pan and the Colorado Sunken pan was found to be 0.623 and 0.647, respectively.
