Irrigation
T. Khalili; M. Sarai Tabrizi; H. Babazadeh; H. Ramezani Etedali
Abstract
Introduction: Water resources management in arid and semi-arid regions is very important specially, in agricultural sector. The major share of water use is daily consumption by humans for drinking, washing and cooking. Furthermore, population growth increases agricultural production demand, and ...
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Introduction: Water resources management in arid and semi-arid regions is very important specially, in agricultural sector. The major share of water use is daily consumption by humans for drinking, washing and cooking. Furthermore, population growth increases agricultural production demand, and this highlights the role of water resources management in the agricultural sector. The 1950’s studies showed 12 countries with a population of 20 million experienced water shortage. Virtual water is the volume of water which is consumed for a production from the beginning stage to the end. Scientists have shown that 96% of water footprints are related to crops, livestock and horticultural productions and only 4% it consumed as domestic water. Water balance data in Qom province shows that 90% of water resources are using in the agricultural sector. Investigation of water footprints in the agricultural sector is highly beneficial to improve water resources management in arid and semi-arid regions such as Qom. Materials and Methods: The research was conducted to find out the production and cultivation water needs in the agricultural sector for 10 years, via calculating the gray, blue and green water footprints using Mekonnen and Hoekstra models. In the livestock sector, water footprint’s information such as the number of livestock and poultry, production of red meat, chicken meat, egg and milk were also determined using the Mekonnen and Hoekstra. The water footprint in fertilizer was calculated using a questionnaire survey. Excel and SAS apps were used to analyze the collected data for all three study sections. Results and Discussion: The results showed that the water footprint in wheat, barley, cotton, onion, tomato, melon, watermelon, alfalfa, and corn were 3018, 2882, 10960, 1463, 1525, 960, 2504, 1683 and 416 m3/ton, respectively. The low irrigation efficiency led to a very high amount of white water footprint in the productions. Green water footprint was very low due to the lack of rainfall. In the livestock sector, the water footprint in red meat and milk were 39 m3/kg and 2.42 m3/lit, respectively which were much more than the global average. In the poultry sector, the water footprint in chicken meat and egg were 7.4 and 4.34 m3/kg, respectively, that were very high compared to the global average. The water footprint in fertilizer for wheat, barley, cotton and alfalfa productions were 2.62, 1.19, 1.07 and 2.54 m3/kg and this amount was higher under nitrogen fertilizer. The average virtual water footprint for chicken meat production in Qom province was 7.4 m3/kg. This amount in the world, USA, India, Russia, Mexico and the Netherlands is equal to 3.92, 2.39, 7.74, 5.76, 5.01 and 2.22 m3/kg respectively. In Netherlands, less water is in use in the agricultural sector than the other countries. In this country, the virtual water footprint in chicken meat is in the best position. India has the highest water consumption in poultry breeding with a consumption of 7.74 m3/kg. The average virtual water footprint in Iran for egg production is 4.34 m3/kg , while the average virtual water footprint for egg production in the world, USA, India, Russia, Mexico and the Netherlands is 3.34, 1.51, 7.53, 4.92, 4.28, and 1.4 m3/kg, respectively. India consumes the most water in the production of eggs such as chicken with a quantity of 7.53 m3/kg and the Netherlands has the least consumption with a value of 1.4 m3/kg . Conclusion: The concept of virtual water footprint in each region reduces the pressure on water resources. For better management in agricultural regions, it is possible to prevent the cultivation of high water demand crops. The most common cause of high water footprint in livestock and poultry is nutrition, so, internationally food import can be a good solution. Industrialization of poultry can also reduce water footprint. The implementation of this research can be a useful clue to the sustainable control and management of water resources and achieving an optimal cultivation pattern in our country and all provinces facing limited water resources.
M. Sarai Tabrizi; H. Babazadeh; mahdi homaee; F. Kaveh Kaveh; M. Parsinejad
Abstract
Introduction: Several mathematical models are being used for assessing the plant response to the salinity of the root zone. The salinity of the soil and water resources is a major challenge for agricultural sector in Iran. Several mathematical models have been developed for plant responses to the salinity ...
