Journal of Water Research in Agriculture
Year:2017 | Volume:30 | Issue:4|Papers Count:10

Optimization of water and nitrogen applicationdecreases production costs, conserves resources, and reduces environmental pollution which occurs as a result of excessive use of these resources. The objective of this study was to optimize applied water and urea in corn fertigation. A field experiment was carried out in furrows, having 165m length and 0.006 m/m slope, in Karaj. The corn hybrid 370 double-cross was planted on June 2008 and 2010. The experiments were carried out according to a factorial arrangement based on randomized complete block design with 4 replicates. Four levels (0, 60%, 80%, and 100%) of the recommended fertilizer value and four levels (60%, 80%, 100%, and 120%) of irrigation water requirement were applied. Fertilizer treatments were accomplished at four critical stages of the growth (before cultivation, seven-leaf stage, shooting stage, and flowering stage). In this study, an analysis of crop yield production, cost and revenue functions, and profit maximization was conducted to determine the optimal water and nitrogen use. The results of multiple regression at 5% level showed that the relationship between the grain yield and the amount of each of the inputs of water and nitrogen was a quadratic function (R2=0.83 and ME=15.53%). The optimal level of urea consumption was dependent on applied water. By increasing the amount of irrigation water, the optimum level of fertilizer consumption is increased. When land is limiting, use of full irrigation (940 mm) and 375 kgurea/ha leads to maximum income. When water is limiting, the optimum amounts of applied water and urea were774 mm (77% of water requirement) and 357 kg/ha (90% of urea recommendation), respectively.

Water pricing is one of the most important economic tools for increasing water demand management in the agricultural sector. In this regard, the purpose of this study, was to determine the economic value of agricultural water from the perspective of demand by using production function approach in wheat for Gorgan County, in 2012-13. In this study, flexible and inflexible functions were used. After estimating these functions, Cobb-Douglas function was chosen as the best production function. Water economic value calculated for wheat crop was 1564.5 Rials per cubic meter. Also, the price elasticity of demand for these products was calculated. According to the results, the absolute price elasticity of water demand for wheat was estimated at 1.28, which is larger than unity and shows that price policies can be an important factor in the control of non-optimized consumption of this valuable input.

Water stress and salinity are among the problems of agricultural production in many parts of the world. In this study, the effect of salinity (2,5 and 8 dS/m), different irrigation levels (120%, 100%, 75%, and 50% of water requirement) and three harvesting times (cuttings) were investigated on some qualitative and quantitative parameters of sorghum silage in the Sistan region. The study was carried out using a factorial split plot design with 12 treatments and 3 replications. The results showed that increasing salinity and irrigation water depth decreased fresh and dry matter yield. However, no significant difference was observed between 100% and 75% crop water requirement treatments. Also, treatments with 2 and 5 dS/m salinity were not significantly different in feed production. Furthermore, the fresh and dry forage yields were higher in the second cutting than in the first and third harvesting. Decrease in irrigation water and increase in salinity decreased protein but increased carbohydrate and proline. The highest amount of protein (16.79 percent) was obtained in the second harvesting and at the salinity of 2 dS/m, while the highest amount of carbohydrates (10.79 mg/gFW) and proline (0.42 mg/gFW) belonged to the third harvesting with salinity of 8 dS/m. By increasing salinity in irrigation water and with the passage of time during the growing season, soil salinity increased and distribution of salinity in the soil profile was more uniform in the treatments that had no water stress. Thus, according to the results, 25% of the plant water consumption can be saved and irrigation with 75% of water requirement and salinity of 5 dS/m would have no significant effect on the amount of forage produced. The best forage quality for livestock consumption was obtained in the second harvesting. However, this experiment was done in one growing season and in the long time reduction in the amount of water and the use of salt water can cause soil salinization and accumulation of salts in the soil. Therefore, it is recommended that the experiment be repeated in the future, before making a final decision about reducing irrigation water.

Tomato is one of the major agricultural products in Fars Province. Previous studies show that the tomato farms under current irrigation systems lose a large volume of water with low water productivity. In the present study, the irrigation requirement and the influence of different irrigation regimes on the yield and water productivity of three cultivars of tomato was studied. The farm under study was located in Marvdasht plain, with a heavy soil texture. The irrigation water was applied based on 60%, 80%, 100%, and 120 percent of Penman Montieth water requirement method, under drip irrigation system. Another treatment was considered and irrigated by the farmer management. Benefit-cost ratio and benefit-cost difference was calculated for economic analysis. Results show that the obtained yield increased with irrigation water while water productivity decreased. The irrigation volumes of water used for the treatments were about 3900 to 7800 cubic meters per hectare. However, only the differences between the treatments 60% and 120% were statistically significant. Economic evaluations showed that the tomato production was not economical with tomato price equal to 2500 Rials, while the water price varies from zero to 6000 Rials. In this situation, the benefit-cost ratios varied from 0.78 to 0.68, respectively. Increase in price of tomato could improve the benefit-cost ratio.

