Resilience Index Research Articles

The resilience of the regional ecosystems: Healthcare-service organizations, public agents and communities in the times of COVID-19

The aim of this study is to compare regional ecosystems' resilience in terms of their ability to contain the spread of Covid-19. This is carried out through institutional measures as well as through spontaneous community behaviour in order to preserve public health and the institutional actions to strengthen the health-care system in dealing with the pandemic. The discussion is framed through the institutional approach. We develop a twostep method. In the first step, regions have been clustered by considering the kind of response to Covid-19, in terms of formal and informal rules. In the second step a random effect panel regression analysis was performed in order to define the effect of the single response variable to Covid-19 on the resilience index over time. Implications for policy makers are then discussed. The first is that coping with a regional emergency requires taking into account regional specificities. Strictly imitative models risk being inconsistent with the characteristics of the area, resulting in outputs that are not homogeneous. The second involves social capital, which is crucial to the application of the norms. In regions with high social capital there is a sense of solidarity that presents itself in informal rules aimed at reinforcing the formal rules. However, there is no sense of conformity for the sake of conformance to the standard.

Recovery and resilience of European temperate forests after large and severe disturbances

AbstractRecent observations of tree regeneration failures following large and severe disturbances, particularly under warm and dry conditions, have raised concerns about the resilience of forest ecosystems and their recovery dynamics in the face of climate change. We investigated the recovery of temperate forests in Europe after large and severe disturbance events (i.e., resulting in more than 70% canopy loss in patches larger than 1 ha), with a range of one to five decades since the disturbance occurred. The study included 143 sites of different forest types and management practices that had experienced 28 disturbance events, including windthrow (132 sites), fire (six sites), and bark beetle outbreaks (five sites). We focused on assessing post‐disturbance tree density, structure, and composition as key indicators of forest resilience. We compared post‐disturbance height‐weighted densities with site‐specific pre‐disturbance densities to qualitatively assess the potential for structural and compositional recovery, overall and for dominant tree species, respectively. Additionally, we analyzed the ecological drivers of post‐windthrow tree density, such as forest management, topography, and post‐disturbance aridity, using a series of generalized additive models. The descriptive results show that European temperate forests have been resilient to past large and severe disturbances and concurrent climate conditions, albeit with lower resilience to high‐severity fire compared with other disturbance agents. Across sites and disturbance agents, the potential for structural recovery was greater than that of compositional recovery, with a large proportion of plots becoming dominated by early‐successional species after disturbance. The models showed that increasing elevation and salvage logging negatively affect post‐windthrow regeneration, particularly for late‐successional species, while pioneer species are negatively affected by increasing summer aridity. These findings provide a key baseline for assessing future recovery and resilience following the recent occurrence of widespread disturbance in the region and in anticipation of future conditions characterized by increasing heat and drought stress.

Self-organization as a mechanism of resilience in dryland ecosystems

Self-organized spatial patterns are a common feature of complex systems, ranging from microbial communities to mussel beds and drylands. While the theoretical implications of these patterns for ecosystem-level processes, such as functioning and resilience, have been extensively studied, empirical evidence remains scarce. To address this gap, we analyzed global drylands along an aridity gradient using remote sensing, field data, and modeling. We found that the spatial structure of the vegetation strengthens as aridity increases, which is associated with the maintenance of a high level of soil multifunctionality, even as aridity levels rise up to a certain threshold. The combination of these results with those of two individual-based models indicate that self-organized vegetation patterns not only form in response to stressful environmental conditions but also provide drylands with the ability to adapt to changing conditions while maintaining their functioning, an adaptive capacity which is lost in degraded ecosystems. Self-organization thereby plays a vital role in enhancing the resilience of drylands. Overall, our findings contribute to a deeper understanding of the relationship between spatial vegetation patterns and dryland resilience. They also represent a significant step forward in the development of indicators for ecosystem resilience, which are critical tools for managing and preserving these valuable ecosystems in a warmer and more arid world.

