نشریه دانش آب و خاک
سال سی و یکم شماره 2 (تابستان 1400)

Accurate estimation of reference evapotranspiration (ETo) is an important issue in agricultural engineering, irrigation scheduling, water resources management, etc. Nowadays, the physics-based Penman-FAO-Monteith model is a standard model of ETo determining as well as calibrating other ETo equations. However, the need for large amount of hydro climatologic data has limited its application, especially in regions without sufficient necessary weather data. The present study aimed at assessing the performance accuracy of empirical temperature/radiation- based ETo models in humid regions and comparing the results with random forest (RF)-based models that used the same input variables of the applied empirical equations. The obtained results showed that the Random forest models gave the most accurate results when compared to the commonly used original and calibrated empirical equations (with similar input variables) with global MAE and SI values of 0.4 and 0.008. Nonetheless, the calibration procedure could not improve the performance accuracy of the equations in some cases.

The concern of the present research was to do a comparative study between the GEP, ANN and ANFIS models to estimate monthly global solar radiation. For this purpose, long-term (24-years) monthly data of global solar radiation (RS, MJ m−2), sunshine hours and air temperature (°C), from Tabriz synoptic station were used. To perform the artificial intelligence models, a new combination of inputs including monthly mean clearness index (KT), monthly temperature range (ΔT), relative sunshine hours (n/N) and extraterrestrial global solar radiation (Ra) were employed. Since the lowest values of MBE and RMSE (0. 13 and 1.97 MJ m−2 respectively) and the highest value of R2 (0.92) were obtained for ANN model, and therefore, the ANN model was selected as the best model to estimate the monthly global solar radiation. Using quarter-quarter (Q-Q) plots revealed that although the ANN model generally presents the best fit for monthly global solar radiation data, this model is found to be not successful in estimating the higher values of monthly global solar radiation data. Therefore, the application of ANN model is recommended for regions with lower solar radiation values. The performance of the ANFIS model was better than other models in covering the highest and lowest values (the first and fourth quarter). Therefore, it can be concluded that the ANFIS model gives more accurate results in the areas with the higher values of solar radiation. The findings also show that unlike previous researches which were carried out in daily scale, the performance of GEP technique for modeling monthly global solar radiation is satisfactory especially in the ranges of 250 to 800 MJ m−2. Thus, it can be inferred that GEP can be more powerful in modeling the phenomena which have low fluctuations or a limited range.

Hydraulic structures situated as an obstacle in front of water flow that changed the flow pattern in their vicinity and causing the local scour around the structure. The scour around the bridge pier is one of the most important phenomena in sediment hydraulics, which creates a hole around the pier and undermines its stability. Different methods have been proposed to prevent or reduce the local scour. In this study, the effects of collars, nanoclay materials and angle of piers have been studied in pier group. The results show that for the pier with the angle of 15 degree was observed the greatest decrease in the depth of the scour hole. Studies show that in the group pier with inclination angle of 15 degrees, there was 14 percent scour hole reduction and with presence of a collar the reduction of scour hole was 86 percent. Also, by using nanoclay materials, the depth of the scour hole in the without collar condition was reduced by 18.5%.

The Bukan plain with its largest wheat production in the province is referred as the West Azerbaijan grain storehouse. Water and soil salinity can cause crop redution. In this research, a computer model of SALTMED was used to simulate wheat yield under different salinity conditions of irrigation water. Field experiments were conducted for five irrigation water treatments with salinities of 3.5, 4.5, 5.5 and 6.5 dS m-1 and a control treatment (Simineh Rood water with 2 dS m-1 salinity) in a completely randomized blocks design. R2, NMRSE, CRM and ME values ​​were calculated at different soil depths for different treatments. The results showed that the SALTMED model had a high accuracy in simulation of the soil moisture and salinity as well as the crop yield. The coefficient of determination for simulating soil moisture was 0.87, soil salinity 0.85 and crop yield 0.92. According to the results, with increasing salinity level of irrigation water, the model accuracy in simulation of the soil moisture was increased, but the model error was decreased in simulating of the crop yield. The simulation results of the SALTMED model showed that the accuracy of the model for crop yields was better than that of soil moisture and for soil moisture was better than that of soil salinity.

Soil water characteristic curve (SWCC) represents the quantative relationship between soil water content and matric suction. Direct measurement of this curve is laborious, time consuming and expensive. Hence, several experimental, mathematical and analytical models have been presented to describe the SWCC. In this research, 11 SWCC models were calibrated using volumetric water content and matric suction data of 27 soil samples of Qorveh-Dehgolan plain agricultural lands. Solver Toolbox in Excel used to calibrate the models and six other soil samples data used for result validation. The R2, RMSE, NRMSE and MBE statistics were used to assess the prediction accuracy of the models. According to the obtained results, for clay and loam textures, Libardi et al and Simmons et al models, for silty clay loam texture, Brooks and Corey model, for clay loam texture, Brooks and Corey and Campbell models, for silty clay texture, Van Genuchten m=1-2/n and Brooks and Corey models and for sandy loam texture, power model were proposed to predict soil water characteristic curve in the soils of the studied lands.

