N. N. Kouhi Chelle Karan; H. Dehghanisanij; A. Alizadeh; E. Kanani
Abstract
Introduction: Drought is one of the factors that threatens the performance of agricultural products, especially corn in most parts of the world. Under conditions of water scarcity, the effectiveness and efficiency of fertilizer use is reduced, especially if fertilizer application is not consistent with ...
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Introduction: Drought is one of the factors that threatens the performance of agricultural products, especially corn in most parts of the world. Under conditions of water scarcity, the effectiveness and efficiency of fertilizer use is reduced, especially if fertilizer application is not consistent with plant growth. Among fertilizers, nitrogen is one of the most important nutrients for corn, and consumption management of this fertilizer has great importance in order to succeed in increasing the production of corn. Therefore, in conditions of water shortage, balanced and optimal use of fertilizer should be considered to achieve increased yield and water use efficiency.
Materials and Methods: This study was conducted to investigate the effect of drip irrigation regimes and different levels of nitrogen fertilizer on yield and yield components of corn and soil moisture changes at the Shaheed Zendrh Rouh Jupar in Kerman province during the years of 2012-2014. The experiment was arranged as a split-plot design based on randomized complete block design with five irrigation regimes (I1 = 100, I2 = 80 and I3 = 60% ETc) as the main-factor and five nitrogen fertilizer level N1 = 0, N2 = 50, N3 = 100, N4 = 150 and N5 = 200 kg/ha) as sub-factor. According to the Kerman Meteorological Station, this region has a semi-arid climate with warm summers and mild winters. To calculate the volume of water consumed, potential evapotranspiration (ETo) was determined using daily meteorological information and Penman-Monteith method (PM). A sampling method was used to measure moisture at different depths of soil.
Results and Discussion: The results showed that the highest yield was due to I1 treatments with 8.85 t/ha, and there was a direct relation between crop reduction and water requirement reduction at all stages of crop production. High nitrogen application had a negative effect on yield. Typically, in soils that lack nitrogen, corn grain yield increased with nitrogen addition. However, after reaching the maximum yield, nitrogen addition has no effect on increase or yield may reduce. The interactions of different levels of water and fertilizer showed that I1N4 and I3N1 treatments had the highest (10.6 ton/ha) and lowest (1.24 ton/ha) value of corn yield, respectively. The highest and lowest grain yield components (thousand grain weight, number of kernels row, number of kernels per row, cob length, cob diameter) were observed in N1 and N3 I1 treatments, respectively. The highest water use efficiency (1.26 kg/m3) was observed in I2N4 treatment and the lowest (0.068 kg/m3) in I3N1 treatment. The results of this study showed that the remaining moisture content in soil decreased by decreasing amount of irrigation water and nitrogen fertilizer in 20 days after planting. At 75 days after planting, reasons such as severe water shortages during growth, reduced root density, high water requirement at this stage of growing season, and the plants need to nutrients have probably caused the roots to absorb as much as possible of the top three water and nutrient. As a result, the moisture that reaches the last layer is less. The results showed that in the last stages of growth compared to other stages, the plant water requirement is reduced and excess water penetrates the lower layers.
Conclusion According to the results of this study, nitrogen fertilizer at 150 kg/ha with 100% water requirement is the best combination for corn farming in semi-arid climates.
M. Mousavi Baygi; Amin Alizadeh; Aboalfazl Mosaedi; Mehdi Jabbari Nooghabi
Abstract
Introduction: Drought is the most complex, but less well-known risk among all natural hazards, which affects more people than any other natural hazard. Meteorological and seasonal hydrological drought is a common phenomenon in tropical countries and is expected to increase further in the future. Drought ...
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Introduction: Drought is the most complex, but less well-known risk among all natural hazards, which affects more people than any other natural hazard. Meteorological and seasonal hydrological drought is a common phenomenon in tropical countries and is expected to increase further in the future. Drought is one of the natural and frequent climate phenomena; Drought risk analysis is a combination of drought risk analysis and drought vulnerability analysis. Drought risk assessment methods can be calculated either by remote sensing methods or by statistical methods or by combining both methods. Drought risk assessment shows a more Suitable and accurate view of the drought because, in addition to drought severity is simultaneously Includes the probability of occurrence of drought and the impact this phenomenon on the environment and the region. In this study, has been made to illustrate Visionary of Changes in future meteorological drought risk.
Materials and methods: The study was conducted as a case study for the Afin sub-basin The average of minimum temperature, mean of maximum temperature, average temperature at 2 meters above ground level and rainfall data in this research have been used. The statistical period used for the base period is 33 years (1983-2015). Future data is derived from three models of the cordex project. The upcoming period is divided into three 27-year periods including the near future (2020-2046), the middle term (2047-2073) and the distant future (2074-2100). In order to investigate the drought in future periods was prepared a combination model of three climatic models using the Bayesian method. Then, the future values of the meteorological parameters were calculated. Drought risk for the upcoming periods was calculated by direct method and modeling method. Finally, a comparison was made between the two methods in order to determine the appropriateness of the predicted model.
Results and discussion: In the survey of the intensity of SPI and SPEI drought indices during the base time period for time scales studied, the SPEI and SPI drought indices showed that both, drought events were the same during the studied period, while the indicator SPEI drought shows more mild and moderate droughts, and the SPI index has shown intense intensity on some scales. In future periods, according to the RCP8.5 scenario, the number of drought events in each period does not differ from the RCP4.5 scenario, but the intensities are higher than RCP4.5. By completing the questionnaire and using exploratory and confirmatory factor analysis methods, the drought vulnerability was determinated 53%. ARIMA (0,0,0) , The appropriate time series model was used to predict the level of risk. In the drought risk prediction section, the results showed that according to the SPI drought index in the upcoming periods, the number of drought events relative to the base period is relatively higher, thus the number of drought events (including four drought conditions) will increase in the far future than the two upcoming middle and nearer periods. According to prediction models of risk, rainfall parameter for all time scales of SPI index and for four time scales of spring, autumn, winter and annual drought index SPEI, is an effective parameter in drought estimation and effect on drought occurrence in the study area.
Conclusion :The results of this study indicate an increase in temperature in future periods based on both RCP emission scenarios. Increasing the severity of droughts in future periods is another result of this study. The risk outcomes obtained from the direct risk-measurement method, which was obtained with CORDEX data as well as the method of using the risk-predictive model obtained in this study,Showed strong correlation and no significant difference in mean, which indicates the model's appropriateness for risk prediction (hazard and after that risk) in the future.Also,The risk outcomes obtained from the direct Risk calculation method, which is based on CORDEX data with the method of using the risk prediction model obtained in this study, indicates an increase in the number of drought events followed by an increase in drought risk events in the region. also, it was observed that Severity of drought risk according to the RCP8.5 release scenario is higher than RCP4.5. For more more accurate results, it is suggested that more models (more than three models) be used from the sixth report of the Intergovernmental Panel on Climate Change.
Alieh Saadatpour; Amin Alizadeh; Ali Naghi Ziaei; azizallah izady
Abstract
Introduction: During the last decades, arid and semi-arid regions has faced a severe problem of depletion of groundwater resources due to the over-exploitation of the aquifer. Moreover, groundwater and surface water are not isolated components of the hydrologic system, but instead ...
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Introduction: During the last decades, arid and semi-arid regions has faced a severe problem of depletion of groundwater resources due to the over-exploitation of the aquifer. Moreover, groundwater and surface water are not isolated components of the hydrologic system, but instead interact in a variety of aspects in which development of one commonly affects the other. Additionally, the interaction is often complicated by agricultural activities including surface water diversion, groundwater pumping and irrigation. This study presents an integrated SWAT-MODFLOW model that couples land surface hydrology and groundwater hydrology to determine spatial groundwater percolation patterns considering allowable groundwater pumping rates for the Neishaboor watershed, Iran. Within the integrated model, the pumped groundwater is applied as irrigation to the cultivated fields within the SWAT model, with deep percolation from the soil profile bottom applied to the MODFLOW model as recharge. The model is tested against observed stream flow and water table elevation, with model output then used to assess and quantify spatial-temporal patterns of groundwater recharge to the aquifer.