Markers for Immunological Resilience: Effects of Moderate- and High-Intensity Endurance Exercise on the Kinetic Response of Leukocyte Subsets

The kinetic responses of leukocyte subsets to exercise and their recovery may serve as indicators of immunological resilience. These time-dependent responses were investigated in healthy young men using a bicycle ergometer test. Fifteen recreationally active male cyclists (20–35 years, VO2max 56.9 ± 3.9 mL kg−1 min−1) performed four exercise protocols with a 1 h duration in a cross-over design: at 70% of the maximal workload (Wmax) in a hydrated and a mildly dehydrated state, at 50% of the Wmax, and intermittently at 85/55% of the Wmax in blocks of 2 min. The numbers of lymphocytes, monocytes, neutrophils, eosinophils, basophils, thrombocytes, and NK cells (CD16 and CD56) were measured at different time points up to 24 h post-exercise. The total leukocyte counts and those of most subsets increased from the start of the exercise, peaking after 30–60 min of exercising. The neutrophil numbers, however, peaked 3 h post-exercise. The CD16brightCD56dim NK cells showed a 1.5-fold increase compared to the CD16brightCD56bright NK cells. Other than for MCP-1, no significant differences were found in the serum cytokine levels. Our results show that exercise intensity is reflected in different time-dependent changes in leukocyte subsets, which supports the concept that the exchange of immune cells between peripheral blood and tissues contributes to enhanced immune surveillance during strenuous exercise.

Assessing dynamical resilience indicators in older adults: a prospective feasibility cohort study

Key summary pointsAimTo examine the feasibility of a prospective cohort study examining dynamical resilience indicators in acutely ill older adults who visited the Emergency Department (ED).FindingsThe intensive examination of dynamical resilience indiciators based on symptoms and physical activity measurements is feasible in older ED patients.MessageThe method of intensive dynamical resilience indicators assessment can be used to study resilience in older ED patients.

Policy Formulation Based on Village Development Index (IDM) in East Java Province

The Ministry of Village published Ministerial Regulation (PERMENDES) No. 2 of 2016 regulation, on the subject of Building Village Index. The building village index is an index composite from the social resilience index, economic resilience index, and ecology resilience index. IDM can be used to measure the success of a village in carrying out village development. Status improvement of villages in the Regency/City of East Java is needed, subsequent to IDM results. The purpose of this research is to describe the condition of villages in regencies/cities in East Java based on the three IDM forming indices and to find out the East Java Government’s policy direction in increasing village potential. The research method used is qualitative descriptive with explanatory/naturalistic research. The result show that, in 2019, the majority of villages in the Regency/City Province East Java were developing villages and there were still two very disadvantaged villages. The result of the distribution of the resilience index shows that the social resilience index is the best distribution. It is necessary to have a strategy to achieve the overall development. The East Java Provincial Government provides a strategy for realizing development through village potential, these strategies include, Lumpang Bude, Bumdesa Clinic, Uncle Village, East Java Puspa, Empowered Village, Bank Mushroom Seeds, Sapa Village, and Simanis.
 Keywords: ecological resilience index, economic resilience index, social resilience index, village development index, village status

Microgrid-based operational framework for grid resiliency enhancement: A case study at KUET campus in Bangladesh

This study investigates the role of microgrids in enhancing the resilience of power systems in response to the power outages caused by severe conditions. A three-step analysis is carried out to achieve this objective. Firstly, the general backgrounds of resilience in power systems are presented, comprising resilience modeling, resilience analysis methods, and resilience enhancement efforts by different sections. Secondly, a time-dependent simulation model is designed for KUET, which incorporates standard indices for measuring, evaluating, and monitoring grid resilience. In this simulation, the total demand for KUET was assumed to be close to 1 MW, and case studies are conducted to determine the performance of the microgrid system under different operating conditions. Load prioritization management strategies have been performed. Finally, a unified resilience evaluation and operational enhancement approach is proposed, which includes a procedure for assessing the impact of severe conditions on power systems and a risk-based defensive islanding procedure. The proposed adaptive islanding method aims to mitigate the grid functionality drop. The results of the case studies illustrate the influence of microgrid structural and operational characteristics on grid resilience. The microgrid implementation improves the Grid Resilience Index (RC) from 0.9 to 1.35, with faster recovery and increased grid hardiness. However, there may be a potential trade-off with a decline in Operational Resilience (Roperational) from 0.133 to 0.069, which needs further investigation. This study contributes to the development of a framework for the measurement of resilience in power systems and provides insights into the use of microgrids as a potential solution for dealing with major power outages.

