Showing 11 results for Water Requirement
A. Hassanli, A. Sepaskhah,
Volume 4, Issue 2 (7-2000)
Abstract
In this study, seven citrus gardens in different parts of Darab were chosen to evaluate the drip irrigation systems. The evaluation process was based on the Merriam and Keller’s model (1978). Besides the evaluation of drip irrigation systems, the water requirement of citrus was estimated using four models including Blany-Criddle modified by FAO, Hargrive-Samani, Pan Evaporation and Solomon-Kodama model. On the basis of the results obtained by Hargrive-Samani with 1296 mm annual water requirements, a comparison was made between irrigation with existing systems and irrigation under favorable and desired conditions.
The results from field measurements indicate a considerable reduction in the emitter discharges. The low pressure and emitter clogging could be two major reasons for the problem. Low pressure at head control, topography, head losses and also using no filter(s) or unefficient filters are the main reasons for the reduction. In some gardens, overirrigation even up to 2.5 times of water requirement was practiced by using extra emitters and increased irrigation times. Overirrigation causes considerable water losses through deep percolation and in reased overwetting area.
Field measurements indicated a good emission uniformity (EU) for the fields with overirrigation. EU in chosen fields varied from 40 to 91%, AELQ varied from 31 to 82% (poor to good) and PELQ varied from 36 to 82%. This study showed that most farmers are not familiar with plant water requirements. The fields with efficient filtration due to using extra emitters per plant are mainly overirrigated. But fields without any filter of unefficient filters are not irrigated sufficiently. The very high manufacturing variation coefficient of IEM emitters (Cv=0.22), which are widely used in Darab, causes a design emission uniformity of 55%.
N. Pirmoradian, A. A. Kamgar Haghighi, A. R. Sepaskhah,
Volume 6, Issue 3 (10-2002)
Abstract
This research was conducted in Kooshkak Farm Research Station of Shiraz University in 1997 and 1998 in order to determine crop coefficient and water requirements of rice, using lysimeter. The variety used was Champa-Kamfiroozi which is an early mature variety and is grown by most farmers in the area. Results showed that potential evapotranspiration varied from 3.76 to 9.34 mm/day. Penman FAO method was used in calculating reference evapotranspiration. Crop coefficient was 0.97 in the initial growth stage, 1.25 in the mid-season growth stage, and 1.09 at the time of harvest. Total crop evapotranspiration rates in 1996 and 1997 were 560 and 757 mm, respectively. Average deep percolation rates in the growing season was 3.4 and 3.5 mm/day in 1996 and 1997, respectively. Finally the total water requirements of rice in 1996 and 1997 were 1983 and 2361 mm, respectively.
J. Niazi, H. R. Fooladmand, S. H. Ahmadi, J. Vaziri,
Volume 9, Issue 1 (4-2005)
Abstract
A research was conducted in Fars province Agricultural Research Center in Zarghan area from 1999 to 2002 to determine the water requirement and crop coefficient of wheat, applying lysimeter.
The results indicated that the water requirements of wheat were 720, 712 and 674 mm in the years of 1999-2000, 2000-2001 and 2001-2002, respectively. Using Penman-Monteith method for estimating reference crop potential evapotranspiration, the crop coefficients for wheat at a four-stage crop growth were 0.37, 0.64, 1.10 and 0.51, respectively. Due to the inaccessibility of the whole weather data, we tried to figure out a solution to determine wheat water requirement to schedule irrigation planning for future. In this respect, we made use of a ten-day class A pan mean evaporation and crop coefficient.
J. Abedi Koupai, J. Khajeali, R. Soleimani, R. Mollaei,
Volume 18, Issue 67 (6-2014)
Abstract
As increasing of disaster such as drought and pest invasion in recent decades, it is essential to find out practical
approaches in optimizing water use and water management for reduce the adverse effects of this disaster in agriculture.
In order to study the effects of water stress and pest stress on corn yield, an experiment was conducted in the research
farm of Isfahan University of Technology. In sprayed and non sprayed of the field, a factorial design, based on the
completely randomized block, was carried out with three treatments of irrigation regimes including intensive stress
(50% water requirement), moderate stress (75% water requirement) and no water stress in four stages of corn growth
from seed germination until tasseling, from tasseling until milky, from milky until harvest and the whole period of corn
growth, in four replications for one year (2005). The results showed that applying water stress on corn reduced seed
yield between 6-62% and also decreased other agronomic characters except protein percentage. Water stress in non
sprayed condition, reduced significantly more physiological characteristics of corn compared to the sprayed condition.
Intensive water stress and pests stresses increasd 3 and 13% of percentage protein, respectively. In sprayed condition
applying moderate stress in first stages of corn until the first of third stage is suggested in drought condition.