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Introduction: Several mathematical models are being used for assessing the plant response to the salinity of the root zone. The salinity of the soil and water resources is a major challenge for agricultural sector in Iran. Several mathematical models have been developed for plant responses to the salinity stress. However, these models are often applicable in particular conditions. The objectives of this study were to evaluate the threshold value of Basil yield reduction, modeling Basil response to salinity and to evaluate the effectiveness of available mathematical models for the yield estimation of the Basil .
Materials and Methods: The extensive experiments were conducted with 13 natural saline water treatments including 1.2, 1.8, 2, 2.2, 2.5, 2.8, 3, 3.5, 4, 5, 6, 8, and 10 dSm-1. Water salinity treatments were prepared by mixing Shoor River water with fresh water. In order to quantify the salinity effect on Basil yield, seven mathematical models including Maas and Hoffman (1977), van Genuchten and Hoffman (1984), Dirksen and Augustijn (1988), and Homaee et al., (2002) were used. One of the relatively recent methods for soil water content measurements is theta probes instrument. Theta probes instrument consists of four probes with 60 mm long and 3 mm diameter, a water proof container (probe structure), and a cable that links input and output signals to the data logger display. The advantages that have been attributed to this method are high precision and direct and rapid measurements in the field and greenhouse. The range of measurements is not limited like tensiometer and is from saturation to wilting point. In this study, Theta probes instrument was calibrated by weighing method for exact irrigation scheduling. Relative transpiration was calculated using daily soil water content changes. A coarse sand layer with 2 centimeters thick was used to decrease evaporation from the surface soil of the pots. Quantity comparison of the used models was done by calculating statistical indices such as maximum error (ME), normalized root mean square error (nRMSE), modeling efficiency (EF), and coefficient of residual mass (CRM). At the end of the experiment, dry matter yield at the different treatments was measured and relative yield was calculated by dividing dry matter yield of treatments on dry matter yield at no stress treatment (control treatment). Leaching requirement in experimental treatments was calculated by Ayarset al., (2012) equation.
Results and Discussion: The results indicated that Basil threshold value based on soil salinity was 2.25
dSm-1 with the yield reduction of 7.2% per dSm-1. The mathematical model of van Genuchten and Hoffman (1984) had a higher precision than other models in simulating Basil yield reduction function based on saturated soil extract salinity. The overall observations revealed that van Genuchten and Hoffman (1984), Steppuhnet al., (2005) and Homaeeet al., (2002) models were accurate for simulating Basil root water uptake and yield response to saturated soil extract salinity. Considering the presented results, it seems that among math-empirical models for salinity stress conditions, model of van Genuchten and Hoffman (1984) is more accurate than Maas and Hoffman (1977), Dirksen and Augustijn (1988) and Homaeeet al., (2002a) models. The works of Green et al., (2006) and Skaggs et al., (2006) came to the same conclusion. Our work indicated that mostly statistical models have lower precision than math-empirical models. Steppuhn et al., (2005a) reported that statistical models had the higher accuracy than math-empirical model of Maas and Hoffman (1977) and among statistical models, the modified Weibull model had the best fit on measured data which is in good agreement with the results of this study.
Conclusion: The goals of this research were to evaluate Basil response to saturated soil extract salinity, to estimate threshold value of Basil crop coefficients, to obtain yield reduction gradient, and also to investigate efficiency of available math-empirical models in estimating reduction functions. The results of this study indicated that the Basil threshold value obtained based on saturated soil extract salinity was 2.25 dSm-1 and the gradient of yield reduction was 7.2% per dSm-1 according to Maas and Hoffman (1977) linear fitting. The reached general conclusion was that among the math-empirical reduction functions, the model of van Genuchten and Hoffman (1984) had the highest accuracy when compared to the models of Maas and Hoffman (1977), Dirksen and Augustijn (1988) and Homaee et al., (2002a). Therefore, it is recommended to use the van Genuchten and Hoffman (1984), Steppuhn et al., (2005), and Homaee et al., (2002) models respectively, instead of the other models in this research.