A Study on the Impact of External Shocks on the Resilience of China’s Grain Supply Chain

Grain supply is the lifeblood of a country, and the stability of the supply chain is a crucial prerequisite for ensuring national grain security. This paper draws on the definition of resilience in physics and economics. It takes supply chain fracture resilience, impact resilience, and synergy resilience as the secondary indicators. It constructs a comprehensive evaluation indicator system of the grain supply chain resilience, measures the resilience indicator of China’s grain supply chain from 1996 to 2021, and analyzes the role of supply, cost, exchange rate, and other external shocks in influencing the resilience of China’s grain supply chain on this basis. The study found that the overall level of China’s total grain supply chain resilience has been growing year by year and can be divided into three stages: low-level stabilization stage, continuous growth stage, and high-level stabilization stage. Grain supply chain fracture resilience has been growing steadily, grain supply chain impact resilience fluctuation is more obvious, and grain supply chain synergy resilience has been changing more gently. In the inquiry of the impact of external shocks on the resilience of China’s grain supply chain, it was found that world grain exports and the RMB exchange rate have a significant positive impact on China’s grain supply chain resilience level, while the international oil price has a significant negative impact. Based on this, the paper puts forward suggestions for ensuring stable production and supply in the grain market, improving the structure of foreign trade in grain, and actively coping with international commodity price shocks.

A study of the coupling between the digital economy and regional economic resilience: Evidence from China.

The contemporary economic landscape has placed significant emphasis on the digital economy and economic resilience, progressively emerging as pivotal focal points for examining the high-quality development of economic systems. However, there remains to be more research on several critical topics. This includes the characteristics of coordinated development between the digital economy and economic resilience systems and their interdependence. In response, this study formulates a comprehensive evaluative framework for digital economy development and regional economic resilience, grounded in the intrinsic mechanisms of both domains. It conducts a thorough evaluation employing entropy weight-TOPSIS methodology. Additionally, leveraging coupling theory, a coordination model's coupling degree serves as the foundational framework for scrutinizing the symbiotic advancement of the digital economy and economic resilience, along with their interdependent nature. The research sample comprises data from 31 provinces and municipalities in China (excluding Hong Kong, Macao, and Taiwan) from 2011 to 2020. Spatial autocorrelation and Geodetector methodologies probe the evolutionary traits and driving factors underlying the coordinated developmental relationship between these two systems. The findings indicate an upward trajectory in China's annual comprehensive development index for digital economy development (from 0.233 to 0.458) and regional economic resilience (from 0.393 to 0.497). The coupling and coordination between the two systems, measured from 0.504 in 2011 to 0.658 in 2020, demonstrate a consistent growth pattern with an average annual increase of 3.01%. These levels exhibit continuous improvement, with comprehensive economic zones manifesting hierarchical results within the coupling range of [0.5, 0.8]. Notably, agglomeration development evinces a pronounced spatial positive correlation, while local Moran scattering points are primarily concentrated in localized migration leaps. Factors such as foreign-funded enterprises' total import and export volume, online payment capability, and fiber-optic cable length greatly influence the coupling relationship. In contrast, other variables exhibit a lower and more fluctuating degree of weighted impact. This study establishes a foundation for the synergistic and effective development of the digital economy and economic resilience within the Chinese region. Simultaneously, it offers valuable insights for research of related subjects in global contexts.

Host-specific growth responses of Larix kaempferi and Quercus acutissima to Asian gypsy moth defoliation in central Korea

As the risk of gypsy moth outbreaks that have detrimental effects on forest ecosystem in the Northern Hemisphere increase due to climate change, a quantitative evaluation of the impact of gypsy moth defoliation is needed to support the adaptive forest management. To evaluate the host-specific impact of gypsy moth defoliation, radial growth and annual carbon accumulation were compared for one severely defoliated (Larix kaempferi (Lamb.) Carrière) and one moderate defoliated (Quercus acutissima Carruth.) host, in defoliated and non-defoliated site using tree-ring analysis. Finally, the resilience indices of radial growth variables were calculated to assess the ability of sampled trees to withstand defoliation. Gypsy moth defoliation mainly decreased latewood width and caused reduction in annual carbon absorption more than 40% for both tree species. However, L. kaempferi, showed the reduced growth until the year following defoliation, while Q. acutissima, showed no lagged growth depression and rapid growth recover. The findings show how each species reacts differently to gypsy moth defoliation and highlight the need of managing forests in a way that takes resilient tree species into account.

