Comparative analysis of two infiltration models for application in a physically based overland flow model
Abstract In the prediction of overland flow, infiltration is an essential component, which should be modeled accurately to achieve optimum runoff rates. Many mathematical models that simulate the details of runoff and erosion process in hillslopes, where the rill-interrill configuration significantl...
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| Autor*in: |
Mallari, Kristine Joy B. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2015 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag Berlin Heidelberg 2015 |
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| Übergeordnetes Werk: |
Enthalten in: Environmental earth sciences - Berlin : Springer, 2009, 74(2015), 2 vom: 15. Feb., Seite 1579-1587 |
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| Übergeordnetes Werk: |
volume:74 ; year:2015 ; number:2 ; day:15 ; month:02 ; pages:1579-1587 |
| Links: |
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| DOI / URN: |
10.1007/s12665-015-4155-7 |
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| Katalog-ID: |
SPR026710536 |
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| 100 | 1 | |a Mallari, Kristine Joy B. |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Comparative analysis of two infiltration models for application in a physically based overland flow model |
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| 520 | |a Abstract In the prediction of overland flow, infiltration is an essential component, which should be modeled accurately to achieve optimum runoff rates. Many mathematical models that simulate the details of runoff and erosion process in hillslopes, where the rill-interrill configuration significantly affects overland flow, employ Horton’s model for infiltration due to its simplicity. However, Horton’s model does not handle adequately antecedent moisture condition (AMC) of soil. In this study, the Green-Ampt infiltration model is incorporated into a physically based overland flow model, which was originally coupled with Horton’s equation in an effort to improve the overland flow model’s prediction ability. In so doing, the model used the Horton and Green-Ampt model as an infiltration component separately and simulated flow to directly compare which infiltration equation performs better with the overland flow model. Calibration using laboratory data produced good results for both Horton with NSE = 0.88 and r2 = 0.92 and Green-Ampt with NSE = 0.90 and r2 = 0.95 while in validation, the Horton-coupled model produced lower NSE = 0.64 and r2 = 0.84 than the Green-Ampt which produced NSE = 0.85 and r2 = 0.85. The results suggest that the Green-Ampt equation can improve the performance of the overland flow model with its ability to account more accurately the AMC and flow processes in the soil. | ||
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| 650 | 4 | |a Hillslope scale |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Horton’s model |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Interrill |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Overland flow model |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Rill |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Arguelles, Anya Catherine C. |4 aut | |
| 700 | 1 | |a Kim, Hwansuk |4 aut | |
| 700 | 1 | |a Aksoy, Hafzullah |4 aut | |
| 700 | 1 | |a Kavvas, M. Levent |4 aut | |
| 700 | 1 | |a Yoon, Jaeyoung |4 aut | |
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10.1007/s12665-015-4155-7 doi (DE-627)SPR026710536 (SPR)s12665-015-4155-7-e DE-627 ger DE-627 rakwb eng Mallari, Kristine Joy B. verfasserin aut Comparative analysis of two infiltration models for application in a physically based overland flow model 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag Berlin Heidelberg 2015 Abstract In the prediction of overland flow, infiltration is an essential component, which should be modeled accurately to achieve optimum runoff rates. Many mathematical models that simulate the details of runoff and erosion process in hillslopes, where the rill-interrill configuration significantly affects overland flow, employ Horton’s model for infiltration due to its simplicity. However, Horton’s model does not handle adequately antecedent moisture condition (AMC) of soil. In this study, the Green-Ampt infiltration model is incorporated into a physically based overland flow model, which was originally coupled with Horton’s equation in an effort to improve the overland flow model’s prediction ability. In so doing, the model used the Horton and Green-Ampt model as an infiltration component separately and simulated flow to directly compare which infiltration equation performs better with the overland flow model. Calibration using laboratory data produced good results for both Horton with NSE = 0.88 and r2 = 0.92 and Green-Ampt with NSE = 0.90 and r2 = 0.95 while in validation, the Horton-coupled