Runoff simulation of two typical urban green land types with the Stormwater Management Model (SWMM): sensitivity analysis and calibration of runoff parameters
Abstract The characteristics of surface runoff and the infiltration properties of urban green land are important to determine the effects of runoff reduction by low-impact development (LID) facilities. In this paper, two typical types of urban green land (lawn and shrub) in Shanghai were selected to...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Xu, Zuxin [verfasserIn] Xiong, Lijun [verfasserIn] Li, Huaizheng [verfasserIn] Xu, Jin [verfasserIn] Cai, Xin [verfasserIn] Chen, Keli [verfasserIn] Wu, Jun [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Environmental monitoring and assessment - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981, 191(2019), 6 vom: 04. Mai |
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| Übergeordnetes Werk: |
volume:191 ; year:2019 ; number:6 ; day:04 ; month:05 |
| Links: |
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| DOI / URN: |
10.1007/s10661-019-7445-9 |
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| Katalog-ID: |
SPR012296597 |
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| 245 | 1 | 0 | |a Runoff simulation of two typical urban green land types with the Stormwater Management Model (SWMM): sensitivity analysis and calibration of runoff parameters |
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| 520 | |a Abstract The characteristics of surface runoff and the infiltration properties of urban green land are important to determine the effects of runoff reduction by low-impact development (LID) facilities. In this paper, two typical types of urban green land (lawn and shrub) in Shanghai were selected to study the runoff characteristics under eight rainfall events. The sensitivity of the runoff parameters was analyzed, and then, the optimal parameters were determined using the Stormwater Management Model (SWMM). The results showed that the interception and infiltration capacities of shrub were greater than those of lawn. The rainfall intensity and rainfall pattern were the major factors that influenced the interception and infiltration of rainwater. The threshold value that generates runoff varied across the eight rainfall events ranged from 1.6 to 28.5 mm for lawn and 4.5 to 32.0 mm for shrub. The maximum reduction ratios of runoff and peak flow for shrub were 52 and 57% higher than them for lawn, respectively. The parameters for shrub were more sensitive to runoff and peak flow compared with those for lawn. Under light rainfalls with a short duration, the maximum infiltration rate and depression storage were more sensitive than those under heavy rainfalls with a long duration. Antecedent dry weather period was not found to be a sensitive parameter except for the shrub under light rainfalls. The relative errors of runoff and dynamic mean runoff (60 min) for lawn and shrub were within ± 9.5%. The errors of peak flow ranged between − 21 and 16.6%. The dynamic runoff characteristics and the parameters for lawn and shrub determined in this study can provide references for simulating urban runoff and planning LID areas. | ||
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| 650 | 4 | |a Rainfall |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Runoff |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Parameter sensitivity |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a SWMM |7 (dpeaa)DE-He213 | |
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| 700 | 1 | |a Li, Huaizheng |e verfasserin |4 aut | |
| 700 | 1 | |a Xu, Jin |e verfasserin |4 aut | |
| 700 | 1 | |a Cai, Xin |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Keli |e verfasserin |4 aut | |
| 700 | 1 | |a Wu, Jun |e verfasserin |4 aut | |
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10.1007/s10661-019-7445-9 doi (DE-627)SPR012296597 (SPR)s10661-019-7445-9-e DE-627 ger DE-627 rakwb eng 333.7 ASE 30.00 bkl 43.00 bkl Xu, Zuxin verfasserin aut Runoff simulation of two typical urban green land types with the Stormwater Management Model (SWMM): sensitivity analysis and calibration of runoff parameters 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The characteristics of surface runoff and the infiltration properties of urban green land are important to determine the effects of runoff reduction by low-impact development (LID) facilities. In this paper, two typical types of urban green land (lawn and shrub) in Shanghai were selected to study the runoff characteristics under eight rainfall events. The sensitivity of the runoff parameters was analyzed, and then, the optimal parameters were determined using the Stormwater