In central region of Iran, increasing soil and water salinity and declining ground and surface water resources have increased the necessity of reducing the effect of salinity on crop yield. Utilization of plastic mulches is an effective method for reducing the salinity hazard on plant growth. In this respect, an experiment was conducted on cantaloupe using factorial combination of four irrigation water salinities of 2, 4, 6 and 8 dS m-1 and three mulch treatments including bare soil (control), transparent (TPM), and black plastic mulch (BPM). The experimental design was randomized complete block design in three replicate. The analysis of variance showed that the effects of saline irrigation water on yield, mean weight of fruit, yield of plant, yield of marketable and non-marketable fruit were highly significant (P<0.01), and on number of harvested fruit were significant (P<0.05). The effect of mulch treatments on fruit yield and mean weight of fruit was highly significant (P<0.01) and on number of fruit per m-2 and number of fruit per plant were significant (P<0.05). The interaction effects of saline irrigation water and mulch were not significant on any of the aforementioned parameters. The cantaloupe yield in 2, 4, 6 and 8 dS m-1 irrigation water treatments across all mulch treatments were 5.12, 4.01, 4.03 and 2.94 kg m-2, respectively, and were significantly different (P<0.01). The plot yield for the control, BPM, and TPM were, respectively, 2.18, 4.47, and 4.69 kg m-2, and there was significant differences (P<0.05) between plastic mulch with the control. With increasing irrigation water salinity from 2 to 8 dS m-1, the average soil salinity in 0 to 60 cm soil layer increased from 4.5 dS m-1 to 11 dS m-1. Increasing salinity of irrigation water enhanced the effect of mulch treatment on decreasing the soil salinity. The relationship between cantaloupe yield and soil salinity was Yr=100- 7.1X(ECe-2.48), where Yr, and ECe (dS m-1) are the relative yield (yield of non-saline to saline treatment yield) and soil electrical conductivity in 0-60 cm soil layer. Therefore, cantaloupe is moderately sensitive to salinity and utilization of plastic mulches to increase earliness and decrease the effect of irrigation water salinity is recommended.

Climate change has important impacts on most of the natural processes, including hydrological cycle. Evapotranspiration, as a part of hydrological cycle, will also undergo these changes. Due to the importance of evapotranspiration in water resources and agricultural management, this research was conducted to study climate change effect on evapotranspiration in Neyshabour plain. Evapotranspiration was calculated for five farms in Neyshabour plain using SWAP software and meteorological and agronomic data. In irrigated farms, the HADCM3, ECHAM5OM and CGCM3T47models were used to calculate crop actual evapotranspiration for 2020-2039 and 2080-2099 periods based on A2, B1 and A1B scenarios and the climate model used in rainfed farms was the HADCM3 based on A2 and B1 scenarios. The greatest calculated difference in evapotranspiration was found between the period 2080-2099 and base period (1992-2011) in the A2 scenario. Also, evapotranspiration values for the period 2080-2099 will increase compared to the period 2020-2039 in all three scenarios. Among the crops of investigate, wheat will have the greatest changes (12%) in evapotranspiration in the future periods compared to the base period, while changes of maize will be only 3%. However, the average daily evapotranspiration of maize during the growing season (about 12 mm/day) will be more than the other crops.

The SEBAL algorithm is used to estimate spatial distribution of actual evapotranspiration using remote sensing imageries of MODIS or Landsat. Despite having a better spatial resolution than MODIS imageries (30 m instead of 1000 m), Landsat imageries do not have an appropriate temporal resolution (every 16 days instead of daily). On the other hand, the daily imageries of MODIS can be difficult to use under cloudy condition. Additionally, it is also a time-consuming process to interpret all the imageries. In this research, we chose the appropriate imageries from MODIS to be able to monitor the sudden weather changes as well as rainfall events and to reduce the interpretation time, while keeping the important information of the daily MODIS imageries in order to obtain the better actual evapotranspiration estimates. Due to the importance of hot and cold pixel selection, whose selection needs time and proficiency, we applied the automated method of hot and cold pixel selection (without user-intervention) using Landsat imageries. To integrate evapotranspiration over time, we used linear-logarithmic interpolation method in addition to linear interpolation method. The estimated actual evapotranspiration by SEBAL was compared to the estimated actual evapotranspiration from water balance equation and SWAT model for 3 years including a wet year (2004-2005), a normal year (2005-2006) and a dry year (2007-2008) in the Neishaboor-Rokh watershed. Furthermore, we used the Budyko framework to validate the evapotranspiration estimated by SEBAL and SWAT. The results showed that in comparison to SWAT, the linear-logarithmic interpolation method performed better than the linear method to estimate evapotranspiration. For linear-logarithmic method, RMSE, MBE, and MAE were 20.4, 0.09, and 18.4 mm year-1, respectively; and for the linear method, they were 21.8, -2.4, and 20.8 mm year-1, respectively. The results also demonstrated that the SEBAL algorithm with automated cold and hot pixel selection is able to have a good estimate of actual evapotranspiration at annual time scale and watershed scale. But, the algorithm does not perform well at HRUs and monthly scale in comparison to SWAT model. Results showed that by taking irrigation into account, evaporation estimated by SEBAL and SWAT follows the Budyko framework.