Materials and Methods: The recently developed SWAT-MODFLOW modeling code simulates spatially-distributed hydrologic processes in the coupled land surface / aquifer system, with SWAT simulating land surface, soil zone, and stream flow routing processes and MODFLOW simulating groundwater flow and groundwater/surface water interaction processes. Modifications which is done to the modeling code includes: 1) Linking pumping from MODFLOW cells to SWAT HRUs for groundwater irrigation and 2) Imposing shallow water table percolation and lateral flow conditions for SWAT HRUs when the MODFLOW-simulated water table is within the soil profile of the HRU. The integrated SWAT-MODFLOW framework is tested in the Neishaboor watershed (9157 km2) for the 1998 to 2011 time period. Climate of the region is classified as semi-arid, with an average annual precipitation of 265 mm that varies considerably from one year to another. The mean annual temperatures changes from 13°C in the mountainous area to 13.8°C in the plain area and the annual potential evapotranspiration is about 2,335 mm. The main crops that are grown in the watershed is irrigated and rain fed wheat during fall and winter and corn silage during summer. Regarding previous studies, about 93.5% of the groundwater withdrawals in the Neishaboor watershed are consumed in agriculture, mostly for irrigation. Therefore, irrigation practices play a crucial role in the water resources balance in the study area. Within the integrated model, the pumped groundwater is applied as irrigation to the cultivated fields within the SWAT model, with deep percolation from the soil profile bottom applied to the MODFLOW model as recharge. The SWAT model was calibrated and tested in SWAT-CUP for the 2001-2009 and 2010-2011 periods, against stream flow and developed model was calibrated manually against groundwater level data.
Results and Discussion: Annual average recharge, calculated from the daily recharge values pass from SWAT to MODFLOW, demonstrating higher recharge rates in the alluvial fans and upland plain. Observed and simulated stream discharge in four hydrometric stations demonstrate good similarity results with the observed hydrograph. The NS values for monthly discharge rates are considered acceptable, however, the field-estimated stream flow estimates contain a high degree of uncertainty. Simulated cell-wise groundwater hydraulic head at the end of the simulation is compared with observation values with the highest water table elevation occurring in the north east and low water table elevation occurring in the outlet. Comparing observed and simulated average groundwater levels at the 48 monitoring wells, the deviation from the 45-degree line is less than 2.5 m for over 73% of the circles. The manual calibrated model can capture the main temporal trend. Overall, the model well captures the long-term characteristics of the regional groundwater level.
Conclusion: In this study, a new coupled model, referred to as SWAT-MODFLOW was used to model a dry and semi-arid region with a complicated irrigation system with groundwater pumping. A comprehensive model, will enable accurate simulations of stream flow and water table fluctuations in watersheds and aquifers respectably. In short, surface water infiltration is passed from SWAT to MODFLOW based on the contributing areas of the HRUs to the groundwater grid. Pumping agriculture water is then calculated and passed back to SWAT. The need for such a model is highlighted by the Neishaboor basin, where the agriculture is completely based on groundwater pumping. The case study in the Neishaboor basin demonstrated the applicability of the model for large, dry basins. The model will be used to determine best management practices for groundwater pumping in the region.
mozhdeh Jamei; mohammad mousavi; Amin Alizadeh; parviz irannejad
Abstract
Introduction: Surface soil moisture is one of the most important variables in the hydrological cycle, and plays a key role in scientific and practical applications such as hydrological modelling, weather forecasting, climate change studies and water resources managements. Microwave radiometry at low ...
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Introduction: Surface soil moisture is one of the most important variables in the hydrological cycle, and plays a key role in scientific and practical applications such as hydrological modelling, weather forecasting, climate change studies and water resources managements. Microwave radiometry at low frequencies (1.4GHz) is an established technique for estimating global surface soil moisture with a suitable accuracy. In recent years, soil moisture measurements have become increasingly available from satellite-based microwave sensors. The ESA’s Soil Moisture and Ocean Salinity (SMOS) satellite was launched in November 2009. It carries the first L-band 2-D synthetic aperture microwave radiometer to provide global estimates of soil moisture with an averaged ground resolution of 43 km over the field of view. The main objective of this research was to validateSMOS soil moisture retrievals over the west and south west of Iran.
Materials and Methods:The study area is located in the west and southwest of Iran which contains five areas belongingto the Ministry of Power. For the validation of SMOS dataover the study area, the SMOS soil moisture retrievals from MIR_SMUDP2 productswere compared with ground-based insitu measurements. The validation process was carried out using Collocation techniquefor the period 2012-2013. Collocation technique is a method used in the field of remote sensing to verify compliance measurements from two or more different instruments. In this study, the collocation codes were developed in Matlab Linux programming language. The ground-based in situ measurements included direct soil moisture measurements at the 5cm depth which were collected from five meteorological stations in the study area. We prepared a file for each station which contained daily soil moisture, date and time, geographical coordinates of metrological stations as input for validation model. The SMOS Level 2 Soil Moisture User Data Product (MIR_SMUDP2 files) version 551, which were provided through the ESA, contains the retrieved soil moisture and simulated TB, dielectric constants, etc. In this work, the ESA’s SMOS Matlab tool on RedHat Linux was used to read and derivesoil moisture data from MIR_SMUDP2 files.Four statistical metrics and Taylor diagram were used for the evaluation error of validation; the Root Mean Squared Difference (RMSD), the centered Root Mean Square Difference (cRMSD), the Mean Bias Error or bias and the correlation coefficient (R).
The Taylor diagrams wereused to represent three different statistical metrics (R, centered Root Mean Square Difference (cRMSD) and standard deviation) on two dimensional plots to graphically describe how closely SMOS dataset matched ground-based observations .
Results and Discussion: Based on the research algorithm and using MATLAB, the Validation model for SMOS soil moisture data was obtained. This model was appliedfor five metrological stations and the collocated soil moisture data from SMOS data and in situ data was saved as output of model to error evaluation. The results of validation errorshoweda good correlation between the SMOS soil moisture andin situ measurements. The highestand lowest correlation coefficientswere shown at Ahvaz (R=0.88) and Sarableh(R=0.75)stations, respectively.According to the bias values, the SMOS soil moisture retrievals had underestimation atAhvaz(MBE=0.04 m3m−3),Sararod(MBE=0.011 m3m−3), Sarableh(MBE=0.048 m3m−3) stations, whereas a slight overestimation of the SMOS product was detectedatthe Darab (MBE=-0.01 m3m−3) andEkbatan (MBE=-0.031 m3m−3) stations. In addition, the Root Mean Squared Difference (RMSD) values between the SMOS data and in situ data varied from 0.02 to 0.062 m3m−3 and at Ahvaz station withRMSD=0.048 m3m−3is close to the targeted SMOS accuracy of 0.04 m3m−3.Based on the Taylor diagrams, SMOS data had the highest correlation (R=0.88) with in situ measurements at Ahwaz stationand the lowest difference (cRMSD=0.008 m3m−3) between two data setswas found at Darab station.
Conclusions:The objective of this paper was to validateESA’s SMOS (Soil Moisture and Ocean Salinity) satellite products in the west and southwest of Iran for the period of 2012-2013. The validation of SMOS soil moisture retrievals from MIR_SMUDP2 products was done by using soil moisture measurements from five meteorological stations. The SMOS soil moisture retrievals showed underestimations at Ahvaz, Sararod andSarableh stations, whereas a slight overestimation werefound at Darab, Ekbatan stations. The validation results and Taylor diagrams showed thatthe SMOS soil moisture retrievals with R=0.88, RMSD=0.048 m3m−3, cRMSD=0.021 m3m−3at Ahvaz stationwasvery close to the targeted SMOS accuracy objectiveof 0.04 m3m−3 and then at Darab station SMOS data with R=0.82, RMSD=0.028 m3m−3,cRMSD=0.008 m3m−3indicateda good agreement with ground soil moisture measurements. Overall, the SMOS soil moisture data hadan acceptableaccuracy and agreement with in situ data at all stations. Therefore, we can use these data sets as a tool to derive soil moisture maps at study areas.
