Analytical solute transport modeling of furrow fertigation using the STANMOD software package
Understanding and better managing the environmental fate of water and fertilizers in agricultural operations requires accurate modeling of the fertilization process under field conditions, including when using furrow fertigation. The STANMOD model has become a popular tool for simulating a range of...
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| Published in: | Journal of Hydrology and Hydromechanics Vol. 73; no. 2; pp. 200 - 209 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
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Bratislava
Sciendo
01.06.2025
De Gruyter Brill Sp. z o.o., Paradigm Publishing Services |
| Subjects: | |
| ISSN: | 1338-4333, 0042-790X, 1338-4333 |
| Online Access: | Get full text |
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| Abstract | Understanding and better managing the environmental fate of water and fertilizers in agricultural operations requires accurate modeling of the fertilization process under field conditions, including when using furrow fertigation. The STANMOD model has become a popular tool for simulating a range of laboratory- and field-scale solute transport problems. By comparison, few if any studies have used this model to analyze solute transport in overland water during furrow fertigation. In this study, we investigate the efficacy of STANMOD in simulating overland solute transport in four irrigated furrows. STANMOD solves the governing advection-dispersion equation (ADE) for the solute transport process analytically. Experimental data were sourced from furrow fertigation experiments carried out at the University of Arizona. This study presents the results of fitting the ADE model in STANMOD to breakthrough curves measured at individual points along furrows, not the entire system. By directly fitting the ADE to measured solute concentrations, the average (or effective) values of dispersion coefficient (or longitudinal dispersivity) and fluid flux in the furrows were optimized using STANMOD. We found the coefficient of determination to be greater than 0.5 for all stations in all furrows, indicating a satisfactory fit of the model to the observed furrow concentration data. Root mean square error (RMSE) values varied over a wide range from 9.9 to 101.7 mg/L. We should point out that in practice flux does decrease along furrows due to infiltration. However, STANMOD assumes flux is constant and does not take its variability into account. Therefore, the optimized pore water velocity and dispersion coefficient represent values averaged over the corresponding domain. We conclude that STANMOD can provide a useful analytical description of solute transport in flowing overland water, thus facilitating furrow fertigation management. |
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| AbstractList | Understanding and better managing the environmental fate of water and fertilizers in agricultural operations requires accurate modeling of the fertilization process under field conditions, including when using furrow fertigation. The STANMOD model has become a popular tool for simulating a range of laboratory- and field-scale solute transport problems. By comparison, few if any studies have used this model to analyze solute transport in overland water during furrow fertigation. In this study, we investigate the efficacy of STANMOD in simulating overland solute transport in four irrigated furrows. STANMOD solves the governing advection-dispersion equation (ADE) for the solute transport process analytically. Experimental data were sourced from furrow fertigation experiments carried out at the University of Arizona. This study presents the results of fitting the ADE model in STANMOD to breakthrough curves measured at individual points along furrows, not the entire system. By directly fitting the ADE to measured solute concentrations, the average (or effective) values of dispersion coefficient (or longitudinal dispersivity) and fluid flux in the furrows were optimized using STANMOD. We found the coefficient of determination to be greater than 0.5 for all stations in all furrows, indicating a satisfactory fit of the model to the observed furrow concentration data. Root mean square error (RMSE) values varied over a wide range from 9.9 to 101.7 mg/L. We should point out that in practice flux does decrease along furrows due to infiltration. However, STANMOD assumes flux is constant and does not take its variability into account. Therefore, the optimized pore water velocity and dispersion coefficient represent values averaged over the corresponding domain. We conclude that STANMOD can provide a useful analytical description of solute transport in flowing overland water, thus facilitating furrow fertigation management. |
| Author | van Genuchten, Martinus Th Ghanbarian, Behzad Ashrafi, Ali Ebrahimian, Hamed |
| Author_xml | – sequence: 1 givenname: Ali surname: Ashrafi fullname: Ashrafi, Ali organization: Department of Plant and Soil Sciences, Oklahoma State University, Stillwater, OK, USA – sequence: 2 givenname: Martinus Th surname: van Genuchten fullname: van Genuchten, Martinus Th organization: Department of Earth Sciences, Utrecht University, Utrecht, The Netherlands – sequence: 3 givenname: Behzad surname: Ghanbarian fullname: Ghanbarian, Behzad organization: Division of Data Science, College of Science, University of Texas at Arlington, Arlington TX, United States – sequence: 4 givenname: Hamed surname: Ebrahimian fullname: Ebrahimian, Hamed email: ebrahimian@ut.ac.ir organization: Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran |
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| SubjectTerms | Advection Agriculture Agrochemicals Biological fertilization Capital costs Civil engineering Dispersion Effectiveness Efficiency Environmental impact Fertigation Fertilization Fertilizer application Fertilizers Fluctuations furrow irrigation Furrows Groundwater Irrigation Modelling Pore water Root-mean-square errors Runoff Software packages Soil sciences Solute transport Solutes STANMOD Transport processes Water velocity |
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| Title | Analytical solute transport modeling of furrow fertigation using the STANMOD software package |
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