Vulnerability Assessment Model Research Articles

Analysis of landscape pattern vulnerability in Dasi river basin at the optimal scale

Since the reform and opening up in 1978, the Dasi River Basin within Jinan’s startup area from replacing old growth drivers with new ones (startup area) has experienced rapid urbanization and industrialization, and the landscape pattern has changed significantly, resulting in a series of eco-environmental problems. In order to more accurately identify the vulnerable areas of landscape pattern, understand their cause mechanism and changing laws, and provide a theoretical basis for the implementation of sustainable landscape pattern planning and management in the region. Four Landsat images of 2002, 2009, 2015 and 2020 were taken as data sources, and the optimal granularity of landscape pattern analysis was determined from the perspective of landscape level and class level by using the coefficient of variation method, granularity effect curve and information loss model, and the optimal amplitude was determined by using the grid method and semi-variance function. Then, the landscape vulnerability assessment model was constructed based on the optimal scale, and its spatiotemporal evolution characteristics and spatial autocorrelation were analyzed. The result showed that: (1) The optimal granularity of landscape pattern analysis in this study area was 80 m, and the optimal amplitude was 350 × 350 m. (2) During 2002–2020, the overall vulnerability of landscape pattern in the southern part of the study area showed an increasing trend, while that in the middle and northern parts showed a decreasing trend. (3) The mean values of the vulnerability index of the overall landscape pattern in 2002, 2009, 2015 and 2020 were 0.1479, 0.1483, 0.1562 and 0.1625, respectively, showing an increasing trend year by year. In terms of land use, during 2002–2020, the average vulnerability indices of forestland and built up land increased by 23.18% and 21.43%, respectively, followed by water body and bare land, increased by 12.18% and 9.52%, respectively, while the changes of cropland and grassland were relatively small, increasing by 5.36% and 5.65%, respectively. (4) During 2002–2020, the landscape pattern vulnerability showed a significant spatial positive correlation in terms of spatial distribution. The Low-Low areas were generally transferred from the southeastern and midwestern to the middle and northern, and the High–High areas were mainly transferred from the middle to the southern. Overall, the degree of the spatial agglomeration of the landscape pattern vulnerability showed an increasing trend.

Precondition Study of a Sponge City: Comprehensive Assessment of the Vulnerability of an Urban Rainwater System

This study introduces the concept of urban rainwater system vulnerability and identifies the indicator factors that affect the vulnerability of rainwater systems. Using the analytic hierarchy process (AHP), an index system for the vulnerability assessment of the rainwater system was established, and a vulnerability assessment model for the rainwater system was constructed. By integrating vulnerability degree, recurrence period, and water depth of ponding, a vulnerability assessment framework for urban rainwater systems was developed. Taking a newly developed urban area in the Suzhou High-Tech Zone as an example, we calculated the vulnerability degree of the urban rainwater system in this area to be 0.6497, indicating a high level of vulnerability and poor system safety. When encountering rainfall with a recurrence period p > 5 years, the city is likely to experience severe waterlogging. Through the analysis and evaluation of the rainwater system’s vulnerability, while clarifying the current state of the rainwater system, it can provide a scientific reference basis for the system’s upgrade, transformation, and optimized operation and management. Although the selection of factors may not be entirely comprehensive, this method allows for adjustments based on the composition and operation of different rainwater systems.

Enhancing Financial Vulnerability Models for Non-Profit Organizations: Integrating Financial Ratios and Macroeconomic Indicators for Comprehensive Risk Assessment

Purpose: This research advances the financial vulnerability prediction model for Non-Profit Organizations (NPOs) by incorporating a comprehensive set of financial and macroeconomic indicators, aiming to refine risk management and strategic planning within the sector. Theoretical Framework: Building upon Tuckman and Chang (1991) foundational work, this study addresses the evolving financial landscape's complexities. It expands on traditional financial ratio analyses to include broader economic conditions affecting NPOs, recognizing the limitations of previous literature. Design/Methodology/Approach: The study analyzes financial data from two NPOs (2017-2021), using three models to assess the influence of internal financial ratios (e.g., Debt Ratio, Cash Ratio, Net Operating Margin) and external macroeconomic factors (e.g., inflation, GDP growth) on NPO financial vulnerability and performance. Findings: Results highlight a significant positive relationship between the Cash Ratio and Return on Assets, underscoring liquidity management’s importance for NPO sustainability. Other factors showed minimal impact, suggesting a nuanced approach to financial vulnerability. Research Implications: The findings emphasize the necessity of integrating financial ratios with macroeconomic indicators in NPO management strategies, offering a refined model for understanding and mitigating financial risk. Originality/Value: This study enhances the financial management literature for NPOs by incorporating macroeconomic indicators into vulnerability assessment models. It provides a comprehensive framework for robust financial planning, filling a crucial gap in non-profit financial analysis and contributing to the sector’s resilience.

