JWSS - Journal of Water and Soil Science

Today, one of the biggest challenges facing the world is the lack of water, especially in the agricultural sector. In this research, we investigated the effects of irrigation method and deficit irrigation with the urban refined effluent on biomass, grain yield, yield components and water use efficiency in single grain crosses 704 maize. This research was carried out in a randomized complete block design with two irrigation systems (furrow irrigation (F) and drip irrigation (T)) and three levels of deficit irrigation treatments of 100 (D₁), 75 (D₂) and 55 (D₃) percent of water requirements in three replications, in 2017, at the collage of Abourihan Research field, University of Tehran, in Pakdasht County. The results showed that the highest yield of biomass was 2.426 Kg m^-2 for full drip irrigation treatments; also, there was no significant difference between D₁ and D₂ treatments. The highest grain yield was 1.240 kg m^-2 for the complete drip irrigation treatment. The highest biomass water use efficiency was obtained for the treatment of 75% drip irrigation, which was equal to 5.3 kg per cubic meter of water. Therefore, a drip irrigation system with 75% water requirement is optimal and could be recommended.

Optimal use of water resources seem to be necessary due to climate change and the recent drought conditions. One of the most important and effective management strategies is increasing water productivity in agriculture. Irrigation method and the use of different levels of nitrogen fertilizer are the effective factors in increasing the water productivity. Therefore, this study was conducted to investigate the effect of the irrigation method and nitrogen fertilizer on the harvest index and water productivity of two wheat cultivars with 36 treatments as a split-split plot based on a completely randomized design with three replications in the research farm of Natural Resources and Agricultural Research Center of Kashmar, during the 2018-2019 time period. The treatments were two irrigation methods including end blocked border and drip irrigation (tape) as  the main plots, three levels of the nitrogen fertilizer from urea source including 0, 50 and 100 kg/ha as the  sub plots and two cultivars of wheat including Pishgam and Sirvan as the sub-sub plots. The results showed that by changing the border irrigation method to the drip irrigation (tape) method, the harvest index and water productivity were increasesignificantly. The results also showed that grain yield and its components, including harvest index and water productivity, had no significant difference in 50 and 100 kg/ha nitrogen levels. On the other hand, grain yield and its components, harvest index and water productivity, were significantly higher in the Sirvan cultivar rather than the Pishgam one (P<0.01). According to the results obtained from this study, the drip irrigation method, 50 kg/ha nitrogen level and Sirvan cultivar could be recommended for the study region. 

In areas with high rainfall distribution, proper irrigation management, including complementary irrigation, is one of the effective strategies to increase crop production. In order to investigate the effect of supplementary irrigation in different growth stages on the yield and water productivity of Autumn rapeseed, an experiment in the form of a complete randomized block design with five irrigation management treatments including rainfed (I1), single irrigation at flowering stage (I2), single Irrigation at pod filling stage (I3), two irrigation at pod filling stage and flowering (I4), three irrigation at flowering,  and pod filling and grain Filling stages (I5) was carried out at Lorestan University Research Field. Results showed that there was a significant difference between the effects of different irrigation treatments at 1% level. The lowest grain yield, biological yield and oil yield were obtained in I1 treatment with 44.62%, 50.95% and 53.58% decrease, as compared to I5 treatment. The results also showed that by applying irrigation at pod filling stage, grain yield and oil yield were increased by 13.22% and 20.23%, as compared to I1 treatment. The highest total productivity for the grain yield and oil yield was obtained in I5 treatment with 0.252 and 0.073 kg / m3. In general, due to the fact that drought stress in rapeseed calving stages reduces yield, the higher the number of irrigations in rapeseed calving stages, the more the yield.

Crop models evaluationin agriculture has been done by researchers. It helps them to determine the most appropriate crop model for the planning and simulation of crop response in different areas. Using can lead time and cost saving, helping to evaluate the effects of different situations on the crops yield, biomass and water use efficiency (WUE). Given the importance of the subject, this study was conducted for the accuracy and efficiency evaluation of AqauCrop and SWAP under three irrigation types (D: sprinkler irrigation with saline water, F: sprinkler irrigation with saline and fresh water, and S: surface irrigation) and five water qualities (S1: 2.5, S2: 3.2, S3: 3.9, S4: 4.6 and S5: 5.1 dS.m^-1). NRMSE results showed that the accuracy of AquaCrop for the simulation of yield, biomass and WUE was 0.07, 0.09 and 0.07, respectively. For SWAP, these were 0.12, 0.04 and 0.13, respectively. According to EF, AquaCrop results for above-mentioned parameters were 0.60, 0.90 and -4.4, and SWAP results were 0.74, 0.73 and -2.0, respectively. So, AquaCrop accuracy and efficiency were better than those of SWAP for the simulation of corn yield and biomass.

The effective use of rainwater is a key issue in agricultural development in arid and semi-arid regions. The tillage system as an important soil management measure can affect the rainwater retention, soil moisture content, and in consequence crop yield in rainfed lands. This study was conducted to evaluate the effects of slope gradient and tillage direction on rainwater use efficiency (RWUE) in rainfed lands in Zanjan Province. The field experiment was performed in five slope gradients (12.6, 15.3, 17, 19.4, and 22%) and two tillage directions (along slope and on contour tillage) at two replications. Mass soil water content was determined at 5-day intervals and runoff was measured after rainfalls. Wheat grain yield was determined for each plot and RWUE was computed using the proportion of wheat grain yield and precipitation. Base on the results, runoff, soil moisture, wheat grain yield, and RWUE were affected by tillage directions, so that runoff in contour line tillage decreased about 6.4 times compared to along slope tillage and in consequence increased soil moisture, wheat grain yield, and RWUE about 8.7, 24.8, and 24.8%, respectively. Increasing runoff production in contour line tillage at steeper slopes was associated with a lower capacity of cultivated furrows that strongly declined soil water retention and negatively affected wheat grain yield and RWUE in the lands. This study revealed that the efficiency of the contour tillage in water retention and RWUE decreases in steeper slopes in rainfed lands.

