Estimation of Water Footprint Compartments in National Wheat Production

Introduction: Water use and pollution have raised to a critical level in many compartments of the world. If humankind is to meet the challenges over the coming fifty years, the agricultural share of water use has to be substantially reduced. In this study, a modern yet simple approach has been proposed through the introduction concept ‘Water Footprint’ (WF). This concept can be used to study the connection between each product and the water allocation to produce that product. This research estimates the green, blue and gray WF of wheat in Iran. Also a new WF compartment (white) is used that is related about irrigation water loss. Materials and Methods: The national green (Effective precipitation), blue (Net irrigation requirement), gray (For diluting chemical fertilizers) and white (Irrigation water losses) water footprints (WF) of wheat production were estimated for fifteen major wheat producing provinces of Iran. Evapotranspiration, irrigation requirement, gross irrigation requirement and effective rainfall were got using the AGWAT model. Yields of irrigated and rain-fed lands of each province were got from Iran Agricultural-Jihad Ministry. Another compartment of the wheat production WF is related about the volume of water required to assimilate the fertilizers leached in runoff (gray WF). Moreover, a new concept of white water footprint was proposed here and represents irrigation water losses, which was neglected in the original calculation framework. Finally, the national WF compartments of wheat production were estimated by taking the average of each compartment over all the provinces weighted by the share of each province in total wheat production of the selected provinces. Results and Discussion: In 2006-2012, more than 67% of the national wheat production was irrigated and 32.3% were rain-fed, on average, while 37.9% of the total wheat-cultivated lands were irrigated and 62.1% was rain-fed from more than 6,568 -ha. The total national WF of wheat production for this period was estimated as 42,143 MCM/year, on average. Different compartments of wheat WF were estimated for 236 plains in fifteen selected provinces. For irrigated areas, the green WFs ranged from 499 to 1,023 m3/ton, the blue WFs from 521 to 1,402 m3/ton, the gray WFs from 337 to 822 m3/ton, and the white WFs from 701 to 2,301 m3/ton. The average total WF for irrigated areas among all the selected provinces is about 3,188 m3/ton, with almost equal shares of blue and green water. For rain-fed areas, the green WFs ranged from 1,282 to 4,166 m3/ton and the gray WFs from 100 to 740 m3/ton. The average total WF for rainfed areas is about 3,071 m3/ton with the share of green WF being nine times the gray WF. In irrigated areas, the percentages of green, blue, gray and white WFs are 23, 25, 17 and 35% of total WF, respectively in each province. The average total WF for irrigated areas is about 3,188 m3/ton with comparable shares of blue and green water. In irrigated areas, Fars, Khorasan and Khuzestan provinces have the largest of the total WF with 5,575, 5,028 and 4,123 MCM/year, respectively. In addition to large cultivated areas and high rates of potential evapotranspiration, high values of gray and white water is another reason for the high volume of total WF in these provinces. Conclusions: The results showed that the green WF related about wheat production in our country is about 2.3 times the blue WF. It confirmed the importance of green water in wheat production. Also the gray water footprint was assessed which is related about nitrogen application. Besides, the white water footprint was proposed here, which represents irrigation water losses. Results showed that the total water footprint in wheat production for the whole country is about 42,143 MCM/year on average over the period of 2006-2012. The ratios of green, blue, gray and white water were 41, 18, 16 and 25%, respectively. Different compartments of wheat WF were estimated for 236 plains over fifteen selected provinces. Total shares of gray and white water footprint were 41% of total wheat production water footprint. The average total WF for irrigated areas among all selected provinces is about 3,188 m3/ton, with almost equal shares of blue and green water. The authors admit that the accuracy of these results is subject to the quality of the input data

Performance evaluation of FAO model for prediction of yield production, soil water and solute balance under environmental stresses (case study winter wheat)

