Showing 9 results for Hydrus
H. Naghavi, M. Hosseini Nia, Sh. Karimi Googhari, M. Irandost,
Volume 16, Issue 61 (10-2012)
Abstract
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.
M. Moradzadeh, H. Moazed, G. Sayyad,
Volume 16, Issue 62 (3-2013)
Abstract
The objective of this study was to investigate the effect of potassium zeolite on ammonium ion sorption and retention in a saturated sandy loam soil in laboratory conditions with four treatments of 0, 2, 4 and 8 g zeolite per kg soil. The study was conducted as a completely randomized block design. Simulation of ammonium ion leaching was performed using Hydrus-1D model in the soil columns. Ammonium nitrate fertilizer with a concentration of 10g per liter was added to soil columns and then leaching was performed. Results of the study showed that adding potassium zeolite to soil causes reduction in the mobility of ammonium ion and increase in the retention of ammonium in soil. Also, the results of the Convection- Dispersion (CDE) and Mobile- Immobile (MIM) models investigation indicated that the ammonium ion sorption by soil followed the Freundlich isotherm model. Absorption isotherms and diffusion and dispersion coefficients were determined using the inverse modeling technique. Based on the results obtained, optimized values of Freundlich isotherm of model were much less than the observed amounts. This shows that the Hydrus-1D model is not able to predict the ammonium ion mobility in soil macropores, and as a result, reduces greatly the amount of absorption parameters. Because the soil was disturbed, CDE model estimation was closer to the observed values in all four treatments
H. Shekofteh, M. Afyuni, M. A. Hajabbasi, H. Nezamabadi-Pour, F. Abbasi, F. Sheikholeslam,
Volume 18, Issue 70 (3-2015)
Abstract
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.
E. Chavoshi, M. Afyuni, M. A. Hajabbasi,
Volume 19, Issue 72 (8-2015)
Abstract
Transport of fluoride and consumption of groundwater with excess fluoride concentrations poses a health threat to millions of people around the world. The objective of this study was to simulate transport of fluoride (F) using HYDRUS-1D model. The study was conducted in lysimeters at Lavark research station site in Isfahan. The treatments consisted of two concentrations of F (157 and 315 mg kg-1). The duration of the study was 125 days. Some of soil physical and chemical properties, soluble F and total F concentration were determined during the study. The results showed the transport of F in calcareous soil profiles. This may be due to the high pH and desorption of F ion as a result of repulsion by the more negatively charged soil surfaces. The highest concentration of total F and water soluble F were observed in the 10 cm surface soil layer. The concentration of F decreased with increased soil depth. The correlation coefficient was significant between the water soluble fluoride and the total fluoride (1% level). Also, the difference between the observed t- value and a critical value on the t distribution is statistically insignificant. It showed that the model simulated successfully water soluble F concentration in the soil profile.
F. Javadzadeh Shakhali, M. Khaledian, M. Navabian, P. Shahinrokhsar,
Volume 20, Issue 75 (5-2016)
Abstract
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.
N. Khanmohamadi, S. Besharat,
Volume 20, Issue 77 (11-2016)
Abstract
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.
