JWSS - Journal of Water and Soil Science

Due to water use increasing, attention to optimal water resources allocation is needed. In recent decades, the use of intelligent evolutionary methods for optimization of water allocation was focused more by researchers. The aim of this study is to development on water resources planning model that determined the proper cultivation, optimal exploitation of groundwater and surface water resources although water allocation among crops is a way to minimize the adverse effects of dehydration and increase its revenue. In this study, for maximizing profits, estimating crop water requirements at different periods to optimize the management of cropping patterns and irrigation management in cultivation in Varamin irrigation network using a new evolutionary algorithm was called the water cycle. Then for validation of this method is that a new approach and ensure the integrity of its performance Its results are compared with a genetic algorithm model and linear programming as our base (R²=0.9963). The results showed that the area cropping pattern was not optimal and the area under cultivation of crops such as wheat, barley, tomatoes, Bamjan, melon, alfalfa reaches zero and the new paradigm of the largest area under cultivation to industrial goods and then was assigned cucumbers. While our revenues have increased about 11 percent. In addition to amount of water in different months remain in the network that can be used for many that such as injection into underground aquifers or other crops based on the amount of water available.

Identification and investigation of changes in the area under cultivation of various crops seem to be essential for the management supply of crop production. In this study, r to identify and investigate change of the area under cultivation in major crop Hoseynabade Mishmast region in Qom province, we used the time series images of OLI and ETM sensors of landsat 8 and 7satellites, according to the crop calendar of this region. By using the vegetation index (NDVI) in the decision tree algorithm, the thresholds of this index were adjusted according to the major crops of this region; then a map of the cultivation pattern of the crop of this region was prepared. In order to evaluate the results, the statistics of the provinces agricultural jihad were used during 2005, 2009, 2014 and 2019 crop years. The results showed that by using the threshold of NDVI index, crops in this region in 2005 included wheat and barley and alfalfa, and their areas had an error of 17/1 and 6/1 percent in comparison with the statistics of agricultural Jihad, respectively; in 2009, wheat and barley, alfalfa and corn had an error of 0/5, 9/6 and 0/1 percent. Also, in 2014, wheat and barley, alfalfa, corn and sophie crops had an error equal to 4/9, 0.4, 11/4 and 2/4 percent, and the same crops in 2019 had an error 0/04, 11/6, 1/4 and 17/5 percent; that error was not significant. According to the results, the appropriate efficiency NDVI index in estimating crop cultivation area was determined by their phenology. Also, in 2009 and 2014, corn and sophie crops were added to the regions crops, and the area under crops cultivation in 2019 was increased, as compared to 2014.

Due to water scarcity, it is impossible to utilize all irrigated cropland in arid and semi-arid areas. Therefore, dense cultivation with a drip irrigation system that delivers water directly to the plant's root zone is an appropriate choice to enhance water productivity. The objectives of the present study were to compare wheat yield and water productivity under two different water distribution patterns in the drip-tape irrigation system and surface irrigation in full irrigation and deficit irrigation levels. The experimental treatments consist of two irrigation systems (drip-tape (DT), and surface irrigation (SU)), and three different irrigation levels (a full irrigation level (W1), two deficit irrigation levels, the irrigation interval twice, and the same irrigation depth of W1 level (W2), applied half of the irrigation depth of W1 level at the same time (W3)). The SU was implemented in place with 100% efficiency to avoid runoff. The yield in full irrigation level in DT was 5338.4 kg/ha and in SU was 5772.8 kg/ha. Applying deficit irrigation in two irrigation systems has different effects due to various water distribution patterns. In the DT, the most yield reduction was in W2, and in SU was in W3. The highest water productivity in DT was observed in W3 with a 1.44 kg/m3 value. The highest water productivity in SU was observed in W2 with a 1.46 kg/m3 value. For each irrigation system, some type of deficit irrigation management is optimal.