Investigating the performance of the differential evolution algorithm in estimating soil hydraulic parameters Abbas Khashei siuki, Samaneh Etminan, Ali Shahidi, Mohsen Pourreza Bilondi, Vahidreza Jalali Water and Soil Management and Modeling, 2024 Introduction The soil water curve is one of the most critical soil hydraulic characteristics. This characteristic is used to determine soil water in the field capacity point and the permanent wilting point (PWP) beside it has a vital role in the application of soil water models in the study of soil-plant-water relationships. This curve is known as the quality soil index which has an effective role in the explanation of agricultural, ecological, and environmental problems. Impressive and efficient management of soil and water resources, water flow and solute transport survey, soil pollution, and contaminant leakage into water sources are dependent upon the accurate estimation of soil water curve parameters. Moreover, this index has a functional role in applying numerical and hydrological models. On the other hand, to better identify and understand its role, different models were provided to describe this curve mathematically. The efficiency of these models depended on the accuracy of estimated parameters in the model structure that was defined. Soil water curve is known as a non-linear relationship that is used to describe the relation between soil and water content or degree of soil saturation. The soil water curve provides essential information for using irrigation methods and about soil resistance and soil mechanical properties. In this research, the performance trend of two meta-heuristic algorithms, including the differential evolution (DE) and particle swarm optimization (PSO), was studied to estimate hydraulic parameters of soil water curves based on the van Genuchten and the Brooks and Cory models in four soil texture classes; loam, silt loam, sandy loam, and sandy clay loam. Besides, this study evaluated the performance of the meta-heuristic algorithm to RETC software. This software has a non-linear square local algorithm. This study can evaluate the ability of the meta-heuristic algorithms to estimate parameters for exponential relationships and nonlinear models. Materials and Methods At the agricultural farm of the University of Birjand, a study was conducted to analyze soil water content in different texture classes. The research involved the random selection of four soil texture classes and the random sampling of 20 points from each class. The soil water content was measured using a sandbox and pressure plate device, covering a broad suction range of 0-15000 cm. In the first phase, soil water curve parameters were estimated for each soil texture using the van Genuchten model and the Brooks and Cory model in the RETC software. Subsequently, the Matlab desktop environment was utilized to apply meta-heuristic algorithms (DE and PSO) to estimate the soil water curve parameters based on the two models. An objective function was defined to minimize the Root Mean Square Error (RMSE) of the meta-heuristic algorithms' performance. Finally, the study compared the performance of the meta-heuristic algorithms (DE and PSO) with the RETC software in estimating soil water curve parameters based on the van Genuchten and Brooks and Cory models, using statistical indices such as RMSE and R2. The soil texture classes play a crucial role in influencing soil water content and nutrient retention, making them an essential factor in agricultural management and crop suitability. The study's findings can contribute to a better understanding of soil water dynamics and the development of improved agricultural practices. Results and Discussion The obtained results of the statistical indices (RMSE and R2) showed that the least value of RMSE was acquired by the differential evolution algorithm (DE) performance. The values of RMSE during the application of the DE algorithm as an estimated method based on the van Genuchten model were 0.0008, 0.0005,0.0004, and 0.0006 also based on the Brooks and Cory were 0.006, 0.006, 0.005, and 0.0005 in sandy clay loam, sandy loam, loam, and silt loam respectively. Also, the highest value of the R2 index was obtained equal to 0.995, 0.996, 0.994, and 0.994 by the utilization of the DE algorithm based on the van Genuchten model in the sandy clay loam, sandy loam, loam, and silt loam respectively. The values of RMSE by the utilization of the PSO algorithm based on the van Genuchten model were 0.0021, 0.006, 0.0057, and 0.006 in the sandy clay loam, sandy loam, loam, and silt loam classes respectively. The highest and lowest values of the RMSE and R2 indices by the application of RETC software were obtained equal to 0.017 and 0.912 (sandy clay loam), 0.01and 0.963 (sandy loam), 0.085 and 0.972 (loam), and 0.01 and 0.924 (silt loam) based on the van Genuchten model. Conclusion It could be concluded that RETC software has poor performance in the estimation of soil water curve parameters in all soil texture classes studied based on the van Genuchten and Brooks and Cory models. This trend represents the weakness of the local algorithms to solve multivariable problems where an exponential relationship exists between the variables and they are influenced by each other. On the other hand, the results show the meta-heuristic algorithms have sufficient ability to estimate parameters in multivariable problems. It could be concluded that the meta-heuristic algorithms have better performance in estimating the parameters of soil hydraulic models. The DE algorithm is the best method to estimate soil hydraulic parameters. The PSO algorithm has the nearest performance to the DE algorithm but the best performance to RETC. Finally, meta-heuristic algorithms are suitable options for estimating soil water curve parameters based on various hydraulic models.