This investigation was performed to evaluate the suitability of three Synthetic Envelopes PP450 manufactured by three local workshops in Khouzestan for drainage purposes in three projects, namely, Dehkhoda, Hendijan, and Ramshir projects (respectively, in the north, south, and in the middle of the Khouzestan province). Experiments were performed in the laboratory using an upward flow permeameter. Recommended criteria for the evaluation of the envelopes were steady discharge with time, gradient ratio (GR) for the determination of soil particle movement and envelope clogging potential, and hydraulic conductivity of soil envelope. According to the results for all the three criteria, type 1 envelope (with tiny pores) was considered suitable for Dehkhoda project soils while for Ramshir project soils, based on the same 3 criteria, envelope 3(with macro pores) was the most suitable followed by envelope 1, while envelope 2 (with medium-sized pores) had a lower technical performance for this soil. For Hendijan project soils, envelopes 3 and 2 were partially suitable because hydraulic conductivity of soil envelope was very low. Summing up, envelope 1 and 3 are recommended for Ramshir project and envelope 1 for Dehkhoda project soils. For Hendijan project soils, envelope 3 needs further testing before making recommendation.

Due to extensive agricultural activities on the plains and the use of chemical fertilizers containing nitrogen, significant amount of this element enter the aquifer. On the other hand, effluent of wastewater treatment plants is used in irrigation and drainage networks as an alternative or supplementary source of surface water. Therefore, adoption of strategies for reducing and controlling the amount of nitrogen that enters the soil and aquifer is an important issue. The aim of this research was to develop a cropping pattern optimization model by quantitative-qualitative conjunctive use of unconventional surface water (wastewater) and groundwater. The three objectives of the model were maximizing profits from cropping pattern, reducing nitrogen leaching, and improving the rate of aquifer recharge. In order to integrate management of wastewater and irrigation water resources, the nonlinear three-objective optimization model was run for 7 scenarios (one-objective, two-objectives, and three-objectives) in water year 2012-2013, for Varamin irrigation network. The input data required for the model were collected in two ways: regional testing and obtaining information from various institutions. Solving one-objective model by first objective (first scenario: improving the network’s profit) showed the 49 percent improvement in the network’s net profit. The second objective (second scenario: reducing of fertilizer consumption) showed 95% reduction of fertilizer consumption, and the third objective (third scenario: improving the aquifer recharge) showed 120% improvement in the aquifer recharge, in comparison to the current situation. Solving the three-objective model (seventh scenario: combined objectives of improving network’s net profit, reducing fertilizer consumption, and improving the aquifer recharge) showed a reduction of 23% in cultivated area, 71% in nitrogen fertilizer consumption, and 13% in conjunctive withdrawals of wastewater and groundwater. Also, these reductions increase net benefit by 6%, aquifer recharge by 29%, and water productivity by 22%. Therefore, the seventh scenario was chosen as the best scenario. The results of this research could be adopted for optimum use of water resources, increasing farmers' benefit, and decreasing nitrogen leaching in irrigation network projects. However, it is to be noted that, generally, use of wastewater for irrigation of food crops is not recommended.

The agricultural sector is known as the largest consumer of water. Due to limited water resources, water productivity needs to be enhanced in this sector. The concept of water productivity has attracted the attention of policy makers in food and water sector at large scale. Remote sensing is used in the assessment and management of soil and water resources in recent decades. In the present research, this method was used to estimate water productivity. Evapotranspiration and actual production levels of dry matter were calculated using SEBAL algorithms and five images from the Landsat 5TM satellite in Qazvin Plain. The results of SEBAL algorithm in five images and lysimeter data were compared and evaluated in the region. The coefficient of determination (15R2">) and their mean absolute difference were 0.9948 and 0.446 mm/day, respectively, which demonstrated the accuracy of remote sensing methods in estimating agricultural water productivity at the basin level. The results showed that water productivity varied from 0.18 to 1.35 in the field. The wheat water productivity values from Landsat 5TM images and lysimeter data were 0.73 and 0.85 kg/m3, respectively, which are relatively close to each other.