JWSS - Journal of Water and Soil Science

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Water deficit, ultraviolet radiation and CO₂ concentration enhancement are three environmental stresses that affect nutrition of human in future. This research was conducted in the Research Greenhouse of Faculty of Agriculture, Tarbiat Modares University in 2006, in order to study leaf qualitative traits of durum wheat under different levels of carbon dioxide (400 and 900 ppm), ultraviolet radiation (UV A, B and C) and water deficit (up to %60 of field capacity). Ultraviolet radiation enhancement increased anthocyanin, flavenoids and carotenoids of durum wheat leaf. There was no significant interaction effect between carbon dioxide and water deficit on anthocyanin and carbohydrates. Also, the interaction effects among the three factors were not significant on anthocyanin, carotenoids, chlorophyll a and a+b. Water deficit decreased leaf proteins. Increasing intensity of ultraviolet radiation and carbon dioxide enrichment decreased soluble leaf protein in durum wheat under water deficit conditions. The results showed that three main environmental stresses which reduce leaf pigment and plant protection due to negative effects of these stresses along with soluble leaf protein reduction decrease qualitative and quantitative yield of the wheat variety.

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Dates of start and end of frost based on minimum shelter temperature equal to or less than 0°C were studied in Zanjan, Ghazvin and Tehran during 1961-2000. The cause of these frosts was determined by weather parameter values at observation hours and the aid of synoptic maps. Frost series based upon last spring or first fall advection are defined and found to be random and normally distributed. The "potential growing season", defined as the interval between spring last and first fall advection frosts, is found to be 29 days in Zanjan, 23 days in Ghazvin and 10 days in Tehran longer than the "growing season" defined by the interval from last spring to first fall occurrences of minimum shelter temperature of 0°C or less. The numbers of radiation frosts in the interval between first radiation frosts in fall or last radiation frost in spring and related advection frost were counted and found that this parameter is greater in Zanjan. Frostless days between the first two fall frosts and last two spring frosts show that the lengthening of spring season with one night protection is possible for 4 days in Zanjan, 6 in Gazvin and 4 in Tehran, providing that first fall and spring last frost is radiation. Results of this study permit estimating the practicality of frost protection for specialized crops in the area of study.

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Global solar radiation (Rs) has wide applications in several disciplines. The data of measured or predicted Rs are widely applied by solar engineers, architects, agriculturists and hydrologists. Due to the importance of Rs, several empirical models have been developed to predict its values all over the world. In this study, Angstrom model was calibrated based on the ratio of actual and possible sunshine hours n/N by using measured daily data of Rs at Bajghah meteorological station in Fars province during 2003-2004. The model was modified by using air temperature for considering the effect of cloudy conditions as well as n/N ratios. The results showed that using both the air temperatures and the ratios of n/N led to a higher accuracy. In regard to estimation of the Rs values, the results showed that mean air temperatures have a higher accuracy compared with differences between maximum and minimum air temperatures. Also, a new local model with higher accuracy was developed based on a number of daily meteorological parameters such as deficit vapor pressure, relative humidity, precipitation, mean air temperature, maximum and minimum air temperatures difference and n/N. This new local model that used different meteorological parameters had the highest accuracy in comparison with the other models. Also, a number of models developed by other investigators for estimation of Rs were calibrated for the study area. Finally, different selected models were validated by using the measured data of Rs in 2005. The results showed that the developed local multi-variable model provided higher accuracy results in comparison with the other radiation models.

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In this research, samples of sugarcane bagasse were irradiated with various amounts (0, 100, 200 and 300 Kilogray) in an electron accelerator (TT200) to evaluate the effects of electron-beam irradiation on dry matter, neutral-detergent fiber (NDF) and acid-detergent fiber (ADF) degradability parameters. The first samples were dried and then ground for chemical analysis. The ruminal degradation parameters of the samples were measured in fistulated cow 3 (400 kg) at times of 0, 6, 12, 24, 48, 72 and 96 h by the terylene bag method. Data were fitted to non-linear degradation model of Orskov and McDonald to calculate degradation parameters of DM, NDF and ADF. The statistical analysis of degradation of various parameters and effective degradability was accomplished by using the GLM procedure of SAS. After variance analysis, the means were compared with Duncan,s new multiplerange test by using a completely randomized design. The washout fractions of DM as well as NDF and ADF increased linearly (P<0.05) with increasing electron irradiation dose, whereas the potentially degradable fractions of NDF and ADF decreased at first, and then, increased. Also, the degradation rate of the b fraction of dry matter increased. Effective degradability of DM, NDF and ADF increased linearly (P<0.05) with increasing irradiation dose. Electron irradiation at doses of 100, 200 and 300 kGy increased the effective degradability of DM, NDF and ADF at rumen outflow rate of 0.05/h (r) by about 7, 11 and 16% 2, 5 and 7% 3, 7 and 10%, respectively.

