Evaluate the potential of permeable pavement for urban runoff reduction DOI Creative Commons

Qingchi Cai,

Jen‐Yang Lin, Chi‐Feng Chen

и другие.

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Фев. 22, 2024

Abstract Permeable pavement (PP) is one of the widely adopted low-impact development measures in construction for enhancing urban water retention capacity, which has received increasing attention. To assess performance PP surface runoff management, a comprehensive study involving hydrological monitoring and simulation was conducted at site Taipei. In phase, data from 41 effective rainfall events were collected, providing robust dataset analysis effects. Subsequently, six distinct implementations four varied scenarios meticulously designed simulated using Storm Water Management Model (SWMM). The results showed that (1) implementation contributes to mitigating site. observed reduction spans significant range, 5–30.8%, with an average rate approximately 14.6% each event. (2) With return period, percentage total peak decreases. marginal control on both decreased levels implementation. (3) reducing flow time arrival relatively weak. (4) A new indicator defined characterize cost-effectiveness project construction, helps management.

Язык: Английский

Multi-stage optimization framework for synergetic grey-green infrastructure in response to long-term climate variability based on shared socio-economic pathways DOI
Shiqi Zhou,

Haifeng Diao,

Jiahui Wang

и другие.

Water Research, Год журнала: 2025, Номер 274, С. 123091 - 123091

Опубликована: Янв. 6, 2025

Язык: Английский

Процитировано

10
Quantifying the efficacy of Low Impact Developments (LIDs) for flood reduction in micro-urban watersheds incorporating climate change DOI
Amrutha Suresh, Sreeja Pekkat, Senthilmurugan Subbiah

и другие.

Sustainable Cities and Society, Год журнала: 2023, Номер 95, С. 104601 - 104601

Опубликована: Апрель 26, 2023

Язык: Английский

Процитировано

27
Development of hazard capacity factor design model for net-zero: Evaluation of the flood adaptation effects considering green - gray infrastructure interaction DOI

Jaekyoung Kim,

Junsuk Kang

Sustainable Cities and Society, Год журнала: 2023, Номер 96, С. 104625 - 104625

Опубликована: Май 6, 2023

Язык: Английский

Процитировано

24
Integrated SUSTAIN-SWMM-MCDM Approach for Optimal Selection of LID Practices in Urban Stormwater Systems DOI Creative Commons

Amirhossein Nazari,

Abbas Roozbahani, Seied Mehdy Hashemy Shahdany

и другие.

Water Resources Management, Год журнала: 2023, Номер 37(9), С. 3769 - 3793

Опубликована: Май 24, 2023

Abstract Rapid urbanization has increased impervious areas, leading to a higher flood hazard across cities worldwide. Low Impact Development (LID) practices have shown efficacy in reducing urban runoff; nevertheless, choosing the best combinations terms of implementation cost and performance is great importance. The present study introduces framework based on green infrastructure, multi-objective optimization, decision support tools determine most cost-effective LID solutions. Storm Water Management Model (SWMM) was employed for rainfall-runoff hydraulic modeling Region 1, District 11 Tehran, Iran. Six scenarios different were developed. system Urban Stormwater Treatment Analysis Integration (SUSTAIN) used optimize evaluate each scenario. selected solutions imported SWMM stormwater performance. Then, two multi criteria making (MCDM) models, including TOPSIS COPRAS, rank four technical economic criteria. Results showed that scenario 4, consisting rain barrels, porous pavements, vegetated swales, had under with 7.68 million USD reduced runoff volume peak flow by 20.77% 19.2%, respectively. However, Under COPRAS method, Scenario 2 combination bio-retention cells, swales than other 3.25 led 15% reduction 4.30% flow. method more sensitive weights chose economical as ideal. 4 concluded be feasible due spatial limitations area. proposed SWMM—SUSTAIN—MCDM could helpful decision-makers design, evaluation, estimation, selection optimal scenarios.

Язык: Английский

Процитировано

21
Enhancing Urban Drainage Infrastructure Through Implementation of Low Impact Development Techniques DOI

Osheen Mehta,

Mitthan Lal Kansal, Deepak Singh Bisht

и другие.