. A. A. Sabziparvar1, S. Ebrahimzadeh2, M. Khodamoradpour3,
Volume 21, Issue 4 (2-2018)
Abstract
The most important factor in determining crop water requirement is estimation of evapotranspiration (ET). Majority of the methodsestimate ET apply series of relatively complex formula,which is then used to determine crop evapotranspiration (ETc). The parameters used in aforesaid methods are: Solar radiation, wind speed, humidity, etc. Unfortunately, in Iran and many countries, long-term records of these parameters are not readily available. The purpose of this study is to calculate the Selianinov Hydrothermic Index that merely requires daily temperature and precipitation data in order to determine correlation coefficients (r) versus ET and Crop Water Requirement (CWR) of some agricultural crops of Iran. First, the Selianinov index is calculated from daily precipitation and temperature during the growth season. Further, the results are correlated against both ETc and CWR. The model results indicate inverse (negative) strong exponential and polynomial relations between the dependent and independent variables. Coefficient of determination (R2) for polynomial equations (on average 0.84) in all crops was better than exponential equations (on average 0.72). Correlation between Selianinov index and CWR indicates that coefficient of determination in both equations was close together (0.83 for polynomial equations and 0.82 for exponential equations).
M. Jahan, B. Amiri,
Volume 22, Issue 3 (11-2018)
Abstract
Factor analysis is one of the multivariate statistical techniques that considers the interrelationships between apparently irrelevant variables and helps researchers to find the hidden reasons for the occurrence of an event. In order to evaluate the effects of different irrigation levels and humic acid foliar application and identify the factors affecting water use efficiencies of sesame (Sesamum indicum L.), maize (Zea mays L.) and common bean (Phaseolus vulgaris L.), a split plots experiment based on RCBD design with three replications was conducted during the 2014-15 growing season, at the Research Farm of Ferdowsi University of Mashhad, Iran. Irrigation levels (50 and 100% of water requirement) and foliar application and non-application of humic acid were assigned to main and sub plots, respectively. The results showed that in sesame, the highest seed yield and biological yield were obtained from 100% of water requirement and humic acid spraying treatment. In maize, humic acid spraying under condition of supplying 50% of water requirement increased seed weight per plant, plant height, and leaf area index and soil pH In bean, the highest seed weight per plant, plant height, leaf area index, crop growth rate and soil phosphorous content were observed in the treatment of 100% of water requirement and humic acid spraying. Factor analysis results also showed that in sesame, the variables of seed yield, biological yield, seed weight per plant, plant height, leaf area index, crop growth rate, soil phosphorous and water use efficiency were assigned to the first factor and the variables of soil nitrogen, soil pH and EC were assigned to the second one. In maize, seed yield was assigned in the same group with the variables of biological yield, leaf area index, crop growth rate, soil phosphorous, EC and pH and water use efficiency; in bean, this was with the variables of seed yield and water use efficiency. In general, the research results revealed that identifying the effective variables in each factor and those logical nominations according to Eco physiological knowledge can lead to the direct management of effective variables with regard to associated factor, thereby leading to water efficiency improvement.
N. Ganji Khorramdel, S. M. R. Hoseini,
Volume 23, Issue 2 (9-2019)
Abstract
Estimation of evapotranspiration is essential for planning, designing and managing irrigation and drainage schemes, as well as water resources management. In this research, artificial neural networks, neural network wavelet model, multivariate regression and Hargreaves' empirical method were used to estimate reference evapotranspiration in order to determine the best model in terms of efficiency with respect to the existing data. The daily data of two meteorological stations of Shahrekord and Farrokhshahr airport in the dry and cold zones of Shahrekord during the period 2013-2004 was used; these included the minimum and maximum temperature, the average nominal humidity, wind speed at 2 meters height and sunshine hours. %75 of the data were validated, and %25 of the data was used for testing the models. Designed network is a predictive neural network with an active sigmoid tangent function hidden in the layer. In the next step, different wavelets including Haar, db and Sym were applied on the data and the neural network-wavelet was designed. To evaluate the models, the method was used by the Penman-Montith Fao and for all four methods, RMSE, MAE and R statistical indices were calculated and ranked. The results showed that the wave-let- neural network with the db5 wavelet had a better performance than other wavelets, as well as the artificial neural network, multivariate regression and the Hargreaves method. The results of wavelet network modelling with the db5 wavelet in the Farrokhshahr station were calculated to be 0.2668, 0.2067 and 0.998, respectively; at the airport station, these were equal to 0.2138, 0.14 and 0.9989, respectively. The results, therefore, showed that the neural network-wavelet performance was more accurate than the other models studied in this study.