Yavar Pourmohamad; Mohammad Mousavi baygi; Amin Alizadeh; Alinaghi Ziaei; Mohammad Bannayan
Abstract
Introductionin current situation when world is facing massive population, producing enough food and adequate income for people is a big challenge specifically for governors. This challenge gets even harder in recent decades, due to global population growth which was projected to increase to 7.8 billion ...
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Introductionin current situation when world is facing massive population, producing enough food and adequate income for people is a big challenge specifically for governors. This challenge gets even harder in recent decades, due to global population growth which was projected to increase to 7.8 billion in 2025. Agriculture as the only industry that has ability to produce food is consuming 90 percent of fresh water globally. Despite of increasing for food demand, appropriate agricultural land and fresh water resources are restricted. To solve this problem, one is to increase water productivity which can be obtain by irrigation. Iran is not only exempted from this situation but also has more critical situation due to its dry climate and inappropriate precipitation distribution spatially and temporally, also uneven distribution of population which is concentrate in small area. The only reasonable solution by considering water resources limitation and also restricted crop area is changing crop pattern to reach maximum or at least same amount of income by using same or less amount of water. The purpose of this study is to assess financial water productivity and optimize farmer’s income by changing in each crop acreage at basin and sub-basin level with no extra groundwater withdrawals, also in order to repair the damages which has enforce to groundwater resources during last decades a scenario of using only 80percent of renewable water were applied and crop area were optimize to provide maximum or same income for farmers.
Materials and methodsThe Neyshabour basin is located in northeast of Iran, the total geographical area of basin is 73,000 km2 consisting of 41,000 km2 plain and the rest of basin is mountains. This Basin is a part of Kalshoor catchment that is located in southern part of Binaloud heights and northeast of KavirMarkazi. In this study whole Neyshabour basin were divided into 199 sub-basins based on pervious study.Based on official reports, agriculture consumes around 93.5percent of the groundwater withdrawals in Neyshabour basin and mostly in irrigation fields, surface water resources share in total water resource withdrawals is about 4.2percent, which means that groundwater is a primary source of fresh water for different purposes and surface water has a minor role in providing water supply services in the Neyshabour basin. To determine crop cultivation area, major crops divided into two groups. two winter crops (Wheat and Barley) and two summer crops (Maize and Tomato). To accomplish land classification by using supervised method, a training area is needed, so different farms for each crop were chosen by consulting with official agricultural organization expert and multiple point read on GPS for each crop. The maximum likelihood (MLC) method was selected for the land cover classification. To estimate the amount of precipitation at each 199 sub-basins, 13 station data for precipitation were collected, these stations are including 11 pluviometry stations, one climatology station and one synoptic station. Actual evapotranspiration (ETa) is needed to estimate actual yield (Ya). Surface Energy Balance Algorithm for Land (SEBAL) technique were applied on Landsat 8 OLI images. To calculate actual ETa, the following steps in flowchart were modeled as tool in ArcGIS 10.3 and a spreadsheet file. To estimate actual crop yield, the suggested procedure by FAO-33 and FAO-66 were followed. Financial productivity could be defined in differently according to interest. In this study several of these definition was used. These definitions are Income productivity (IP) and Profit productivity (PP). To optimize crop area, linear programing technique were used.
Results and discussionaverage actual evapotranspiration result for each sub-basin are shown in context. In some sub-basins which there were no evapotranspiration are shown in white. And it happens in those sub-basins which assigned as desert in land classification. In figures 8 and 9 minimum amount of income and profit productivity for wheat and barley is negative, this number means in those area the value of precipitation is higher than value of evapotranspiration, so lower part of eq. 21 and 22 would be negative and in result water productivity would be negative. Since most of precipitation occurs during cold season of the year these numbers are expected. Two sub-basins of 43 and 82 has the value of negative, it means in these two sub-basins groundwater are recharging during the year 2014-2015.The maximum value of income and profit productivity belong to wheat and barley which are winter crops and mostly rain fed, so amount applied water would be so low and in result productivity increased. Among the summer crops maize has the most income and profit income which can be interpret due to their growing period and the crop types. Maize has around 110 days to reach to maturity and harvest, on the other hand tomato needs 145 days to harvest. Some plant is C3 and some are C4. C4 plants produce more biomass than C3 crops with same amount of water which leads to more productivity. The results showed that tomato should have the most changes in area reduction (0.2) and maize should have no changes in both scenarios. Crop area should reduce to 66percent of current cultivation area to maintain ground water level and only 6percent reduction in cultivation area would result in 20percent groundwater recharging.
Conclusion to save groundwater resources or even retrieve the only water resource, cultivation area must reduce if the crop pattern will not change. In this study only four crops were studied. It seems best solution is to introduce alternative crop.
najmeh khalili; Kamran Davary; Amin Alizadeh; Hossein Ansari; Hojat Rezaee Pazhand; Mohammad Kafi; Bijan Ghahraman
Abstract
Introduction:Many existing results on water and agriculture researches require long-term statistical climate data, while practically; the available collected data in synoptic stations are quite short. Therefore, the required daily climate data should be generated based on the limited available data. ...
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Introduction:Many existing results on water and agriculture researches require long-term statistical climate data, while practically; the available collected data in synoptic stations are quite short. Therefore, the required daily climate data should be generated based on the limited available data. For this purpose, weather generators can be used to enlarge the data length. Among the common weather generators, two models are more common: LARS-WG and ClimGen. Different studies have shown that these two models have different results in different regions and climates. Therefore, the output results of these two methods should be validated based on the climate and weather conditions of the study region.
Materials and Methods:The Sisab station is 35 KM away from Bojnord city in Northern Khorasan. This station was established in 1366 and afterwards, the meteorological data including precipitation data are regularly collected. Geographical coordination of this station is 37º 25׳ N and 57º 38׳ E, and the elevation is 1359 meter. The climate in this region is dry and cold under Emberge and semi-dry under Demarton Methods. In this research, LARG-WG model, version 5.5, and ClimGen model, version 4.4, were used to generate 500 data sample for precipitation and temperature time series. The performance of these two models, were evaluated using RMSE, MAE, and CD over the 30 years collected data and their corresponding generated data. Also, to compare the statistical similarity of the generated data with the collected data, t-student, F, and X2 tests were used. With these tests, the similarity of 16 statistical characteristics of the generated data and the collected data has been investigated in the level of confidence 95%.
Results and Discussion:This study showed that LARS-WG model can better generate precipitation data in terms of statistical error criteria. RMSE and MAE for the generated data by LAR-WG were less than ClimGen model while the CD value of LARS-WG was close to one. For the minimum and maximum temperature data there was no significant difference between the RMSE and CD values for the generated and collected data by these two methods, but the ClimGen was slightly more successful in generating temperature data. The X2 test results over seasonal distributions for length of dry and wet series showed that LARS-WG was more accurate than ClimGen.The comparison of LARS-WG and ClimGen models showed that LARS-WG model has a better performance in generating daily rainfall data in terms of frequency distribution. For monthly precipitation, generated data with ClimGen model were acceptable in level of confidence 95%, but even for monthly precipitation data, the LARS-WG model was more accurate. In terms of variance of daily and monthly precipitation data, both models had a poor performance.In terms of generating minimum and maximum daily and monthly temperature data, ClimGen model showed a better performance compared to the LARS-WG model. Again, both models showed a poor performance in terms of variance of daily and monthly temperature data, though LAR-WG was slightly better than ClimGen. For lengths of hot and frost spells, ClimGen was a better choice compared to LARS-WG.
Conclusion:In this research, the performances of LARS-WG and ClimGen models were compared in terms of their capability of generating daily and monthly precipitation and temperature data for Sisab Station in Northern Khorasan. The results showed that for this station, LARS-WG model can better simulate precipitation data while ClimGen is a better choice for simulating temperature data. This research also showed that both models were not very successful in the sense of variances of the generated data compared to the other statistical characteristics such as the mean values, though the variance for monthly data was more acceptable than daily data.
N. Khalili; K. Davary; A. Alizadeh; M. Kafi; H. Ansari
Abstract
Modeling of crop growth plays an important role in evaluation of drought impacts on rainfed yield, choosing an optimum sowing date, and managerial decision-makings. Aquacrop model is a new crop model that developed by Food and Agriculture Organization (FAO), that is a model for simulation of crop yield ...