Management Model (SWMM). The results showed that the interception and infiltration capacities of shrub were greater than those of lawn. The rainfall intensity and rainfall pattern were the major factors that influenced the interception and infiltration of rainwater. The threshold value that generates runoff varied across the eight rainfall events ranged from 1.6 to 28.5 mm for lawn and 4.5 to 32.0 mm for shrub. The maximum reduction ratios of runoff and peak flow for shrub were 52 and 57% higher than them for lawn, respectively. The parameters for shrub were more sensitive to runoff and peak flow compared with those for lawn. Under light rainfalls with a short duration, the maximum infiltration rate and depression storage were more sensitive than those under heavy rainfalls with a long duration. Antecedent dry weather period was not found to be a sensitive parameter except for the shrub under light rainfalls. The relative errors of runoff and dynamic mean runoff (60 min) for lawn and shrub were within ± 9.5%. The errors of peak flow ranged between − 21 and 16.6%. The dynamic runoff characteristics and the parameters for lawn and shrub determined in this study can provide references for simulating urban runoff and planning LID areas. Green land (dpeaa)DE-He213 Rainfall (dpeaa)DE-He213 Runoff (dpeaa)DE-He213 Parameter sensitivity (dpeaa)DE-He213 SWMM (dpeaa)DE-He213 Xiong, Lijun verfasserin aut Li, Huaizheng verfasserin aut Xu, Jin verfasserin aut Cai, Xin verfasserin aut Chen, Keli verfasserin aut Wu, Jun verfasserin aut Enthalten in Environmental monitoring and assessment Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 191(2019), 6 vom: 04. Mai (DE-627)31281738X (DE-600)2012242-1 1573-2959 nnns volume:191 year:2019 number:6 day:04 month:05 https://dx.doi.org/10.1007/s10661-019-7445-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE 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_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_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 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 30.00 ASE 43.00 ASE AR 191 2019 6 04 05 |
| spelling |
10.1007/s10661-019-7445-9 doi (DE-627)SPR012296597 (SPR)s10661-019-7445-9-e DE-627 ger DE-627 rakwb eng 333.7 ASE 30.00 bkl 43.00 bkl Xu, Zuxin verfasserin aut Runoff simulation of two typical urban green land types with the Stormwater Management Model (SWMM): sensitivity analysis and calibration of runoff parameters 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The characteristics of surface runoff and the infiltration properties of urban green land are important to determine the effects of runoff reduction by low-impact development (LID) facilities. In this paper, two typical types of urban green land (lawn and shrub) in Shanghai were selected to study the runoff characteristics under eight rainfall events. The sensitivity of the runoff parameters was analyzed, and then, the optimal parameters were determined using the Stormwater Management Model (SWMM). The results showed that the interception and infiltration capacities of shrub were greater than those of lawn. The rainfall intensity and rainfall pattern were the major factors that influenced the interception and infiltration of rainwater. The threshold value that generates runoff varied across the eight rainfall events ranged from 1.6 to 28.5 mm for lawn and 4.5 to 32.0 mm for shrub. The maximum reduction ratios of runoff and peak flow for shrub were 52 and 57% higher than them for lawn, respectively. The parameters for shrub were more sensitive to runoff and peak flow compared with those for lawn. Under light rainfalls with a short duration, the maximum infiltration rate and depression storage were more sensitive than those under heavy rainfalls with a long duration. Antecedent dry weather period was not found to be a sensitive parameter except for the shrub under light rainfalls. The relative errors of runoff and dynamic mean runoff (60 min) for lawn and shrub were within ± 9.5%. The errors of peak flow ranged between − 21 and 16.6%. The dynamic runoff characteristics and the parameters for lawn and shrub determined in this study can provide references for simulating urban runoff and planning LID areas. Green land (dpeaa)DE-He213 Rainfall (dpeaa)DE-He213 Runoff (dpeaa)DE-He213 Parameter sensitivity (dpeaa)DE-He213 SWMM (dpeaa)DE-He213 Xiong, Lijun verfasserin aut Li, Huaizheng verfasserin aut Xu, Jin verfasserin aut Cai, Xin verfasserin aut Chen, Keli verfasserin aut Wu, Jun verfasserin aut Enthalten in Environmental monitoring and assessment Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 191(2019), 6 vom: 04. Mai (DE-627)31281738X (DE-600)2012242-1 1573-2959 nnns volume:191 year:2019 number:6 day:04 month:05 https://dx.doi.org/10.1007/s10661-019-7445-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE 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_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_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 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 30.00 ASE 43.00 ASE AR 191 2019 6 04 05 |