Influence of Natural Disasters on Social Conditions in Village Communities in Indonesia

Natural disasters have a negative impact on various aspects of life. Through natural disasters, the order of life in an area will be disrupted. The social condition of society is one component that has a negative impact. Therefore, this research aims to determine the negative impact of natural disasters on the social aspects of society. The data used in this research comes from 2021 Podes data and the 2022 and 2023 Social Resilience Index. The method used in this research is multiple linear regression. The results of this research indicate that natural disasters have a negative impact on social aspects. Of the three independent variables in this study, it is known that volcanic eruptions have the deepest significant negative impacts, both 1 year after the event and 2 years after the event. Through this research, it is known that the social aspects of society will be negatively impacted by natural disasters. For this reason, an extra role is needed from the government to carry out evacuations when a disaster occurs, and also carry out mitigation from the start in order to minimize negative impacts.

A stochastic two-stage microgrid formation strategy for enhancing distribution network resilience against earthquake event incorporating distributed energy resources, parking lots and responsive loads

The sustainability of energy systems has been severely affected in recent years by the quantity and intensity of high-impact, low-probability events. As a result, the resilience concept has been introduced to analyze the operation of networks against such events. This paper proposes a stochastic two-stage microgrid formation formulation to maximize the restored loads and enhance the resilience index of electrical distribution systems in the face of earthquake events. In this regard, an earthquake incident is modeled in the first step utilizing geographical data, peak ground acceleration and fragility curves. Then, a two-stage linear programming and graph theory is applied to form microgrids in response to the mentioned disturbances, where the variables in the planning and operating states are optimized in the first and second stages, respectively. The influence of different components including diesel generators, renewable energies, storage units and electric vehicles is investigated. In addition, the role of responsive loads and uncertainties related to line failure, load variation, renewable resources availability and electric vehicles are considered during the analysis. The results for various scenarios validate that the presented approach increases load supply capability and resiliency index by 38.7% and 38.8%, respectively.

Evaluation method for psychological resilience of athletes in high-intensity sports training based on evolutionary neural network

To enhance the psychological resilience of athletes, a method for evaluating the psychological resilience of High-intensity Interval Training (HIIT) athletes based on evolutionary neural networks is studied. From the six criteria of frustration coping, personal characteristics, self-promotion, self-regulation, internal protection and external protection, the evaluation index of psychological resilience of athletes in sports High-intensity Interval Training is selected; the audition indicators are qualitatively analyzed according to the principle of indicator selection, and the indicators that do not meet the requirements are eliminated; Cluster analysis and coefficient of variation analysis are used to carry out quantitative analysis on the remaining evaluation indicators after qualitative analysis; the indicators after quantitative analysis are improved, to build the assessment index system of psychological resilience of athletes in high-intensity sports training. The Back Propagation (BP) neural network is optimized by a genetic algorithm, and the evolutionary neural network is constructed. The index data set is input into the evolutionary neural network as a sample, and the index weight value is output through training. The evaluation result and corresponding evaluation grade are determined based on the index weight value and membership degree. The experimental results show that when the number of hidden layers is 3, the calculation of evaluation index weights is the best; The weight of personal traits obtained from the evaluation results is the highest (0.206), while the weight of external protection is the lowest (0.151), and the evaluation results are basically consistent with the expert results. The above results show that this method can accurately evaluate the psychological resilience of athletes and significantly enhance their psychological resilience.

Evaluating resilience of coastal communities upon integrating PRISMA protocol, composite resilience index and analytical hierarchy process

This research intends to investigate the resilience of coastal communities to natural hazards upon adopting: (i) Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol as a novel approach for the selection of resilience indicators and major components; (ii) Analytical Hierarchy Process to generate a weight for each indicator and major component of resilience; and (iii) indexing method to calculate the extent of resilience for each community. The results highlight that 25.81 % of the communities in the study area are registered in the very low to low resilience class, whereas 58.07 % are classified as very high to high. Additionally, this research identifies 11 critical action areas for building resilience in Khulna City, which is crucial for major stakeholders in setting up development strategies and plans for disaster risk reduction and sustainability.