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Modeling of crop growth plays an important role in evaluation of drought impacts on rainfed yield, choosing an optimum sowing date, and managerial decision-makings. Aquacrop model is a new crop model that developed by Food and Agriculture Organization (FAO), that is a model for simulation of crop yield based on “yield response to water“ with meteorological, crop, soli and management practices data as inputs. This model has to be calibrated and validated for each crop species and each location. In this paper, the Aquacrop has been calibrated and evaluated for rainfed wheat in Sisab station (Northern Khorasan). For this purpose, daily meteorological data and historical yield data from two cropping season (2007-2008 and 2008-2009) in the Sisab station have been used to calibrate this model. Next, meteorological data and historical yield data of five cropping season (2002-2003 to 2006-2007) are used to validate the model. The result shows that the Aqucrop can accurately predict crop yield as R2, RMSE, NRMSE, ME, and D-Index are achieved 0.86, 0.062, 5.235, 0.917 and 0.877, respectively.
javad baghani; A. Alizadeh; H. Ansari; M. Azizi
Abstract
Introduction: Production and growth of plants in many parts of the world due to degradation and water scarcity have been limited and particularly, in recent decades, agriculture is faced with stress. In the most parts of Iran, especially in the Khorasan Razavi province, drought is a fact and water is ...
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Introduction: Production and growth of plants in many parts of the world due to degradation and water scarcity have been limited and particularly, in recent decades, agriculture is faced with stress. In the most parts of Iran, especially in the Khorasan Razavi province, drought is a fact and water is very important. Due to melon cultivation in this province, and the conditions of quality and quantity of water resources and water used to produce the melon product in this province, any research done on the use of saline and brackish waters is statistically significant.
Materials and Methods: To study the effects of different water salinity and water management on some of the agronomic traits of late summer melon with drip irrigation, an experiment with 7 treatments and 3 repetitions was conducted in a randomized complete block design, in Torogh station, Mashhad. The irrigation treatments were: 1- fresh water from planting to harvesting, 2- water (3 dS/m) from planting to harvesting, 3- water (6 dS/m) from planting to harvesting, 4- water (6 dS/m) from 20 days after plantation to harvesting, 5-water (6 dS/m) from 40 days after plantation to harvesting, 6-water (3 dS/m) from 20 days after plantation to harvesting, 7-water (6 dS/m) from 40 days after plantation to harvesting.
Row spacing and plant spacing were 3 m and 60 cm, respectively and the pipe type had 6 liters per hour per unit of meters in the drip irrigation system.
Finally, the amount of salinity water, number of male and female flowers, number of seed germination, dry leaves' weight, leaf area, chlorophyll (with SPAD) etc. were measured and all data were analyzed by using MSTAT-C software and all averages of data, were compared by using the Duncan test.
Results and Discussion The results of analysis of data showed the following:
Number of seeds germination: Salinity in water irrigation had no significant effects on the number of seed germination. However, there was the most number of seed germinations in the fresh water treatments. However, with increased water salinity, the time of seed germination reduced. The maximum delay in germination of seeds was in the treatment that was irrigated with fresh water from the beginning of cultivation.
Number of flowers: First, the male flowers appeared and after 5 to 7 days, the appearance of female flowers began. The effect of irrigation treatments on female flower appearance was significant. With increased water salinity, the number of male flowers decreased. There was the lowest male flower in the treatment that was irrigated with saline water from the beginning, but there was no significant difference among the other treatments.
Root, steam and leaves: The effect of saline irrigation water on dried leaves’ weight and dry root weight was significant at 1% and 5% levels, respectively. Fresh treatment and salinity treatment have the least and the most root dries weight, respectively (irrigated from the beginning with fresh or saline water). Two treatments that were irrigated with fresh and brackish water from thebeginning of cultivation have the highest leaf growth. The same trend was true for steams.
In general, in all treatments, after applying different quality water to the end of the growing season, the trend of plant growth was similar to the others.
Chlorophyll: One of the most common measurements made by plant scientists is the determination of Chlorophyll concentration. The SPAD index was used for comparison of chlorophylls. With an increase of the salt in irrigation water, the SPAD index was also increased.
The maximum and minimum SPAD was in the treatments that were irrigated with saline water (treatment A) and fresh water (treatment C) from the beginning of cultivation, respectively.
Yield: With increasing the salinity of water, the total yield decreased. Salinity in irrigation water had a significant effect (at the 5% level) on total yield. The mean yield of brackish and salinity irrigation water treatments were 17.5% and 26% less than the fresh water irrigation treatment, respectively.These differences were significant. However, there was no significant difference between the yield of cases using brackish or salt water.
Conclusion: The results showed the following:
Salinity in irrigation water had no significant effect on the number of seed germinations. However, there was the most number of seed germinations in the fresh water treatments, but by raising the salinity of water, the time of seed germination was reduced.
With increasing the salinity of water, the number of male flowers decreased. There was the lowest male flower in the treatment that were irrigated with salt water from the beginning, but there was no significant difference between the other treatments.
The effect of salinity water on leaf dry weight and dry root was significant at 1% and 5% levels, respectively. Fresh and salinity treatments have the least and the most root dry weight, respectively (irrigated from the beginning with fresh or salt water). Two treatments that were irrigated with fresh and brackish water from the beginning of cultivation have the highest leaf growth.
The same trend was true for steams.
Two treatments that were irrigated with fresh and brackish water from the beginning of cultivation have the highest leaves areas. And they had significant difference with other irrigation treatments.
With an increase in the salt in irrigation water, the SPAD index also increased.
The mean yield of brackish and salinity water irrigation treatments were 17.5% and 26% less than that of fresh water irrigation treatment, respectively.These differences were significant. But there was no significant difference between the yield of brackish and salt water.
maysam majidi; a. Alizade; m. vazifedoust; a. faridhosseini
Abstract
Introduction: Water when harvested is commonly stored in dams, but approximately up to half of it may be lost due to evaporation leading to a huge waste of our resources. Estimating evaporation from lakes and reservoirs is not a simple task as there are a number of factors that can affect the evaporation ...
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Introduction: Water when harvested is commonly stored in dams, but approximately up to half of it may be lost due to evaporation leading to a huge waste of our resources. Estimating evaporation from lakes and reservoirs is not a simple task as there are a number of factors that can affect the evaporation rate, notably the climate and physiography of the water body and its surroundings. Several methods are currently used to predict evaporation from meteorological data in open water reservoirs. Based on the accuracy and simplicity of the application, each of these methods has advantages and disadvantages. Although evaporation pan method is well known to have significant uncertainties both in magnitude and timing, it is extensively used in Iran because of its simplicity. Evaporation pan provides a measurement of the combined effect of temperature, humidity, wind speed and solar radiation on the evaporation. However, they may not be adequate for the reservoir operations/development and water accounting strategies for managing drinking water in arid and semi-arid conditions which require accurate evaporation estimates. However, there has not been a consensus on which methods were better to employ due to the lack of important long-term measured data such as temperature profile, radiation and heat fluxes in most lakes and reservoirs in Iran. Consequently, we initiated this research to find the best cost−effective evaporation method with possibly fewer data requirements in our study area, i.e. the Doosti dam reservoir which is located in a semi-arid region of Iran.
Materials and Methods: Our study site was the Doosti dam reservoir located between Iran and Turkmenistan borders, which was constructed by the Ministry of Water and Land Reclamation of the Republic of Turkmenistan and the Khorasan Razavi Regional Water Board of the Islamic Republic of Iran. Meteorological data including maximum and minimum air temperature and evaporation from class A pan were acquired from the Doosti Dam weather station. Relative humidity, wind speed, atmospheric pressure and precipitation were acquired from the Pol−Khatoon weather station. Dew point temperature and sunshine data were collected from the Sarakhs weather station. Lake area was estimated from hypsometric curve in relation to lake level data. Temperature measurements were often performed in 16−day periods or biweekly from September 2011 to September 2012. Temperature profile of the lake (required for lake evaporation estimation) was measured at different points of the reservoir using a portable multi−meter. The eighteen existing methods were compared and ranked based on Bowen ratio energy balance method (BREB).
