Evaluation of synergy ability and reconstruction of synergy organization for marine disaster monitoring and early warning in coastal cities, China

In order to improve the synergy level of marine disaster monitoring and early warning in coastal cities, an evaluation index system of 21 factors with 5 dimensions was constructed based on the synergy theory. The weights of all levels of indicators were determined by coefficient of variation method, and 24 representative coastal cities in China were evaluated by multi-layer gray correlation method. The evaluation results showed that: the level of synergy in each dimension of 24 coastal cities is uneven, and the distribution level is not high. The level of synergy of marine disaster monitoring and early warning in coastal cities is positively correlated with the level of economic development. The level of synergy of monitoring and early warning of marine disasters in 24 coastal cities is not high, which is generally distributed in medium and low levels. Furthermore, according to the evaluation results and the current situation of marine disaster monitoring and early warning in coastal cities, a network organization structure is proposed to enhance the synergy ability of the monitoring and early warning of coastal cities, so as to provide practical basis for the construction of China's coastal cities in the global marine disaster monitoring and early warning synergy.


Introduction
With global warming and rising sea levels, China's coastal cities are facing increasingly severe marine disasters.Disasters such as storm tides, red tides, huge waves, coastal erosion occur frequently, which has posed a serious threat to the safety of life and property in China's coastal cities (Hou et al., 2020).According to the data published in the ''China Marine Disaster Bulletin'': In the past ten years, the direct economic losses caused by marine disasters in coastal cities in China have reached an average of 10.004 billion yuan per year, and the average number of deaths (including missing) has reached 63 people per year.The losses caused by storm tides are particularly serious, accounting for about 97%.Disaster data showed that it is a long-term and arduous task for coastal city government to continuously enhance the ability of disaster prevention and mitigation; among them, accelerating the continuous improvement of the synergy ability of marine disaster risk monitoring and early warning is an important measure to rapidly enhance the disaster prevention and mitigation capabilities of coastal cities, which is also the primary task of disaster prevention and mitigation in coastal cities in China (Liu et al., 2022).
At present, the synergy ability of marine disaster risk monitoring and early warning in coastal cities in China has been generally improved, but it is still weak.Disaster risk monitoring and early warning collaboration are more limited to the scope of its jurisdiction, failing to effectively break through departmental and regional boundaries (Xu,31).Realize the linkage and coordination between coastal cities, especially on how to scientifically build the influencing factors of disaster risk monitoring and early warning synergy capabilities and effectively evaluate the current status of coastal cities' disaster risk monitoring and early warning synergy, and how to reconstruct the marine disaster monitoring and early warning organization of coastal cities based on the evaluation results is a practical problem that urgently needs to be solved in the construction of disaster prevention and mitigation in coastal cities in China, and it is also a hot issue being discussed by the scholars at home and abroad.
At present, the research on the evaluation of synergy of disaster risk monitoring and early warning and the collaborative organization structure is still in the preliminary stage.There are few related documents.The related results mainly focus on disaster monitoring and early warning mechanism, platform construction and application, emergency coordination evaluation research and emergency coordination mechanism construction, etc.
2 Literature review

Disaster monitoring and early warning mechanism
In the research of disaster monitoring and early warning mechanism, the research mainly focuses on the construction of disaster monitoring and early warning system, response mode and coordinated control.He et al.(2017) analyzed the development trend of the mountain flood disaster monitoring and early warning system in terms of the information sharing, dynamic early warning model and standardization, combined with descriptions of both its data structure and its big data characteristics (''4 V ?1C'').Henriksen, Hans et al.(2018) proposed a framework to reformulate the classic view of Early Warning and Monitoring Systems toward a participatory one.The new framework is developed for flood risks (from multiple flood hazards), using examples from selected Nordic and other European countries.Gonzalez et al.(2019) proposed a strategy based on the design and implementation of an early warning system (EWS) for extreme weather events.Xue et al.(2020) selected road monitoring video, used image difference operation and support vector machine (SVM) algorithm to identify the waterlogging area and used the region growing method to extract the waterlogging area range, which can be used for continuous monitoring and early warning of urban waterlogging in real time.

