مجله تحقیقات آب و خاک ایران
سال پنجاه و چهارم شماره 8 (پیاپی 92، آبان 1402)

The aim of this research is to predict the effects of future climate change on cotton yield in Birjand region. In this research, the BCM2 general circulation model under two release scenarios B1 and A1B in three periods (2025 to 2050, 2050 to 2075, and 2075 to 2100) was examined to predict future climate conditions and to generate daily climate parameters of the LARS-WG microscale model. Daily climate data obtained from LARS-WG output were used as inputs for DSSAT model (crop simulation model) to simulate cotton growth under future climate. The selection and preparation of a suitable plot of land for the implementation of the project was done in the beginning of October 2018. The intended experimental design was factorial split plots. The DSSAT model provided acceptable results for cotton yield and phenological stages, and this success was confirmed when the values simulated by the model were compared with the data collected from the field experiments. The maximum NRMSE is related to HW simulation, which is calculated as 9.7%. The value of this index for simulating the phenology stages is much lower and its value is reduced to 1.5%. The results of this research show that the DSSAT model can be a promising tool for predicting yield, leaf area, nitrogen accumulation, phenology and biomass of different cotton cultivars and other crops grown in the region. It seems that this study is useful and appropriate for farmers and their making decisions. The results of the simulations showed that due to future climate change and increase in temperature and carbon dioxide concentration in Birjand city, cotton yield will increase. On average, under all scenarios, the average yield of cotton will increase by 15% in the period of 2025 to 2050, by 15.44% in the period of 2050 to 2075 and by 18.15% in the period of 2075 to 2100. The simulation has shown that climate change increased cotton yield (from 14.73 to 18.53 percent) and reduced the length of the cotton growing season. The main reason for the increase in cotton yield can be attributed to the increase in carbon dioxide concentration.

Due to the necessity of regular and rapid evaluation of nitrate, the development of methods with the ability to detect this compound accuratly and simple is important. Nowadays, colorimetric methods have received much attention due to their ability to detect simple and visual. In this study, which was carried out in 2022 with cooperation of Tehran university and the Agricultural Biotechnology Research Institute, a colorimetric method based on etching of gold nanorods for qualitative and quantitative detection of nitrate was presented. the measurement of nitrate ions (after reduction of nitrate to nitrite by zinc powder) at room temperature is possible by changing the size of the plasmonic nanoparticles and subsequently generating measurable signals, including spectral and color changes. Under optimal conditions, a good linear relationship between nitrate concentration and colorimetric response in the range of 0.5 to 3.0 mM (R2=0.995) with a detection limit of 173.3 μM was found. Also, considering that vegetables, especially leafy vegetables, have a high potential in nitrate absorption, in this research cress plant was used as an indicator plant to investigate the efficiency of the sensor in determining the nitrate of leafy plants. Recovery values for nutrient solution and cress tissue samples was in the range of  94.4 to 101.9 and 93.4 to 98.5%, respectively, and relative standard deviation (RSD) for all samples was calculated below 2.1%. As a result, the presented method in this study provides the possibility of monitoring the actual level of nitrate in cress plant samples.

The purpose of this study was to investigate the effect of the depth of application and the discharge of drippers on the distribution of soil salinity in the sugarcane field under subsurface drip irrigation. This research was conducted as a split-plot experiment based on complete random blocks design in four replications. Experimental treatments including two dripper distances on the secondary pipe (including L1: 30 cm with a flow rate of 2.2 L h-1 and L2: 50 cm with a flow rate of 3.8 L h-1) and three dripper placement depths (Including D1: 15 cm, D2: 25 cm and D3: 35 cm). In order to investigate the effect of different treatments on salinity distribution in the soil, soil samples were collected four and six months after the start of subsurface drip irrigation, from the soil around the drippers at different intervals. The results of the salinity distribution pattern showed that under the conditions of subsurface drip irrigation, the highest salinity was observed in the bottom of the furrow and in the upper layer of the soil on the mound. Six months after the start of subsurface drip irrigation, the salinity of the soil profile in all treatments increased compared to the beggining, so that the salinity of the area around the drippers in most of the treatments reached above 3 dS m-1. The highest amount of salinity in the upper soil layers was observed in D3L2 treatment. Also, the most favorable salinity distribution pattern in the root development area was observed in D2L1 treatment. Therefore, it can be concluded that the use of drippers at a depth of 25 cm with intervals of 30 cm and a flow rate of 2.2 L h-1 is more suitable for managing soil salinity in the subsurface drip irrigation system.