Results and Discussion: The estimated annual evaporation values by all of the applied methods in this study, ranged from 21 to 113mcm (million cubic meters). BREB annual evaporation obtained value was equal to 69.86mcm and evaporation rate averaged 5.47mm d-1 during the study period. According to the results, there is a relatively large difference between the obtained evaporation values from the adopted methods. The sensitivity analysis of evaporation methods for some input parameters indicated that the Hamon method (Eq. 16) was the most sensitive to the input parameters followed by the Brutsaert−Stricker and BREB, and radiation−temperature methods (Makkink, Jensen−Haise and Stephen−Stewart) had the least sensitivity to input data. Besides, the air temperature, solar radiation (sunshine data), water surface temperature and wind speed data had the most effect on lake evaporation estimations, respectively. Finally, all evaporation estimation methods in this study have been ranked based on RMSD values. On a daily basis, the Jensen−Haise and the Makkink (solar radiation, temperature group), Penman (Combination group) and Hamon (temperature, day length group) methods had a relatively reasonable performance. As the results on a monthly scale, the Jensen−Haise and Makkink produced the most accurate evaporation estimations even by the limited measurements of the input data.
Conclusion: This study was carried out with the objective of estimating evaporation from the Doosti dam reservoir, and comparison and evaluation of conventional method to find the most accurate method(s) for limited data conditions. These examinations recognized the Jensen−Haise, Makkink, Hamon (Eq. 17), Penman and deBruin methods as the most consistent methods with the monthly rate of BREB evaporation estimates. The results showed that radiation−temperature methods (Jensen−Haise and Makkink) have appropriate accuracy especially on a monthly basis. Also deBruin, Penman (combination group), Hamon and Papadakis (temperature group) methods produced relatively accurate results. The results revealed that it is necessary to calibrate and adjust some evaporation estimation methods for the Doosti dam reservoir. According to the required input data, sensitivity and accuracy of these methods, it can be concluded that Jensen−Haise and Makkink were the most appropriate methods for estimating the lake evaporation in this region especially when measured data were not available.
A. Lashkari; Mohammad Bannayan Aval; A. Koocheki; A. Alizadeh; Y. S. Choi; S.-K. Park
Abstract
Introduction: Consistency and transparency in climate data and methods facilitate comparisons across regions or between models in each of these assessments, particularly when market linkages between regions are emphasized (14 and 15). However, the density and quality of stationary climate data varies ...
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Introduction: Consistency and transparency in climate data and methods facilitate comparisons across regions or between models in each of these assessments, particularly when market linkages between regions are emphasized (14 and 15). However, the density and quality of stationary climate data varies widely through space and time, with the best coverage in developed countries and less reliable coverage in the Tropics and Southern Hemisphere (15). So, several groups have collected these data and constructed harmonized, global gridded datasets at monthly resolution. However, these require weather generators synthesize daily resolution before they may be applied to crop models and are therefore likely to miss events that are important for the calibration and validation of agricultural models. Regional gridded observational networks have also been created (e.g., E-Obs in Europe, (8); APHRODITEin Asia, (21)), however many regions and variables are not covered by any such network and inter comparing sites between regions with different methodologies introduces inconsistencies (). Recently, AgMERRA climate forcing dataset provide daily, high-resolution, continuous, meteorological series over the 1980–2010 period designed for applications examining the agricultural impacts of climate variability and climate change. These datasets combine daily resolution data from retrospective analyses (the Modern-Era Retrospective Analysis for Research and Applications, MERRA) with in situ and remotelysensed observational datasets fortemperature, precipitation, and solar radiation, leading to substantial reductions in bias in comparisonto a network of 2324 agriculturalregion stations from the Hadley Integrated Surface Dataset (HadISD) (5).Therfore, this research was done in order to investigate the possibility of using AgMERRA climate forcing dataset to estimate missing data in in-situ daily temperature and precipitation observations in Mashhad plain.
Materials and Methods: The study area was Mashhad plain in KhorasanRazavi province, located in the northeast of Iran. Climate data corresponding to Mashhad plain extracted by means of geographical characteristics of Mashhad (for the 1980-2010 periods) and Golmakan (1987-2010 period) stations from AgMERRA dataset. The goodness of fit of AgMERRA climate forcing dataset was done by means of Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Mean Bias Error (MBE) tests and R2. The root mean-squared error (RMSE) is computed to measure the coincidence between measured and modelled values and Mean Bias Error (MBE) is simply to examine the overall model error.Furthermore, probability distribution function of observed daily data and AgMERRA data for both Golmakan and Mashhad stations calculated. Eventually, mean and variance of AgMERRA and in-situ data were calculated to have a more accurate comparison of simulated and observed data.
Results: Results indicated that AgMERRA dataset has a good performance in estimating daily maximum and minimum temperature in Mashhad Plain. RMSE, MAE and MBE for daily precipitation illustrated a good performance of AgMERRA data. However, R2 value was 0.43 and 0.25 for Mashhad and Golmakan stations, respectively. Although the probability distribution function of daily maximum and minimum temperature and precipitation indicated the same trend for both studied stations, comparison of mean and variance of observed daily maximum and minimum temperature and precipitation and AgMERRA data for Mashhad and Golmakan stations showed different results. The difference between mean of AgMERRA and observed daily maximum temperature for Mashhadand Golmakan stations was 3.42 and 2.10 C°, respectively. It was 4.68 and 3.05 C° for minimum daily temperature for Mashhad and Golmakan, respectively, and the difference between mean of AgMERRA and observed daily precipitation was 0.06 and 0.28 mm.day-1 for Mashhad and Golmakan, respectively.
Discussion and Conclusion: This research showed that using AgMERRA climate forcing dataset could be a reliable tool to estimate missing data of in-situtemperature observations. Although the performance of AgMERRA dataset was good for daily precipitation, distribution of simulated precipitation compare with observed precipitation was different. Concerning AgMERRA precipitation data some points have to keep in mind that precipitation in arid and semi-arid regions tends to be more variable in time than in humid regions. In fact, the distinctive features of arid and semiarid regions affect precipitation modeling on a discrete event basis and a continuous basis (7, 10, 13).Results of this research illustrated the same trend and it revealed that AgMERRAdataset could not simulate the precipitation distribution in Mashhad plain. It seems that comparing AgMERRAprecipitation data with OPHRODITE dataset and other dataset can give us more accurate vision about AgMERRA dataset. Furthermore, it seems that it is needed to do more researches regarding investigation of performances of crop model results by using AgMERRA dataset as climate data input, because this dataset was released for agricultural application.
A. Mianabadi; A. Alizadeh; Seied Hosein Sanaei-Nejad; M. Bannayan Awal; A. Faridhosseini
Abstract
Precipitation is a key input to different crop and hydrological models. Usually, the rain gauge precipitation data is applied for the most management and researching projects. But because of non-appropriate spatial distribution of rain gauge network, this data does not have a desirable accurate. So estimation ...
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Precipitation is a key input to different crop and hydrological models. Usually, the rain gauge precipitation data is applied for the most management and researching projects. But because of non-appropriate spatial distribution of rain gauge network, this data does not have a desirable accurate. So estimation of daily areal rainfall can be obtained by spatial interpolation of rain gauges data. However, direct application of these techniques may produce inaccurate results. In the last years, applying the remote sensing for estimation of rainfall have got so popular all around the word and many techniques have been developed based on the satellite data with high temporal and spatial resolution. In this paper, CMORPH model was validated for precipitation estimation over the northeast of Iran. Results showed that this model could not estimate precipitation accurately in daily scale, but in monthly and seasonal scale the estimation was more accurate. Farooj and Namanloo station had the highest correlation equal to 0.31 in daily scale. The highest correlation in monthly scale was equal to 0.62 for Barzoo, Namanloo and Se yekAb station. In Seasonal scale Gholaman station had the highest correlation which was equal to 0.63. Also, the probability of detection has been estimated accurately by CMORPH. But this technique did not have an accurate estimation for wet and dry days, mean annual precipitation and the number of non-rainy days.