Platform construction and application research for disaster risk monitoring and early warning
In terms of platform construction and application research for disaster risk monitoring and early warning, it mainly focuses on the application of monitoring and early warning methods, system design and platform construction.Zhang (2020) designed a geological disaster monitoring and early warning system based on big data analysis and used a multi-sensor data fusion algorithm based on the D-S evidence theory and fuzzy mathematics to realize the integration of geological multi-dimensional heterogeneous monitoring data.Wang (2021) combined the randomness of velocity data in evolution process of landslide disasters, using Markov chain theory with no aftereffect to describe the randomness process, and introduced it into landslide warning to establish landslide warning model based on dynamic prediction of future velocity status by Markov chain theory.Lima et al.(2021) proposed a deep-learning neural network using Exponential Linear Unit activation functions for early and accurate warnings for flash floods.Bai et al. (1) took the Xingyi landslide in China as the research object and adopted an improved data analysis method and a comprehensive multi-threshold warning model to improve the accuracy of landslide warning.

Emergency coordination evaluation
In terms of emergency coordination evaluation, the current research mainly focuses on the evaluation of the coordination degree of emergency response.F. In terms of the construction of emergency coordination mechanism, Valecha, (2020) developed a framework for identifying emergency interactions that illustrate the templatic and dynamic styles as well as the active and passive patterns of interactions by examining data from the emergency reports and contributed to research in areas of interagency cooperation and emergency management.Based on the perspective of inter-organizational collaboration, Zhang et al. (2016) examined the formation mechanism of quick emergency response capability of urban rail transit and proposed the concept model hypothesis, in order to highlight the inter-organizational emergency collaboration relationships and the quick emergency response capability.Cai et al. (2017) compared the layout decision method in the existing management model and the hierarchical collaborative reserve layout method and established a multiobjective multi-level collaborative layout model under scenario analysis; Lin (2020) studied the relationship between data, tools and business process reorganization and constructed a multi-agent collaborative governance mechanism for network public opinion in emergencies.

Research gap
It can be seen from the above literature that although there are few documents involving marine disaster monitoring and early warning synergy and collaborative organization construction, the existing research has fruitful results in the basic theories, method applications and platform construction of disaster monitoring and early warning.For example, in the research of disaster risk monitoring and early warning, although the existing literature focuses on the implementation methods and operating systems of monitoring and early warning from the perspective of single disasters, in general, the existing literature mainly focuses on monitoring and early warning decision-making, organizational structure, process and resource guarantee, which provides a reference for this paper to study the evaluation index system of marine disaster monitoring and early warning synergy.In addition, a small amount of literature studied the evaluation of synergy degree of emergency response, which also provides a reference for the study of the evaluation method of marine disaster monitoring and early warning synergy degree and the coordinated organization structure.
The scientific problems to be solved in this paper: (1) Based on the synergy theory, construct an evaluation index system for the synergy degree of marine disaster monitoring and early warning in coastal cities; (2) Evaluate the marine disaster monitoring and early warning synergy in coastal cities in China; (3) According to the evaluation results and practical problems, the coordinated organization structure of marine disaster monitoring and early warning in coastal cities will be reconstructed.
The main innovation of this research is as follows: Construct a set of marine disaster monitoring and early warning synergy evaluation index system based on synergy theory; Use the multi-layer gray correlation method to evaluate the synergy degree of marine disaster monitoring and early warning in coastal cities in China; Reconstruct the coordinated organization structure of marine disaster monitoring and early warning based on the evaluation results.
3 Problem statement The organizational structure shown in Fig. 1 reflects the principles of unified leadership, hierarchical responsibility and rapid response in China's coastal cities in marine disaster monitoring and early warning, and to a large extent; it also reflects the guarantee function of various regions in the overall planning and management of monitoring and early warning resources.It reflects the organizational function of hierarchical leadership in unified command and accurate information transmission and also reflects the coordination function of various departments in the region in monitoring and early warning response.For example: In terms of marine disaster monitoring and information transmission procedures, marine environmental monitoring stations in accordance with the ''China Coastal Observation Regulations'' timely and accurately monitor the disaster-causing elements of various marine disasters, and if any abnormalities are found, they will promptly report to the higher authorities and the national marine environment forecast center; The monitoring data of marine disasters are transmitted in accordance with the ''China Marine Environmental Monitoring Station and Volunteer Ship Monitoring Data Transmission Regulations'' to ensure that marine forecasting centers at all levels obtain monitoring data in a timely manner; Municipal and county-level maritime bureaus, in accordance with the ''Marine Data Buoy Real-time Data Transmission Regulations'', transmit buoy monitoring data to marine forecast Fig. 1 The organization structure of marine disaster monitoring and early warning in coastal cities in China, Source: Maritime Safety Administration of the People's Republic of China centers at all levels in a timely manner; The National Marine Environmental Monitoring Center analyzes and processes the shore-based ice measurement radar monitoring data, and transmits them to the National Marine Environmental Forecast Center, the Beihai Marine Forecast Center, and the provincial marine forecast stations in a timely manner.In short, each marine management department performs its own duties and cooperates closely to ensure the rapid and effective transmission of marine disaster monitoring information.

