Uncertainty analysis of urban sewer system using spatial simulation of radar rainfall fields: New York City case study
The goal of this study is to investigate the uncertainty of an urban sewer system’s response under various rainfall and infrastructure scenarios by applying a recently developed nonparametric copula-based simulation approach to extreme rainfall fields. The approach allows for Monte Carlo simulation...
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| Veröffentlicht in: | Stochastic environmental research and risk assessment 2018-08, Vol.32 (8), p.2293-2308 |
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| creator | Hamidi, Ali Farnham, David J. Khanbilvardi, Reza |
| description | The goal of this study is to investigate the uncertainty of an urban sewer system’s response under various rainfall and infrastructure scenarios by applying a recently developed nonparametric copula-based simulation approach to extreme rainfall fields. The approach allows for Monte Carlo simulation of multiple variables with differing marginal distributions and arbitrary dependence structure. The independent and identically distributed daily extreme rainfall events of the corresponding urban area, extracted from nationwide high resolution radar data stage IV, are the inputs of the spatial simulator. The simulated extreme rainfall fields were used to calculate excess runoff using the Natural Resources Conservation Service’s approach. New York City is selected as a case study and the results highlight the importance of preserving the spatial dependence of rainfall fields between the grids, even for simplified hydrologic models. This study estimates the probability of combined sewer overflows under extreme rainfall events and identifies the most effective locations in New York City to install green infrastructure for detaining excess stormwater runoff. The results of this study are beneficial for planners working on stormwater management and the approach is broadly applicable because it does not rely on extensive sewer system information. |
| doi_str_mv | 10.1007/s00477-018-1563-8 |
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The approach allows for Monte Carlo simulation of multiple variables with differing marginal distributions and arbitrary dependence structure. The independent and identically distributed daily extreme rainfall events of the corresponding urban area, extracted from nationwide high resolution radar data stage IV, are the inputs of the spatial simulator. The simulated extreme rainfall fields were used to calculate excess runoff using the Natural Resources Conservation Service’s approach. New York City is selected as a case study and the results highlight the importance of preserving the spatial dependence of rainfall fields between the grids, even for simplified hydrologic models. This study estimates the probability of combined sewer overflows under extreme rainfall events and identifies the most effective locations in New York City to install green infrastructure for detaining excess stormwater runoff. 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Appl. in Environmental Science ; Monte Carlo simulation ; Natural resources ; Original Paper ; Physics ; Probability Theory and Stochastic Processes ; Radar ; Radar data ; Rainfall ; Resource conservation ; Runoff ; Sewer systems ; Spatial distribution ; Statistics for Engineering ; Storm runoff ; Stormwater ; Stormwater management ; Uncertainty analysis ; Urban areas ; Waste Water Technology ; Water Management ; Water Pollution Control</subject><ispartof>Stochastic environmental research and risk assessment, 2018-08, Vol.32 (8), p.2293-2308</ispartof><rights>The Author(s) 2018</rights><rights>Stochastic Environmental Research and Risk Assessment is a copyright of Springer, (2018). All Rights Reserved. © 2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). 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The approach allows for Monte Carlo simulation of multiple variables with differing marginal distributions and arbitrary dependence structure. The independent and identically distributed daily extreme rainfall events of the corresponding urban area, extracted from nationwide high resolution radar data stage IV, are the inputs of the spatial simulator. The simulated extreme rainfall fields were used to calculate excess runoff using the Natural Resources Conservation Service’s approach. New York City is selected as a case study and the results highlight the importance of preserving the spatial dependence of rainfall fields between the grids, even for simplified hydrologic models. This study estimates the probability of combined sewer overflows under extreme rainfall events and identifies the most effective locations in New York City to install green infrastructure for detaining excess stormwater runoff. The results of this study are beneficial for planners working on stormwater management and the approach is broadly applicable because it does not rely on extensive sewer system information.