Research Paper
Mahsa Sameti; NOZAR GHAHREMAN; Khalil Ghorbani
Abstract
The capability of M5 model tree in estimating reference evapotranspiration in two stations, namely, Shiraz and Kermanshah, was studied. The daily weather data including mean air temperature, sunshine hours, precipitation, dew point temperature, mean relative humidity, wind speed and actual vapor pressure ...
Read More
The capability of M5 model tree in estimating reference evapotranspiration in two stations, namely, Shiraz and Kermanshah, was studied. The daily weather data including mean air temperature, sunshine hours, precipitation, dew point temperature, mean relative humidity, wind speed and actual vapor pressure were collected and used as input variables for daily estimation of potential evapotranspiration by Penman-Montieth and Hargreaves-Samani equations. As the main goal of this study, the performance of M5 model tree in predicting reference evapotranspiration was evaluated. The results showed that the skill of M5 model in predicting ET by both methods was high but its performance in predicting Penman-Montieth values was relatively more, with R2 of 0.975 and 0.973 and RMSE values of 0.346 and 0.361 for Shiraz and Kermanshah, respectively, while the corresponding values for Hargreaves-Samani equation were Shiraz:R2=0.837, RMSE=0.844, and Kermanshah:R2=0.979, RMSE= 0.774. Sensitivity analysis revealed that the most significant variables in Penman-Montieth equation in Shiraz station were, respectively, air temperature, dew point, sunshine hours, and wind, while in Kermanshah station, important factors were air temperature, sunshine hours, wind, relative humidity, and dew point, respectively. Further studies are recommended in other climates for more scrutiny.
Masoud Mohammadi; Bijan Ghahreman; Kamran Davari; Majid Vazifehdoost; Hamideh Noori
Abstract
Field studies to determine optimum amount of water required for maximum production are time-consuming and expensive. Therefore, in this study the agro-hydrological model SWAP 3.03 was used to simulate winter wheat yield under different qualities and quantities of irrigation water and to determine water-salinity-yield ...
Read More
Field studies to determine optimum amount of water required for maximum production are time-consuming and expensive. Therefore, in this study the agro-hydrological model SWAP 3.03 was used to simulate winter wheat yield under different qualities and quantities of irrigation water and to determine water-salinity-yield optimum function. Irrigation treatments consisted of four water salinity levels (S1=0.7, S2=2, S3=4 and S4=6 dS/m), three amounts of water (W1=80, W2=100, and W3=120 mm), and six levels of management allowed depletion (MAD1=0.3, MAD2= 0.4, MAD3= 0.5, MAD4= 0.6, MAD5= 0.7 and MAD6= 0.8). Yield and water use efficiency values were determined in different modes and the best MAD value obtained was 0.5. Yield data were fitted to different forms of production functions (simple linear, logarithmic linear, quadratic and transcendental) and the best one was established based on sensitivity analysis. The maximum grain yield (6619 kg/ha) corresponded to W1S1MAD2 treatment and the minimum yield (2048 kg/ha) corresponded to W1S4 MAD3 treatment. The results showed that the quadratic production function was optimal for production and could be recommended. Investigation of the maximum values of error (ME) showed that the logarithmic linear and simple linear functions had the highest error. In the irrigation treatments, W1S1MAD3 and W1S1MAD4 with 0.61 kg /m3 had the highest water use efficiency. However, water use efficiency decreased when water stress and salinity increased. The iso-yield curve showed that by increasing amounts of irrigation, more saline water could be applied without a change in yield.
Research Paper
Arash Tafteh; Niazali Ebrahimipak; Hossin Babazadeh; Fereydoon Kaveh
Abstract
Management of water distribution in the Qazvin Plain is planned on monthly intervals. Therefore, production functions which can accurately predict yield reduction under deficit irrigation on monthly basis are needed. This study was conducted with the following purpose: assessment of the production functions ...