The main problem
This paper summarized the main problems of the organization structure of marine disaster monitoring and early warning in coastal cities in China from 4 aspects: the level of cross-domain department coordination, the subjects of the cross-domain monitoring and early warning collaboration, the monitoring information sharing level and the ability to integrate and exchange monitoring and early warning resources, as shown in Table 1.
In this paper, coefficient of variation method is used to determine the weights of all levels of indicators, and multi-layer gray correlation evaluation method based on gray system theory is used to evaluate the coordination of Marine disaster monitoring and early warning of 24 coastal cities in China.In the following, the indices, parameters and vectors to develop the proposed model are defined first.

Indices
v i Index of the coefficient of variation of the i-th.o i Index of the standard deviation of the i-th index.
x i Index of the average of the i-th index.w i The weight of each indicator.

Parameters f nk k
The original data value of the n-th coastal city in the k-th index, k = 1,2,…,21 is the index number, n = 1,2,…,24 is the coastal city number.
q n The comprehensive evaluation value of the n-th coastal city.
w k The weight value of the k-th indicator.

Vectors
A The index variation coefficient and the value.Q The correlation degree vector.W The weight vector of k indicators.

Definition of disaster monitoring and early warning synergy
Synergy theory was originally founded by the German scientist Harken.This theory believes that the total utility of the integration of the various elements of the system through conscious behavior is greater than the sum of the utility of each part.The emergency synergy refers to the process in which two or more organizations conduct collective emergency actions through knowledge sharing, resource exchange and information communication in order to achieve common goals (Huang et al., 2020).According to the definition of emergency synergy, in order to achieve a common emergency goal, two or more emergency organizations are required to achieve comprehensive integration and mutual cooperation in knowledge sharing, resource exchange and information communication.This comprehensive integration and mutual cooperation are called emergency synergy, which is comprehensively embodied in the main decision-making synergy, resource exchange Table 1 Main problems of the organization structure of marine disaster monitoring and early warning in coastal cities in China

Dimension
The main problems The level of cross-domain department coordination 1. Relatively smooth vertical coordination but insufficient horizontal linkage development

the lack of a global organization, resulting in insufficient utilization of resources and inconsistent global actions
The subjects of the cross-domain monitoring and early warning collaboration 1.The unity of the subjects of the cross-domain monitoring and early warning collaboration