Application of the fuzzy analytic hierarchy process for water resources in the Wadi AlHasa catchment, Jordan

This article introduces a groundwater vulnerability assessment model that utilises the fuzzy analytic hierarchy process (FAHP) in the Wadi AlHasa catchment, Jordan. The assessment takes into account both geomorphological and hydrogeological variables, employing a comprehensive methodology that integrates various parameters. To evaluate the catchment, the study employs remote sensing and Geographic Information System (GIS) techniques. The analysis of the digital elevation model enables the creation of a map illustrating the diverse geomorphology of the catchment. This geomorphology significantly influences drainage density, direction, and the spatial distribution and intensity of flash flood events. Moreover, the study develops and maps a fuzzy FAHP DRASTIC vulnerability index, which proves to be a valuable tool for assessing the susceptibility of groundwater resources to contamination. The unique feature of the index is its ability to incorporate uncertain or subjective data, providing a means to evaluate the significance of various influencing factors. This information serves as critical support for decision-making and management efforts geared towards safeguarding and enhancing groundwater resources. Within the study area, the DRASTIC vulnerability index values span from 0.08325 to 0.28409, with 18% of the site exhibiting a high vulnerability rate. Additionally, the article implements a managed aquifer recharge model (MAR), with 31% of the area falling into MAR classes. Among these, 22.1% are classified as a high MAR class, while 0.7% belong to a very high MAR class. These findings underscore the feasibility of MAR projects in regions with limited water resources.

Spatio-Temporal Pattern and Vulnerability Assessment of the Human Settlements along the Beibu Gulf Coast of Guangxi, China

Human settlement development is intricately linked to production and life, and development quality is a partial indicator of the local community’s social, economic, cultural, and environmental progress. Furthermore, the human settlements’ vulnerability affects their sustainable development potential. Due to the “One Belt, One Road” initiative and land and sea corridor development in southwestern China, the Beibu Gulf coast in Guangxi is the sole waterway bridgehead used by China for opening trade with ASEAN. By examining the region’s human settlements and its potential for sustainable development, we established a benchmark for the region’s seaward economy and human settlements to achieve synergistic progress, as well as to enhance regional integration. Based on the systematic evaluation of the quality of human settlements along the Beibu Gulf coast in Guangxi, the vulnerability assessment model of human settlement was adopted to analyse the vulnerability and spatial–temporal patterns of nearby human settlements in 2010–2019, while the multiple linear regression model was used to explore their influencing factors. Our findings indicate that the quality of human settlements in the study area has experienced three distinct stages. In the early stage (2010–2012), we noted an overall year-on-year increase in settlement quality. However, in the middle stage (2013–2016), Fangchenggang and Beihai experienced a decline followed by an increase, while Qinzhou demonstrated a steady growth in settlement quality. Qinzhou continued to experience growth, albeit at a slower rate, while Fangchenggang’s rate of increase surpassed that of Beihai. The human settlements’ high-quality centre shifted between Qinzhou and Fangchenggang in the late stage (2017–2019). Additionally, in recent years, the settlements’ high-quality centre has shifted towards the western part of the region. The habitat’s sensitivity has grown slowly, as has the responsiveness index, but the vulnerability index continues to decline, and it is characterised by a spatial differentiation ranging from low to high values in a centre–east–west direction. The region’s human settlement quality is primarily influenced by economic development. The region’s habitat vulnerability is primarily caused by responsibility, and the primary factors affecting responsibility are regional imbalances in social service development, the population’s welfare, and employment and infrastructure.