</description><subject>Aquatic Pollution</subject><subject>Case studies</subject><subject>Chemistry and Earth Sciences</subject><subject>Combined sewer overflows</subject><subject>Computational Intelligence</subject><subject>Computer Science</subject><subject>Computer simulation</subject><subject>Dependence</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Environment</subject><subject>Extreme weather</subject><subject>Green infrastructure</subject><subject>Hydrologic models</subject><subject>Hydrology</subject><subject>Information systems</subject><subject>Infrastructure</subject><subject>Math. Appl. in Environmental Science</subject><subject>Monte Carlo simulation</subject><subject>Natural resources</subject><subject>Original Paper</subject><subject>Physics</subject><subject>Probability Theory and Stochastic Processes</subject><subject>Radar</subject><subject>Radar data</subject><subject>Rainfall</subject><subject>Resource conservation</subject><subject>Runoff</subject><subject>Sewer systems</subject><subject>Spatial distribution</subject><subject>Statistics for Engineering</subject><subject>Storm runoff</subject><subject>Stormwater</subject><subject>Stormwater management</subject><subject>Uncertainty analysis</subject><subject>Urban areas</subject><subject>Waste Water Technology</subject><subject>Water Management</subject><subject>Water Pollution Control</subject><issn>1436-3240</issn><issn>1436-3259</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kD1PwzAQhiMEEhX0B7BZYg74M3HYUMWXVMFSBibLcS6VIXWKL6HKv8dVEUwsdzc87yvdk2UXjF4xSstrpFSWZU6ZzpkqRK6PshmTosgFV9Xx7y3paTZH9HXKKFFVjM6yr9fgIA7Wh2EiNthuQo-kb8kYaxsIwg4iwQkH2JARfVgT3NrB246g34xdOvuwx6NtbEzTh9Z2HWk9dA3ekGfYkbc-fpCFT_3OIhAcxmY6z04ShzD_2WfZ6v5utXjMly8PT4vbZe6EqoZcqpJpKiSHVtQlcA0CgKuGKy0b2VJX16IotLUKqJPONo0qHSslKxnVXImz7PJQu4395wg4mPd-jOlLNJwqKatCS54odqBc7BEjtGYb_cbGyTBq9oLNQbBJgs1esNEpww8ZTGxYQ_xr_j_0DQBjfwQ</recordid><startdate>20180801</startdate><enddate>20180801</enddate><creator>Hamidi, Ali</creator><creator>Farnham, David J.</creator><creator>Khanbilvardi, Reza</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7ST</scope><scope>7XB</scope><scope>88I</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>KR7</scope><scope>L6V</scope><scope>M2P</scope><scope>M7S</scope><scope>PATMY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>S0W</scope><scope>SOI</scope><orcidid>https://orcid.org/0000-0001-6235-0303</orcidid></search><sort><creationdate>20180801</creationdate><title>Uncertainty analysis of urban sewer system using spatial simulation of radar rainfall fields: New York City case study</title><author>Hamidi, Ali ; Farnham, David J. ; Khanbilvardi, Reza</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c359t-457180342ef3b7e28e3ee25d2584d4f0cbb3668aa5e0c4cadd57c17417108253</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Aquatic Pollution</topic><topic>Case studies</topic><topic>Chemistry and Earth Sciences</topic><topic>Combined sewer overflows</topic><topic>Computational Intelligence</topic><topic>Computer Science</topic><topic>Computer simulation</topic><topic>Dependence</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Environment</topic><topic>Extreme weather</topic><topic>Green infrastructure</topic><topic>Hydrologic models</topic><topic>Hydrology</topic><topic>Information systems</topic><topic>Infrastructure</topic><topic>Math. 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The approach allows for Monte Carlo simulation of multiple variables with differing marginal distributions and arbitrary dependence structure. The independent and identically distributed daily extreme rainfall events of the corresponding urban area, extracted from nationwide high resolution radar data stage IV, are the inputs of the spatial simulator. The simulated extreme rainfall fields were used to calculate excess runoff using the Natural Resources Conservation Service’s approach. New York City is selected as a case study and the results highlight the importance of preserving the spatial dependence of rainfall fields between the grids, even for simplified hydrologic models. This study estimates the probability of combined sewer overflows under extreme rainfall events and identifies the most effective locations in New York City to install green infrastructure for detaining excess stormwater runoff. The results of this study are beneficial for planners working on stormwater management and the approach is broadly applicable because it does not rely on extensive sewer system information.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s00477-018-1563-8</doi><tpages>16</tpages><orcidid>https://orcid.org/0000-0001-6235-0303</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Aquatic Pollution Case studies Chemistry and Earth Sciences Combined sewer overflows Computational Intelligence Computer Science Computer simulation Dependence Earth and Environmental Science Earth Sciences Environment Extreme weather Green infrastructure Hydrologic models Hydrology Information systems Infrastructure Math. Appl. in Environmental Science Monte Carlo simulation Natural resources Original Paper Physics Probability Theory and Stochastic Processes Radar Radar data Rainfall Resource conservation Runoff Sewer systems Spatial distribution Statistics for Engineering Storm runoff Stormwater Stormwater management Uncertainty analysis Urban areas Waste Water Technology Water Management Water Pollution Control |
| title | Uncertainty analysis of urban sewer system using spatial simulation of radar rainfall fields: New York City case study |
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