The difficulty of social mobilization mechanisms to effectively implement
The monitoring information sharing level 1.The lack of a unified monitoring information system, legal technical specifications, data standards and exchange formats between government departments 2. The lack of a global monitoring and early warning information sharing mechanism (Liu et al., 2011) The ability to integrate and exchange monitoring and early warning resources 1.The lack of global resource integration and exchange mechanism Evaluation of synergy ability and reconstruction of synergy organization for marine disaster... synergy, organizational guarantee synergy, process synergy, and information sharing synergy.Early warning system is an integrated concept.The United Nations International Strategy for Disaster Reduction (UNISDR) (2009) defines it as: An integrated system of hazard monitoring, forecasting and prediction, disaster risk assessment, communication and preparedness activities systems and processes that enables individuals, communities, governments, businesses and others to take timely action to reduce disaster risks in advance of hazardous events.In view of this, this paper defines the synergy of disaster monitoring and early warning as: In order to improve the efficiency and reduce the risk of disaster monitoring and early warning, through close and mutual cooperation, multiple organizations involved in monitoring and early warning can integrate and continuously optimize the sub collaborative systems such as decision-making of monitoring and early warning subjects, exchange of monitoring and early warning resources, organizational support of monitoring and early warning, monitoring and early warning process and monitoring and early warning information sharing.

