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Resilience assessment for urban drainage systems is a fundamental aspect of building resilient cities. Recently, some scholars have proposed the Global Resilience Analysis (GRA) method, which assesses resilience based on the functional performance of different system failure scenarios. Compared to traditional system dynamics methods, the GRA method considers the impact of internal structural failure on resilience but requires a large amount of computation. This research proposed an improved GRA method to enhance computational efficiency and practicality by reducing the number of system scenario simulations. Firstly, a hydrodynamic model of the drainage network of Haidian Island has been constructed using the Storm Water Management Model (SWMM) and Python. Secondly, the GRA method was improved using cluster analysis and convergence analysis to reduce the simulation scenarios. Thirdly, a resilience assessment index was established through system function functions, and two types of resilience enhancement measures, centralized and distributed, were proposed. The results show: (i) resilience assessment increases the computational efficiency by 25% compared to the traditional GRA method; (ii) the resilience index of the existing drainage network within Haidian Island is less than the design value (0.7) in all failure scenarios, indicating a lower level of recovery capability; (iii) compared to the centralized strategy, which is only effective when the system failure level is less than 9%, the distributed strategy enhances the resilience of the urban drainage system at a higher failure level (77%).
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Cidades , China , Modelos Teóricos , IlhasRESUMO
China produces a large amount of industrial effluent with multiple pollutants contained, along with a flourishing economy. This study aims to examine the dynamics between China's industrialization and accompanying environmental pressure based on the gray water footprint (GWF) concept. A newly proposed net GWF (NetGWF) and the decoupling index (DI) are applied to evaluate China's industrial activities during 2002-2015 in different modes considering typical, all, and individual pollutants. The NetGWF dynamics are further quantitatively decomposed into 17 effects of not only commonly assessed drivers but also industrial fixed capital formation, inventory variation, and import, using an advanced dynamic decomposition analysis approach. Results show NetGWF is an effective indicator measuring domestic water pollution stress from industrialization, with NetGWF-AllPlt (estimated using all pollutants) validated to be more reliable and sensitive than NetGWF-COD&NH3N (estimated using Chemical oxygen demand and Ammonia nitrogen). An overall decoupling between China's industrialization and wastewater pollution is identified with most of DIs less than 1.0 caused mainly by decreased (by around 40%) industrial NetGWFs for 2002-2015. Industrial fixed capital formation and export have caused main components of China's industrial GWF, with proportions of 37.3% and 30.8%, respectively, followed by urban household consumption (16.8%). Volatile phenol, Petroleum, and Ammonia nitrogen are recognized as three decisive contaminants to the industrial NetGWFs. Technological development is the dominant contributor (-50%) to decreasing China's industrial NetGWFs, while fixed capital formation (18%) and export (16%) are principal drivers increasing the NetGWFs. Based on these, we expect to provide informative findings for building a pollution-decoupled industrialization.
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Poluentes Ambientais , Desenvolvimento Industrial , Análise da Demanda Biológica de Oxigênio , China , Água , Poluição da ÁguaRESUMO
Investigation into water resources sustainability (WRS) is vital for a regional sustainable development strategy. This paper aimed to quantitatively evaluate the WRS in mainland China using a three-layer indicator system. Three important factors significantly affecting WRS are: water resources quantity (WRQ), water intensity (WI) and water efficiency (WE). Assessment of the three indicators was carried out in 356 cities where each indicator was graded from "very low" to "very high" according to the value magnitude. China was then classified into four zones to differentiate regional variations of the impact of water intensity and efficiency on sustainability. Results showed that 34% of the areas had "medium" to "high" WI indicator values and 58% of the areas had "low" to "very low" WE indicator values. The indicator values of WI were ordered as Zone I > Zone II > Zone III > Zone IV; whereas the WRS were ordered as: Zone I < Zone II < Zone III < Zone IV. It is recommended that water resource policies be turned to a more sustainable management strategy in areas with high WI and low WE. Zone I regions should be focused on particularly with limited resources and extreme exploitation. The results provide a valuable basis for macro-level decision-making concerned with regional sustainable development strategy for the entire mainland China.