Water Resources Management, Год журнала: 2024, Номер 38(12), С. 4517 - 4540

Опубликована: Май 6, 2024

Язык: Английский

Процитировано

7
Predicting the performance of green stormwater infrastructure using multivariate long short-term memory (LSTM) neural network DOI Creative Commons
Md Abdullah Al Mehedi, Achira Amur, Jessica L. Metcalf

и другие.

Journal of Hydrology, Год журнала: 2023, Номер 625, С. 130076 - 130076

Опубликована: Авг. 10, 2023

The expected performance of Green Stormwater Infrastructure (GSI) is typically quantified through numerical models based on hydrologic parameters and physics-based equations. With models, the choice a spatio-temporal discretization scheme for computational domain strenuous task that requires extensive calibration potentially lab-based experimentation. GSI has high temporal dynamics due to natural, anthropogenic, climatic processes are not well represented by traditional which calibrated against only few historical observations have user-defined constrained set outcomes. Deep learning-based predictive such as Long Short-Term Memory (LSTM) neural networks, offer an exciting opportunity quantify performance, accounting its highly dynamic constantly evolving nature leveraging advancements in observational data. A LSTM regression can overcome some limitations associated with hydrological aid development fully data-informed predictor. To demonstrate model outcomes, both methods were applied rain garden Villanova, PA, USA. Specifically, was used predict recession ponded water depth using five years observed eight predictors (i.e., precipitation, air temperature, soil moisture content at 10 cm, 35 65 cm 91 depth) target variable rate) considered training/testing model. comparative study USEPA Storm Water Management Model (SWMM) performed observe continuous rate time series specific storms. had score, Root Mean Square Error (RMSE), 0.081 series, outperforming SWMM score 2.173 when compared In case storm-specific prediction, also outperformed simulation four storms lower RMSE values application predicting crucial stride towards efficient real-time forecasting.

Язык: Английский

Процитировано

16
A multi-objective optimization and evaluation framework for LID facilities considering urban surface runoff and shallow groundwater regulation DOI

Yishuo Jiang,

Jiake Li, Jiayu Gao

и другие.

Journal of Cleaner Production, Год журнала: 2024, Номер 478, С. 143921 - 143921

Опубликована: Окт. 9, 2024

Язык: Английский

Процитировано

4
Modeling the First Flush Effect of Urban Micropollutants with Sensitivity Analysis and Uncertainty Analysis DOI

Daeun Yun,

Seok Min Hong, Soobin Kim

и другие.

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
An Uncertainty Analysis of Low-Impact Development Based on the Hydrological Process with Invariant Parameters and Equivalent Effects: Supporting Sustainable Urban Planning DOI Open Access

Xinyi Shu,

Chenlei Ye,

Zongxue Xu

и другие.

Sustainability, Год журнала: 2025, Номер 17(6), С. 2587 - 2587

Опубликована: Март 14, 2025

Climate change and urbanization are increasingly threatening urban environments through pluvial flooding, prompting the widespread use of coupled hydrological–hydrodynamic models. These models provide accurate flood simulations forecasting capabilities, they can analyze benefits low-impact development stormwater control measures in surface-flooding processes. However, most studies have primarily focused on analyzing effects for specific events, lacking an analytical framework that accounts uncertainty. This research proposes a evaluating uncertainty pluvial-flood control, combining urban-scale simulation, modeling, analysis, while constructing nonlinear dependencies between features reflecting surface-flood-control benefits. Based analysis copula methods, this aims to support sustainable planning decision-making approach management. The results show assessment method based generalized likelihood is effective. By comparing posterior joint distribution with prior distribution, different governance performance metrics, joint, synergistic, conditional, combined all exhibit consistent trends as metrics change. current presents innovative simulating at scale, providing valuable insights mitigation strategies.

Язык: Английский

Процитировано

0
Study on SWMM Calibration and Optimizing the Layout of LID Based on Intellgent Algorithm: A Case in Campus DOI
Kehan Liu, Jiake Li, Jiayu Gao

и другие.

Water Resources Management, Год журнала: 2025, Номер unknown

Опубликована: Апрель 8, 2025

Язык: Английский

Процитировано

0