In the present study, a model was developed using a system dynamics approach to simulate and optimize the profitability of crops of the Jofeyr (Isargaran) Irrigation and Drainage Network located in Khuzestan Province. To validate the results, the statistical indicators of root mean square error (RMSE), standard error (SE), mean biased error (MBE), and determination coefficient (R²) were used. To validate the simulation results of the benefit-cost ratio, the values of these indicators were obtained 0.25, 0.19, 0.005, and 0.96, respectively. Then, to determine the optimal cultivated area of the network and increase the profitability, the cropping pattern was determined both non-stepwise and stepwise in 2013 to 2017 cropping years. In the non-stepwise, the cultivated area of each crop changed from zero to 2 times of current situation. In stepwise, due to social and cultural conditions of inhabitants, this change was slow and 10% of the current situation every year. The analysis of the results showed the success of the model in optimizing and achieving the desired goals and the total benefit-cost ratio increased in all years both non-stepwise and stepwise. For example, in 2017 compared to 2016, production costs decreased by 7.1 percent and sales prices increased by 5.8 percent, and increased the benefit-cost in 2017 compared to the previous year. The results showed that the present model has good accuracy in simulating and optimizing the irrigation network, its cropping pattern, and defining other scenarios.

In precision agriculture, a productivity rating system is a significant tool to quantitatively assess soil quality. An experiment was conducted in Bilavar, Kermanshah to evaluate the spatial variability of physical indicators of soil quality of a rapeseed (Brassica napus) field. Spatial variability analysis of soil physical properties measured on a rectangular grid (100 m×100 m) was carried out using a geostatistical analyst extension of Arc-GIS software. Five physical soil quality indicators including bulk density (BD), non-capillary porosity (NCP), field saturated hydraulic conductivity (Ks), available water retention capacity (AWC), and organic carbon (OC) were determined. The physical rating index (PRI) at each sampling point was determined by multiplying the rating values for all five parameters. Results revealed that major ranges of semivariogram for Ks and AWC varied between 137-145 m and for BD, OC, and NCP they were relatively long (161-205 m). Clay and NCP showed moderate spatial dependence (0.68 and 0.28, respectively) whereas the rest of the parameters showed weak spatial dependence. Also, the correlation between PRI and the biological yield of rapeseed was fairly good (R²=0.68). Investigation of zoning maps of soil physical properties showed an increase in BD and a decrease in AWC and NCP parameters depending on changes in soil texture and organic matter content in some parts of the field. In general, the PRI index is an important tool in the quantitative assessment of soil physical conditions, and based on it and zoning maps can improve the physical quality of soil in agricultural fields.

The agricultural sector depends largely upon water and energy resources to fulfill sufficient water for producing adequate food for the rapidly growing world’s population. It requires great effort to improve water and energy productivity for agricultural products to provide consumers’ health as well as environmental protection. In this study, the volume of irrigated water, crop yield, water productivity, and the consumed energy for onion crops irrigated with sprinkler or surface irrigation methods under farmer management were measured and compared. The measurements were recorded from 2020 to 2021, on 17 farms across Esfahan Province where onion was a main crop in the region. The measured data from the foregoing two irrigation methods were statistically analyzed using t-test and Pearson correlation coefficients. The outcomes revealed that the volume of irrigated water as well as crop yield was greater for surface irrigation method compared to sprinkler irrigation, and the differences were statistically significant. Moreover, water productivity for onions irrigated with a sprinkler irrigation system was significantly higher (p<0.01) in comparison with onions irrigated with the surface method. In addition, the results indicated a significantly direct correlation between the volume of irrigated water and onion yield, whereas a significantly indirect correlation was observed between the volume of irrigated water and water productivity. A significantly inverse correlation was found between the productivity of energy for irrigation and energy consumption; so, an increase in the energy for irrigation resulted in a decrease in energy productivity. Based on the results of this study, the sprinkler method is more effective than the surface for irrigation of onion.

Evapotranspiration variations (ET₀) were investigated and analyzed using Minitab16 software for the 2010-2019 period using the Nizab system's data in Yazd province, and then ET₀ was predicted until 2027. Based on the results, the increase of ET₀ in cities of Yazd province was affected by the enhancement in wind speed and weather temperature, and the decrease in relative humidity from 2010 to 2019. To determine the appropriate model, Ardakan, Abarkooh, and Taft cities were selected as a representative in each climatic group, and ET₀ data for the years 2010 to 2015 were considered as the input data of the software and ET₀ data for the years from 2016 to 2019 were used to validate the determined model. The prediction of the determined models showed an increasing trend of ET₀ for cold seasons in Ardakan and Abarkoh by 2027. Also, the model prediction showed a decreasing trend of ET₀ for hot seasons in Taft by 2027. Also, the ET0 will not change significantly in cold seasons. In Abarkoh and Ardakan cities, autumn-spring crops such as wheat and in Taft city, spring-summer crops such as sunflower will be more affected by ET₀ variations.