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10.1007/s10661-019-7445-9 doi (DE-627)SPR012296597 (SPR)s10661-019-7445-9-e DE-627 ger DE-627 rakwb eng 333.7 ASE 30.00 bkl 43.00 bkl Xu, Zuxin verfasserin aut Runoff simulation of two typical urban green land types with the Stormwater Management Model (SWMM): sensitivity analysis and calibration of runoff parameters 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The characteristics of surface runoff and the infiltration properties of urban green land are important to determine the effects of runoff reduction by low-impact development (LID) facilities. In this paper, two typical types of urban green land (lawn and shrub) in Shanghai were selected to study the runoff characteristics under eight rainfall events. The sensitivity of the runoff parameters was analyzed, and then, the optimal parameters were determined using the Stormwater Management Model (SWMM). The results showed that the interception and infiltration capacities of shrub were greater than those of lawn. The rainfall intensity and rainfall pattern were the major factors that influenced the interception and infiltration of rainwater. The threshold value that generates runoff varied across the eight rainfall events ranged from 1.6 to 28.5 mm for lawn and 4.5 to 32.0 mm for shrub. The maximum reduction ratios of runoff and peak flow for shrub were 52 and 57% higher than them for lawn, respectively. The parameters for shrub were more sensitive to runoff and peak flow compared with those for lawn. Under light rainfalls with a short duration, the maximum infiltration rate and depression storage were more sensitive than those under heavy rainfalls with a long duration. Antecedent dry weather period was not found to be a sensitive parameter except for the shrub under light rainfalls. The relative errors of runoff and dynamic mean runoff (60 min) for lawn and shrub were within ± 9.5%. The errors of peak flow ranged between − 21 and 16.6%. The dynamic runoff characteristics and the parameters for lawn and shrub determined in this study can provide references for simulating urban runoff and planning LID areas. Green land (dpeaa)DE-He213 Rainfall (dpeaa)DE-He213 Runoff (dpeaa)DE-He213 Parameter sensitivity (dpeaa)DE-He213 SWMM (dpeaa)DE-He213 Xiong, Lijun verfasserin aut Li, Huaizheng verfasserin aut Xu, Jin verfasserin aut Cai, Xin verfasserin aut Chen, Keli verfasserin aut Wu, Jun verfasserin aut Enthalten in Environmental monitoring and assessment Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 191(2019), 6 vom: 04. Mai (DE-627)31281738X (DE-600)2012242-1 1573-2959 nnns volume:191 year:2019 number:6 day:04 month:05 https://dx.doi.org/10.1007/s10661-019-7445-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE 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_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_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 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 30.00 ASE 43.00 ASE AR 191 2019 6 04 05 |
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10.1007/s10661-019-7445-9 doi (DE-627)SPR012296597 (SPR)s10661-019-7445-9-e DE-627 ger DE-627 rakwb eng 333.7 ASE 30.00 bkl 43.00 bkl Xu, Zuxin verfasserin aut Runoff simulation of two typical urban green land types with the Stormwater Management Model (SWMM): sensitivity analysis and calibration of runoff parameters 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The characteristics of surface runoff and the infiltration properties of urban green land are important to determine the effects of runoff reduction by low-impact development (LID) facilities. In this paper, two typical types of urban green land (lawn and shrub) in Shanghai were selected to study the runoff characteristics under eight rainfall events. The sensitivity of the runoff parameters was analyzed, and then, the optimal parameters were determined using the Stormwater Management Model (SWMM). The results showed that the interception and infiltration capacities of shrub were greater than those of lawn. The rainfall intensity and rainfall pattern were the major factors that influenced the interception and infiltration of rainwater. The threshold value that generates runoff varied across the eight rainfall events ranged from 1.6 to 28.5 mm for lawn and 4.5 to 32.0 