One of the strategies of using low-soluble P farctions in the soil is selection and cultivation of plants and varieties with high P uptake efficiency. According to the necessity of P uptake efficiency and effective mechanisms in commercial varieties of sugarcane knowledge, a pot experiment was carried out in greenhouse condition in Hakim Farabi Agro-Industry CO.. The treatments were P fertilizer (including: blank (P0), 125 (P50) and 250 (P100) kg ha-1 as triple superphosphate) and varieties of sugarcane (including: CP57-614, CP69-1062 and CP48-103) in three sampling times (including: 45, 90 and 130 days after planting) with three replications in factorial based on completely randomized design. In this study, P uptake, root length, specific root length, root to shoot ratio and P influx were evaluated at each sampling time. In low available P condition, the CP48 and the CP57 varieties able to uptake more P and then considered as efficient P varieties. However, CP69 has less ability to uptake of P in this condition. In this condition, CP48 variety, P uptake was increased by 13% and 45% compared to CP57 and CP69 varieties respectively. However, CP57 showed enhancement of P uptake up to 29% compared to CP69 variety. Phosphorus influx decreased in CP57 and CP69 varieties by 53% and 67% respectively with aging of sugarcane that the greatest decrease of influx was observed in CP69 variety. In the CP48 variety, P influx increased up to 66%, which can be an effective factor in more P uptake. Therefore, these differences in the ability of P uptake in sugarcane varieties and mechanisms affecting P uptake can improve the management of P fertilizer consumption especially in ratoon.

Due to the upcoming climate threats, challenge of water shortage and its impact on the food security of the growing population in Iran, the optimal use of soil and water resources is very important. With the development of remote sensing technologies, free access to a variety of field data has become widely available, which can be used to reduce the uncertainty of simulation models. The aim of this study was to simulate actual evapotranspiration (ETa) and rice crop coefficients (Kc) during its growth stages using the SWAP model updated with satellite data and evaluate the accuracy of the results with/without updating. This research was conducted at the National Rice Research Institute of Iran in Rasht in the year of 2017. Based on the obtained results, total ETa measured by lysimeter and simulated by SWAP model with and without updating were 395.4, 373.2 and 363.6 mm, respectively. The average crop coefficients during the growth stages of vegetative, reproductive and ripening were estimated as 1.13, 1.49, 1.21, respectively. The crop coefficients for the proposed stages estimated by SWAP model without using satellite data were 1.02, 1.39, 1.04, respectively. After updating with satellite data, the crop coefficients were modified as 1.05, 1.43 and 1.07, respectively. Finally, the statistical analysis indicated that the SWAP model has a reasonable performance in estimation of ETa (RMSE=0.89; EF=0.98; R2=0.74) and rice crop coefficients (RMSE=0.53; EF=0.96; R2=0.63). The results indicate that the SWAP model combined with satellite data improved the accuracy of ETa estimation (RMSE=0.75; EF=0.99; R2=0.86) and rice crop coefficient (RMSE=0.40; EF=0.99; R2=0.74) at field scale.

The rapid, accurate, and low-cost determination of soil properties has particularly important for land planning and management. The objective of this study was to evaluate the Vis-NIR spectral reflectance of soils, as a rapid, cost-effective, and non-destructive technique, for estimating some soil properties [sand, silt, clay, pH, and calcium carbonate equivalent (CCE)] by partial least-square regression (PLSR) and bagging-PLSR methods. For this purpose, a total of 220 composite soil samples were collected from 0-20 cm depth in Ghorveh Plain, Kurdistan province, in September 2019. The selected soil properties were measured by standard laboratory methods. The proximal spectral reflectance of soil samples was also measured within the 350-2500 nm range (Vis-NIR) using a handheld spectroradiometer. Different pre-processing methods were assessed after recording the spectra. The results indicated that the R2 values for the PLSR method ranged from 0.58 to 0.76, while the bagging-PLSR produced R2 values between 0.59 and 0.74. The RMSE values obtained for sand, silt, clay, CCE, and pH were 17.43, 7.65, 7.83, 7.94, and 0.66, respectively for the PLSR, and 16.66, 7.63, 8.13, 7.71, and 0.45 for the bagging-PLSR. Based on the ratio of prediction to deviation (RPD) values, the bagging-PLSR model achieved the best performance in predicting sand and CCE. However, for clay and pH prediction, the PLSR model was the most accurate. Both the PLSR and bagging-PLSR models yielded identical predictions for silt content, with an RPD value of 1.53. Overall, the results showed that PLSR and bagging-PLSR models have acceptable accuracy for estimating the proposed properties of the soils.

Furrow irrigation is one of the most common and suitable methods of surface irrigation that is used in the fields of Mirzakochek Khan Sugarcane Company in the southwest of Khuzestan. Considering the problems that sugarcane companies have recently had due to the water resources scarcity, increasing the efficiency of surface irrigation systems with the aim of reducing water supply from Karun River is necessary. This study was conducted to investigate the effect of slope, furrow length and discharge on water application (Ea) and storage efficiencies (Es) as split-split plots and randomized complete blocks design with three replications from August 2018 to September 2019 in one of the farms of Mirza Kochakh Khan Company. This study was carried out with three treatments, each at three levels, including: slope of 0.02, 0.04 and 0.06%, length of 150, 200 and 250 meters and flow rate of 2, 2.5 and 3 l/s. Ea was obtained between 64.7% and 77.4% and Es between 65.2% and 100%. The highest Ea was corresponded to a slope of 0.04%, a flow rate of 2 l/s and a length of 250 meters. The highest Es was corresponded to the slopes of 0.04 and 0.06%, flow rate of 2 l/s and the length of 250 meters. Consequently, the slope of 0.04%, the flow rate of 2 l/s and the length of 250 meters are sujestted for furrow irrigation system of the sugarcane lands in the south of Ahvaz due to the optimal value of Ea and Es.