Modeling variability of infiltration tests in ephemeral stream beds as a random function for uncertainty quantification
Abstract Infiltration processes are highly variable in space and time, and therefore, building reliable hydrological models without considering the variability is questionable. In this research, we propose a methodology that can systematically handle the variability in the infiltration process. The...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2023-02-01
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| Series: | Applied Water Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s13201-023-01870-0 |
| _version_ | 1797863910109347840 |
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| author | Burhan Niyazi Milad Masoud Amro Elfeki Natarajan Rajmohan Abdulaziz Alqarawy Mohamed Rashed |
| author_facet | Burhan Niyazi Milad Masoud Amro Elfeki Natarajan Rajmohan Abdulaziz Alqarawy Mohamed Rashed |
| author_sort | Burhan Niyazi |
| collection | DOAJ |
| description | Abstract Infiltration processes are highly variable in space and time, and therefore, building reliable hydrological models without considering the variability is questionable. In this research, we propose a methodology that can systematically handle the variability in the infiltration process. The methodology is based on the theory of random functions in a dimensionless formalism that allows the derivation of a generalized model from the observed infiltration test data. The Monte Carlo technique is utilized to generate hypothetical infiltration tests that carputer the characteristics of the real tests. The methodology is applied to a case study in ephemeral stream beds located in Al Madinah Al Munawarah Province in Saudi Arabia. The measurements are made by the double-ring infiltrometer. Beta distribution fits the dimensionless cumulative infiltration relatively well at a 1% significant level at all times, and therefore, it can be used to model the uncertainty in hydrological modeling. High variability is observed in infiltration tests at the early time (a platykurtic distribution with high dispersion); however, it decreases at the late time (Leptokurtic distribution with low dispersion) since the infiltration reaches a steady infiltration. Some extreme tests show different behavior from the fourteen tests that cannot be captured by the model and therefore need special treatment. |
| first_indexed | 2024-04-09T22:44:18Z |
| format | Article |
| id | doaj.art-e5db8fbe02bb4d4381aa8e4c06ba49ec |
| institution | Directory Open Access Journal |
| issn | 2190-5487 2190-5495 |
| language | English |
| last_indexed | 2024-04-09T22:44:18Z |
| publishDate | 2023-02-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Applied Water Science |
| spelling | doaj.art-e5db8fbe02bb4d4381aa8e4c06ba49ec2023-03-22T12:01:40ZengSpringerOpenApplied Water Science2190-54872190-54952023-02-0113311410.1007/s13201-023-01870-0Modeling variability of infiltration tests in ephemeral stream beds as a random function for uncertainty quantificationBurhan Niyazi0Milad Masoud1Amro Elfeki2Natarajan Rajmohan3Abdulaziz Alqarawy4Mohamed Rashed5Water Research Center, King Abdulaziz UniversityWater Research Center, King Abdulaziz UniversityFaculty of Meteorology, Environment and Arid Land Agriculture, King Abdulaziz UniversityWater Research Center, King Abdulaziz UniversityWater Research Center, King Abdulaziz UniversityWater Research Center, King Abdulaziz UniversityAbstract Infiltration processes are highly variable in space and time, and therefore, building reliable hydrological models without considering the variability is questionable. In this research, we propose a methodology that can systematically handle the variability in the infiltration process. The methodology is based on the theory of random functions in a dimensionless formalism that allows the derivation of a generalized model from the observed infiltration test data. The Monte Carlo technique is utilized to generate hypothetical infiltration tests that carputer the characteristics of the real tests. The methodology is applied to a case study in ephemeral stream beds located in Al Madinah Al Munawarah Province in Saudi Arabia. The measurements are made by the double-ring infiltrometer. Beta distribution fits the dimensionless cumulative infiltration relatively well at a 1% significant level at all times, and therefore, it can be used to model the uncertainty in hydrological modeling. High variability is observed in infiltration tests at the early time (a platykurtic distribution with high dispersion); however, it decreases at the late time (Leptokurtic distribution with low dispersion) since the infiltration reaches a steady infiltration. Some extreme tests show different behavior from the fourteen tests that cannot be captured by the model and therefore need special treatment.https://doi.org/10.1007/s13201-023-01870-0Infiltration testsMonte Carlo methodBeta distributionDimensionless curvesAl Madinah Al MunawarahSaudi Arabia |
| spellingShingle | Burhan Niyazi Milad Masoud Amro Elfeki Natarajan Rajmohan Abdulaziz Alqarawy Mohamed Rashed Modeling variability of infiltration tests in ephemeral stream beds as a random function for uncertainty quantification Applied Water Science Infiltration tests Monte Carlo method Beta distribution Dimensionless curves Al Madinah Al Munawarah Saudi Arabia |
| title | Modeling variability of infiltration tests in ephemeral stream beds as a random function for uncertainty quantification |
| title_full | Modeling variability of infiltration tests in ephemeral stream beds as a random function for uncertainty quantification |
| title_fullStr | Modeling variability of infiltration tests in ephemeral stream beds as a random function for uncertainty quantification |
| title_full_unstemmed | Modeling variability of infiltration tests in ephemeral stream beds as a random function for uncertainty quantification |
| title_short | Modeling variability of infiltration tests in ephemeral stream beds as a random function for uncertainty quantification |
| title_sort | modeling variability of infiltration tests in ephemeral stream beds as a random function for uncertainty quantification |
| topic | Infiltration tests Monte Carlo method Beta distribution Dimensionless curves Al Madinah Al Munawarah Saudi Arabia |
| url | https://doi.org/10.1007/s13201-023-01870-0 |
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