model produced lower NSE = 0.64 and r2 = 0.84 than the Green-Ampt which produced NSE = 0.85 and r2 = 0.85. The results suggest that the Green-Ampt equation can improve the performance of the overland flow model with its ability to account more accurately the AMC and flow processes in the soil. Green-Ampt infiltration model (dpeaa)DE-He213 Hillslope scale (dpeaa)DE-He213 Horton’s model (dpeaa)DE-He213 Interrill (dpeaa)DE-He213 Overland flow model (dpeaa)DE-He213 Rill (dpeaa)DE-He213 Arguelles, Anya Catherine C. aut Kim, Hwansuk aut Aksoy, Hafzullah aut Kavvas, M. Levent aut Yoon, Jaeyoung aut Enthalten in Environmental earth sciences Berlin : Springer, 2009 74(2015), 2 vom: 15. Feb., Seite 1579-1587 (DE-627)599673451 (DE-600)2493699-6 1866-6299 nnns volume:74 year:2015 number:2 day:15 month:02 pages:1579-1587 https://dx.doi.org/10.1007/s12665-015-4155-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 74 2015 2 15 02 1579-1587 |
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10.1007/s12665-015-4155-7 doi (DE-627)SPR026710536 (SPR)s12665-015-4155-7-e DE-627 ger DE-627 rakwb eng Mallari, Kristine Joy B. verfasserin aut Comparative analysis of two infiltration models for application in a physically based overland flow model 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag Berlin Heidelberg 2015 Abstract In the prediction of overland flow, infiltration is an essential component, which should be modeled accurately to achieve optimum runoff rates. Many mathematical models that simulate the details of runoff and erosion process in hillslopes, where the rill-interrill configuration significantly affects overland flow, employ Horton’s model for infiltration due to its simplicity. However, Horton’s model does not handle adequately antecedent moisture condition (AMC) of soil. In this study, the Green-Ampt infiltration model is incorporated into a physically based overland flow model, which was originally coupled with Horton’s equation in an effort to improve the overland flow model’s prediction ability. In so doing, the model used the Horton and Green-Ampt model as an infiltration component separately and simulated flow to directly compare which infiltration equation performs better with the overland flow model. Calibration using laboratory data produced good results for both Horton with NSE = 0.88 and r2 = 0.92 and Green-Ampt with NSE = 0.90 and r2 = 0.95 while in validation, the Horton-coupled model produced lower NSE = 0.64 and r2 = 0.84 than the Green-Ampt which produced NSE = 0.85 and r2 = 0.85. The results suggest that the Green-Ampt equation can improve the performance of the overland flow model with its ability to account more accurately the AMC and flow processes in the soil. Green-Ampt infiltration model (dpeaa)DE-He213 Hillslope scale (dpeaa)DE-He213 Horton’s model (dpeaa)DE-He213 Interrill (dpeaa)DE-He213 Overland flow model (dpeaa)DE-He213 Rill (dpeaa)DE-He213 Arguelles, Anya Catherine C. aut Kim, Hwansuk aut Aksoy, Hafzullah aut Kavvas, M. Levent aut Yoon, Jaeyoung aut Enthalten in Environmental earth sciences Berlin : Springer, 2009 74(2015), 2 vom: 15. Feb., Seite 1579-1587 (DE-627)599673451 (DE-600)2493699-6 1866-6299 nnns volume:74 year:2015 number:2 day:15 month:02 pages:1579-1587 https://dx.doi.org/10.1007/s12665-015-4155-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 74 2015 2 15 02 1579-1587 |
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10.1007/s12665-015-4155-7 doi (DE-627)SPR026710536 (SPR)s12665-015-4155-7-e DE-627 ger DE-627 rakwb eng Mallari, Kristine Joy B. verfasserin aut Comparative analysis of two infiltration models for application in a physically based overland flow model 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag Berlin Heidelberg 2015 Abstract In the prediction of overland flow, infiltration is an essential component, which should be modeled accurately to achieve optimum runoff rates. Many mathematical models that simulate the details of runoff and erosion process in hillslopes, where the rill-interrill configuration significantly affects overland flow, employ Horton’s model for infiltration due to its simplicity. However, Horton’s model does not handle adequately antecedent moisture condition (AMC) of soil. In this study, the Green-Ampt infiltration model is incorporated into a physically based overland flow model, which was originally coupled with Horton’s equation in an effort to improve the overland flow model’s prediction ability. In so doing, the model used the Horton and Green-Ampt model as an infiltration component separately and simulated flow to directly compare which infiltration equation performs better with the overland flow model. Calibration using laboratory data produced good results for both Horton with NSE = 0.88 and r2 = 0.92 and Green-Ampt with NSE = 0.90 and r2 = 0.95 while in validation, the Horton-coupled model produced lower NSE = 0.64 and r2 = 0.84 than the Green-Ampt which produced NSE = 0.85 and r2 = 0.85. The results