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Recursos Hídricos , Água , China , Cidades , Conservação dos Recursos NaturaisRESUMO
Flood is a serious challenge that increasingly affects the residents as well as policymakers. Flood vulnerability assessment is becoming gradually relevant in the world. The purpose of this study is to develop an approach to reveal the relationship between exposure, sensitivity and adaptive capacity for better flood vulnerability assessment, based on the fuzzy comprehensive evaluation method (FCEM) and coordinated development degree model (CDDM). The approach is organized into three parts: establishment of index system, assessment of exposure, sensitivity and adaptive capacity, and multiple flood vulnerability assessment. Hydrodynamic model and statistical data are employed for the establishment of index system; FCEM is used to evaluate exposure, sensitivity and adaptive capacity; and CDDM is applied to express the relationship of the three components of vulnerability. Six multiple flood vulnerability types and four levels are proposed to assess flood vulnerability from multiple perspectives. Then the approach is applied to assess the spatiality of flood vulnerability in Hainan's eastern area, China. Based on the results of multiple flood vulnerability, a decision-making process for rational allocation of limited resources is proposed and applied to the study area. The study shows that multiple flood vulnerability assessment can evaluate vulnerability more completely, and help decision makers learn more information about making decisions in a more comprehensive way. In summary, this study provides a new way for flood vulnerability assessment and disaster prevention decision.
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Desastres , Inundações , Lógica Fuzzy , China , Modelos TeóricosRESUMO
The analysis of the influencing factors of flash floods, one of the most destructive natural disasters, is the basis of scientific disaster prevention and mitigation. There is little research considering the influence of tropical cyclones (TCs) and water conservancy projects on flash floods, which cannot be ignored in the island areas where flash floods often occur due to the complex influence of various factors. In this study, under the pressure-state-response framework (PSR framework), the factors affecting the distribution of flash floods on Hainan Island, China, from 1970 to 2010 were quantitatively analyzed by using the geographical detector method. By dividing the time period, give full play to the advantages of the PSR framework and show the evolution process of various factors. Different from inland areas, extreme precipitation and tropical cyclones play a major role in the spatial distribution of flash floods on Hainan Island, China, and the driving force of tropical cyclones is 1.1 times that of extreme precipitation on average. Medium-sized reservoirs play the greatest role in the prevention of flash floods on Hainan Island, and their driving forces reach 0.38 times of extreme precipitation on average, followed by large-sized reservoirs and small-sized reservoirs. Large-sized reservoirs are limited in quantity and have limited effectiveness in preventing flash floods on Hainan Island. Therefore, in the forecasting and risk management of flash flood in the island area, more attention should be paid to the impact of extreme precipitation and TCs, and the role of medium-sized reservoir should be fully exerted.
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Tempestades Ciclônicas , Desastres , Inundações , Água , Gestão de RiscosRESUMO
Risk assessment is an effective means to alleviate urban flood disasters and has attracted the attention of many studies. However, most previous studies about urban flood risk assessment often focused more on urban inundation area and depth, less on the inter-relationship of the components of risk. In this study, an urban flood risk assessment approach that characterizes the relationship among the three components of risk "hazard-exposure-vulnerability" (H-E-V) is developed. Firstly, eleven flood risk indicators are selected based on the flood simulation results of urban flood model and statistical data to establish the urban flood risk assessment index system. Then, the combination of analytic hierarchy process (AHP) and entropy weight method is employed to determine the weight of each indicator and the comprehensive urban flood risk is assessed. Most importantly, the coupling coordination degree model (CCDM) is used to reveal the relationship among H-E-V. After applying this method to Haikou city, China, the results show that the comprehensive effect and the coupling coordination degrees among H-E-V have a multidimensional impact on urban flood risk. For example, some sub-catchments, although at high risk of flooding, may experience a potential waste of resources. Urban flood assessment can be made more detailed and three-dimensional by comparing hazard, exposure, and vulnerability horizontally. Understanding and grasping the internal relationships among these three risk components can help implement flood prevention measures, optimize the allocation of flood prevention resources, and effectively reduce urban flood risks.
