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Lin F, Ren H, Qin J, Wang M, Shi M, Li Y, Wang R, Hu Y. Analysis of pollutant dispersion patterns in rivers under different rainfall based on an integrated water-land model. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 354:120314. [PMID: 38401493 DOI: 10.1016/j.jenvman.2024.120314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 02/05/2024] [Accepted: 02/06/2024] [Indexed: 02/26/2024]
Abstract
In the context of rapid urban expansion, the interaction between humanity and nature has become more prominent. Urban land and rivers often exist as distinct entities with limited material exchange. However, during rainfall, these two systems interconnect, resulting in the transfer of land-derived pollutants into rivers. Such transfer significantly increases river pollutant levels, adversely affecting water quality. Therefore, developing a water quality simulation and prediction model is crucial. This model should effectively illustrate pollutant movement and dispersion during rain events. This study proposes a comprehensive model that merges the Storm Water Management Model (SWMM) with the Environmental Fluid Dynamics Code (EFDC). This integrated model assesses the spread and dispersion of pollutants, including Ammonia Nitrogen (NH3-N), Total Phosphorus (TP), Total Nitrogen (TN), and Chemical Oxygen Demand (COD), within urban water cycles for various rainfall conditions, thus offering critical theoretical support for managing the water environment. The application of this model under different rainfall intensities (light, moderate and heavy) provides vital insights. During light rainfall, the river's natural purification process can sustain surface water quality at Class IV. Moderate rainfall causes accumulation of pollutants, reducing water quality to Class V. Conversely, heavy rainfall rapidly increases pollutant concentrations due to higher inflow, pushing the river to a degraded Class V status, which is beyond its natural purification capacity, necessitating engineering solutions to reattain Class IV quality. Furthermore, pollutant accumulation in downstream river sections is more influenced by flow rate than by rainfall intensity. In summary, the SWMM-EFDC integrated model proves highly effective in predicting river water quality, thereby significantly aiding urban water pollution control.
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Affiliation(s)
- Fei Lin
- Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, 230031 Hefei, China; Intelligent Agriculture Engineering Laboratory of Anhui Province, 230031 Hefei, China; Hefei Institutes of Collabrative Innovation for Intelligent Agriculture, 231131 Hefei, China; Hefei Intelligent Agricultural Valley Co., Ltd, 231131 Hefei, China
| | - Honglei Ren
- College of Civil Engineering, Hefei University of Technology, 230009 Hefei, China
| | - Jingsha Qin
- Hefei Intelligent Agricultural Valley Co., Ltd, 231131 Hefei, China; School of Resources and Environmental Engineering, Anhui University, 230601 Hefei, China
| | - Manqi Wang
- Hefei Intelligent Agricultural Valley Co., Ltd, 231131 Hefei, China; School of Resources and Environmental Engineering, Anhui University, 230601 Hefei, China
| | - Ming Shi
- Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, 230031 Hefei, China; Intelligent Agriculture Engineering Laboratory of Anhui Province, 230031 Hefei, China; Hefei Institutes of Collabrative Innovation for Intelligent Agriculture, 231131 Hefei, China
| | - Yucheng Li
- Hefei Intelligent Agricultural Valley Co., Ltd, 231131 Hefei, China; School of Resources and Environmental Engineering, Anhui University, 230601 Hefei, China
| | - Rujing Wang
- Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, 230031 Hefei, China; Intelligent Agriculture Engineering Laboratory of Anhui Province, 230031 Hefei, China; Hefei Institutes of Collabrative Innovation for Intelligent Agriculture, 231131 Hefei, China; Hefei Intelligent Agricultural Valley Co., Ltd, 231131 Hefei, China
| | - Yimin Hu
- Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, 230031 Hefei, China; Intelligent Agriculture Engineering Laboratory of Anhui Province, 230031 Hefei, China; Hefei Institutes of Collabrative Innovation for Intelligent Agriculture, 231131 Hefei, China; Hefei Intelligent Agricultural Valley Co., Ltd, 231131 Hefei, China.