Evaluation indicators for synergy of marine disaster monitoring and early warning in coastal cities
According to the definition of disaster monitoring and early warning synergy, the synergy of marine disaster monitoring and early warning of coastal cities is mainly embodied in five aspects: the decision-making of monitoring and early warning subjects, the exchange of monitoring and early warning resources, the guarantee of monitoring and early warning organizations, the monitoring and early warning response process, and the sharing of monitoring and early warning information, etc.
(1) Decision-making synergy of monitoring and early warning subjects.The decision-making synergy of monitoring and early warning subjects plays a leading role in the monitoring and early warning of marine disasters in coastal cities.All participating entities need to reach agreement on the decision-making issues of the entire process of marine disaster monitoring and early warning, and form a jointly recognized decision-making plan and contractual relationship agreed to comply with, which is mainly reflected in the synergy between decision-making subjects and collaboration with government, enterprises (social groups) and the public (Shan et al., 2022).(2) Monitoring and early warning resources exchange synergy.Monitoring and early warning resource exchange synergy provides technical and resource support for marine disaster monitoring and early warning and plays a core supporting role, which is mainly reflected in the uniformity of professional technical standards, the sharing of monitoring and early warning facilities, the level of monitoring and early warning equipment, and the sharing of monitoring and early warning knowledge.(3) Monitoring and early warning organizations guarantee synergy.Coastal cities have similar geographical features and marine disaster types.In the event of a major marine disaster, the coverage of disaster is large, and it is necessary to achieve cross-departmental and cross-regional cooperation, and establish an organization with unified command, clear division of labor, information sharing and high synergy, which is a key guarantee for enhancing the synergy of marine disaster monitoring and early warning.It is mainly reflected in the orderliness of the organization structure, the response efficiency of the organizational hierarchy, the level of cross-department synergy in the same city and the level of synergy between departments in different cities (Zheng et al., 2018).( 4) Monitoring and early warning process synergy.The monitoring and early warning process is mainly embodied in the preliminary synergy, preparation synergy, response synergy, and post-evaluation synergy capabilities of monitoring and early warning.It is a key measure for the synergy of marine disaster monitoring and early warning.Among them, the preliminary synergy is mainly reflected in the completeness of basic monitoring data, the maintenance level of monitoring and early warning facilities and equipment and the completeness of the monitoring and early warning network; the preparation of synergy is mainly reflected in the deployment of monitoring and early warning personnel, and the monitoring and early warning funding; response synergy is mainly reflected in the adequacy of monitoring and early warning information collection, the analysis and judgment of monitoring and early warning information, the effectiveness of monitoring and early warning equipment and the completeness of the communication guarantee network; the postevaluation synergy is mainly reflected in the application and execution of evaluation results.(5) Monitoring and early warning information sharing synergy.The coordination of monitoring and early warning information sharing plays a role in information transmission in the entire marine disaster monitoring and early warning coordination process.It is the core guarantee for the improvement of monitoring and early warning coordination, which is mainly reflected in the ability of monitoring and warning information transmission speed, information sharing timeliness and information quality provision.
Based on the definition of emergency synergy theory and disaster monitoring and early warning synergy, this paper proposed an evaluation index system of 25 factors in 5 dimensions that affect the synergy of marine disaster monitoring and early warning in coastal cities.In order to further reflect the comprehensiveness, representativeness and scientificity of indicators, the indicators are improved by consulting a large number of documents, expert interviews and questionnaire surveys, obtain the expert scoring data for indicator screening, and the principal component analysis method is used to conduct the initial indicators.The process is as follows: Step 1 Through literature review, expert interviews and questionnaires, the original 5 dimensions and 25 factors were increased or decreased.Increase the response speed of the decision-making subjects and the efficiency of group decision-making in the dimension of the decision-making synergy of the monitoring and early warning entities; in the dimension of monitoring and early warning resource exchange synergy, three factors are added: the timely rate of monitoring and early warning, the technical support of monitoring and early warning, and the ability to mobilize monitoring and early warning resources; increase the unity of organizational action in the dimension of monitoring and early warning organizations guarantee synergy; add two factors in the dimension of monitoring and early warning process synergy: the unified mobilization of monitoring and early warning teams and the uniformity of evaluation standards; in the monitoring and early warning information sharing synergy dimension, the clarification factor of the subjects of information responsibility is added.This addition changes the indicators from the original 5 dimensions with 25 factors to 5 dimensions with 34 factors.
Step 2 The expert 7-level scale assignment method is used to obtain index screening data.According to the relevance and importance of the indicators, experts score 34 factors in 5 dimensions according to the 7-level scale assignment method.
Step 3 Factor dimension reduction.According to the principal component analysis method, the cumulative contribution rate of the index is obtained, and the factors with the characteristic root greater than 1 are retained, and the explanatory power reaches 83%.The factors with the characteristic root less than 1 are deleted, which belongs to the index with weak explanatory power.The deleted factors include: the group decision-making efficiency and the response speed between the decision-making subjects in the dimension of the synergy of decision-making of the monitoring and early warning subjects; the monitoring and early warning resource mobilization capabilities, monitoring and early warning facilities and equipment sharing, and the uniformity of professional technical standards in the dimension of monitoring and early warning resource exchange synergy; the order of the organizational structure and the level of inter-departmental collaboration in the same city in the dimension of the synergy of the monitoring and early warning organization guarantee; the monitoring and early warning facility maintenance level, the adequacy of monitoring and early warning information collection, the completeness of the communication support network, and the unified mobilization of monitoring and early warning teams in the dimension of the synergy of the monitoring and early warning process; the factors such as the speed of monitoring and early warning information transmission and the clarification of information responsibility subjects in the dimension of monitoring and early warning information sharing synergy.Finally, the evaluation index system of 21 factors in 5 dimensions is obtained, as shown in Table 2.
Step 4 Calculate indicator weights.This paper uses the coefficient of variation method to determine the weights of all levels of indicators in Table 3, the steps are as follows: (1) According to the sample data, calculate the average value and standard deviation of each indicator; (2) Calculate the coefficient of variation based on the mean and standard deviation: In the formula ; v i is the coefficient of variation of the i-th index, o i is the standard deviation of the i-th index, and x i is the average of the i-th index.
(3) Calculate the index variation coefficient and the value of A: (4) Use the normalization method to get the weight w i of each indicator.Divide the coefficient of variation of each indicator by the sum of the coefficient of variation of the indicator: 3.4 Evaluation of Synergy of marine disaster monitoring and early warning in coastal cities  The results showed that the qualitative index values assigned by experts have good statistical significance, and the reliability of the evaluation data is high.The final score of each qualitative index is calculated as the average value (Fig. 2).