mm for shrub. The maximum reduction ratios of runoff and peak flow for shrub were 52 and 57% higher than them for lawn, respectively. The parameters for shrub were more sensitive to runoff and peak flow compared with those for lawn. Under light rainfalls with a short duration, the maximum infiltration rate and depression storage were more sensitive than those under heavy rainfalls with a long duration. Antecedent dry weather period was not found to be a sensitive parameter except for the shrub under light rainfalls. The relative errors of runoff and dynamic mean runoff (60 min) for lawn and shrub were within ± 9.5%. The errors of peak flow ranged between − 21 and 16.6%. The dynamic runoff characteristics and the parameters for lawn and shrub determined in this study can provide references for simulating urban runoff and planning LID areas. Green land (dpeaa)DE-He213 Rainfall (dpeaa)DE-He213 Runoff (dpeaa)DE-He213 Parameter sensitivity (dpeaa)DE-He213 SWMM (dpeaa)DE-He213 Xiong, Lijun verfasserin aut Li, Huaizheng verfasserin aut Xu, Jin verfasserin aut Cai, Xin verfasserin aut Chen, Keli verfasserin aut Wu, Jun verfasserin aut Enthalten in Environmental monitoring and assessment Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 191(2019), 6 vom: 04. Mai (DE-627)31281738X (DE-600)2012242-1 1573-2959 nnns volume:191 year:2019 number:6 day:04 month:05 https://dx.doi.org/10.1007/s10661-019-7445-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE 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_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_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 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 30.00 ASE 43.00 ASE AR 191 2019 6 04 05 |
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10.1007/s10661-019-7445-9 doi (DE-627)SPR012296597 (SPR)s10661-019-7445-9-e DE-627 ger DE-627 rakwb eng 333.7 ASE 30.00 bkl 43.00 bkl Xu, Zuxin verfasserin aut Runoff simulation of two typical urban green land types with the Stormwater Management Model (SWMM): sensitivity analysis and calibration of runoff parameters 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The characteristics of surface runoff and the infiltration properties of urban green land are important to determine the effects of runoff reduction by low-impact development (LID) facilities. In this paper, two typical types of urban green land (lawn and shrub) in Shanghai were selected to study the runoff characteristics under eight rainfall events. The sensitivity of the runoff parameters was analyzed, and then, the optimal parameters were determined using the Stormwater Management Model (SWMM). The results showed that the interception and infiltration capacities of shrub were greater than those of lawn. The rainfall intensity and rainfall pattern were the major factors that influenced the interception and infiltration of rainwater. The threshold value that generates runoff varied across the eight rainfall events ranged from 1.6 to 28.5 mm for lawn and 4.5 to 32.0 mm for shrub. The maximum reduction ratios of runoff and peak flow for shrub were 52 and 57% higher than them for lawn, respectively. The parameters for shrub were more sensitive to runoff and peak flow compared with those for lawn. Under light rainfalls with a short duration, the maximum infiltration rate and depression storage were more sensitive than those under heavy rainfalls with a long duration. Antecedent dry weather period was not found to be a sensitive parameter except for the shrub under light rainfalls. The relative errors of runoff and dynamic mean runoff (60 min) for lawn and shrub were within ± 9.5%. The errors of peak flow ranged between − 21 and 16.6%. The dynamic runoff characteristics and the parameters for lawn and shrub determined in this study can provide references for simulating urban runoff and planning LID areas. Green land (dpeaa)DE-He213 Rainfall (dpeaa)DE-He213 Runoff (dpeaa)DE-He213 Parameter sensitivity (dpeaa)DE-He213 SWMM (dpeaa)DE-He213 Xiong, Lijun verfasserin aut Li, Huaizheng verfasserin aut Xu, Jin verfasserin aut Cai, Xin verfasserin aut Chen, Keli verfasserin aut Wu, Jun verfasserin aut Enthalten in Environmental monitoring and assessment Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 191(2019), 6 vom: 04. Mai (DE-627)31281738X (DE-600)2012242-1 1573-2959 nnns volume:191 year:2019 number:6 day:04 month:05 https://dx.doi.org/10.1007/s10661-019-7445-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE 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_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_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 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 30.00 ASE 43.00 ASE AR 191 2019 6 04 05 |