Constrained trait variation by water availability modulates radial growth in evergreen and deciduous Mediterranean oaks

Spatial and temporal variation in functional traits allows trees to adjust to shifting environmental conditions such as water stress. However, the change of traits, both mean and variances, along water availability gradients and across growing seasons, as well as their covariation with tree performance, have been rarely assessed. We examined intraspecific trait variation in coexisting evergreen (Quercus ilex ssp. ilex and Q. ilex ssp. ballota) and deciduous (Quercus faginea and Quercus humilis) Mediterranean oaks along a wide water availability gradient in northeastern Spain during six years. We measured leaf area (LA), shoot twig mass (Sm), leaf mass per area (LMA) and the ratio of shoot twig to leaf biomass (Sm:Lm). We characterized tree performance through basal area increment (BAI) and drought resilience indices. Higher variation was found within individuals than between individuals across populations and years. Within species, we found trait adjustments toward more conservative water-use (low LA and Sm and high LMA) with increasing drier conditions. Intraspecific trait variation was constrained by water availability, particularly on the deciduous species. In Q. ilex, trait variance of LMA positively covaried with annual BAI, whereas variance of LA, Sm and Sm:Lm was positively related to resistance and resilience against the severe 2012 drought in deciduous oaks. Our results support a tradeoff between the ability to tolerate drought and the capacity to cope with unpredictable changes in the environment through increased intraspecific trait variation, which may have implications on tree performance in the face of increased extreme events.

Standardized framework for assessing soil quality at antimony smelting site by considering microbial-induced resilience and heavy metal contamination

Antimony smelting activities damage the soil and vegetation surroundings while generating economic value. However, no standardized methods are available to diagnose the extent of soil degradation at antimony smelting sites. This study developed a standardized framework for assessing soil quality by considering microbial-induced resilience and heavy metal contamination at Xikuangshan antimony smelting site. The soil resilience index (SRI) and soil contamination index (SCI) were calculated by Minimum Data Set and geo-accumulation model, respectively. After standardized by a multi-criteria quantitative procedure of modified Nemerow's pollution index (NPI), the integrated assessment of soil quality index (SQI), which is the minimum of SRINPI and SCINPI, was achieved. The results showed that Sb and As were the prominent metal(loid) pollutants, and significant correlations between SQI and SRI indicated that the poor soil quality was mainly caused by the low level of soil resilience. The primary limiting factors of SRI were Fungi in high and middle contaminated areas, and Skermanella in low contaminated area, suggesting that the weak soil resilience was caused by low specific microbial abundances. Microbial regulation and phytoremediation are greatly required to improve the soil quality at antimony smelting sites from the perspectives of pollution control and resilience improvement. This study improves our understanding of ecological effects of antimony smelting sites and provides a theoretical basis for ecological restoration and sustainable development of mining areas.

Ketahanan Psikologis pada Anak Jalanan: Dasar Pengembangan Layanan Intervensi bagi Konselor Komunitas

The purpose of this study was to determine the level of psychological resilience of street children in Semarang Social Service Institutions. This study uses a quantitative approach with an ex post facto research design. This research was conducted at two locations, namely the Mandiri Children's Social Service Center in Semarang and the Wira Adhi Karya Social Service Center in Semarang. The population in this study amounted to 150 street children. The research sample was 110 street children who were taken by area random sampling technique. The research instrument used was a psychological resilience scale. This study uses validity and reliability tests. Based on the 70 statement items on the psychological resilience scale, there are 48 statement items that are declared valid and reliable. This study uses data analysis techniques, namely descriptive analysis. Based on the results of the descriptive analysis, it was revealed that the psychological resilience of street children in Semarang Social Service Institutions was in the moderate category with M = 135 and SD = 15.4. While the researchers also revealed based on the results of the descriptive analysis that street children are in the moderate category on each indicator of psychological resilience according to the theory of Connor & Davidson.

Urban Flood Resilience Assessment of Zhengzhou Considering Social Equity and Human Awareness

Flooding is one of the world’s most devastating natural disasters, and the effects of global climate change further intensify its impact. In the context of flood management, urban resilience emerges as a promising perspective. While existing urban resilience assessment systems predominantly encompass economic, social, ecological, and infrastructural factors, they often neglect crucial dimensions like social equity and human awareness. We aimed to assess urban flood resilience considering social equity and human awareness. We have developed an indicator system called the 3-Dimentional Disaster Urban Flood Resilience Index System (3D-UFRIS) to address the issue. We also introduced social media data to explore the use of big data in urban flood resilience assessment. Scrapy was used to collect data and AHP-EWM was used to calculate the results. Our findings reveal a layered distribution of urban flood resilience of Zhengzhou, categorized into five levels: highest, higher, medium, lower, and lowest resilience. Notably, the highest resilience areas, covering a mere 3.06% of the total area, were primarily situated in the Jinshui district, characterized by strong economic activity, high public awareness, and a history of waterlogging incidents. Conversely, the lowest resilience areas, encompassing the largest portion at 36%, were identified in Zhongmou County, Xinzheng, and Shangjie District, marked by lower public awareness and limited medical accessibility. This study presents a pioneering approach to comprehending urban disaster resilience, offering valuable insights into mitigating flood-related risks and enhancing urban planning strategies.