Read More
Management of water distribution in the Qazvin Plain is planned on monthly intervals. Therefore, production functions which can accurately predict yield reduction under deficit irrigation on monthly basis are needed. This study was conducted with the following purpose: assessment of the production functions using different methods including, minimum, average, multiplicative, Raes method, and product with yield response factor (Ky) power as applied by FAO and Najarchi yield response factors. To estimate tomato yield under different deficit irrigations and evaluation of empirical methods, a study was conducted by using randomized complete block design with irrigation interval treatments including T1, T2, T3, and T4 representing, respectively, 60, 90,120, and 150 mm evaporation from class A pan between consecutive irrigations. The study had three replications and was carried out at the Faizabad Agricultural Research Station, in Qazvin. The results showed that maximum water requirement of tomato plant was 1073 mm, T1 treatment had the maximum yield with 88500 kg/ha and T4 treatment had the minimum yield with 57000 kg/ha. Also, according to statistical comparisons, the proposed method that estimated the plant response factor based on monthly power had the minimum root mean square error (RMSE) and normal root mean square error (NRMSE), while it had the highest agreement index and coefficient of determination (R2).The plant yield response factors were determined in June, July, August, September, and October as, respectively, 0.7, 1.1, 1.1, 1.14 and 0.4. The value of this factor for initial growth, plant development satge, mid-season, and late-season were, respectively, 0.7, 1.1, 1.14, and 0.4, while the average for the whole growing period was determined as 0.89 by using the proposed method. As a result, the proposed method is suggested as a convenient method.
Research Paper
Nabi Ashrafi; Ali Nikbakht; Mehdi Gheysari; Nemat Etemadi; Rikardo fernandezescobar
Abstract
A principle that is of high importance in sustainable landscape management and water-wise landscaping is the wise use of low-quality water resources in agriculture and urban landscape maintenance. In addition, use of trees with low water requirement is a major factor in landscaping. In order to investigate ...
Read More
A principle that is of high importance in sustainable landscape management and water-wise landscaping is the wise use of low-quality water resources in agriculture and urban landscape maintenance. In addition, use of trees with low water requirement is a major factor in landscaping. In order to investigate the impact of water quality and its application method on nutrients absorption by olive trees, an experiment was carried out during 2010-2012 in Isfahan University of Technology on one-year old olive trees. The trees were irrigated by two methods i.e. a new subsurface leaky irrigation (SLI) system and surface irrigation, and two water quality treatments i.e. clear and reclaimed water, for two years Results showed that recycled water increased nutrient elements nitrogen, phosphorous, potassium, and magnesium (N, P, K, Mg) in leaves of the plants. The applied recycled water improved height, shoot number, and chlorophyll content. Irrigating trees by SLI system enhanced growth and shoot number. Nutrient elements (N, Mg, P) content in trees grown under SLI irrigation system was higher than surface system. To sum up, this experiment showed that recycled water could be a promising source for landscape trees irrigation. Also, SLI in this research was more efficient than the surface system in irrigation of urban landscape.
Research Paper
Meysam Ramezani; Shokoofeh Salehi; Abdolmajid Liaghat; Mohammad Ali Gholami Sefidkouhi
Abstract
Soil water retention curve (SWRC) is necessary for many studies, such as unsaturated hydraulic conductivity and solute transport in porous media. However, its direct measurement is time consuming and expensive. In this study, an optimization method was developed in order to estimate soil water retention ...
Read More
Soil water retention curve (SWRC) is necessary for many studies, such as unsaturated hydraulic conductivity and solute transport in porous media. However, its direct measurement is time consuming and expensive. In this study, an optimization method was developed in order to estimate soil water retention curve from limited measured points, such as water contents at field capacity and permanent wilting point. The main advantage of this method is that it is database independent. Three data sets including 156 soil samples from Belgium and Iran were used. Using van-Genuchten water retention model with restriction m=1-1/n and assuming residual water content to be equal to zero, vG model parameters such as and were optimized using two measured points and, consequently, SWRC was estimated (proposed method). Bulk density was used in order to estimate porosity in this method. In addition to the proposed method, ROSETTA model was applied to estimate vG model parameters and SWRC from sand, silt, and clay contents, bulk density, and water contents at field capacity and permanent wilting point. The MR, RMSE and AIC values for the proposed method were -0.00084, 0.031 and -8636 (cm3.cm-3) and for ROSETTA method were -0.037, 0.051 and -7327 (cm3.cm-3), respectively. Comparison of estimated SWRC using the proposed and ROSETTA method showed that the developed optimization method estimated SWRC more accurately than ROSETTA model.
Research Paper
Hamidreza Javani; Hassan Ojaghloo; Abdolmajid Liaghat
Abstract
Direct measurement of soil water retention curve parameters is hard, costly, and sensitive. One of the good indirect methods in prediction of soil water retention curve is Arya-Paris model, which uses the soil particle size distribution (PSD) data. The AP model estimates pore radius ( ri ) from the radius ...