Integrated SEAWAT model and GALDIT method for dynamic vulnerability assessment of coastal aquifer to seawater intrusion

Seawater intrusion (SI) has become a global issue exacerbated by intense anthropogenic activities and climate change. It is imperative to seek a synergistic strategy to reconcile environmental and economic benefits in the coastal regions. However, the intricate SI process and data scarcity present formidable challenges in dynamically assessing the coastal groundwater vulnerability. To address the challenge, this study proposed a novel framework that integrates the existing vulnerability assessment method (GALDIT) and variable-density groundwater model (SEAWAT). The future scenarios from 2019 to 2050 were investigated monthly under climate change (SSP1–2.6, SSP2–4.5, SSP3–7.0 and SSP5–8.5) and human activities (80 % and 50 % of current groundwater abstraction) in Longkou city, China, a typical coastal region subject to extensive SI, compared with the status quo in 2018. Results indicated that by 2050, the high vulnerability area, is in a narrow buffer within 1.2 km from the shoreline and exhibits minor changes while the salt concentration here increased by about 2700 mg/L compared with the current situation. The moderate vulnerability zone expands by about 30 km2, and the low vulnerable area decreases proportionally. The groundwater over-abstraction is identified as a more critical factor compared to the regional precipitation under climate change. When groundwater abstraction is reduced to 80 % of the current scale, the expansion rate of the moderate-vulnerable area slows down significantly, with an expansion area of only 18 km2 by 2050. Further reducing groundwater abstraction to 50 % of the current scale shifts the evolution trend of the medium-vulnerable area from expansion to contraction, with the area shrinking by about 11 km2 by 2050. The integrated vulnerability assessment framework can be applied not only in the similar coastal regions but also provides insights into other natural hazards.

Vulnerability assessment and analysis of cryosphere changes in the Western Sichuan Plateau

ABSTRACT A vulnerability assessment model and indicator system for the changes in the cryosphere in the Western Sichuan Plateau are constructed based on the “exposure–sensitivity–adaptive capacity” framework. The model aims to capture the multiple characteristics of vulnerability to cryosphere changes in the region by selecting influencing factors from three dimensions: exposure, sensitivity, and adaptive capacity. Furthermore, the study explores the interrelationships among vulnerability dimensions and employs geographical detectors to analyze the driving mechanisms of vulnerability. The ultimate goal is to provide a scientific and rational basis for developing effective adaptation strategies to prevent and mitigate cryosphere-related disasters in the area. The main findings are as follows: (1) The vulnerability to cryosphere changes in the Western Sichuan Plateau exhibits a distribution pattern characterized by higher vulnerability in the west and lower vulnerability in the east. (2) There is a significant correlation between vulnerability and geographical location, characterized by two types of distribution patterns: high–high aggregation and low–low aggregation. The aggregation patterns are relatively stable but exhibit spatial heterogeneity. (3) The vulnerability to cryosphere changes in the Western Sichuan Plateau is the combined result of natural geographical conditions, socioeconomic development levels, and other factors.

Introducing reverse Multi Influencing Factor technique in DRASTIC model for groundwater vulnerability assessment

Effective groundwater resource management has become essential to the development of urbanized areas, particularly in regions with significant agricultural and industrial activity. In the present study, a multi-criteria decision-analysis techniques methodology was used to assess the groundwater vulnerability of Seonath basin. The objective of this study is to identify the areas that are more susceptible to groundwater contamination by incorporating various hydrogeological layers from DRASTIC into the geographical information system (GIS) platform. To enhance the weights of the DRASTIC parameters used for the identification of the groundwater vulnerability index values, apart from the application of the widely-used multiple influencing factors (MIF) method, a new modified MIF method (hereafter named RMIF) was also introduced and applied. Based on their index map, the final results were classified into five vulnerable classes: very low, low, moderate, high, and very high. Lower index values indicated areas that were less vulnerable, and vice versa. DRASTIC-RMIF is performing better than DRASTIC and DRASTIC-MIF, respectively majority of the total area lies in moderately vulnerable zones: 77.50 %, 70.52 % and 28.20 %. In order to validate the groundwater vulnerability zones, we also attempted to test and create a relationship between nitrate and the final groundwater vulnerability result. And the coefficient of determination of DRASTIC, DRASTIC–MIF, and DRASTIC–RMIF methods were 0.6, 0.4, and 0.8, respectively. From this validation DRASTIC-RMIF obtained the most accurate result among all weighting techniques due to local hydrogeological condition. Model validation showed a significant association between the sample nitrate concentration values and the DRASTIC-RMIF model index values. Decision/Policy makers must identify vulnerable zones in order to manage and maintain an identification system for groundwater supplies.

