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2020 | OriginalPaper | Buchkapitel

20. Model Improvement for Effect Evaluation of Low Impact Development Measures

verfasst von : Yuting Meng, Na Li, Jing Wang, Qian Yu, Nianqiang Zhang

Erschienen in: Advances in Hydroinformatics

Verlag: Springer Singapore

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Abstract

Low impact development (LID) practices, such as bioretention and green roof, aim to increase infiltration and retention to manage urban flood. Flood simulation model is an effective tool for scheme comparison at the design stage. In addition, it is also a good method to evaluate the effects of LID after construction. The Flood Risk Analysis Software (FRAS), developed independently by China Institute of Water Resources and Hydropower Research (IWHR), is integrated software that can simulate the whole flood process, mainly including 1D-2D coupling hydraulic model, hydrological model and drainage model. And FRAS also has accurate and reasonable structure routines for urban flood simulation because of the coupling calculation of different models. In order to reflect the influences of LID measures on runoff generation and confluence more accurately, the following improvements were made based on the original software: (1) The SCS method is added to the original rainfall-runoff model due to its simple but sensitive parameter, which can comprehensively reflect initial soil moisture, soil type and land use type of different LID measures. Additionally, it is coupled with the 2D surface hydraulic model in real-time to precisely describe the infiltration process. (2) According to the main functions and characteristics of different LID practices, three typical measures, i.e., green roof, bioretention and porous pavement, are set as special land use types, respectively. The parameters and calculation methods are adjusted accordingly in the model. After these improvements, the model can have more precise simulation about the increased infiltration and flood retention of LID measures.

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Metadaten
Titel
Model Improvement for Effect Evaluation of Low Impact Development Measures
verfasst von
Yuting Meng
Na Li
Jing Wang
Qian Yu
Nianqiang Zhang
Copyright-Jahr
2020
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-15-5436-0_20