M. Golabi, M. Albaji, A. Naseri,
Volume 21, Issue 3 (11-2017)
Abstract
In the present study Hydrus-1D software was used to simulate electrical conductivity, pH and sodium, potassium, calcium, magnesium, chloride and sulfate ions. Field experiments were performed at the Sugarcane Research Center located in south of Ahvaz on sugarcane varieties CP48-103 with four water treatments (one treatment was Karun river water and three treatments were diluted drainage water) and three replications. The samples were collected from 0-30, 30-60 and 60-90 cm soil depth before irrigation and electrical conductivity and anions and cations of soil were measured in the laboratory. Sensitivity analysis and calibration were first performed with the aim of verifying the Hydrus-1D software. The sensitivity analysis indicated that the software had maximum sensitivity to the saturated volumetric water content. Minimum sensitivity was for the inverse of the air-entry suction, tortuosity parameter, residual volumetric water contents and moderate sensitivity was for hydraulic conductivity at natural saturation. Also, the software did not show any sensitivity to empirical parameter related to the pore size distribution that is reflected in the slope of water retention curve. In calibration stage the amount of hydraulic conductivity at natural saturation, residual volumetric water contents, saturation volumetric water contents, the inverse of the air-entry suction, empirical parameter related to the pore size distribution and tortuosity were obtained as 18 (cm/day), 0.04 (cm3/cm3), 0.63(cm3/cm3), 0.012 (cm-1), 1.2 and 0.6 respectively. The results showed that the coefficient of determination of all parameters was more than 0.85 which confirms the appropriate capabilities of the model in simulation of electrical conductivity, pH, anions and cations. In the modeling carried out the amount of NRMSE was between 11 and 18 percent which indicates good performance of the model. The Nash-Sutcliffe efficiency criterion was obtained 0.72 to 0.8 that indicates a good match of the model with reality. The coefficient of residual mass in this paper was positive for electrical conductivity, pH and sodium, potassium, calcium, magnesium and negative for chloride and sulfate. The positive and negative coefficient of the residual mass shows less and over estimation of the model.
A. Khorsand, M. Bazaneh, S. Besharat, K. Zeynalzadeh,
Volume 22, Issue 4 (3-2019)
Abstract
Subsurface drip irrigation systems, compared to other irrigation systems (basin and furrow), enhance the delivery of water and nutrients directly into the root zone. The purposes of this study were to determine wetting front advancement in a subsurface drip irrigation and to compare the results with the HYDRUS 2D model simulation. In this study, the irrigation using T-Tape was carried out on a sandy-loam soil by two emitters at different irrigation times. The Wet moisture meter device was used to determine the soil water content. Evaluation of the simulated and measured soil water content was performed by using the adjusted determination coefficient (R2), relative error (RE), and the normalized root mean square error (NRMSE). Based on the results, the NRMSE of soil water content prediction for the emitters at the depths of 20 and 40 cm was calculated to be in the range of 10 to 19 and 10 to 13 percent, respectively. Also, RE for the emitters at depths of 20 and 40 cm was in the range of -16 to -5 and 8 to 11 percent, respectively. The average R2 for the emitters at depths of 20 and 40 cm was calculated to be 0.87 and 0.98, respectively. Also, five scenarios (F1, F2, T1, T2 and S1) were evaluated to assess the amount of water stored in the soil profile and water mass balance. The results indicated that the model could be used to predict the soil water content subsurface drip irrigation.
F. Ansari Samani, S. H. Tabatabaei, F. Abbasi, E. Alaei,
Volume 23, Issue 3 (12-2019)
Abstract
Simulation of water and salt transfer in soil is very effective in managing optimal water and fertilizer use in the field. In this study, the HYDRUS-1D model was used to simulate the transfer of water and bromide in a laboratory column of soil with clay loam texture. Soil hydraulic parameters (including air entry point) α, (saturated hydraulic conductivity) ks, (residual moisture content) θr (saturation moisture content) θs, (pore and particle joint parameter) l (parameter of moisture curve shape) n through measurement and using Retc software was obtained Solubility transfer parameters including difiusion coefficient and actual velocity were estimated using soil hydraulic parameters and bromide concentration data by reverse modeling method. According to the target coefficients, the sensitivity analysis of the physical model was performed .The results showed that the correlation coefficient of observation and simulation bromide concentration in optimal mode was 0.84%. accordingly, the diffusion coefficient was estimated to be 4.9 cm. based on the results of the sensitivity analysis, the saturation hydraulic conductivity had the greatest effect on the variation of this parameter, so that the amount sensitivity coefficient of this parameter was 2.64 The RMSE coefficient with a value of 0.04 was the lowest and ME coefficient with the value of -0.0001 had the most parameter variations.