Comparison of differences in performance between pigs whose sires were identified using different selection strategies after experimental infection with PRRSV.

The objective of this study was to evaluate differences in the performance of offspring of boars selected with an index emphasizing resilience and boars selected based on a traditional index, emphasizing feed efficiency and carcass quality (traditional) index vs. a customized (resilience) index. The resilience index was identical to the traditional index, except that extra emphasis was placed on piglet vitality (increased by 66%), growth rate (decreased by 14%), and feed intake (increased substantially by 5,157%). Sows were mated to either boars selected based on the resilience index or boars selected on the traditional index. Weaned offspring were vaccinated for Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) and experimentally infected with PRRSV RFLP 1-7-4 four weeks later. Offspring were allocated to pens (n ~ 27 pigs/pen; n = 27 pens/group) by sire-selection group for a total of 1,458 pigs in 54 pens. The weight of each pen was recorded on 0, 42, and 110 d postinfection (DPI) and used to calculate average daily gain (ADG), average daily feed intake (ADFI), and feed conversion ratio (FCR). Mortalities were recorded from 0 to 110 DPI and necropsies were routinely performed to characterize pathogens present within the barn. Pigs classified as full value (i.e., >104kg and void of defects) were slaughtered and hot carcass weight (HCW), backfat, loin depth, and lean weight were obtained from the slaughter plant. Effects of progeny group on performance, carcass characteristics, and mortality rate were estimated with a mixed linear model. Differences between progeny groups in ADG (P > 0.27), HCW (P = 0.68), backfat (P = 0.13), or loin depth (P = 0.39), and mortality rate (P = 0.29) were not detected. From 0 to 42 DPI, offspring of boars selected based on the resilience index had higher ADFI (0.06kg/d, P = 0.01) and higher FCR (0.12, P = 0.01). In summary, results from this study do not support selection of boars for increased feed intake, piglet viability, and robustness in order to prevent losses caused by PRRSV, but selection response was only measured after one generation of male selection. The impact of multiple generations of selection, or the development of an index including traits derived from data collected under disease-challenged conditions should be explored. The data collected for this study are a valuable resource to explore additional genetic selection strategies for enhanced resilience to a multifactorial PRRS challenge.

Analysis of mechanism and optimal value of urban built environment resilience in response to stormwater flooding

The concept of urban resilience focuses on understanding the process and mechanisms of disaster occurrence, providing innovative approaches to address stormwater flooding. However, existing studies primarily concentrate on enhancing overall system resilience, with limited research examining the temporal progression from stormwater disturbance to flood generation. To fill this gap, this study categorizes the development process of stormwater flooding into three periods: disturbance resistance (DR), adjustment and adaptation (AA), and rapid recovery (RR). Using the SWMM (Storm Water Management Model) software, 27 representative parcels in the Beijing-Tianjin-Hebei region of China were simulated. By sequentially considering single-indicator control variables, resilience indicators that significantly impact the three periods were identified through the construction of a stormwater flooding resilience indicator library. Subsequently, resilience models for each disaster phase were constructed using the BP (Back Propagation) neural network, and genetic algorithms were employed to optimize the models and determine the optimal values of resilience indicators for each period. Finally, the research findings were summarized into a resilience design method for the built environment to address stormwater flooding, accompanied by a guide for improving stormwater flooding resilience.The study reveals the following key findings: (1) the influence of physical and spatial elements in the built environment on stormwater flooding formation varies across different stages of the disaster process; (2) distinct resilience indicators operate at different times and in different ways throughout the entire stormwater flooding resilience process; (3) enhancing stormwater flooding resilience in the built environment does not necessarily require setting specific threshold values for each influencing indicator; instead, an optimal single value emerges when multiple indicators interact. Moreover, when multiple indicators interact, an optimal combination module with the best value for a single indicator exists. This study investigates the complete cycle from storm disturbance to flood disaster formation, offering both solutions for cities to mitigate storm flood disasters and advancing theoretical research on urban storm flood resilience while fostering interdisciplinary integration.