M. Mohajerpour; A. Alizadeh; Mohammad Mousavi baygi
Abstract
Interception is one of the important and effective parameters on ET and hydrological relation, which is ignored in many situations. In order to investigate the effectiveness of LAI and extinction coefficient on amount of interception, in this study wheat and soybean were cultivated in thelysimeters of ...
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Interception is one of the important and effective parameters on ET and hydrological relation, which is ignored in many situations. In order to investigate the effectiveness of LAI and extinction coefficient on amount of interception, in this study wheat and soybean were cultivated in thelysimeters of agricultural school of Fredowsi Uni. of Mashhad, in Spring and Summer 2012 in the same treatments. The results showed that there is relationship between interception and LAI and extinction coefficient. By increasing LAI, interception increased significantly (slope 0.15). The maximum amount of interception was 1.19 cm in soybean by 6.19 LAI and in wheat cultivars was 1.1cm in 4.58LAI. Also by decreasing the extinction coefficient, interception increased by the rate of 1.023. Results showed that in the same LAI (3.2), wheat interception was more than soybean, 0.74 and 0.5 respectively. While in the same extinction coefficient interceptions was the same in two crops. Standardization the amount of interception by LAI, showed that the effect of the crop on interception is still remained, while by standardize the interception by extinction coefficient, the influence of crop on standard interception removed. The obtained result showed that the type of crop has a significant effect on interception, which can be shown by extinction coefficient.
S. Emamifar; A. Alizadeh
Abstract
Estimation the amount of radiation reaching the Earth's surface (Rs) is an important factor in the energy balance models simulation of plant growth and evapotranspiration estimation. Most Estimation models to radiation reaching the Earth's surface use satellite data and they are based on land surface ...
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Estimation the amount of radiation reaching the Earth's surface (Rs) is an important factor in the energy balance models simulation of plant growth and evapotranspiration estimation. Most Estimation models to radiation reaching the Earth's surface use satellite data and they are based on land surface temperatures. In this study, the Accuracy of solar radiation estimation is investigated Using four different models of neural networks (with the names of ANN1,ANN2, ANN3, ANN4) with the inputs Including products land surface temperature MODIS sensor (models 1 and 2 , and models 3 and 4 are based on MOD11A1 MYD11A1 products, respectively), extraterrestrial radiation (Ra) and relative sunshine (n / N). The results show that four neural network models are able to estimate the amount of radiation reaching the Earth's surface with good correlation (R2>. 85). However, models based on MOD11A1 products have a higher accuracy than models based on MYD11A1 products. Neural network model of ANN1 (based on MOD11A1 products, relative sunshine and extraterrestrial radiation (Ra)) with the coefficient of determination (R2) equal to .9332 and the root mean square error (RMSE) equal to 1.4448 MJ per square meter per day is more accurate on the estimation of solar radiation than other models. The results also showed that the Neural network model ANN2, comparing with Hargreaves and Samani models based on air temperature and extraterrestrial radiation, is More accurate in estimating of solar radiation.
B. Ashraf; A. Alizadeh; M. Mousavi Baygi; M. Bannayan Awal
Abstract
Scince climatic models are the basic tools to study climate change and because of the multiplicity of these models, selecting the most appropriate model for the studying location is very considerable. In this research the temperature and precipitation simulated data by BCM2, CGCM3, CNRMCM3, MRICGCM2.3 ...
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Scince climatic models are the basic tools to study climate change and because of the multiplicity of these models, selecting the most appropriate model for the studying location is very considerable. In this research the temperature and precipitation simulated data by BCM2, CGCM3, CNRMCM3, MRICGCM2.3 and MIROC3 models are downscaled with proportional method according A1B, A2 and B1 emission scenarios for Torbat-heydariye, Sabzevar and Mashhad initially. Then using coefficient of determination (R2), index of agreement (D) and mean-square deviations (MSD), models were verified individually and as ensemble performance. The results showed that, based on individual performance and three emission scenarios, MRICGCM2.3 model in Torbat-heydariye and Mashhad and MIROC3.2 model in Sabzevar had the best performance in simulation of temperature and MIROC3.2, MRICGCM2.3 and CNRMCM3 models have provided the most accurate predictions for precipitation in Torbat-heydariye, Sabzevar and Mashahad respectively. Also simulated temperature by all models in Torbat-heydariye and Sabzevar base on B1 scenario and, in Mashhad based on A2 scenario had the lowest uncertainty. The most accuracy in modeling of precipitation was resulted based on A2 scenario in Torbat-heydariye and, B1 scenario in Sabzevar and Mashhad. Investigation of calculated statistics driven from ensemble performance of 5 selected models caused notable reduction of simulation error and thus increase the accuracy of predictions based on all emission scenarios generally. In this case, the best fitting of simulated and observed temperature data were achieved based on B1 scenario in Torbat-heydariye and Sabzevar and, A2 scenario in Mashhad. And the best fitting simulated and observed precipitation data were obtained based on A2 scenario in Torbat-heydariye and, B1 scenario in Sabzevar and Mashhad. According to the results of this research, before any climate change research it is necessary to select the optimum GCM model for the studying region to simulate climatic parameters.
A. Moghaddam; A. Alizadeh; Alinaghi Ziaei; A. Farid Hosseini; D. Fallah Heravi
Abstract
Genetic Algorithm as a one of the main evolutionary algorithms has had a most successful role in the water distribution network optimization.This algorithmhas been undergoing many reforms and improved versions are published. A type of genetic algorithms is Fast Messy Genetic Algorithm (FMGA), that has ...
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Genetic Algorithm as a one of the main evolutionary algorithms has had a most successful role in the water distribution network optimization.This algorithmhas been undergoing many reforms and improved versions are published. A type of genetic algorithms is Fast Messy Genetic Algorithm (FMGA), that has the ability to increase the convergence rate in solving optimization problems with reducing the length of chromosomes and removing the inefficient genes, meanwhile studying the chromosomes which are not equal in terms of gene strings.In this paper, for evaluation of the FMGA performance in solving water distribution network optimization problems, after the sensitivity analysis and determining the best values of these parameters, two benchmark networks and a real network are analyzed, which are named Two-loop network, the Hanoi network and Jangal City network, respectively, and the results were compared with previous researches. Least-cost in two loop network was estimated after 2880 number of function evaluations that had significant improvements compared to the results of previous researches. In Hanoi network, the minimum cost obtained equal to 6.045×106 $ that is less than other researchers results are issued so far. After proving the efficiency of algorithm, its performance was shown in design of real Jangal city network according to increasing network size and design constraints.
S.A. Haghayeghi; A. Alizadeh
Abstract
Permissible working hours of agricultural wells in the Neyshabour plain was determined equal 4120 hours by regional water authority of Khorasan-e-Razavi. This research was conducted to introduce method of working hours of agricultural wells in the Khorasan-e-Razavi province (case study of Neyshabour ...
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Permissible working hours of agricultural wells in the Neyshabour plain was determined equal 4120 hours by regional water authority of Khorasan-e-Razavi. This research was conducted to introduce method of working hours of agricultural wells in the Khorasan-e-Razavi province (case study of Neyshabour plain) and analyse effective parameters on working time of wells. For this purpose, the area of agronomy and horticulture crops was obtained for the years of 2001 to 2010. Water requirement of these crops was extracted from the water national document. Working hours of wells for every months would be calculated by deviding gross irrigation requirement to average hydromodul of three maximum months. The calculations to assess the effect of sowing pattern was done separately in two phases, for all crops pattern and for major crops pattern. In the thirth and forth phases, the effect of annual variation of water requirement and irrigation hydromodul were assessed on the working hours of Neyshabour plain wells. The results showed that instead of using all crops pattern, it is possible to use just major crops in calculating of working hours of wells. Annual variation of sowing pattern and water requirement in the Neyshabour plain have significant effect (95% confidence) on working hours of wells. By suppose the constant area under crops in the Neyshabour plain, adjust in calculating of working hours of wells was done using measured hydromodul in the region. In adjusted method, the annual working hours showed increase averagely 440 (11%) hours in compare to permissible working hours of Neyshabour plain (4120 hours). This variety in working hours of wells cause to be near to existence and realy conditions of the Neyshabour plain. In an agronomy year, it is possible to have an acceptable forcasting for working hours of regional wells by determining the sowing area of wheat and barley.