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Daily solar radiation intercepted at the earth’s surface is an input required for water resources, environmental and agricultural studies. However, the measurement of this parameter can only be done in a few places. This has led researchers to develop a number of methods for estimating solar radiation based on frequently available meteorological records such as hours of sunshine or air temperature. In this study two empirical Angestrom and Hargreaves- Samani models, which are respectively based on air temperature and sunshine duration were calibrated and evaluated for estimating solar radiation in southeast of Tehran, Iran. Also, two neural networks models were presented using similar inputs and above-mentioned empirical models. The results showed that the both empirical and neural network models provided closer agreement with the measured values, but the models based on sunshine hours gave better estimates than the models based on air temperature. The neural network model based on sunshine hours with a R2 of 0.97 and a RMSE of 1.34 MJ m-2 d-1 provided the best results

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In this study, the remote sensing statistical approach was used to determine the global solar radiation from NOAA-AVHRR satellite data in southeast of Tehran. This approach is based on the linear correlation between a satellite derived cloud index and the atmospheric transmission measured by the clearness index on the ground. A multiple linear regression model was also used to convert the five AVHRR data channels and extraterrestrial radiation to global solar radiation. The results of this study showed that multiple linear regression model estimated the solar radiation with an R2 of 0.93 and a root mean square error (RMSE) of 5.8 percent, which was better than the statistical approach.

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Global solar radiation (Rs( on a horizontal surface in the estimation of evapotranspiration of plants and hydrology studies is an important factor. Average daily global solar radiation on a horizontal surface was estimated by artificial neural networks (ANNs) and five empirical models including FAO (No.56), Hargreaves-Samani, Mahmood-Hubard, Bahel and Annandale. The weather data was selected from Karaj, Shiraz, and Ramsar weather stations, which have arid, semi arid and very humid climates (based on De Martonne classification). Daily solar radiation was measured at the three sites selected. The ANN, with actual duration of sunshine and maximum possible duration of sunshine as input parameters, generated daily solar radiation estimates with highest level of accuracy among all models tested. Rs estimates by ANNs with only temperature indices as input and by Hargreaves-Samani, Annandale and Mahmood-Hubard, which are all temperature oriented models, had lower accuracy at all three sites. In contrast, ANNs with actual duration of sunshine and maximum possible sunshine hours as inputs in Karaj, Shiraz and Ramsar station with root mean square error (RMSE) of 2.08, 1.85 and 2.05 Mj m-2 day-1 respectively were the best models. After ANNs, FAO-56 model which is based on sunshine hours produced results closer to the measured values. Rs estimates by ANNs with only temperature indices as input and by Hargreaves-Samani, Annandale and Mahmood-Hubard which are all temperature oriented models, had lower accuracy at all the three sites. These models are not appropriate for estimating daily global solar radiation.

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Reference evapotranspiration (ET0) is a necessary parameter for calculating crop water requirements and irrigation scheduling. In this study, a method was presented as ET0 is estimated with NOAA satellite imagery in the irrigation network. In this method, a pixel from a set of pixels within the irrigation network was chosen with the highest vegetation index, and its surface temperature (Ts) with extraterrestrial radiation parameter (Ra) was used as inputs of the model. The M5 model tree for converting Ta and Ra to ET0 was used as input variables. In this research, Gazvin irrigated area was selected as a case study. A total of 231 images of NOAA satellite related to irrigation season of the study area were used. The results obtained by the M5 model were compared with the Penman–Monteith results, and error values were found within acceptable limits. The coefficient of determination (R2), percentage root mean square error (PRMSE) and the percentage mean bias error (PMBE) were found to be 0.81, 8.5% and 2.5%, respectively, for the testing data set.