Assessing the hydraulic parameter’s uncertainty of the HYDRUS model using DREAM method Samaneh Etminan, Vahidreza Jalali, Majid Mahmodabadi, Abbas Khashei-Siuki, Mohsen Pourreza Bilondi Water and Soil Management and Modeling, 2023 IntroductionThe accuracy and efficiency of the analytical and numerical models to describe water flow in soil, in unsaturated environments are affected by input data uncertainty, model structure uncertainty, and hydraulic required parameters by the model. Parameter uncertainty has an impact on the model simulation by displaying uncertainty in the simulation results. Hence, the quantitative assessment of the parameter uncertainty and its influence on the model simulation is important in reducing simulation uncertainty. The Bayesian method is a common method for uncertainty analysis that has widespread application in science and engineering to reconcile the concepts of model structure with data (assimilation of input and model outputs, and inference of the parameters). Therefore, a Markov chain Monte Carlo (MCMC) algorithm based on the Bayesian inference to improve the computational efficiency of the analysis was used. The DREAM algorithm is one of the adaptive methods, the Markov chain sampling method which is known as an effective method in used soil-water models due to searching in vast space and solving complex models with a large number of variables. In addition, one of the main problems in using Bayesian inference for hydrological models is their nonlinear relations and using them in heterogenic conditions, DREAM algorithm has been developed to use Bayesian analysis in soil-water problems. Hence, this study has taken the efficiency of the DREAM algorithm as a global optimization method and convergence parser in sampling chain paths and posterior distribution of parameters. The HYDRUS model is a hydraulic model to study the soil-water processes that include nonlinear equations. In addition, center pivot irrigation is a modern method of water management that need to study using hydraulic models under various conditions. Hence, the main purpose of this article is assessment the role of the management method and environmental prevailing conditions in the uncertainty of hydraulic parameters and model structure in estimating water flow under a center pivot irrigation system in four-year alfalfa cultivation. Materials and MethodsThe profile was dug at 120 cm depth. The soil profile was divided into three layers and two soil texture classes. The physical-chemical soil properties were studied in each layer. Assessment of soil properties stated that exists a heterogeneous layer in this soil profile. TDR was used to measure soil water content before, after, and during every irrigation period. Soil water content was measured from 10 June to 11 September 2018 consecutively. The van Genuchten-Mualem equation was used to estimate soil hydraulic parameters and describe water flow in the HYDRUS model. The HYDRUS model is coupled with the DREAM algorithm to evaluate parameter uncertainty and the model structure uncertainty based on measured soil water content data using TDR in every three categorized layers. In this article the p-factor, d-factor, and S and T indices were used to evaluate parameter uncertainty, the model structure uncertainty, and model performance. Results and DiscussionThe qualitative evaluation of soil hydraulic parameters was compiled by the posterior distributions of parameters in every three depths. The parameters had a normal distribution, the model could be recognized the value of parameters, whereas the parameters didn't have a normal distribution and had high uncertainty. The “α” parameter had high uncertainty in every three depths, in other words, in two soil texture classes, this parameter compared to other parameters had high uncertainty. Along heterogeneous soil profiles, the "α", "θs", and "n" parameters were shown high uncertainty to the Hydraulic conductivity parameter of soil saturation. The value of p-factor and d-factor were obtained equal to 83.6 and 0.13 on the soil surface and 10 and 0.14 on the subsurface soil. Reducing the p-factor index in the lower soil layers explained the overlap between measured soil water content points with estimated soil water content. So, along the soil profile could be observed high uncertainty of soil hydraulic parameters under center pivot irrigation. On the other hand, increasing the d-factor index in the sub-surface soil stated increased confidence intervals which indicate the model structure uncertainty and the poor performance of the HYDRUS model in heterogenic conditions. Also, the value of two indices of S and T were obtained 0.3 and 0.76 for the surface layer and 0.88 and 1.4 in the lower soil layers respectively. The values of S and T indices stated the ability of the DREAM algorithm to reduce parameter uncertainty and the model structure uncertainty in soil surface whereas the trend of changes in the two indices explained Asymmetry of the confidence interval with respect to the measured points and the pre-estimation of the model in the lower soil layers. Therefore, the trend of the d-factor, S and T indices showed the influence of the mathematical-physics concepts in the HYDRUS model structure in the heterogenic layer and unsaturated conditions. The research results stated the ability of the HYDRUS model in describing water flow under center pivot irrigation as a novel method of managing water sources, especially in arid and semi-arid areas. Even though, the results of the assessment indices showed decreasing model performance in the lower soil layers. Conclusion The results of soil profile indicated the effect of parameter uncertainty and the model structure uncertainty in soil moisture estimation affected by management and environmental conditions. In addition, the results showed the ability of the DREAM algorithm to simultaneously evaluate the uncertainty of the parameters and the model structure in order to increase the accuracy of the HYDRUS model under the applied conditions. Also, in this study, the DREAM algorithm indicated the role of the heterogeneous layer in parameter uncertainty and its effect on the accuracy of the model performance. The DREAM algorithm is a practical and management option to evaluate the HYDRUS model during the application of the center pivot irrigation method at the farm level. So, this is an appropriate option to study the efficiency of the HYDRUS model using modern methods in agricultural practices. Moreover, to survey the efficiency of hydraulic models under the prevailing conditions could be used the ability of the DREAM algorithm based on the Markov chain.