Multi-layer gray correlation evaluation method for marine disaster monitoring and early warning synergy
In the selection of evaluation methods, there are currently few evaluation methods for emergency synergy.The representative result is from Pan (2014),which used the coupling degree theory in physics to describe the synergy degree of the system; there is a lot of research on evaluation methods of emergency systems, and a mature method system has been formed, mainly including simple comprehensive evaluation methods, such as comprehensive index method, efficiency coefficient method, comprehensive integral method; operational research methods, such as fuzzy comprehensive evaluation method, DEA method; multivariate statistical methods, such as principal component analysis method, factor analysis method, cluster analysis method, discriminant analysis method.The above evaluation methods are more targeted at the problem of data certainty, and it is difficult to effectively solve the asymmetry problems of partial data determination, part of information uncertainty or data completely unknown.
Although the fuzzy comprehensive evaluation method can deal with the problem of uncertain data, the method needs to know the fuzzy level of the index in advance and cannot effectively deal with the fuzzy index problem with disordered characteristics.In view of this, this paper adopts the multi-layer gray correlation evaluation method based on gray system theory to evaluate the synergy of marine This research An evaluation index system for the synergy degree of marine disaster monitoring and early warning in coastal cities

Marine Disaster
Evaluation of synergy ability and reconstruction of synergy organization for marine disaster... disaster monitoring and early warning of 24 coastal cities in China.This method is a multi-factor statistical analysis method that uses the similarity of geometric shapes to analyze the influence of factors (He,5), which can better deal with the comprehensive evaluation of fuzzy indicators with disordered characteristics.
(1) Single-layer gray correlation evaluation (1) Construct the original evaluation matrix M In the formula, f nk k represents the original data value of the n-th coastal city in the k-th index, k = 1,2,…,21 is the index number, n = 1,2,…,24 is the coastal city number.
(2) Standardized processing of indicators In order to eliminate the difference of inconsistent index dimensions and different magnitudes, the original evaluation matrix M needs to be standardized.For positive indicators, the following formula is used for normalization.
For negative indicators, use the following formula for normalization.
After the normalization of formulas ( 5) and ( 6), the following normalized matrix Rij is obtained.
(3) Determine the optimal index set D In the formula, d k is the optimal value of the k-th index in the normalized matrix Rij.(4) Calculate correlation coefficient Suppose the correlation coefficient between the kth index of the n-th coastal city and the optimal value of the k-th index is b n ðkÞ, then, In the formula, According to formula (9), the incidence matrix A is obtained.
(5) Calculate weighted correlation degree In the formula, Q ¼ q 1 ; q 2 ; . ..; q n ½ is the correlation degree vector, the table is the comprehensive evaluation result vector of n coastal cities, q n is the comprehensive evaluation value of the n-th coastal city, the larger the q n , the better the synergy performance of the n-th coastal city in a certain dimension; W ¼ w 1 ; w 2 ; . ..; w k ½ is the weight vector of k indicators, w k is the weight value of the k-th indicator.
After a single-layer gray correlation evaluation, the synergy of 24 coastal cities in 5 dimensions can be obtained, that is, the comprehensive evaluation of the second layer (factor layer) is completed.In order to classify the 5 dimensions of synergy level, the evaluation results need to be further normalized to classify according to Table 1.If the overall synergy of the 24 coastal cities is to be obtained, a multi-level gray correlation evaluation is required, that is, a comprehensive evaluation of the first dimensional layer needs to be completed.
According to the previous single-layer gray correlation evaluation results, the evaluation result vectors of 24 coastal cities in 5 dimensions are obtained, as shown in Table 4.
Q 1 * Q 5 are formed into the original evaluation matrix of the dimensional layer, and then, the first dimensional layer is evaluated.The evaluation method and steps are the same as the single-layer evaluation method.After the evaluation of the first dimensional layer is completed, the overall evaluation results of the coordination of marine disaster monitoring and early warning of 24 coastal cities can be obtained; then, the evaluation results are normalized to facilitate classification.
(3) Collaboration rating In this paper, referring to the classification standard by Su (2018), the 24 coastal cities are divided into the level of synergy in each dimension and the overall level of synergy.The classification standard is shown in Table 5.