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Concerning the drying problem of the Lake Urmia in Iran, so far the relevant scientific research has not been conducted based on watershed management principles. The surface solar radiation (Rs) is one of the key input parameters in most of reference evapotranspiration (ET0) prediction models. In the present research, four solar radiation models were evaluated to predict the monthly-mean values of daily ET0 at seven synoptic stations located in the Lake Urmia basin during the 1985-2005 period. For the ET0 prediction, we applied the Penman-Monteith-FAO 56 model (PMF56). At first, we evaluated four radiation models consisting of Hybrid: H, Ångström-Prescott: AP, Modified Daneshyar: MD, and Modified Sabbagh: MS. Four statistical criteria used included the mean error (ME), the mean absolute error (MAE), the root mean square error (RMSE), and the mean percentage error (MPE). The mean RMSE value of hybrid model was 1.7 MJ/m2/day while the RMSEs for the AP, the MD and the MS models were 2.9, 2.3, and 2.9 MJ /m2/day, respectively. The results revealed a higher performance of hybrid model to predict the monthly radiation. In addition, the Rs models used in the original PMF56 model were compared with a case in which the measured daily Rs data was used. Finally, by integrating the hybrid model and the PMF56, we developed a coupled model as PMF56-Hybrid. The application of the Hybrid and the MD models resulted in a decrease in the RMSEs. The AP model used in the PMF56 showed about 19% overestimation.

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Accurate estimation of ET₀ in any region is very important. The aim of this study is to compare and calibrate the 20 empirical methods of estimating evapotranspiration (ET₀) based on three categories in monthly timescale at the Urmia Lake watershed. These categories are: 1) temperature-based models (Hargreaves (HG), Thornthwaite (TW), Blaney-Criddle (BC), Linacre (Lin)), 2) radiation-based model (the Doorenbos-Pruitt (DP), Priestly-Taylor (PT), Makkink (Mak), Jensen-Haise (JH), Turc (T), Abtew (A), McGuinness-Bordne (MB)) and 3) mass transfer-based model (Meyer (M), Dalton (D), Rohwer (R), Penman (P), Brockamp-Wenner (BW), Mahringer (Ma), Trabert (Tr), WMO and Albrecht (AL)). For this purpose, the information of 10 synoptic meteorological stations during the period of 1986-2010 was used. Results from the above mentioned methods were compared with the output of the FAO Penman-Monteith (PMF-56) method. Performance of the methods evaluated using the R², RMSE, MBE and MAE statistics. The best and worst methods of each category were determined for the study area. The best methods of each category were calibrated for the area under study. Results indicated that there is a significant difference between the results of selected methods of each category and the PMF-56 method. Performance of the selected methods remarkably increased after calibration. Among the temperature-based group, the HG method having the median R² value of 0.9597 was recognized as the best method. After calibration the medians of RMSE, MBE, and MAE were 72.09, 3.14 and 10.70 mm/ month, respectively. After HG, the Lin and BC found to be the best second and third methods in the study area. The TW showed Large error, therefore, it was not a suitable method for ET₀ estimation in study area. Among the radiation-based group, the DP model was selected as the best method in the study area. Furthermore, the median of R² values was 0.982. In this method, the medians of RMSE, MBE and MAE after calibration were 7.89. -0.62 and 6.03 mm/month, respectively. Following DP, the PT method was recognized as the 2^nd best one. The methods namely M, JH, T, A and MB were put in the 3^rd to seventh rank of the radiation category. Finally, among the mass transfer-based group, having R²=0.8945, the Meyer method was selected as the best method of this group for the study area. In the mentioned method (after calibration) the medians of RMSE, MBE, and MAE were 21.8, -8.7 and 17.3 mm per month, respectively. From mass transfer based group, the D method was found as the second best method in the study area. The methods namely R, P, BW, Ma, Tr, WMO and A were ranked 3^rd to 7^th, respectively. In general, the performance of radiation based methods was superior than others in Urmia Lake basin. Temperature based methods and mass transfer based methods were ranked second and third, respectively. Further examination of the performance resulted in the following rank of accuracy as compared with the PMF-56: DP (Radiation based), HG (Temperature based) and Meyer (Mass transfer). In general, it can be concluded that after calibration the DP method is suitable to estimate reference crop evapotranspiration among 20 selected methods in the Urmia Lake basin.

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