JWSS - Journal of Water and Soil Science

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Knowing about the way water is distributed in the soil is essential for designing and managing the Subsurface Drip Irrigation systems (SDI). Since carrying out experiments to recognize the form of moisture distribution in the soil is too complicated and time-consuming, using numerical simulations can be an efficient, effective substitute method to design these systems. One of these models is HYDRUS-2D, which is able to simulate the movement of water, heat and solute in saturated and unsaturated conditions in soil. This research aims to figure out the extent to which the HYDRUS-2D model is able to estimate wetting pattern in soil around a dripper. The simulations’ findings were compared to the data gathered from the field, including SDI system in different irrigation times, and 72 hours after irrigation. Moreover, the rates of error were measured for all points and distances from the dripper in all times of irrigation and also beyond that. The results indicated that the model can simulate the changes, trend similar to what happened in the soil profile. However, it estimated the rate of soil moisture with higher errors in those points in which the wetting took place, with the maximum error rate being RMSE= 0.05 per every 1.5 hours after irrigation starting point in the depth of 30 centimeters where dripper is placed. Also, with an increase in the irrigation time, and soil moisture evening which resulted from redistribution of moisture, the model resulted in better estimations. 72 hours after finishing the irrigation, the estimates were closer to real figures with an average error estimate of RMSE= 0.002.

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The conventional application of nitrogen fertilizers via irrigation is likely to be responsible for the increased nitrate concentration in groundwater of areas dominated by irrigated agriculture. This requires appropriate water and nutrient management to minimize groundwater pollution and to maximize nutrient use efficiency and production. To fulfill these requirements, drip fertigation is an important alternative. Design and operation of drip fertigation system requires understanding of nutrient leaching behavior in cases of shallow rooted crops such as potatoes, which cannot extract nutrient from lower soil depth. This study deals with neuro-fuzzy modeling of nitrate leaching from a potato field under a drip fertigation system. In the first part of the study, a two-dimensional solute transport model (HYDRUS-2D) was used to simulate nitrate leaching from a sandy soil with varying emitter discharge rates and various amounts of fertilizer. The results from the modeling were used to train and validate an adaptive network-based fuzzy inference system (ANFIS) in order to estimate nitrate leaching. Radii of clusters in ANFIS were tuned and optimized by genetic algorithm. Relative mean absolute error percentage (RMAEP) and correlation coefficient (R) between measured and obtained data from HYDRUS were 0.64 and 0.99, respectively. Results showed that ANFIS can accurately predict nitrate leaching in soil. The proposed methodology can be used to reduce the effect of uncertainties in relation to field data.

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Soil moisture is one of the main input parameters in many models for monitoring and predicting crop yield. The ability of mathematical models has allowed correct application of brackish water and selection of management options. The purpose of this research was to evaluate the performance of HYDRUS-2D for simulating soil volumetric water content in a heterogeneous heavy soil under field conditions. Three volumes of irrigation water (10, 15 and 20 L) and three salinity levels of irrigation water (1.279, 2.5 and 5 dSm^-1) were exerted in a linear drip irrigation system with three replications. In order to check the amount of soil volumetric water content, soil profiles were drilled to 40 cm depth and vertical wall of drip irrigation line was networked. Soil volumetric water content was measured with a TDR MiniTrase kit 6050X3K1B model. The observed soil moisture values were compared with the simulated ones using statistical indices (i.e. nRMSE and CRM).  The results indicated that mean soil volumetric water content distribution in irrigation water with different levels of salinities was in the range of field capacity. The range of nRMSE values varied from 0.91 to 2.07 percent in different replications. According to calculated nRMSE values, performance of the simulation model, was ranked as excellent for simulation of soil volumetric water content. Range of CRM values was shown to be from -0.0080 to 0.0170 that was really low. Results of these two statistics indicate high ability of the model in simulating soil volumetric water content using estimating hydraulic parameters by inverse solution.

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Accurate design of drip irrigation systems requires sufficient understanding of horizontally and vertically distribution of water flow in soil and modeling the wetting pattern dimensions created under the drip source. Field and laboratory activities are not suitable for this purpose considering their time and financial constraints and it is necessary to apply accurate software for determination of several equations in different situations. This research aimed to present simple models for calculation of wetting pattern dimensions in different discharges and structures in drip irrigation system. For this purpose, HYDRUS-2D model was implemented for four discharges in the same soil texture and different soil textures in the same discharge. The values obtained from running the software such as depth and maximum diameter of wetting pattern have been fitted with time values and corresponding equations were obtained. The results of statistical indices for all obtained equations (R>0.96, RMSE<2.12 and MAD<1.38) represent suitable accuracy of corresponding equations in determination of pattern dimensions under the drip source. The results also showed that Loamy Sand and Silt textures, respectively, have maximum and minimum depth and wetting pattern diameter.