Global Review of Modification, Optimization, and Improvement Models for Aquifer Vulnerability Assessment in the Era of Climate Change

Global Review of Modification, Optimization, and Improvement Models for Aquifer Vulnerability Assessment in the Era of Climate Change

Sustainable development assessment of ecological vulnerability in arid areas under the influence of multiple indicators

The fragile ecosystems of arid areas are highly vulnerable, especially under the impact of human activities. Therefore, there is an urgent need to develop appropriate ecological vulnerability assessment models for these areas. In this study, Zhongwei City was taken as the study area. And a multi-indicator comprehensive assessment system was constructed using the optimized featured indicators-vulnerability scoping diagram (FVSD) model. The weights for each indicator were determined using the analytic hierarchy process-entropy weight (AHP-EW) method, leading to the creation of the ecological vulnerability map of Zhongwei City. The results showed that the overall ecological vulnerability of Zhongwei City is high and there is a significant spatial aggregation. There was obvious spatial heterogeneity in the distribution of vulnerability, with high vulnerability mainly concentrated in Haiyuan County, showing a decreasing trend from south to north. Watershed area index, annual average temperature, PM10 and annual afforestation index were the most important indicators affecting the ecological vulnerability, the fragile environmental conditions and human activities combine to shape the spatial heterogeneity of ecological vulnerability. The results of the study have important theoretical and practical implications in guiding ecological management of Zhongwei City. Moreover, the research framework can be replicated in different areas and is instructive for ecological vulnerability studies.

Deriving community vulnerability indices by analyzing multi-resolution space-borne data and demographic data for extreme weather events in global cities

Climate change in the Anthropocene is cited as one of the main reasons for extreme weather events around the world. There is a need for rapid vulnerability assessment models that may be deployed in near-real time to assist stake holders in driving the required mitigation and adaptation efforts to such events, especially in the Global South. We present an approach to derive Community Vulnerability Index (CVI) to flooding by using an integrated geospatial computational model and illustrate the methodology for six global cities. Time-series of multi-resolution space-borne optical and synthetic aperture radar (SAR) data were analyzed to derive land cover metrics from before and after flood imagery for delineating and mapping the land cover and the spatial extent of flash floods. A texture-based analysis was employed on the SAR data to delineate the spatial extent of flash floods, and this was integrated with the land cover metrics derived from the optical Sentinel-2 (Level 2A) orthorectified surface reflectance imagery. Land cover classification based on supervised image classification yielded a minimum overall accuracy of 71% when only SAR data was available after floods, and increased to 87% with the availability of cloudless Sentinel-2 data. A weighted index method, using weights derived through Factor Analysis, was used to assign appropriate weights to the composite variables derived from satellite datasets and demographic datasets for developing the CVI. The model was developed and tested on global cities with contrasting economies and validated by cross checking results with reliable open source surrogate data. The model provides an effective, adaptable, and cost-effective approach for vulnerability assessment and may provide information for policy makers to design appropriate resilience and adaptation efforts.

Rainstorm waterlogging vulnerability assessment of subway stations in the central area of Tianjin

ABSTRACTRainstorm and waterlogging disasters of underground rail transit have recently become a vital safety problem. In this paper, a model of vulnerability assessment is established, and 14 indicators are selected to establish an indicator system for 109 stations in the central area of Tianjin. Analytic Hierarchy Process(AHP) and Entropy Weight Method (EWM) were used to determine the subjective and objective weights of indicators. A distance function was introduced to calculate the combined weights and improve the weights’ rationality. The results show that there are 34 high and medium-high vulnerability stations, and 41 low and medium-low vulnerability stations. Except for Line 2, the vulnerability level of subway stations on the rail lines decreased from the edge to the centre. Nankai District had the most high-vulnerability stations (seven of the 20 high-vulnerability stations). The main influence factors were the waterproofing capacity of the subway, the digital elevation model, the station type, the height of the exit, and the entrance steps.

A modified DRASTIC model for groundwater vulnerability assessment using connecting path and analytic hierarchy process methods.