Read More
Direct measurement of soil water retention curve parameters is hard, costly, and sensitive. One of the good indirect methods in prediction of soil water retention curve is Arya-Paris model, which uses the soil particle size distribution (PSD) data. The AP model estimates pore radius ( ri ) from the radius (Ri) of spherical particles by scaling pore with a parameter α. In this study, data from soil particle-size distribution, soil water retention curve, bulk density, and porosity of 96 different soils including sandy, loamy sand, sandy loam, and silty loam were used to help assessing methods of estimating the scale parameter. The values of scaling parameter obtained from the inverse method for the sandy, loamy sand, sandy loam, and silty loam were 1.32, 1.36, 1.45, and 1.23, respectively. Use of the linear method for sandy and silty loam soils resulted in α values of 1.34 and 1.25, respectively, while, by using the constant method (recommended by Arya et al) for sandy loam and loamy sand, α values were1.37 and 1.46, respectively, which were the closest to the real calculated values. By studying the variations of α in different soil textures and moisture contents, it was noted that there was no significant relationship between α and the amount of sand in the soil. However, increase in the soil moisture increased the value of α while the correlation coefficient for α and soil moisture was calculated at 0.45.
Research Paper
Mohammad Modares; Mohammadreza Rezaee; Mohammad Naseri
Abstract
Kashaf Rood River, which passes through Mashhad city, is a seasonal river constantly attacked by all kinds of municipal, industrial, and agricultural wastes. In this research, 5 stations were selected along the river and water was sampled for analysis in spring 2012. Some crops and their soil were ...
Read More
Kashaf Rood River, which passes through Mashhad city, is a seasonal river constantly attacked by all kinds of municipal, industrial, and agricultural wastes. In this research, 5 stations were selected along the river and water was sampled for analysis in spring 2012. Some crops and their soil were also sampled for measurement of heavy metals. Mean of the concentration of each heavy metal was compared in water samples with its maximum permissible amount for drinking, irrigation, and aquatic life, using Student’s t-test (in confidence level of %95). Results showed that there was significant difference between concentration of Pb and Cr in water of the river and the maximum permissible amount for drinking, irrigation, and aquatic life.. The amount of Hg was obtained to be higher than the maximum permissible amount for drinking in all stations, except for station 2 (Parkand Abad). Amount of Cr in wheat seed and corn leaf was much lower than the permissible limit. No significant correlation between concentration of Pb in soil, wheat seed, and leaf of corn was obtained at confidence level of %95 ( P>0.05), while significant correlation between concentration of Cr in soil, wheat seed, and corn leaf was obtained at confidence level of %95 ( P>0.05). There was no significant (P>0.05) correlation between concentration of Hg in soil, wheat seed, and corn leaf.
Research Paper
Sonia Zebardast; Hasan Tabatabi; Behzad Ghorbani
Abstract
Furrow irrigation is one of the common surface irrigation methods whose hydraulic behavior is under the influence of the inflow hydrograph. Accurate prediction of the advance phase is very important for design, management, and evaluation of this kind of surface irrigation system. In this study, the advance ...
Read More
Furrow irrigation is one of the common surface irrigation methods whose hydraulic behavior is under the influence of the inflow hydrograph. Accurate prediction of the advance phase is very important for design, management, and evaluation of this kind of surface irrigation system. In this study, the advance phase was simulated for six different hydrograph conditions of continuous and cutback inflows to furrow by using surface irrigation mathematical models. Field experiments were performed in Aboureihan campus, located in the southeast of Tehran province. The field data collected included inflow and outflow hydrographs, advance and recession data, cross sectional area and geometry of furrow, field slope, and infiltrated water depth along the furrows. The results showed that the least value of root mean square error(RMSE) (with an average of 6.32) and the highest value of the model efficiency factor (average 0.95) were related to the cutback hydrograph whose flow was reduced to 0.75 of the initial inflow after 60% of the cutoff time. The highest value of the RMSE (with an average of 12.30) and the least value of the model efficiency factor (with an average of 0.83) belonged to the continuous hydrograph whose discharge was reduced to 0.25 of the total discharge and irrigation continued for the entire time of irrigation. The results also showed that in cutback inflows section, the hydrodynamic, zero-inertia, and kinematic wave models were not applicable for reduction of flow in any lengths or any times. The selection of mathematical model for simulation of the advance of flow in the furrow depends on the amount of inflow and cut off time.
Research Paper
Yahya Parvizi
Abstract
This study was conducted to evaluate the present management of border irrigation system in 16 wheat, sugar beet, alfalfa, and bean farms that use traditional border irrigation in Lorestan province. The relationship between management allowed deficit (MAD), soil moisture deficit before irrigation (SMD), ...