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Xu, Zuxin @@aut@@ Xiong, Lijun @@aut@@ Li, Huaizheng @@aut@@ Xu, Jin @@aut@@ Cai, Xin @@aut@@ Chen, Keli @@aut@@ Wu, Jun @@aut@@ |
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In this paper, two typical types of urban green land (lawn and shrub) in Shanghai were selected to study the runoff characteristics under eight rainfall events. The sensitivity of the runoff parameters was analyzed, and then, the optimal parameters were determined using the Stormwater Management Model (SWMM). The results showed that the interception and infiltration capacities of shrub were greater than those of lawn. The rainfall intensity and rainfall pattern were the major factors that influenced the interception and infiltration of rainwater. The threshold value that generates runoff varied across the eight rainfall events ranged from 1.6 to 28.5 mm for lawn and 4.5 to 32.0 mm for shrub. The maximum reduction ratios of runoff and peak flow for shrub were 52 and 57% higher than them for lawn, respectively. The parameters for shrub were more sensitive to runoff and peak flow compared with those for lawn. Under light rainfalls with a short duration, the maximum infiltration rate and depression storage were more sensitive than those under heavy rainfalls with a long duration. Antecedent dry weather period was not found to be a sensitive parameter except for the shrub under light rainfalls. The relative errors of runoff and dynamic mean runoff (60 min) for lawn and shrub were within ± 9.5%. The errors of peak flow ranged between − 21 and 16.6%. 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Xu, Zuxin |
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Xu, Zuxin ddc 333.7 bkl 30.00 bkl 43.00 misc Green land misc Rainfall misc Runoff misc Parameter sensitivity misc SWMM Runoff simulation of two typical urban green land types with the Stormwater Management Model (SWMM): sensitivity analysis and calibration of runoff parameters |
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333.7 ASE 30.00 bkl 43.00 bkl Runoff simulation of two typical urban green land types with the Stormwater Management Model (SWMM): sensitivity analysis and calibration of runoff parameters Green land (dpeaa)DE-He213 Rainfall (dpeaa)DE-He213 Runoff (dpeaa)DE-He213 Parameter sensitivity (dpeaa)DE-He213 SWMM (dpeaa)DE-He213 |
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ddc 333.7 bkl 30.00 bkl 43.00 misc Green land misc Rainfall misc Runoff misc Parameter sensitivity misc SWMM |
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Runoff simulation of two typical urban green land types with the Stormwater Management Model (SWMM): sensitivity analysis and calibration of runoff parameters |
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Runoff simulation of two typical urban green land types with the Stormwater Management Model (SWMM): sensitivity analysis and calibration of runoff parameters |
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Environmental monitoring and assessment |
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Xu, Zuxin Xiong, Lijun Li, Huaizheng Xu, Jin Cai, Xin Chen, Keli Wu, Jun |
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Xu, Zuxin |
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runoff simulation of two typical urban green land types with the stormwater management model (swmm): sensitivity analysis and calibration of runoff parameters |
| title_auth |
Runoff simulation of two typical urban green land types with the Stormwater Management Model (SWMM): sensitivity analysis and calibration of runoff parameters |
| abstract |
Abstract The characteristics of surface runoff and the infiltration properties of urban green land are important to determine the effects of runoff reduction by low-impact development (LID) facilities. In this paper, two typical types of urban green land (lawn and shrub) in Shanghai were selected to study the runoff characteristics under eight rainfall events. The sensitivity of the runoff parameters was analyzed, and then, the optimal parameters were determined using the Stormwater Management Model (SWMM). The results showed that the interception and infiltration capacities of shrub were greater than those of lawn. The rainfall intensity and rainfall pattern were the major factors that influenced the interception and infiltration of rainwater. The threshold value that generates runoff varied across the eight rainfall events ranged from 1.6 to 28.5 mm for lawn and 4.5 to 32.0 mm for shrub. The maximum reduction ratios of runoff and peak flow for shrub were 52 and 57% higher than them for lawn, respectively. The parameters for shrub were more sensitive to runoff and peak flow compared with those for lawn. Under light rainfalls with a short duration, the maximum infiltration rate and depression storage were more sensitive than those under heavy rainfalls with a long duration. Antecedent dry weather period was not found to be a sensitive parameter except for the shrub under light rainfalls. The relative errors of runoff and dynamic mean runoff (60 min) for lawn and shrub were within ± 9.5%. The errors of peak flow ranged between − 21 and 16.6%. The dynamic runoff characteristics and the parameters for lawn and shrub determined in this study can provide references for simulating urban runoff and planning LID areas. |