Groundwater plays a vital role in supporting water for the different needs of domestic, agricultural, and industrial sectors, and its vulnerability assessment to pollution is a valuable tool for establishing protective and preventive management. DRASTIC is a well-known GIS-based model for assessing groundwater vulnerability to pollution, which uses seven parameters including depth-to-water level, net recharge, aquifer media, soil media, topography, the impact of the vadose zone, and hydraulic conductivity. The predefined weights of DRASTIC parameters have made a barrier to its applicability for different regions with different hydroclimatic conditions. To overcome this problem, it has been suggested to apply analytic hierarchy process (AHP) method for modifying the model by adjusting the weights of the parameters. AHP is a widely used method to elicit experts' judgments about different involving parameters through constructing pairwise comparison matrixes (PCMs). Since AHP calculates the weights by performing pairwise comparisons between the parameters, achieving consistent comparisons is difficult when the number of parameters increases. The objective of this research is to modify the DRASTIC model by integrating the connecting path method (CPM) and AHP. The proposed methodology involves asking experts to perform a number of pairwise comparisons between the parameters and then construct an incomplete PCM using the obtained information. To complete the missing values in the PCM, CPM is employed. The CPM is an effective approach that not only estimates missing judgments but also ensures minimal geometric consistency. The proposed method along with DRASTIC and pesticide DRASTIC models is applied to Khoy County, which is located in the northwest part of Iran. The efficiency of the proposed method was further confirmed through the results of the Pearson coefficient test conducted on nitrate concentrations. The test revealed correlation values of 0.47, 0.27, and 0.57 for DRASTIC, pesticide DRASTIC, and modified DRASTIC, respectively. These results demonstrated that the proposed method provides a more precise evaluation of groundwater vulnerability.

Recharge and vulnerability assessment of groundwater resources in North west India: Insights from isotope-geospatial modelling approach

Recent studies indicate dwindling groundwater quantity and quality of the largest regional aquifer system in North West India, raising concern over freshwater availability to about 182 million population residing in this region. Widespread agricultural activities have resulted severe groundwater pollution in this area, demanding a systematic vulnerability assessment for proactive measures. Conventional vulnerability assessment models encounter drawbacks due to subjectivity, complexity, data-prerequisites, and spatial–temporal constraints. This study incorporates isotopic information into a weighted-overlay framework to overcome the above-mentioned limitations and proposes a novel vulnerability assessment model. The isotope methodology provides crucial insights on groundwater recharge mechanisms (18O and 2H) and dynamics (3H) - often ignored in vulnerability assessment. Isotopic characterisation of precipitation helped in establishing Local Meteoric Water Line (LMWL) as well as inferring contrasting recharge mechanisms operating in different aquifers. Shallow aquifer (depth < 60 m) showed significant evaporative signature with evaporation loss accounting up to 18.04% based on Rayleigh distillation equations. Inter-aquifer connections were apparent from Kernel Density Estimate (KDE) and isotope correlations. A weighted overlay isotope-geospatial model was developed combining 18O, 3H, aquifer permeability, and water level data. The central and northern parts of study area fall under least (0.29%) and extremely (1.79%) vulnerable zones respectively, while majority of the study area fall under moderate (42.71%) and highly vulnerable zones (55.20%). Model validation was performed using groundwater NO3– concentration, which showed an overall accuracy up to 82%. Monte Carlo Simulation (MCS) was performed for sensitivity analysis and permeability was found to be the most sensitive input parameter, followed by 3H, 18O, and water level. Comparing the vulnerability map with Land Use Land Cover (LULC) and population density maps helped in precisely identifying the high-risk sites, warranting a prompt attention. The model developed in this study integrates isotopic information with vulnerability assessment and resulted in model output with good accuracy, scientific basis, and widespread relevance, which highlights its crucial role in formulating proactive water resource management plans, especially in less explored data-scarce locations.

Proposed vulnerability assessment model for masonry buildings on slow-moving landslides based on physical models and field observations

Proposed vulnerability assessment model for masonry buildings on slow-moving landslides based on physical models and field observations

Vulnerability Assessment of the Upper-Middle Pleistocene (qp2-3) Aquifer in Ho Chi Minh City, Vietnam Using GIS and Expanded DRASTIC Methods

The groundwater vulnerability assessment model (DRASTIC) for zoning sensitivity based on natural and objective factors of aquifers is currently used and applied widely. In this study, we have expanded the weights in the DRASTIC index through the Entropy weight-based technique and visualized them in association with GIS for assessing the vulnerability of the Upper-Middle Pleistocene aquifer in Ho Chi Minh City, Vietnam. The value of Entropy weights calculated from the collected dataset of 106 monitoring boreholes of the study area. The Entropy-DRASTIC results divided into three categories: 9.45% of the study area was in the high vulnerability zones, low and medium vulnerability zones are 21.5% and 69.05% of the total study area, respectively. The highly vulnerable area, which is shallow aquifer roofs and recharged significantly (directly from rains or runoff from the surface flows exposed to contaminants from runoff flows). Low vulnerability areas with clay cover are weak permeability and medium vulnerability area is a sizable transitional zone surrounding the high and low vulnerability. This result suggests that the DRASTIC index model in association with GIS is a useful tool to assist policymakers in formulating solutions for the use of groundwater resources. Importantly, this finding is useful to the local authorities in shaping regulations on the use and exploitation of groundwater resources in suburban areas, where the public water supply network is inadequate, constrained groundwater resource and exposed to contamination.