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Conservation of water resources through the use of unconventional resources in irrigation; Simulation perspective VJ S. Etminan 3rd International Youth Forum on Soil and Water Conservation , 2021 2021.0
Trend of soil nitrate changes under irrigation with treated municipal wastewater V Etminan, S, and Jalali 3rd international Congress on Water Desalination: Application of Advanced … , 2021 2021.0
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Estimating soil hydraulic conductivity using different data-driven models of ANN, GMDH and GMDH-HS K Qaderi, V Jalali, S Etminan, M Masoumi Shahr-babak, M Homaee Paddy and Water Environment 16 (4), 823-833 , 2018 2018.0 Citations: 9
Soil organic matter spatial variation assessment based on the geostatistical models V Jalali, S Etminan GlobalSoilMap-Digital Soil Mapping from Country to Globe, 127-130 , 2017 2017.0
نقش خصوصيات خاک با مواد مادري متفاوت بر پايداري خاکدانه در حوضه شصت کلاته استان گلستان اطمينان سمانه, كياني فرشاد, خرمالي فرهاد, حبشي هاشم مجله الكترونيك مديريت خاك و توليد پايدار 1 (2), 39-59 , 0
MOST CITED SCHOLAR PUBLICATIONS
Assessing an efficient hybrid of Monte Carlo technique (GSA-GLUE) in uncertainty and sensitivity analysis of vanGenuchten soil moisture characteristics curve S Etminan, V Jalali, M Mahmoodabadi, AK Siuki, MP Bilondi Computational Geosciences 25 (1), 503-514 , 2021 2021.0 Citations: 9
Estimating soil hydraulic conductivity using different data-driven models of ANN, GMDH and GMDH-HS K Qaderi, V Jalali, S Etminan, M Masoumi Shahr-babak, M Homaee Paddy and Water Environment 16 (4), 823-833 , 2018 2018.0 Citations: 9
Assessing the hydraulic parameter’s uncertainty of the HYDRUS model using DREAM method S Etminan, V Jalali, M Mahmodabadi, A Khashei-Siuki, ... Water and Soil Management and Modelling 3 (4), 1-15 , 2022 2022.0 Citations: 6
Effect of application of wastewater treatment on soil chemical and physical properties under millet cultivation A Khashei Siuki, MH SayariZohan, A Shahidi, S Etminan International Journal of Environmental Science and Technology 20 (11), 11851 … , 2023 2023.0 Citations: 5
GLUE algorithm capability in estimating the van Genuchten soil–water characteristic parameters and their uncertainties S Etminan, V Jalali, M Mahmoodabadi, A Khashei Siuki, ... Paddy and Water Environment 20 (2), 227-239 , 2022 2022.0 Citations: 5
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Assessing an efficient hybrid of Monte Carlo technique (GSA-GLUE) in Uncertainty and Sensitivity Analysis of vanGenuchten Soil Moisture Characteristics Curve E Samaneh, J Vahidreza, M Majid, BM Pourreza Computational Geosciences 25 (1), 503-514 , 2021 2021.0 Citations: 1
Investigating the effects of deficit irrigation by using purified urban wastewater on the yield and physiological characteristics of millet A Khashei Siuki, M Sayari, A Shahidi, S Etminan Irrigation and Water Engineering 11 (2), 238-249 , 2020 2020.0 Citations: 1
Study of Water Flow and Nitrate Transport under Center Pivot Irrigation Using the HYDRUS-3D Model S Etminan, V Jalali كﺎﺧ و بآ, 259 , 2025 2025.0
Simulation of Soil Nitrate Transport Process under Center Pivot Irrigation Using the HYDRUS-PSO Optimizer Model S Etminan, V Jalali, M Mamodabadi, A Khashie Siuki Iranian Water Research Journal 17 (3), e11513 , 2023 2023.0
Conservation of water resources through the use of unconventional resources in irrigation; Simulation perspective VJ S. Etminan 3rd International Youth Forum on Soil and Water Conservation , 2021 2021.0
Trend of soil nitrate changes under irrigation with treated municipal wastewater V Etminan, S, and Jalali 3rd international Congress on Water Desalination: Application of Advanced … , 2021 2021.0
Application of GLUE method to estimate uncertainty of alpha and n parameters in soil moisture characteristic curve VR Jalali, S Etminan, M Mahmoodabadi, A Khashei-Siuki, ... Journal of Water and Soil Conservation 27 (1), 197-211 , 2020 2020.0
کاربرد روش GLUEدر برآورد عدم قطعیت پارامترهای آلفا و n در منحنی رطوبتی خاک جلالی, وحیدرضا, اطمینان, محمود آبادی, خاشعی سیوکی, پوررضا مجله پژوهشهای حفاظت آب و خاک 27 (1), 197-211 , 2020 2020.0
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