P. Shojaei, M. Gheysari, H. Nouri, H. Esmaeili, S. Eslamian,
Volume 23, Issue 3 (12-2019)
Abstract
Creation and conservation of urban parks is challenging in arid environments where daily thermal extremes, water scarcity, air pollution and shortage of natural green spaces are more conspicuous. Water scarcity in the arid regions of Iran is major challenge for water managers. Accurate estimation of urban landscape evapotranspiration is therefore critically important for cities located in naturally dry environments, to appropriately manage irrigation practices. This study investigated two factor-based approaches, Water Use Classifications of Landscape Species (WUCOLS) and Landscape Irrigation Management Program (LIMP), to measure the water demand in a botanic garden. The irrigation water volume applied was compared with the gross water demand for the period from 2011 to 2013. On average, WUCOLS estimated an average annual irrigation need of 1164 mm which is 15% less than the applied value of 1366 mm while the LIMP estimate of 1239 mm was 9% less than the applied value. Comparison of estimated and applied irrigation showed that a water saving of 9% can be made by the LIMP method. The outcomes of this research stressed the need to modify the irrigation requirements based on effective rainfall throughout the year, rather relying on long-term average data.
N. Salamati, H. Dehghanisanij, L. Behbahani,
Volume 26, Issue 2 (9-2022)
Abstract
Increasing crop production per unit volume of water consumption requires recognizing the most dependent variable in drip irrigation to the volume of water consumption and also identifying the most important variables independent of water productivity in surface and subsurface drip irrigation for optimal use of available water resources. The present research was carried out in Behbahan Agricultural Research Station during four cropping seasons (2013-2017) on a Kabkab date variety. Experimental treatments include the amount of water in the subsurface drip irrigation method based on two levels of 75% and 100% water requirement and in surface drip irrigation based on 100% water demand. Data were analyzed using a randomized complete block design with three replications. The results of the analysis of variance of the mean of different irrigation treatments in quantitative traits showed that the effect of irrigation was significant at the level of 1% in terms of cluster weight index, fruit weight, and fruit flesh to kernel weight ratio. The results of regression analysis of variance showed that in the dependent variable of cluster weight, the consumption water volume explained 19.1% (R2 = 0.191) of the fluctuations of the dependent variable (cluster weight). Among all the studied variables, the volume of water consumption explained the most significant changes in date cluster drying. Fruit moisture with t (2.096) and equivalent beta coefficient (0.046) had a significant positive effect on water productivity at the level of 5%. The results of the Pearson correlation coefficient showed that the effect of yield on changes in water productivity was much greater than the volume of water consumed so the yield caused significant changes in water productivity. While the effect of water consumption on water productivity was not significant.
N. Salamati, M. Moayeri, F. Abbasi,
Volume 27, Issue 2 (9-2023)
Abstract
The objective of the present study was to conduct field studies for direct measurement of canola under farmers' management in one crop season (2019-2020) in 27 farms in Behbahan, Khuzestan province. Water requirement was calculated based on the FAO Penman-Monteith model using the daily statistics of the Behbahan synoptic meteorological station. A T-test was used to statistically compare the results such as the depth of irrigation and applied water productivity in the field in different irrigation systems. Linear multivariate regression analysis was used to investigate the effects of the independent variable on the dependent parameter of water productivity. The volume of applied water in the fields ranged from 4085.5 to 7865.3 m3/ha. The results of comparing the average yield of two irrigation systems in the t-test showed that the two sprinkler and surface irrigation systems with yields of 2614 and 2330 kg/ha, respectively, were not significantly different. Applied water productivity in traditional and modern irrigation systems was calculated to be 0.386 and 0.486 kg/m3, respectively, which had significant differences. The results of the analysis of variance in the regression model showed that among the independent variables, yield with t-statistic (23.997) and equivalent beta coefficient (0.880) had the most significant positive effect at a 1% level on applied water productivity. After that, the volume of applied water (irrigation water + effective rainfall) with a t-statistic of (-11.702) and a beta coefficient of equivalent (-0.793) had the most negative and significant effect at the level of 1% on the applied water productivity. The results of the Pearson correlation coefficient showed that irrigation events had a positive and significant correlation at a 5% level with applied water and yield. These correlations were 0.455 and 0.380, respectively. By increasing irrigation events, the volume of applied water has practically decreased and has become as close as the plant needs, and has increased water productivity.
M. Paritaghinezhad, H.r. Kamali, S. Jamshidi, M. Abdolahipour,
Volume 27, Issue 2 (9-2023)
Abstract
According to the effects of climate change on evapotranspiration and using of water resources, climate change prediction is vital due to water resources management improvement and decreasing damages of drought. The first rank of mango production in Iran belonged to Hormozgan province and the most amount of mango produced in Minab plain. In the present study, the amount of evapotranspiration of mango plants was calculated with FAO Penman-Monteith from 1985 to 2020 using meteorological data at Minab station. The evapotranspiration values of the plant were estimated from 2021 to 2100 with two optimistic and pessimistic scenarios using the last version of CMIP (CMIP6), atmospheric-ocean general circulation models, and performing statistical deviation corrections by the Python software. The results showed that the values of annual evapotranspiration will increase by 0.31 and 1.23 mm on average in the optimistic and pessimistic scenario, respectively in the future due to the increase in annual temperature.