"Application of Catastrophe Theory to Assess Transport Sector Vulnerability using Macro-Environment Factors – A Case of Floods in the Perlis State of Malaysia "

Decision-makers must possess rapid assessment tools to evaluate the vulnerability of the transport sector in light of the disaster-support function. Earlier vulnerability assessment models were often prone to subjectivity in quantifying and determining transport vulnerabilities. The present paper examines the macro-environment to select factors affecting transport sector vulnerabilities. A total of 30 criteria and indicators are chosen within five factors, namely Social, Technological, Environmental, Economic and Political (STEEP), to assess the macro-level vulnerability assessment taking the flood-prone State of Perlis in Malaysia as a case study. Owing to the inherent advantages of eliminating subjective and qualitative aspects, catastrophe theory is applied to obtain multiple assessment indices defining vulnerabilities and relative importance. The results obtained using the catastrophe assessment system based on STEEP factors reveal high transport vulnerability values for social factors, followed by economic, political, environmental and technical factors. Results show that among the social factors, gender, age, and income play a significant role in defining vulnerability. Other than social factors affecting transport vulnerability, the economic condition of the state, land use distribution, political attitude and the role of civic society were also found to have significant influence. Findings suggest that the immobility of the mass population and the unavailability of sufficient infrastructure and technology are the major factors of high vulnerability. The present research urges the policymakers to focus on areas such as transport systems more usable for the elderly, promoting gender equality in the transport sector and planning better transport accessibility, particularly for low-income population, that can help to improve their effective mobility and make transport system more affordable to all. The developed assessment model is simple and operational, giving decision-makers an alternative approach to assess transport vulnerabilities.

Assessment of Building Physical Vulnerability in Earthquake-Debris Flow Disaster Chain

Large earthquakes not only directly damage buildings but also trigger debris flows, which cause secondary damage to buildings, forming a more destructive earthquake-debris flow disaster chain. A quantitative assessment of building vulnerability is essential for damage assessment after a disaster and for pre-disaster prevention. Using mechanical analysis based on pushover, a physical vulnerability assessment model of buildings in the earthquake-debris flow disaster chain is proposed to assess the vulnerability of buildings in Beichuan County, China. Based on the specific sequence of events in the earthquake-debris flow disaster chain, the seismic vulnerability of buildings is 79%, the flow impact and burial vulnerabilities of damaged buildings to debris flow are 92% and 28% respectively, and the holistic vulnerability of buildings under the disaster chain is 57%. By comparing different vulnerability assessment methods, we observed that the physical vulnerability of buildings under the disaster chain process is not equal to the statistical summation of the vulnerabilities to independent hazards, which implies that the structural properties and vulnerability of buildings have changed during the disaster chain process. Our results provide an integrated explanation of building vulnerability, which is essential for understanding building vulnerability in earthquake-debris flow disaster chain and building vulnerability under other disaster chains.

ECONOMIC VULNERABILITY OF SPECIALIZED TOURISM CITY: A CASE STUDY IN SOUTHWEST OF CHINA

Global epidemics, wars, and lack of resources pose threats to society and the tertiary industry. After the world went through a period of de-globalization for a short period of time since the year 2019, the Global tourism industry suffers a fatal blow. The main objective of this paper is to evaluate the economic vulnerability of a specialized tourism city Dali (a typical tourism city in China) and propose risk avoidance strategies for its sustainable tourism development. This paper establishes a vulnerability assessment model from the aspects of sensitivity and responding capacity by using the set pair analysis (SPA) model to evaluate the economic vulnerability of Dali. The obstacle evaluation model and the entropy value method were used to analyze its obstacle factors. This research employs the National Economic and Social Development Statistics as its primary data source, augmented by the Statistical Yearbook and Yearbooks from different years. The results show that the change of the vulnerability of Dali's tourism economic system is relatively stable, but in general the vulnerability is at a high level in most years. According to the analysis of obstacle factors, the ratio of tourist arrivals to local population, Elasticity coefficient of tourism to industrial growth and National economy (GDP) output value are the main obstacles to reduce the vulnerability of Dali's tourism economy.

Comparative analysis of DRASTIC and GOD model for groundwater vulnerability assessment

Comparative analysis of DRASTIC and GOD model for groundwater vulnerability assessment