In this study, the FAO agro-hydrological model was investigated and evaluated to predict of yield production, soil water and solute balance by winter wheat field data under water and salt stresses. For this purpose, a field experimental was conducted with three salinity levels of irrigation water include: S1, S2 and S3 corresponding to 1.4, 4.5 and 9.6 dS/m, respectively, and four irrigation depth levels include: I1, I2, I3 and I4 corresponding to 50, 75, 100 and 125% of crop water requirement, respectively, for two varieties of winter wheat: Roshan and Ghods, with three replications in an experimental farm of Birjand University for 1384-85 period. Based on results, the mean relative error of the model in yield prediction for Roshan and Ghods were obtained 9.2 and 26.1%, respectively. The maximum error of yield prediction in both of the Roshan and Ghods varieties, were obtained for S1I1, S2I1 and S3I1 treatments. The relative error of Roshan yield prediction for S1I1, S2I1 and S3I1 were calculated 20.0, 28.1 and 26.6%, respectively and for Ghods variety were calculated 61, 94.5 and 99.9%, respectively, that indicated a significant over estimate error under higher water stress. The mean relative error of model for all treatments, in prediction of soil water depletion and electrical conductivity of soil saturation extract, were calculated 7.1 and 5.8%, respectively, that indicated proper accuracy of model in prediction of soil water content and soil salinity

Detection of major weather patterns reduces number of simulations in climate impact studies

With climate change posing a serious threat to food security, there has been an increased interest in simulating its impact on cropping systems. Crop models are useful tools to evaluate strategies for adaptation to future climate; however, the simulation process may be infeasible when dealing with a large number of G × E × M combinations. We proposed that the number of simulations could significantly be reduced by clustering weather data and detecting major weather patterns. Using 5, 10 and 15 clusters (i.e., years representative of each weather pattern), we simulated phenology, cumulative transpiration, heat‐shock‐induced yield loss (heat loss) and grain yield of four Australian cultivars across the Australian wheatbelt over a 30‐year period under current and future climates. A strong correlation (r2≈1) between the proposed method and the benchmark (i.e., simulation of all 30 years without clustering) for phenology suggested that average duration of crop growth phases could be predicted with substantially fewer simulations as accurately as when simulating all 30 seasons. With mean absolute error of 0.64 days for phenology when only five clusters were identified, this method had a deviation considerably lower than the reported deviations of calibrated crop models. Although the proposed method showed higher deviations for traits highly sensitive to temporal climatic variability such as cumulative transpiration, heat loss and grain yield when five clusters were used, significantly strong correlations were achieved when 10 or 15 clusters were identified. Furthermore, this method was highly accurate in reproducing site‐level impact of climate change. Less than 7% of site × general circulation model (GCM) combinations (zero for phenology) showed incorrect predication of the direction (+/−) of climate change impact when only five clusters were identified while the accuracy further increased at the regional level and with more clusters. The proposed method proved promising in predicting selected traits of wheat crops and can reduce number of simulations required to predict crop responses to climate/management scenarios in model‐aided ideotyping and climate impact studies

Laboratory study of the soil clay percent influence on the need for subsurface drainage system envelopes

The necessity of the use of subsurface drainage envelopes (envelopes) is one of the major concerns which are brought up in the first stages of design and construction of a drainage project. Clay percentage of soil is the first index to predict this requirement. In this study, in order for the calculation of gradient ratio (GR) and the assessment of clogging potential and soil particles movement into the drainpipe, the permeameter test was carried out on three samples with clay and clay loam textures. Treatments in this experiment were drainage systems with and w/o envelopes. In system with envelope, two types of envelopes (granular and fiber) were used. Through conducting this experiment, discharge variation, system permeability, gradient ratio and exit gradient were investigated. The results showed that the values of gradient ratio in the systems without envelope in most cases were greater than one which indicates high particle movement potentials. Nevertheless, soil particles movement happened when the values of this index exceeded 3. The ratio of outflow from the systems with mineral and synthetic envelopes to the ones without envelope ranged 2.0-3.5 and 1.4-1.8, respectively. As hydraulic gradient was increased, system hydraulic conductivity decreased in a way that the greater decrease happened in the system without envelope. Furthermore, by the calculation of hydraulic failure gradient and its comparison to exit gradient at different hydraulic gradient values, the resistance of soil particles against flow pressure was analyzed. The results indicated that the system without envelope had the least and the most performance in samples No. 2 and 3, respectively