suggest that the Green-Ampt equation can improve the performance of the overland flow model with its ability to account more accurately the AMC and flow processes in the soil. Green-Ampt infiltration model (dpeaa)DE-He213 Hillslope scale (dpeaa)DE-He213 Horton’s model (dpeaa)DE-He213 Interrill (dpeaa)DE-He213 Overland flow model (dpeaa)DE-He213 Rill (dpeaa)DE-He213 Arguelles, Anya Catherine C. aut Kim, Hwansuk aut Aksoy, Hafzullah aut Kavvas, M. Levent aut Yoon, Jaeyoung aut Enthalten in Environmental earth sciences Berlin : Springer, 2009 74(2015), 2 vom: 15. Feb., Seite 1579-1587 (DE-627)599673451 (DE-600)2493699-6 1866-6299 nnns volume:74 year:2015 number:2 day:15 month:02 pages:1579-1587 https://dx.doi.org/10.1007/s12665-015-4155-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 74 2015 2 15 02 1579-1587 |
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10.1007/s12665-015-4155-7 doi (DE-627)SPR026710536 (SPR)s12665-015-4155-7-e DE-627 ger DE-627 rakwb eng Mallari, Kristine Joy B. verfasserin aut Comparative analysis of two infiltration models for application in a physically based overland flow model 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag Berlin Heidelberg 2015 Abstract In the prediction of overland flow, infiltration is an essential component, which should be modeled accurately to achieve optimum runoff rates. Many mathematical models that simulate the details of runoff and erosion process in hillslopes, where the rill-interrill configuration significantly affects overland flow, employ Horton’s model for infiltration due to its simplicity. However, Horton’s model does not handle adequately antecedent moisture condition (AMC) of soil. In this study, the Green-Ampt infiltration model is incorporated into a physically based overland flow model, which was originally coupled with Horton’s equation in an effort to improve the overland flow model’s prediction ability. In so doing, the model used the Horton and Green-Ampt model as an infiltration component separately and simulated flow to directly compare which infiltration equation performs better with the overland flow model. Calibration using laboratory data produced good results for both Horton with NSE = 0.88 and r2 = 0.92 and Green-Ampt with NSE = 0.90 and r2 = 0.95 while in validation, the Horton-coupled model produced lower NSE = 0.64 and r2 = 0.84 than the Green-Ampt which produced NSE = 0.85 and r2 = 0.85. The results suggest that the Green-Ampt equation can improve the performance of the overland flow model with its ability to account more accurately the AMC and flow processes in the soil. Green-Ampt infiltration model (dpeaa)DE-He213 Hillslope scale (dpeaa)DE-He213 Horton’s model (dpeaa)DE-He213 Interrill (dpeaa)DE-He213 Overland flow model (dpeaa)DE-He213 Rill (dpeaa)DE-He213 Arguelles, Anya Catherine C. aut Kim, Hwansuk aut Aksoy, Hafzullah aut Kavvas, M. Levent aut Yoon, Jaeyoung aut Enthalten in Environmental earth sciences Berlin : Springer, 2009 74(2015), 2 vom: 15. Feb., Seite 1579-1587 (DE-627)599673451 (DE-600)2493699-6 1866-6299 nnns volume:74 year:2015 number:2 day:15 month:02 pages:1579-1587 https://dx.doi.org/10.1007/s12665-015-4155-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 74 2015 2 15 02 1579-1587 |
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10.1007/s12665-015-4155-7 doi (DE-627)SPR026710536 (SPR)s12665-015-4155-7-e DE-627 ger DE-627 rakwb eng Mallari, Kristine Joy B. verfasserin aut Comparative analysis of two infiltration models for application in a physically based overland flow model 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag Berlin Heidelberg 2015 Abstract In the prediction of overland flow, infiltration is an essential component, which should be modeled accurately to achieve optimum runoff rates. Many mathematical models that simulate the details of runoff and erosion process in hillslopes, where the rill-interrill configuration significantly affects overland flow, employ Horton’s model for infiltration due to its simplicity. However, Horton’s model does not handle adequately antecedent moisture condition (AMC) of soil. In this study, the Green-Ampt infiltration model is incorporated into a physically based overland flow model, which was originally coupled with Horton’s equation in an effort to improve the overland flow model’s prediction ability. In so doing, the model used the Horton and Green-Ampt model as an infiltration component separately and simulated flow to directly compare which infiltration equation performs better with the overland flow model. Calibration using laboratory data produced good results for both Horton with NSE = 0.88 and r2 = 0.92 and Green-Ampt with NSE = 0.90 and r2 = 0.95 while in validation, the Horton-coupled model produced lower NSE = 0.64 and r2 = 0.84 than the Green-Ampt which produced NSE = 0.85 and r2 = 0.85. The results suggest that the Green-Ampt equation can improve the performance of the overland flow model with its ability to account more accurately the AMC and flow processes in the soil. Green-Ampt infiltration model (dpeaa)DE-He213 Hillslope scale (dpeaa)DE-He213 Horton’s model (dpeaa)DE-He213 Interrill (dpeaa)DE-He213 Overland flow model (dpeaa)DE-He213 Rill (dpeaa)DE-He213 Arguelles, Anya Catherine C. aut Kim, Hwansuk aut Aksoy, Hafzullah aut Kavvas, M. Levent aut Yoon, Jaeyoung aut Enthalten in Environmental earth sciences Berlin : Springer, 2009 74(2015), 2 vom: 15. Feb., Seite 1579-1587 (DE-627)599673451 (DE-600)2493699-6 1866-6299 nnns volume:74 year:2015 number:2 day:15 month:02 pages:1579-1587 https://dx.doi.org/10.1007/s12665-015-4155-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 74 2015 2 15 02 1579-1587 |