| abstractGer |
Abstract The characteristics of surface runoff and the infiltration properties of urban green land are important to determine the effects of runoff reduction by low-impact development (LID) facilities. In this paper, two typical types of urban green land (lawn and shrub) in Shanghai were selected to study the runoff characteristics under eight rainfall events. The sensitivity of the runoff parameters was analyzed, and then, the optimal parameters were determined using the Stormwater Management Model (SWMM). The results showed that the interception and infiltration capacities of shrub were greater than those of lawn. The rainfall intensity and rainfall pattern were the major factors that influenced the interception and infiltration of rainwater. The threshold value that generates runoff varied across the eight rainfall events ranged from 1.6 to 28.5 mm for lawn and 4.5 to 32.0 mm for shrub. The maximum reduction ratios of runoff and peak flow for shrub were 52 and 57% higher than them for lawn, respectively. The parameters for shrub were more sensitive to runoff and peak flow compared with those for lawn. Under light rainfalls with a short duration, the maximum infiltration rate and depression storage were more sensitive than those under heavy rainfalls with a long duration. Antecedent dry weather period was not found to be a sensitive parameter except for the shrub under light rainfalls. The relative errors of runoff and dynamic mean runoff (60 min) for lawn and shrub were within ± 9.5%. The errors of peak flow ranged between − 21 and 16.6%. The dynamic runoff characteristics and the parameters for lawn and shrub determined in this study can provide references for simulating urban runoff and planning LID areas. |
| abstract_unstemmed |
Abstract The characteristics of surface runoff and the infiltration properties of urban green land are important to determine the effects of runoff reduction by low-impact development (LID) facilities. In this paper, two typical types of urban green land (lawn and shrub) in Shanghai were selected to study the runoff characteristics under eight rainfall events. The sensitivity of the runoff parameters was analyzed, and then, the optimal parameters were determined using the Stormwater Management Model (SWMM). The results showed that the interception and infiltration capacities of shrub were greater than those of lawn. The rainfall intensity and rainfall pattern were the major factors that influenced the interception and infiltration of rainwater. The threshold value that generates runoff varied across the eight rainfall events ranged from 1.6 to 28.5 mm for lawn and 4.5 to 32.0 mm for shrub. The maximum reduction ratios of runoff and peak flow for shrub were 52 and 57% higher than them for lawn, respectively. The parameters for shrub were more sensitive to runoff and peak flow compared with those for lawn. Under light rainfalls with a short duration, the maximum infiltration rate and depression storage were more sensitive than those under heavy rainfalls with a long duration. Antecedent dry weather period was not found to be a sensitive parameter except for the shrub under light rainfalls. The relative errors of runoff and dynamic mean runoff (60 min) for lawn and shrub were within ± 9.5%. The errors of peak flow ranged between − 21 and 16.6%. The dynamic runoff characteristics and the parameters for lawn and shrub determined in this study can provide references for simulating urban runoff and planning LID areas. |
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Runoff simulation of two typical urban green land types with the Stormwater Management Model (SWMM): sensitivity analysis and calibration of runoff parameters |
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https://dx.doi.org/10.1007/s10661-019-7445-9 |
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Xiong, Lijun Li, Huaizheng Xu, Jin Cai, Xin Chen, Keli Wu, Jun |
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|
| score |
7.40236 |