M. Khorami; A. Alizadeh; H. Ansari
Abstract
Increased use of drip irrigation systems in the country and farmer's tendency to use more efficient irrigation systems, has caused need to know about parameters and factors that affect irrigation efficiency. This Study was done to examine how water moves in the soil and soil moisturere distribution at ...
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Increased use of drip irrigation systems in the country and farmer's tendency to use more efficient irrigation systems, has caused need to know about parameters and factors that affect irrigation efficiency. This Study was done to examine how water moves in the soil and soil moisturere distribution at Weather Station of Ferdowsi University of Mashhad. Inthisstudy, Hydrus 2D/3D Model performed by using data from laboratory and field analysis. Thes imulation results of soil moistureina 48 hour period were compared with the results offield measurements. The results showed that the model is very capable in simulating moisture contentin thesoil. Statisticalerroranalysiswas described to estimate model parameters using Maximumerror (ME), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). Based on the results of RMSE parameter in volume tricsoil moisture, forallintervals and all discharges RMSE was less than 10 percent that it shows that model hashigh ability in simulation. Maximum Error was up to 5% of and Mean Absolute Error was up to 2.05 % of volumetric moisture content.
M. Karimzadeh; A. Alizadeh; M. Mohammady Arya
Abstract
One of the important factors that limits the maintenance and expansion of agriculture in irrigated lands of arid areas is the water shortage. Reuse of the municipal waste water effluent as one of the uncommon water resources especially around the big cities has received a lot of attention. One of the ...
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One of the important factors that limits the maintenance and expansion of agriculture in irrigated lands of arid areas is the water shortage. Reuse of the municipal waste water effluent as one of the uncommon water resources especially around the big cities has received a lot of attention. One of the most important physical properties of the soil affected by using wastewater is the saturated soil hydraulic conductivity (Ks). In order to investigate the effect of wastewater on Ks, the farms with sand, silty loam and clay were selected from the area around Parkand Abad (2) refinery in Mashhad that has been irrigated during the past 5 years with wastewater. Undistirbed sample was selected and saturated with water , wastewater and mixture of them was used to determine the amount of ks (with constant head method) and the of soil in laboratory. The results showed that the farms with wastewater with total suspended solids of 60 mg per litere floating in water limits the ks in different textures. The reduction in soil with clay texture as about 9 Percent and in silty loam and sand was about 4.5 and 2 Percent respectively. Using water as the liquid of experiment didn’t have any effect on increasing the amount Ks so that leaching the soil under the irrigation with wastewater increased the soil saturation up to 3 percent That shows no effect of leaching in improving the water direction. The most change of pb was observed in clay soil about 11 percent and the least in sand texture soil about 0.6 percent that with respect to the amount of floating materials in wastewater (60 mg) per liter the use of wastewater has been effective in blocking the soil openings. It seems that the floating material in waste water soil aggregation and the duration of continuous use of wastewater are effective factors in changing the physical properties of soil such as Conductivity of water saturated soil.
S. Esfandyari; hossein dehghani; A. Alizadeh; K. Davary
Abstract
The present study was aimed to determine the effect of drip irrigation methods and nitrogen levels and their interaction on corn root development and study of the root movement model. For this purpose, a split plot field experiment based on randomized complete block with irrigation method in two levels ...
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The present study was aimed to determine the effect of drip irrigation methods and nitrogen levels and their interaction on corn root development and study of the root movement model. For this purpose, a split plot field experiment based on randomized complete block with irrigation method in two levels (surface and subsurface drip) as main treatment and Nitrogen fertilization in two levels (50 and 100% of fertilizer requirement) as sub main treatment at 3 replications was conducted at Agricultural Engineering Research Institute, Karaj, Iran using corn variety 370 double-cross. Monitoring of root depth was performed by digging trenches and observation of soil profile. The samples were collected during the growing season with 10 day intervals (8 times totally) and root weight in different soil layers was measured by harvesting of soil monoliths and washing in plastic filters under water pressure. Results showed that the depth of root development up to 20 days after planting was significantly more in surface irrigation method compare to subsurface drip irrigation method; but it was not significant in 30 to 80 days after planting at 5% level. The depth of root development was not significantly different in different nitrogen levels in fertigation method at 5% level. Interaction of irrigation methods and nitrogen levels also didn’t show significant effect on depth of root development at different corn stages growth at 5% level. Root width development was not significantly different in all treatments. The most root distribution observed at 20 to 40 cm and 0 to 20 cm of soil layer in subsurface drip irrigation and subsurface drip irrigation methods, respectively. The lowest root density was observed at 40 to 60 cm soil layer in both studied irrigation methods. Also the roots were more uniformly distributed in soil in subsurface drip irrigation method compare to surface drip irrigation method. The most accurate root depth estimation was achieved by the linear, Borg & Grims and Cropwat models, respectively.
H. Moradi; H. Ansari; majid hashemi nia; A. Alizadeh; A. Vahidian Kamyad; S.M.J. Mosavi
Abstract
Evapotranspiration is one of the major components of hydrologic cycle and estimation of irrigation needs. In recent years the use of intelligent systems for estimating hydrological phenomena has increased significantly.In this study the possibility of using fuzzy inference system efficiency, creating ...
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Evapotranspiration is one of the major components of hydrologic cycle and estimation of irrigation needs. In recent years the use of intelligent systems for estimating hydrological phenomena has increased significantly.In this study the possibility of using fuzzy inference system efficiency, creating a bridge between meteorological parameters and evapotranspiration, and comparing the accuracy of reference evapotranspiration using these systems were investigated. After analyzing the different models and different combinations of daily meteorological data, five models for estimating daily reference evapotranspiration were presented. For these models, the calculated evapotranspirationfrom Penman-Monteith-FAO equation was considered as a baseand the efficiency of other models was evluated using statistical methods such as root mean squared error, error of the mean deviation, coefficient of determination,Jacovides(t) and Sabbaghet al. (R2/t) criteria. The used data were collected from Mashhad’s meteorological synoptic station for a period of 50-years (from 1339 to 1389).From the available data, 75 percentwas used for training the model and the rest of 25 percent was utilized for the testing purposes. The results derived from the fuzzy models with different input parameters as compared with Penman-Monteith-FAO and Hargreaves-Samani methods showed that fuzzy systems were very well able to estimate the daily reference evapotranspiration.Fuzzy model so that the highest correlation with the four input variables (r=0.99) had in mind and evaluate other parameters, the model with two parameters, temperature and relative humidity (RMSE=0.96, MBE =0.18, R2=0.95, t=22, = and R2 / t=0.04) match very well with the model Penman - Monteith - FAO had stage training. In the test phase, training phase was very similar results and the model with the second phase of temperature and relative humidity will get the best match. According to the results of this study it can be concluded that fuzzy model approach is an appropriate method to estimatethe daily reference evapotranspiration. In addition, the fuzzy models do not require complex calculations which are required forcombination methods.
M.H. Najafi Mood; A. Alizadeh; K. Davari; M. Kafi; A. Shahidi
Abstract
This experiment was conducted based upon a factorial split plot design consisting of three factors: salinity with three levels (2.2, 5.5 and 8.3 dS/m), irrigation with four levels (50%, 75%, 100% and 125%), cultivars with two levels (Varamin and Khordad). There were three replicates for each treatment ...
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This experiment was conducted based upon a factorial split plot design consisting of three factors: salinity with three levels (2.2, 5.5 and 8.3 dS/m), irrigation with four levels (50%, 75%, 100% and 125%), cultivars with two levels (Varamin and Khordad). There were three replicates for each treatment combination. Salinity was considered as main plot while the other factors were arranged as sub plots in the experiment. Effects salinity and deficit irrigation on yield for cultivars of cotton studied with Marginal Production(MP), Marginal Rate of Technical Substitution(MRTS) and Value of Marginal Production(VMP) indexes. Also for economics analysis, optimum depth of irrigation for deficit irrigation and complete irrigation depth were determined for tow cultivar. MPI showed That in deficit irrigation condition, yield of Khordad less than Varamin, for 1 centimeter of irrigation depth. But in over irrigation level , decreasing yield of Khordad rather than Varamin. Also MPECw showed, That yield decreased 31.8 Kg/ha on Varamin and 76.5 Kg/ha on Khordad cultivars, by increasing 1 dS/m salinity of irrigation water. MRTS index showed for instant yield, when salinity of irrigation water decrease 1 dS/m, must be increase depth of irrigation, 1.68, 3.85 cm for Varamin and Khordad respectively. So that, in equal situation of irrigation water salinity, optimum irrigation depth for Khordad was rather than Varamin.Also in all of salinity levels, optimum irrigation depth, for Khordad was rather than Varamin.
