Urban road waterlogging risk assessment based on the source–pathway–receptor concept in Shenzhen, China

Sun, Dianchen; Wang, Huimin; Huang, Jing; Zhang, Jingxuan; Liu, Gao-Feng

doi:10.1111/jfr3.12873

Cited by 8 publications

(3 citation statements)

References 45 publications

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“…After doing extensive research on the flooding problem, researchers both at home and abroad have developed a systematic system of flooding risk assessment methodologies (Zheng et al 2022;Sun et al 2022). This paper's novelty is to combine the CATREG with the AHP technique, which enhances the accuracy of the flood risk assessment model while weakening the AHP method's shortcomings in giving weights that are more subjective.…”

Section: Categorical Regression and Analytic Hierarchy Processmentioning

confidence: 99%

Urban flooding risk assessment from an categorical regression-analytic hierarchy process

Ren

Wei

Wang

et al. 2023

Preprint

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The rapid development of urbanization and the impact of human activities have increased the impermeability of urban underlying surfaces, and the drainage capacity of urban drainage systems cannot meet the needs of cities, leading to frequent urban waterlogging. Taking the main urban area of Fuxin City in Liaoning Province as an example, this paper establishes a coupled hydrodynamic model based on Infoworks ICM model to simulate urban waterlogging. Six index factors are chosen for categorical regression(CATREG) and the analytic hierarchy process(AHP) to establish a model for waterlogging risk assessment by analyzing the three components of the urban waterlogging disaster system, the hazard-causing factors, the hazard-forming environment, and the disaster-affected body. The scenario simulation results and the index system technique are used to develop an urban waterlogging risk assessment model, and GIS spatial analysis technology is used to create an intuitive risk assessment map. The findings reveal that: (1) the optimal coupling of several risk assessment models for urban flooding risk assessment improves the assessment results' comprehensiveness and integration, and can provide a stable foundation for urban flooding management. (2) The dense distribution of pipelines in the study area's city center and the distribution of water outlets in the city's southern part have resulted in the distribution of flood-prone spots in the city's southern part, and reconstruction of underground pipeline networks and the construction of drainage pumping stations should be completed around it to reduce the risk level of this area.

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Section: Categorical Regression and Analytic Hierarchy Processmentioning

confidence: 99%

Urban flooding risk assessment from an categorical regression-analytic hierarchy process

Ren

Wei

Wang

et al. 2023

Preprint

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“…Existing risk assessment methods include RPN (Risk Priority Number) for sorting internal system component failures and using fault trees [ 14 ], Bayesian networks [ 15 ], and Markov chains [ 16 ], which are used to study interrelationships among risks. Similarly, SPRC [ 17 ], FMEA [ 18 ], and influence diagrams [ 19 ] are adept at assessing the impact of singular events like floods or fires. These techniques provide avenues for quantitatively assessing continuous risks posed by sensor failures in information gathering, decision-making, and execution.…”

Section: Introductionmentioning

confidence: 99%

A Risk Evaluation Framework in System Control Subject to Sensor Degradation and Failure

Yuan,

Xu,

Adjallah

et al. 2024

Sensors

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Sensor degradation and failure often undermine users’ confidence in adopting a new data-driven decision-making model, especially in risk-sensitive scenarios. A risk assessment framework tailored to classification algorithms is introduced to evaluate the decision-making risks arising from sensor degradation and failures in such scenarios. The framework encompasses various steps, including on-site fault-free data collection, sensor failure data collection, fault data generation, simulated data-driven decision-making, risk identification, quantitative risk assessment, and risk prediction. Leveraging this risk assessment framework, users can evaluate the potential risks of decision errors under the current data collection status. Before model adoption, ranking risk sensitivity to sensor data provides a basis for optimizing data collection. During the use of decision algorithms, considering the expected lifespan of sensors enables the prediction of potential risks the system might face, offering comprehensive information for sensor maintenance. This method has been validated through a case study involving an access control.

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“…In freshwater systems, lakes are considered receptors or sinks in which material and pollutants tend to accumulate and pathways are processes of transport, dilution, and transformation of pollutants in their catchments. The SPR model has been applied as a simple conceptual model for illustrating systems and processes leading to a specific outcome in several environmental risk assessments [10][11][12], such as flood risks and erosion [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Investigating the Impact of Wildfires on Lake Water Quality Using Earth Observation Satellites

Caroni,

Pinardi,

Free

et al. 2024

Applied Sciences

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A study was carried out to investigate the effects of wildfires on lake water quality using a source dataset of 2024 lakes worldwide, covering different lake types and ecological settings. Satellite-derived datasets (Lakes_cci and Fire_cci) were used and a Source Pathway Receptor approach applied which was conceptually represented by fires (burned area) as a source, precipitation/drought representing transport dynamics, and lakes as the ultimate receptor. This identified 106 lakes worldwide that are likely prone to be impacted by wildfires via a terrestrial pathway. Satellite-derived chlorophyll-a (Chl-a) and turbidity variables were used as indicators to detect changes in lake water quality potentially induced by wildfires over a four-year period. The lakes with the largest catchment areas burned and characterized by regular annual fires were located in Africa. Evidence for a strong influence of wildfires was not found across the dataset examined, although clearer responses were seen for some individual lakes. However, among the hydro-morphological characteristics examined, lake depth was found to be significant in determining Chl-a concentration peaks which were higher in shallow and lower in deep lakes. Lake turbidity responses indicated a dependence on lake catchment and weather conditions. While wildfires are likely to contribute to the nutrient load of lakes as found in previous studies, it is possible that in many cases it is not a dominant pressure and that its manifestation as a signal in lake Chl-a or turbidity values depends to a large part on lake typology and catchment characteristics. Assessment of lake water quality changes six months after a fire showed that Chl-a concentrations either increased, decreased, or showed no changes in a similar number of lakes, indicating that a lake specific ecological and hydro-morphological context is important for understanding lake responses to wildfires.

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Urban road waterlogging risk assessment based on the source–pathway–receptor concept in Shenzhen, China

Cited by 8 publications

References 45 publications

Urban flooding risk assessment from an categorical regression-analytic hierarchy process

Urban flooding risk assessment from an categorical regression-analytic hierarchy process

A Risk Evaluation Framework in System Control Subject to Sensor Degradation and Failure

Investigating the Impact of Wildfires on Lake Water Quality Using Earth Observation Satellites

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