Read More
This study was conducted to evaluate the present management of border irrigation system in 16 wheat, sugar beet, alfalfa, and bean farms that use traditional border irrigation in Lorestan province. The relationship between management allowed deficit (MAD), soil moisture deficit before irrigation (SMD), and infiltrated depth of water indicated that, in most cases, deficit or stress irrigation were common. This had caused high water application and storage efficiencies, while, in many cases, irrigation was insufficient to meet crop requirement. These findings indicated the imbalance between system fractions and excessive depletion of soil moisture before irrigation. Efficiency of water application, storage, and deficit/excess ranged from 10.5% to 95.5%, 21.6% to 100%, and 9.3% to 100%, respectively, while deep percolation and tail water efficiencies were, respectively, 0.6 to 83.5 and zero to 42.9. Advance and recession curves implicated the effects of initial soil moisture, slope gradient, and border dimensions on entrance flow and distribution uniformity of water. Uniformity of water distribution indexes was low and caused water loses by deep percolation. Results indicated that irrigation management was inefficient. Insufficiency of farmers’ knowledge about soil moisture condition and the correct time of irrigation, inefficient and traditional exploitation and the system of land tenure and shortage of water resources, improper irrigation scheduling, as well as imbalance between irrigation system design and management lead to water losses and reduced irrigation efficiency.
Research Paper
Farzaneh GHaemizadeh; Omid Bahmani
Abstract
In areas where there is not a balance between discharge and Recharge from the aquifer, the water table is dropping and then reduction in quality and quantity of the water aquifer is caused, and as a result; artificial recharge is necessary. Using fuzzy logic operators to determine the suitable locations ...
Read More
In areas where there is not a balance between discharge and Recharge from the aquifer, the water table is dropping and then reduction in quality and quantity of the water aquifer is caused, and as a result; artificial recharge is necessary. Using fuzzy logic operators to determine the suitable locations for artificial recharge may provide the desirable results. At this study attempted to use the fuzzy patterns to find the suitable location and provide management method, for artificial recharge of Nahavand’s aquifer, using GIS techniques. For this purpose, seven geographical information layers including slope, land use, surface infiltration, aquifer depth, aquifer quality, and net recharge and transmissivity were used. The results (as the output maps) showed that according to Fuzzy pattern, 5.94 percent of the total area (equivalent to 27.12 square kilometer area of the aquifer) which are widely scattered, rated good and very good in terms of artificial recharge of Nahavand’s aquifer.
Research Paper
Farhad Rejali
Abstract
One of the beneficial effects of mycorrhizal symbiosis is declining the deleterious effects of environmental stresses in plants. Drought stress is one of the most important environmental stresses which is the results of our country climate. In this situation decline of mineral uptake especially phosphorus ...
Read More
One of the beneficial effects of mycorrhizal symbiosis is declining the deleterious effects of environmental stresses in plants. Drought stress is one of the most important environmental stresses which is the results of our country climate. In this situation decline of mineral uptake especially phosphorus and zinc have more negative effects than lack of water in plant growth. Mycorrhizal fungi by increasing the mineral uptake can alleviate the part of plant growth and yield decline in drought stress. In order to evaluate the mycorrhizal fungi potential to decline the deleterious effects of drought stress , one greenhouse research with 10 fungal treatments in 3 levels of moisture including 8 , 16 and 32 %(w/w) and 4 replication for each treatments in completely randomized factorial was designed .Parameters such as shoot dry matter, root dry matter, colonization percentage and uptake of P, K Zn, Fe, Mn and Cu were determined. Results showed that moisture treatments had meaningful effect (P<0.01) on all parameters and fungal treatments also had meaningful effects (P<0.01) in colonization percentage and (P<0.05) on shoot dry matter and uptake of P, Zn and Fe .Three fungal species including Glomus mossea, Glomua intraradices and Glomus etunicatum were more effective than other species.
Research Paper
NOZAR GHAHREMAN; Azar Sahragard
Abstract
Leaf Wetness Duration (LWD) is a key element in plant water balance. Water wets leaf surfaces following various events such as rainfall, dew formation, etc. The result of the interaction between atmosphere and the plant leaf and canopy characteristics determine the leaves wetness duration (LWD) on the ...