Results And Discussion
According to the evaluation method of 3.2.1 to evaluate the coordination of marine disaster monitoring and early warning of 24 coastal cities, the evaluation is divided into two stages.The first stage is to evaluate the 5 dimensions of the coordination of marine disaster monitoring and early warning of 24 coastal cities; the second stage is the overall evaluation of the coordination of marine disaster monitoring and early warning in 24 coastal cities.
The first stage: 5 dimensions evaluation of the coordination of marine disaster monitoring and early warning in 24 coastal cities.This stage is a single-layer gray correlation evaluation, which uses 21 factors to evaluate 5 dimensions.The evaluation results are shown in Table 6.
Table 6 reflects the performance of 24 coastal cities in 5 dimensions, and the ranking results are shown in Fig. 3.
(1)Uneven distribution of synergy levels in each dimension.In the dimension of decision-making coordination of monitoring and early warning subjects, 7 cities have a high level, accounting for 29%, including Dalian, Shanghai, Shantou, Lianyungang, Shenzhen, Xiamen and Zhuhai.The remaining 17 cities have a medium level, accounting for 71%.In the coordination of monitoring and early warning resource exchange, there are 4 high-level cities, accounting for 17%, including Dalian, Guangzhou, Zhuhai and Shanghai, and 13 medium level cities, accounting for 71%, including Quanzhou, Lianyungang and Nantong, Shantou, Qingdao, Haikou, Xiamen, Zhoushan, Shenzhen, Ningbo, Zhanjiang, Qinhuangdao, Sanya, Wenzhou, Yingkou, Tianjin and Fuzhou, three low-level cities, accounting for 15%, including Weihai, Yantai and Beihai.In the dimension of coordination of monitoring and early warning organizations, there are 9 high-level cities, accounting for 38%, including Dalian, Zhuhai, Shanghai, Shenzhen, Lianyungang, Guangzhou, Xiamen, Tianjin Monitoring and early warning subject decision-making synergy U1 Q 1 =½q 1 1 ; q 1 2 ; . ..; q 1 n Q 2 Monitoring and early warning resource exchange synergy U2 Q 2 =½q 2 1 ; q 2 2 ; . ..; q 2 n Q 3 Monitoring and early warning organizations guarantee synergy U3 Q 3 =½q 3 1 ; q 3 2 ; . ..; q 3 n Q 4 Monitoring and early warning process synergy U4 Q 4 =½q 4 1 ; q 4 2 ; . ..; q 4 n Q 5 Monitoring and early warning information sharing synergy U5 Q 5 =½q 5 1 ; q 5 2 ; . ..; q 5 n and Sanya.The remaining 15 cities are medium level, accounting for 62%.In the dimension of synergy in the monitoring and early warning process, there are 3 highlevel cities, accounting for 13%, including Fuzhou, Guangzhou, and Shenzhen, and 6 low-level cities, accounting for 25%, including Weihai, Sanya, Yantai, and Quanzhou, Yingkou and Beihai, and the other 15 cities are classified as medium.In the dimension of collaborative sharing of monitoring and early warning information, there are 11 high-level cities, accounting for 46%, including Shenzhen, Fuzhou, Shanghai, Guangzhou, Ningbo, Wenzhou, Zhoushan, Sanya, Shantou, Qinhuangdao and Haikou, and the remaining 13 cities are classified as medium, accounting for 54%.Cities that perform better in all five dimensions are Dalian, Shanghai, Zhuhai, Shenzhen and Guangzhou.Compared with other cities, these five cities perform well in some key factors.These key factors include coordination among decision-makers, collaboration with governments, timeliness rate of monitoring and early warning, equipment level of monitoring and early warning, unity of organization and action, coordination level between departments in different cities, completeness of monitoring basic data and completeness of monitoring and early warning network.(2)The distribution of synergy in the five dimensions of coastal cities is in the middle and low levels.In general, among the five dimensions, there are an average of 7 cities with a high level, accounting for 29%, an average of 15 cities with a medium level, accounting for 63%, and an average of 2 cities with a low level, accounting for 8%, the city with a very high level is 0, indicating that the coordination level of the various subsystems of the marine disaster monitoring and early warning coordination of coastal cities in China is not high, and most of them are distributed in the middle and low level (Fig. 4), that is, the coordination is mostly below 0.6, especially the monitoring and early warning organization guarantee coordination, resource exchange coordination and information sharing coordination level is not high, which is the key construction content of coastal cities.