In order to investigate the effect of super absorbent polymer (A200) and manure on reducing drought stress effects in wheat (Triticum aestivum) cultivars, a factorial experiment was carried out based on randomized complete block design with three replications. This study was done at the research field of Agricultural Research Center, West-Azerbaijan (Saatlo) during 2017-2018 cropping seasons. The first factor was irrigation at two levels: normal conditions (irrigation after 75 mm evaporation from class A pan) and drought stress conditions (irrigation after 220 mm evaporation from class A pan). The second factor was super absorbent polymer 200 kg ha-1, manure 40 ton ha-1, their concomitant application and the control (no manure) and the third factor included wheat cultivars (Mihan, Heidari and Zarineh). The results indicated that drought stress, as compared to the normal irrigation reduced grain yield about 32%. Separate and concomitant application of super absorbent polymer and manure in comparison with the control, increased grain yield by 20, 22 and 33%, respectively. Between cultivars, Mihan cultivar for grain yield, 1000-kernel weight, grain per spike and spike per square meter was superior under two different moisture conditions. Application super absorbent polymer and manure with increasing plant access to water and decreasing drought stress led to improved grain yield components including, 1000-kernel weight and grain per spike in wheat different cultivars that cause to increased grain yield. Under optimum irrigation and drought stress conditions, the highest income from grain yield and straw was obtained from the use of manure and Heidari cultivar.

In this study, the new method of self-organized maps (SOM) was used to cluster the piezometers in the Urmia aquifer and identify piezometers with similar behavior, in consequence the optimal groundwater monitoring network was determined. To achieve this goal, at first the normalization of monthly groundwater level data over a period of 13 years (2002-2015) was done and then the K-means non-hierarchical clustering algorithm was used to determine the number of optimal clusters. Then, using the SOM model which is one of the most widely used neural network models in the clustering techniques, spatial preprocessing operations were performed for all piezometers and the clusters were detected using a groundwater depth map. Also, the representative piezometers of each cluster were determined using the piezometers Euclidean distance. According to the results of clustering and its good compatibility with changes in groundwater level at each piezometer, it should be noted that the SOM clustering algorithm has a high capability for clustering. Results show that this type of network is able to detect the appropriate data patterns that can help identify the characteristics of members of each cluster. Therefore, it seems that the SOM clustering algorithm can be used to analyze the quantitative behavior of the aquifer (groundwater level changes) and find a few representative piezometers, thus providing an acceptable assessment of aquifer behavior in a short time and at the lowest cost.

Moisture distribution is one of the most important factors in selecting the suitable irrigation method for a crop. In this study, distribution of soil moisture content in sugarcane subsurface drip irrigation in silty-clay soil, was investigated. The experiments were carried out with drippers having the discharge rate of 1.2 liter per hour, three installation depths of 15, 20 and 30 centimeters (d15, d20, d30), and two spaces of 50 and 60 centimeters (L50 and L60), at three replications. Soil water content sampling during the experiment was performed at the three stages with three horizontal distances of 0, 30 and 60 cm from the drip pipe and at depths of 0-30, 6-30 and 90-60 cm, respectively. Using HYDRUS-2D, moisture distribution around the supply pipes installed at three depths in the condition of 60 cm distance between the drippers, was determined. To evaluate the accuracy of HYDRUS, the moisture content was measured by TDR device at 15 observation points around supply pipe. The moisture content around the supply pipe within the horizontal distance of 60 cm and the vertical distance of 90 cm was within range of wilting point and field capacity. Accuracy of HYDRUS-2D software in simulation of soil moisture around the supply pipe for condition of 60 cm distance between the drippers at the depths of d15, d20, and d30 based on the NRMSE criterion, were in the medium, good and medium range, respectively.

Researches show that one of the most effective factors on bridge destruction is bridge pier scour. That one of the methods used to reduce of scour around bridge piers is installing collar. The collars protect the river bed against vortex flow in the vicinity of the piers. In this research, the role of collar as a control structure of bridge pier scour was investigated along with the effect of its shape. Therefore, dimensions of collar were investigated on bridge pier scour reduction and application diagrams proposed. Results show that increasing dimensions of collars will increase the efficiency of performance comparing of both collars indicated, that collar with dimensions have better performance in reducing scour than collar . Larger collar does prevent sediment movement due to lift vortex in downstream of bridge pier and for this reason. On the other hand, with decreasing roughness at the surfaces collar from 40% to 50%, the reduction of scour increases from 39% to 58%.

The objective of this research was to evaluate the effect of pruning waste compost and plant growth promoting rhizobacteria (PGPR) on some biological properties of calcareous soil, A factorial experiment was carried out in a completely randomized design under greenhouse condition in rhizobox. The factors were as the organic matter (compost, pruning wastes and without organic matter), microbial inoculation (PGPR and no inoculation) and soil (rhizosphere and non-rhizosphere soils). At the end of the growth period of wheat, microbial biomass carbon, microbial biomass phosphorus, microbial respiration, substrate-induced respiration and alkaline phosphatase in the rhizosphere and non-rhizosphere soils were determined. The results showed that the application of compost and inoculation of PGPR significantly increased the microbial biomass carbon, microbial biomass phosphorus and alkaline phosphatase activity compared to non-inoculated treatment. Furthermore, compost treatment increased the microbial biomass carbon, microbial biomass phosphorus and alkaline phosphatase activity in the rhizosphere soil by 1.23, 1.59 and 1.05 times compared to those in the non-rhizosphere soil, respectively. Microbial respiration and substrate-induced respiration in the rhizosphere soil of pruning wastes treatment were 10.55 and 2.23 times higher than those in the non-rhizosphere soil, respectively. It was concluded that application of organic matters and microbial inoculation caused to improvement in soil quality indices.