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Mallari, Kristine Joy B. @@aut@@ Arguelles, Anya Catherine C. @@aut@@ Kim, Hwansuk @@aut@@ Aksoy, Hafzullah @@aut@@ Kavvas, M. Levent @@aut@@ Yoon, Jaeyoung @@aut@@ |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR026710536</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230401020009.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201007s2015 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s12665-015-4155-7</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR026710536</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s12665-015-4155-7-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Mallari, Kristine Joy B.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Comparative analysis of two infiltration models for application in a physically based overland flow model</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2015</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer-Verlag Berlin Heidelberg 2015</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract In the prediction of overland flow, infiltration is an essential component, which should be modeled accurately to achieve optimum runoff rates. Many mathematical models that simulate the details of runoff and erosion process in hillslopes, where the rill-interrill configuration significantly affects overland flow, employ Horton’s model for infiltration due to its simplicity. However, Horton’s model does not handle adequately antecedent moisture condition (AMC) of soil. In this study, the Green-Ampt infiltration model is incorporated into a physically based overland flow model, which was originally coupled with Horton’s equation in an effort to improve the overland flow model’s prediction ability. In so doing, the model used the Horton and Green-Ampt model as an infiltration component separately and simulated flow to directly compare which infiltration equation performs better with the overland flow model. Calibration using laboratory data produced good results for both Horton with NSE = 0.88 and r2 = 0.92 and Green-Ampt with NSE = 0.90 and r2 = 0.95 while in validation, the Horton-coupled model produced lower NSE = 0.64 and r2 = 0.84 than the Green-Ampt which produced NSE = 0.85 and r2 = 0.85. The results suggest that the Green-Ampt equation can improve the performance of the overland flow model with its ability to account more accurately the AMC and flow processes in the soil.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Green-Ampt infiltration model</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Hillslope scale</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Horton’s model</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Interrill</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Overland flow model</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Rill</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Arguelles, Anya Catherine C.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Kim, Hwansuk</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Aksoy, Hafzullah</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Kavvas, M. 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Mallari, Kristine Joy B. |
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Mallari, Kristine Joy B. misc Green-Ampt infiltration model misc Hillslope scale misc Horton’s model misc Interrill misc Overland flow model misc Rill Comparative analysis of two infiltration models for application in a physically based overland flow model |
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Comparative analysis of two infiltration models for application in a physically based overland flow model Green-Ampt infiltration model (dpeaa)DE-He213 Hillslope scale (dpeaa)DE-He213 Horton’s model (dpeaa)DE-He213 Interrill (dpeaa)DE-He213 Overland flow model (dpeaa)DE-He213 Rill (dpeaa)DE-He213 |
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misc Green-Ampt infiltration model misc Hillslope scale misc Horton’s model misc Interrill misc Overland flow model misc Rill |
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comparative analysis of two infiltration models for application in a physically based overland flow model |