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Dell'Oca A, Guadagnini A, Riva M. Probabilistic assessment of failure of infiltration structures under model and parametric uncertainty. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 344:118466. [PMID: 37421819 DOI: 10.1016/j.jenvman.2023.118466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 06/09/2023] [Accepted: 06/18/2023] [Indexed: 07/10/2023]
Abstract
We focus on the quantification of the probability of failure (PF) of an infiltration structure, of the kind that is typically employed for the implementation of low impact development strategies in urban settings. Our approach embeds various sources of uncertainty. These include (a) the mathematical models rendering key hydrological traits of the system and the ensuing model parametrization as well as (b) design variables related to the drainage structure. As such, we leverage on a rigorous multi-model Global Sensitivity Analysis framework. We consider a collection of commonly used alternative models to represent our knowledge about the conceptualization of the system functioning. Each model is characterized by a set of uncertain parameters. As an original aspect, the sensitivity metrics we consider are related to a single- and a multi-model context. The former provides information about the relative importance that model parameters conditional to the choice of a given model can have on PF. The latter yields the importance that the selection of a given model has on PF and enables one to consider at the same time all of the alternative models analyzed. We demonstrate our approach through an exemplary application focused on the preliminary design phase of infiltration structures serving a region in the northern part of Italy. Results stemming from a multi-model context suggest that the contribution arising from the adoption of a given model is key to the quantification of the degree of importance associated with each uncertain parameter.
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Affiliation(s)
- Aronne Dell'Oca
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Carrer de Jordi Girona, 18-26, 08304, Barcelona, Spain; Dipartimento di Ingegneria Civile e Ambientale (DICA), Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milano, Italy
| | - Alberto Guadagnini
- Dipartimento di Ingegneria Civile e Ambientale (DICA), Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milano, Italy; Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, 85721, USA
| | - Monica Riva
- Dipartimento di Ingegneria Civile e Ambientale (DICA), Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milano, Italy; Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, 85721, USA.
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Modeling the Hydrologic Performance and Cost-Effectiveness of LID in a Residential Park Area Using a Decentralized Design Approach. HYDROLOGY 2022. [DOI: 10.3390/hydrology9040062] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Low Impact Development (LID) is one of the current research interests toward green infrastructures and urban flood control that have the capability to return developed watersheds to pre-development hydrological conditions, bringing numerous water quantity and quality benefits, while being cheaper than their traditional counterparts. However, there is a current research gap about LIDs within tropical regions. This study aims to evaluate the cost efficiency of LID scenarios in varying surface areas through a cost-effectiveness (C/E) analysis and to assess flow reduction and infiltration improvement of the cost-effective LID scenarios using US EPA Stormwater Management Model (SWMM) in a tropical residential catchment receiving an annual rainfall of 1780.5 mm (70.1″), under a Type 1 Philippine Climate. Results have shown that the Weibull plotting position generated the largest rainfall amounts. A total of 2112 manually simulated LID scenarios were modeled to obtain the cost-effective or optimal LID scenarios, where they can generate a maximum of 38.67% flow reduction and 29.73% peak flow reduction, all observed in the multiple LID scenarios. At high rainfall amounts, the multiple LID scenarios can also peak at a 1113% increase in total infiltration in the given sub-catchments. Determining the target capture goal, applicable LID types, and cost estimations from a pilot project are vital components in the future application of LIDs in these regions.
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Comparison of the Engineering Strategies for Low Impact Development in a Densely Populated Old Urban Area. WATER 2022. [DOI: 10.3390/w14071149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Most old urban areas of China have a dense population, severely indurated underlying surface, and highly developed underground space. Those increase the waterlogging risk and obstruct the stormwater management in old urban areas. To propose an appropriate engineering strategy for low impact development (LID) transformation in an urban area, a simulation was carried out by storm water management model (SWMM) in this project. Bioretention cells, permeable pavements, and green roofs were selected according to the study area surface. Runoff control performance of single LID control and combined schemes were compared. Results illustrate that only 50.21% of roofs can build green roofs in urban areas with dense populations, and the runoff control performance of green roofs is unsatisfactory, while bioretention cells and permeable pavements can effectively mitigate runoff caused by storms with a recurrence period less than 10 years, and combined LID controls can obtain better runoff control performance with less construction area. Those outcomes screened out the LID controls suitable for application in densely populated old urban areas and put forward reasonable engineering practice strategies. This study provides guidance and reference for the LID transformation in the densely populated old urban area.
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