A. Hosseinpour Buri Abadi; Gh. Haghnia; A. Alizadeh; A. Fotovat
Abstract
Increasing population, limitation of water resources, and also enormous volume of municipal wastewater and need to dispose of these wastewaters safety, has been increased of necessity of reuse of wastewater. Disposal of wastewater in soil is one of the most economical methods of their disposal. Different ...
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Increasing population, limitation of water resources, and also enormous volume of municipal wastewater and need to dispose of these wastewaters safety, has been increased of necessity of reuse of wastewater. Disposal of wastewater in soil is one of the most economical methods of their disposal. Different soil characteristics, type of wastewater and method of its application are issues that affect wastewater treatment efficiency in the soil. For this purpose, an experiment was carried out in 12 polyethylene columns during 7 periods of 15 days in Ferdowsi University of Mashhad. A statistical “factorial design” was used. Raw and treated wastewaters from Parkandabad Treatment Plant were applied under continuous and intermittent flood conditions in columns filled with silty loam soil. At the end of experiment, soil columns were divided and soil samples from depths of 0-25, 25-50 and 50-100 cm each column were collected. Properties such as pH, salinity, concentration of NO3, PO4, TOC, Ni and Cd were measured in soil solution samples and also Leachates were taken in each period of experiment. The result showed that the mean values of each of the above mentioned parameters, with exception of pH and salinity, were lower in leachate compared to the wastewaters entering the soil. However, with continuous application of wastewaters increase in the amount of these components (with exception of salinity and Ni) were observed. The amount of Cd in leachate samples of any periods was undetected. Considering the effect of wastewater application on soil chemical properties, value of all parameters (except salinity) in comparison to their initial values have increased in the soil solution. Based on the above results, disposal of wastewaters (especially raw wastewater) on soil should be managed carefully. So that by sound usage of wastewaters, environmental risks resulting from disposal of them are reducing to the lowest level in nature.
S.A. Ghassemi; Sh. Danesh; A. Alizadeh
Abstract
Abstract
One of the major aspects of water resources management in the arid and semi-arid regions is the use of unconventional water sources such as effluents from wastewater treatment plants. As a result, assessment of water supply potential as well as fertilizer values of these unconventional water ...
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Abstract
One of the major aspects of water resources management in the arid and semi-arid regions is the use of unconventional water sources such as effluents from wastewater treatment plants. As a result, assessment of water supply potential as well as fertilizer values of these unconventional water sources is an important issue in any comprehensive resource management program. In this study, the water supply potential and fertilizer values of the effluents from the City of Mashhad wastewater treatment plants (Olang, Parkand-Abad #1 & Parkand-Abad #2) was assessed based on: 1) the effluents' nitrogen and phosphorus contents, 2) common types of agricultural crops in the region (wheat, barley, tomato), and 3) the crops water and fertilizer requirements over their growing season. The results of this research indicated that the water supply potential of the effluents from above mentioned wastewater treatment plants for irrigation of wheat, barley and tomato are equivalent to 962, 870 and 729 hectares, respectively. Moreover, based on the results of the integrated model used in this research, the use of the effluents can provide 87.2, 74.4 and 133.6 kg.ha-1 available nitrogen and 36.7, 31.7 and 62.0 kg.ha-1 phosphorus for wheat, barley and tomato, respectively. In terms of economic assessments, the water value of the effluents corresponded to 89.6×106 Rials for wheat, 67.4×106 Rials for barley, and 125.0×106 Rials for tomato. In terms of fertilizer value, the corresponding economic assessment represented values of 1.97×109, 1.44×109, and 4.68×106 Rials. In general, the net results of the economic analysis performed indicated that the use of the effluents from the City of Mashhad wastewater treatment plants in agriculture can reduce the cost of production by 33, 31 and 28 percent for wheat, barley and tomato, respectively.
Keywords: Wastewater, Agriculture, Water Resource, Nitrogen, Phosphorus, Economic Analysis
N. Majidi; A. Alizadeh; M. Ghorbani
Abstract
Abstract
In refrence to un appropriate time and place dispersal of precipitation in Iran and having low efficiency in agriculture, water as the most limitative factor in agriculture is discussing. In this study, the existing pattern of Mashhad-CHenaran plain is considering and with gathering data related ...
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Abstract
In refrence to un appropriate time and place dispersal of precipitation in Iran and having low efficiency in agriculture, water as the most limitative factor in agriculture is discussing. In this study, the existing pattern of Mashhad-CHenaran plain is considering and with gathering data related to 1388, with target of decrease in water consuming, optimum and nearly optimum cropping pattern was determined. In order to reach to this target, we used linear programming and modeling to generate alternatives. Related result which were reached from linear programming showed that use of all under cropping area and also reaching gross margin like existing pattern, the amount of water consuming had been decreased which is resulted from new compound of yields in production system. Also in the optimal state surface of products such as sugar beet, beans and sunflower due to high water consumption and having lower gross margin were removed from the cropping pattern. Also nearly optimum pattern showed that even an increase of 5% and 7% in amount of consuming water rather than optimum position, only at most 1.5% gross margin had been increased, that because of importance using continuous of water resource and protection of this worthful resource, so extra utilization doesn’t recommend. In refrence to result, using making optimum patterns in codifying cropping pattern in plain are recommended.
Keywords: Optimal Cropping Pattern, Water Resources Management, Lineare programming, Nearly optimal programming
N. Sayari; A. Alizadeh; M. Bannayan Awal; A.R. Farid Hossaini; M.R. Hessami Kermani
Abstract
Abstract
The climate change was known to force local hydrology, through changes in the pattern of precipitation, temperature and the other hydrological variables. In this research, the impact of global warming on maximum and minimum temperature, precipitation and evapotranspiration (wheat, corn, tomato ...
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Abstract
The climate change was known to force local hydrology, through changes in the pattern of precipitation, temperature and the other hydrological variables. In this research, the impact of global warming on maximum and minimum temperature, precipitation and evapotranspiration (wheat, corn, tomato and sugar beet) of Kashafrood basin under two climate change scenarios (A2 and B2), and the output of two GCM models (HadCM3 and CGCM2) for three period of times (2010-2039, 2040-2069 and 2070-2099), were investigated. For evaluation two scenarios were downscaled into local level with Automated Statistical Downscaling (ASD) model. Precipitation was expected to decrease and/or increase, depends on applied GCM. The results indicated that the annual precipitation decreased for three periods under CGCM2 model and also for two scenarios (A2 and B2) as much as 13%-16% decreasing, the annual precipitation for three periods under HadCM3 model and two scenarios (A2 and B2) as much as 2%-8% increasing. The maximum and minimum temperatures in the Kashafrood basin was predicted, which increased by CGCM2 and HadCM3 models with two scenarios. Based on the HadCM3 model, maximum and minimum temperatures were expected to increase 2.4 0C to 5.8 0C and 0.6 0C to 3.8 0C, respectively; for 2070-2099 periods. For CGCM2 model, maximum and minimum temperatures were expected to increase 0.06 0C to 2.59 0C and 0.1 0C to 1.9 0C respectively; for 2070-2099. Evapotranspiration under A2 and B2 scenarios and HadCM3 model was increased but increasing in evapotranspiration with CGCM2 model under both scenarios was not significant in many cases. The comparison of two models and also two scenarios indicated that more critical status for A2 scenario by using two GCM models for this basin.
Keywords: Climate change, General circulation model, Downscaling, HadCM3, CGCM2, Kashaf rood basin, Evapotranspiration