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Comparative analysis of two infiltration models for application in a physically based overland flow model |
| abstract |
Abstract In the prediction of overland flow, infiltration is an essential component, which should be modeled accurately to achieve optimum runoff rates. Many mathematical models that simulate the details of runoff and erosion process in hillslopes, where the rill-interrill configuration significantly affects overland flow, employ Horton’s model for infiltration due to its simplicity. However, Horton’s model does not handle adequately antecedent moisture condition (AMC) of soil. In this study, the Green-Ampt infiltration model is incorporated into a physically based overland flow model, which was originally coupled with Horton’s equation in an effort to improve the overland flow model’s prediction ability. In so doing, the model used the Horton and Green-Ampt model as an infiltration component separately and simulated flow to directly compare which infiltration equation performs better with the overland flow model. Calibration using laboratory data produced good results for both Horton with NSE = 0.88 and r2 = 0.92 and Green-Ampt with NSE = 0.90 and r2 = 0.95 while in validation, the Horton-coupled model produced lower NSE = 0.64 and r2 = 0.84 than the Green-Ampt which produced NSE = 0.85 and r2 = 0.85. The results suggest that the Green-Ampt equation can improve the performance of the overland flow model with its ability to account more accurately the AMC and flow processes in the soil. © Springer-Verlag Berlin Heidelberg 2015 |
| abstractGer |
Abstract In the prediction of overland flow, infiltration is an essential component, which should be modeled accurately to achieve optimum runoff rates. Many mathematical models that simulate the details of runoff and erosion process in hillslopes, where the rill-interrill configuration significantly affects overland flow, employ Horton’s model for infiltration due to its simplicity. However, Horton’s model does not handle adequately antecedent moisture condition (AMC) of soil. In this study, the Green-Ampt infiltration model is incorporated into a physically based overland flow model, which was originally coupled with Horton’s equation in an effort to improve the overland flow model’s prediction ability. In so doing, the model used the Horton and Green-Ampt model as an infiltration component separately and simulated flow to directly compare which infiltration equation performs better with the overland flow model. Calibration using laboratory data produced good results for both Horton with NSE = 0.88 and r2 = 0.92 and Green-Ampt with NSE = 0.90 and r2 = 0.95 while in validation, the Horton-coupled model produced lower NSE = 0.64 and r2 = 0.84 than the Green-Ampt which produced NSE = 0.85 and r2 = 0.85. The results suggest that the Green-Ampt equation can improve the performance of the overland flow model with its ability to account more accurately the AMC and flow processes in the soil. © Springer-Verlag Berlin Heidelberg 2015 |
| abstract_unstemmed |
Abstract In the prediction of overland flow, infiltration is an essential component, which should be modeled accurately to achieve optimum runoff rates. Many mathematical models that simulate the details of runoff and erosion process in hillslopes, where the rill-interrill configuration significantly affects overland flow, employ Horton’s model for infiltration due to its simplicity. However, Horton’s model does not handle adequately antecedent moisture condition (AMC) of soil. In this study, the Green-Ampt infiltration model is incorporated into a physically based overland flow model, which was originally coupled with Horton’s equation in an effort to improve the overland flow model’s prediction ability. In so doing, the model used the Horton and Green-Ampt model as an infiltration component separately and simulated flow to directly compare which infiltration equation performs better with the overland flow model. Calibration using laboratory data produced good results for both Horton with NSE = 0.88 and r2 = 0.92 and Green-Ampt with NSE = 0.90 and r2 = 0.95 while in validation, the Horton-coupled model produced lower NSE = 0.64 and r2 = 0.84 than the Green-Ampt which produced NSE = 0.85 and r2 = 0.85. The results suggest that the Green-Ampt equation can improve the performance of the overland flow model with its ability to account more accurately the AMC and flow processes in the soil. © Springer-Verlag Berlin Heidelberg 2015 |
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| title_short |
Comparative analysis of two infiltration models for application in a physically based overland flow model |
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https://dx.doi.org/10.1007/s12665-015-4155-7 |
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Arguelles, Anya Catherine C. Kim, Hwansuk Aksoy, Hafzullah Kavvas, M. Levent Yoon, Jaeyoung |
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| score |
7.402648 |