جستجوی مقالات مرتبط با کلیدواژه « Field water management » در نشریات گروه « آب و خاک »

Saving, optimizing water consumption, and improving productivity and efficiency indicators in agricultural sector are important and necessary. Miandoab region is of particular importance as a model of reducing consumption in order to conserve real water for the restoration of Lake Urmia. This research was conducted to evaluate water consumption reduction scenarios at the farm level using AquaCrop plant model in Miandoab region. For this purpose, the information on farms related to the sustainable agriculture project of Iran's Wetlands Protection Plan in Miandoab region was used. The data from the first year (the crop year 2016-2017) and the second year (the crop year 2017-2018) were used for model calibration and validation, respectively. The evaluation of statistical indicators shows the accuracy and high ability of the model in simulating grain yield. After the calibration and validation of the model, the irrigation planning scenarios were analyzed and evaluated in the form of reducing irrigation depth by 10, 20, and 30% for the conditions of the second year. The results of field measurements in 2017-2018 showed that the average irrigation depth and the applied irrigation (Irrigation + effective precipitation) for wheat were 405.44 and 580.44 mm respectively and mean grain yield was 8340 kg/ha, then irrigation water productivity and applied irrigation productivity were 2.27 and 1.52 kg/ , respectively. Also, the results of the study of deficit irrigation scenarios showed that the S3 scenario (30% irrigation water reduction) will reduce only 10% crop yield and water productivity will increase from 1.53 to 1.72 kg/ . The values of water productivity indices were calculated using balance components and performance simulated by the model for each farm. In general, the results showed that it is possible to increase the grain yield of wheat and water productivity using AquaCrop model for proper and accurate irrigation planning and crop management improvement, in order to save and conserve water on a farm scale.

North Mahyar plain in Isfahan, is one of the plains which has confront water crisis. In these circumstances, attention to the capacity of the resources and proper management is an important issue to pass this condition. Chitsazan et al. (2013) noted that artificial neural network is able to figure out the relation of hydrologic parameter. Also, this tool can be used in water resources management (Coppola et al., 2005). Therefore, by applying artificial neural network, water-table data and cropping pattern in plain, three land-use scenarios were designed. Water table was simulated for water year of 2008 with one-layer network, Levenberg–Marquardt algorithm, and three functions in MATLAB­­_R2012a. Water table map was prepared by using simulated water table in ArcGIS 10.2, and zoning was performed according to the costs of water pumping. Results showed that 61-86 percent of the plain in all three scenarios had medium limitation. Also, using different management in field like fallowing and planting low-water use crops caused 3 and 5 percent increase in acreage of "without limitation" lands, respectively.