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Desastres , Inundações , Desastres/prevenção & controle , Cidades , Medição de Risco/métodos , ChinaRESUMO
The water scarcity in China's coal bases is intensifying due to rapid development of modern coal chemical industry and inefficient water utilization. Previous studies on industrial water optimization were predominantly focused on direct water, overlooking the associated indirect water consumptions throughout supply chains. In this study, a water footprint (WF)-based allocation optimization framework is developed to obtain optimal solutions for water resources utilization constrained by quantity of water supply and coal chemical production related limiting factors. The framework comprises a novel WF accounting model especially used for the coal-to-chemical industry and a water allocation optimization model that integrates direct and indirect water consumptions. A typical major large-scale coal base in China was chosen as the study area. Results showed that the cradle-to-gate WF of the various coal-based products ranged from 2.01 m3/t to 70.85 m3/t, in which the internal operational and supply-chain blue WFs were the dominant contributors. Statistical analysis suggested that the volumetric WF of the coal-based products was strongly correlated with both market price and production stage while the variation of WF increased as products were further processed. Optimization result indicated that the maximized economic income of the products under current scenario was 66.23 billion CNY/year in the study area, whereas the overlapping of limited water resources and the insufficiency of downstream production capacity restricted the economic performance by over 20%. In addition, sensitivity analysis was conducted and the results showed that, in order to improve the overall economic income, deployment of more advanced technologies for saving water should be prioritized over that for saving feedstock, while conservation of power was the least preferable.
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Public health risks from urban floods are a global concern. A typhoon is a devastating natural hazard that is often accompanied by heavy rainfall and high storm surges and causes serious floods in coastal cities. Affected by the same meteorological systems, typhoons, rainfall, and storm surges are three variables with significant correlations. In the study, the joint risk of rainfall and storm surges during typhoons was investigated based on principal component analysis, copula-based probability analysis, urban flood inundation model, and flood risk model methods. First, a typhoon was characterized by principal component analysis, integrating the maximum sustained wind (MSW), center pressure, and distance between the typhoon center and the study area. Following this, the Gumbel copula was selected as the best-fit copula function for the joint probability distribution of typhoons, rainfall, and storm surges. Finally, the impact of typhoons on the joint risk of rainfall and storm surges was investigated. The results indicate the following: (1) Typhoons can be well quantified by the principal component analysis method. (2) Ignoring the dependence between these flood drivers can inappropriately underestimate the flood risk in coastal regions. (3) The co-occurrence probability of rainfall and storm surges increases by at least 200% during typhoons. Therefore, coastal urban flood management should pay more attention to the joint impact of rainfall and storm surges on flood risk when a typhoon has occurred. (4) The expected annual damage is 0.82 million dollars when there is no typhoon, and it rises to 3.27 million dollars when typhoons have occurred. This indicates that typhoons greatly increase the flood risk in coastal zones. The obtained results may provide a scientific basis for urban flood risk assessment and management in the study area.
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Tempestades Ciclônicas/estatística & dados numéricos , Planejamento em Desastres/métodos , Chuva , Ondas de Maré/estatística & dados numéricos , China , Cidades , Inundações/economia , Modelos Teóricos , Análise Multivariada , Medição de RiscoRESUMO
Catastrophic flooding resulting from extreme meteorological events has occurred more frequently and drawn great attention in recent years in China. In coastal areas, extreme precipitation and storm tide are both inducing factors of flooding and therefore their joint probability would be critical to determine the flooding risk. The impact of storm tide or changing environment on flooding is ignored or underestimated in the design of drainage systems of today in coastal areas in China. This paper investigates the joint probability of extreme precipitation and storm tide and its change using copula-based models in Fuzhou City. The change point at the year of 1984 detected by Mann-Kendall and Pettitt's tests divides the extreme precipitation series into two subsequences. For each subsequence the probability of the joint behavior of extreme precipitation and storm tide is estimated by the optimal copula. Results show that the joint probability has increased by more than 300% on average after 1984 (αâ=â0.05). The design joint return period (RP) of extreme precipitation and storm tide is estimated to propose a design standard for future flooding preparedness. For a combination of extreme precipitation and storm tide, the design joint RP has become smaller than before. It implies that flooding would happen more often after 1984, which corresponds with the observation. The study would facilitate understanding the change of flood risk and proposing the adaption measures for coastal areas under a changing environment.