A Theoretical Nonlinear Regression Model of Rainfall Surface Flow Accumulation and Basin Features in Park-Scale Urban Green Spaces Based on LiDAR Data
Green infrastructure is imperative for efficiently mitigating flood disasters in urban areas. However, inadequate green space planning under rapid urbanization is a critical issue faced by most Chinese cities. Aimed at theoretically understanding the rainwater storage capacity and improvement potent...
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MDPI AG
2023-07-01
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| Online Access: | https://www.mdpi.com/2073-4441/15/13/2442 |
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| author | Hengshuo Huang Yuan Tian Mengjia Wei Xiaoli Jia Peng Wang Aidan C. Ackerman Siddharth G. Chatterjee Yang Liu Guohang Tian |
| author_facet | Hengshuo Huang Yuan Tian Mengjia Wei Xiaoli Jia Peng Wang Aidan C. Ackerman Siddharth G. Chatterjee Yang Liu Guohang Tian |
| author_sort | Hengshuo Huang |
| collection | DOAJ |
| description | Green infrastructure is imperative for efficiently mitigating flood disasters in urban areas. However, inadequate green space planning under rapid urbanization is a critical issue faced by most Chinese cities. Aimed at theoretically understanding the rainwater storage capacity and improvement potential of urban green spaces, a synthetic simulation model was developed to quantify rainfall surface flow accumulation (FA) based on the morphological factors of a flow basin: the area, circumference, maximum basin length, and stream length sum. This model consisted of applying the Urban Forest Effects-Hydrology model (UFORE-Hydro) to simulate the actual precipitation-to-surface runoff ratio through a procedure involving canopy interception, soil infiltration, and evaporation; additionally, a relatively accurate multiple flow direction-maximum downslope (MFD-md) algorithm was applied to distribute the surface flow in a highly realistic manner, and a self-built “extraction algorithm” extracted the surface runoff corresponding to each studied basin alongside four fundamental morphological parameters. The various nonlinear regression functions were assessed from both univariable and multivariable perspectives. We determined that the Gompertz function was optimal for predicting the theoretical quantification of surface FA according to the morphological features of any given basin. This article provides parametric vertical design guidance for improving the rainwater storage capacities of urban green spaces. |
| first_indexed | 2024-03-11T01:25:40Z |
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| id | doaj.art-a1a2238a92b74d05927cb63b2b11cd4d |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-11T01:25:40Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
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| series | Water |
| spelling | doaj.art-a1a2238a92b74d05927cb63b2b11cd4d2023-11-18T17:48:20ZengMDPI AGWater2073-44412023-07-011513244210.3390/w15132442A Theoretical Nonlinear Regression Model of Rainfall Surface Flow Accumulation and Basin Features in Park-Scale Urban Green Spaces Based on LiDAR DataHengshuo Huang0Yuan Tian1Mengjia Wei2Xiaoli Jia3Peng Wang4Aidan C. Ackerman5Siddharth G. Chatterjee6Yang Liu7Guohang Tian8College of Environmental Science and Forestry, State University of New York, 1 Forestry Drive, Syracuse, NY 13210, USAGeophysical Institute, University of Alaska Fairbanks, 2156 Koyukuk Drive, Fairbanks, AK 99775, USACollege of Landscape Architecture and Art, Henan Agricultural University, No. 63 Nongye Road, Zhengzhou 450002, ChinaInstitute of Landscape Architecture, Urban Planning and Garden Art, Hungarian University of Agriculture and Life Sciences (MATE), Vármegye u. 3-5, 1052 Budapest, HungaryManagement Centre of Zhengzhou Green Expo Park, Renwen Road, Zhengzhou 451464, ChinaCollege of Environmental Science and Forestry, State University of New York, 1 Forestry Drive, Syracuse, NY 13210, USACollege of Environmental Science and Forestry, State University of New York, 1 Forestry Drive, Syracuse, NY 13210, USACollege of Landscape Architecture and Art, Henan Agricultural University, No. 63 Nongye Road, Zhengzhou 450002, ChinaCollege of Landscape Architecture and Art, Henan Agricultural University, No. 63 Nongye Road, Zhengzhou 450002, ChinaGreen infrastructure is imperative for efficiently mitigating flood disasters in urban areas. However, inadequate green space planning under rapid urbanization is a critical issue faced by most Chinese cities. Aimed at theoretically understanding the rainwater storage capacity and improvement potential of urban green spaces, a synthetic simulation model was developed to quantify rainfall surface flow accumulation (FA) based on the morphological factors of a flow basin: the area, circumference, maximum basin length, and stream length sum. This model consisted of applying the Urban Forest Effects-Hydrology model (UFORE-Hydro) to simulate the actual precipitation-to-surface runoff ratio through a procedure involving canopy interception, soil infiltration, and evaporation; additionally, a relatively accurate multiple flow direction-maximum downslope (MFD-md) algorithm was applied to distribute the surface flow in a highly realistic manner, and a self-built “extraction algorithm” extracted the surface runoff corresponding to each studied basin alongside four fundamental morphological parameters. The various nonlinear regression functions were assessed from both univariable and multivariable perspectives. We determined that the Gompertz function was optimal for predicting the theoretical quantification of surface FA according to the morphological features of any given basin. This article provides parametric vertical design guidance for improving the rainwater storage capacities of urban green spaces.https://www.mdpi.com/2073-4441/15/13/2442surface runoff<i>k</i>-means clusterhydrological modeltheoretical simulationextraction algorithmMFD-md |
| spellingShingle | Hengshuo Huang Yuan Tian Mengjia Wei Xiaoli Jia Peng Wang Aidan C. Ackerman Siddharth G. Chatterjee Yang Liu Guohang Tian A Theoretical Nonlinear Regression Model of Rainfall Surface Flow Accumulation and Basin Features in Park-Scale Urban Green Spaces Based on LiDAR Data Water surface runoff <i>k</i>-means cluster hydrological model theoretical simulation extraction algorithm MFD-md |
| title | A Theoretical Nonlinear Regression Model of Rainfall Surface Flow Accumulation and Basin Features in Park-Scale Urban Green Spaces Based on LiDAR Data |
| title_full | A Theoretical Nonlinear Regression Model of Rainfall Surface Flow Accumulation and Basin Features in Park-Scale Urban Green Spaces Based on LiDAR Data |
| title_fullStr | A Theoretical Nonlinear Regression Model of Rainfall Surface Flow Accumulation and Basin Features in Park-Scale Urban Green Spaces Based on LiDAR Data |
| title_full_unstemmed | A Theoretical Nonlinear Regression Model of Rainfall Surface Flow Accumulation and Basin Features in Park-Scale Urban Green Spaces Based on LiDAR Data |
| title_short | A Theoretical Nonlinear Regression Model of Rainfall Surface Flow Accumulation and Basin Features in Park-Scale Urban Green Spaces Based on LiDAR Data |
| title_sort | theoretical nonlinear regression model of rainfall surface flow accumulation and basin features in park scale urban green spaces based on lidar data |
| topic | surface runoff <i>k</i>-means cluster hydrological model theoretical simulation extraction algorithm MFD-md |
| url | https://www.mdpi.com/2073-4441/15/13/2442 |
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