Read More
Leaf Wetness Duration (LWD) is a key element in plant water balance. Water wets leaf surfaces following various events such as rainfall, dew formation, etc. The result of the interaction between atmosphere and the plant leaf and canopy characteristics determine the leaves wetness duration (LWD) on the plant. This variable is measured by electronic sensors, but, due to the difficulty of measurement, various empirical models using meteorological data have been developed for its estimation. Despite their limitations, these models are widely used. In this study, two empirical models of LWD estimation using relative humidity were evaluated at Paliz station in Fars province. The simplest empirical model uses only the relative humidity (RH), and wetness occurs when the RH is greater than a certain threshold. On the basis of different studies under wet conditions, for several plants, a threshold value of 87% RH has been determined for this purpose. In this study, the optimized RH-threshold model did a better job compared to non-optimized constant threshold and the extended threshold models in both warm and cold seasons.
Research Paper
Somayeh Hejabi; Javad Bazrafshan
Abstract
Drought is a temporary and recurring meteorological event, which originates from the lack of precipitation relative to its long-term average. Since drought forecasting has a critical role in water resources management, in this study, six types of stochastic models (AR, MA, ARMA, non-seasonal ARIMA, seasonal ...
Read More
Drought is a temporary and recurring meteorological event, which originates from the lack of precipitation relative to its long-term average. Since drought forecasting has a critical role in water resources management, in this study, six types of stochastic models (AR, MA, ARMA, non-seasonal ARIMA, seasonal ARIMA and multiplicative ARIMA) skill in modeling and forecasting the Standardized Precipitation Index (SPI) time series was evaluated. For reaching this purpose, the monthly total precipitation data related to ten synoptic stations with hyper humid to very dry climates (1973-2007) were used. At first, by transferring the optimum distribution cumulative probability of precipitation to cumulative probability distribution of standard normal, the SPI values in three time scales of 3, 6 and 12 months were calculated. Then, the development of models was done on SPI values related to period of 1973 to 2000, over a multi stage process (Identification, Parameter estimation, Diagnostic check) and the most appropriate stochastic model was determined for each time series from the candidate models. In order to validate the chosen models, at first, one to twelve lead times ahead forecasting was done for period of 2001 to 2007.Then, the values and the classes of the observed and the forecasted SPI were compared. The results of evaluating the models accuracy in forecasting the SPI values over chosen stations showed that in one month lead time ahead drought forecasting, over 3-month time scale, the stochastic model of Bushehr station (r=0.70, RMSE= 0.66) and over 6 and 12-month time scales, the stochastic model of Hamedan Nojeh station (6-month time scale: r=0.84, RMSE=0.41; 12-month time scale: r=0.93, RMSE=0.30) have the most accuracy comparing with stochastic model of other stations. Moreover, the forecasting error decreases with increasing the time scale and the forecasting accuracy decreases with increasing the lead time. The results of evaluating the models accuracy in forecasting the SPI classes based on Kappa statistic (K), showed that the maximum agreement of the observed and the forecasted classes for one lead time ahead forecasting, about 3, 6 and 12-month time scales is related to Bushehr (K=0.46), Gorgan (K=0.66) and Zahedan (K=0.81), respectively. Moreover, the agreement of the observed and the forecasted classes increases with increasing the time scale and the agreement of the observed and the forecasted classes decreases with increasing the lead time.
Research Paper
ahmad ali keykha; Mahdieh Mosnen; Mahmood Saboohi
Abstract
Water is one of the scarcest inputs in most countries and is used in agricultural production. In Iran, where the average annual rainfall is 240 mm with sporadic distribution and spatial and temporal variations, this input becomes more important. Sistan ...
Read More
Water is one of the scarcest inputs in most countries and is used in agricultural production. In Iran, where the average annual rainfall is 240 mm with sporadic distribution and spatial and temporal variations, this input becomes more important. Sistan and Baluchistan is a dry province of the country that faces water shortage problem in many years. To solve water supply fluctuations and scarcity in Sistan region, Chahnimeh water reservoir was established to store water in wet seasons and, consequently, decrease damages in the dry seasons. The aim of this study was modeling of the Chahnimeh water reservoir management using goal programming to determine optimal water for domestic, agricultural, and environmental sector and its sensitivity analysis. Therefore, a matrix with 142 in 154 dimension of aims and systemic and goal constraints were constructed. Then, this model was solved using goal programming. Considering the historical data, results show that water requirement of domestic and environment sectors can be provided, but some agricultural water may not be supplied. Therefore, if in the first six months of the year water is stored in Chahnimeh reservoir, in the next six months, there would be no water shortage, Also, if irrigation efficiency increases, decision makers can increase the cultivated area.