The second stage: the overall evaluation of the coordination of marine disaster monitoring and early warning in 24 coastal cities.This stage belongs to multi-layer gray correlation evaluation, which uses 5 dimensions to evaluate the overall situation of marine disaster monitoring and early warning synergy.It belongs to the first layer of evaluation.The evaluation results are shown in Table 7.
(1) The level of coordination in monitoring and early warning of marine disasters in coastal cities in China is not high.
It can be seen from Table 4 that only Shenzhen and Zhuhai, accounting for 8%, belong to the high level of synergy.From the perspective of dimensional performance, the two cities have outstanding performance in three dimensions: organizational guarantee coordination, resource exchange coordination and information sharing coordination.Cities with a very high level of synergy are 0; 9 cities with a middle level of synergy, accounting for 38%; 13 cities with a low level of synergy, accounting for 54%.It can be seen from Fig. 5 that 92% of coastal cities in China have low-to-medium level monitoring and early warning coordination, and the overall level of coordination is not high.
(2) The level of economic development is positively correlated with the synergy of marine disaster monitoring and early warning in coastal cities.
It is further sorted according to the synergy (Fig. 6).From the ranking results, the more developed the economic level of the city, the level of synergy is generally better than that of the less developed city, indicating that the level of economic development affects the level of monitoring and early warning synergy.
In short, from the above evaluation results, it can be seen that the coordination of marine disaster monitoring and early warning in coastal cities in China is unevenly distributed.Cities with high economic levels have generally high levels of coordination.On the contrary, cities with underdeveloped economies have low levels of coordination.The overall level of coordination of monitoring and early warning in China's coastal cities is in the low to midlevel, which is reflected in the low level of inter-departmental coordination, low level of monitoring and early warning disaster information sharing, insufficient organizational support, and weak resource exchange capabilities.The existing marine disaster monitoring and early warning platform needs to be integrated and reconstructed to meet the marine disaster monitoring and early warning needs of China's coastal cities.

Managerial insights and practical implications
According to the above discussion and analysis of the current situation, the key to reconstruct the collaborative organization structure of marine disaster monitoring and early warning in coastal cities is to establish and improve the global collaborative organization structure of monitoring and early warning.On this basis, the timely sharing of monitoring and early warning information and the effective exchange of monitoring and early warning resources are realized, the operation mechanism of the monitoring and early warning system is established, and the multi-agent linkage response of monitoring and early warning is realized, etc.Since the marine disaster monitoring and early warning management system involves multiple stakeholders, it requires the cooperation of multiple departments and multiple subjects among coastal cities.This kind of multi-subject, multi-department, crosscity and cross-regional collaboration forms an intricate network relationship.It is necessary to adopt a networked governance model to build a networked marine disaster monitoring and early warning collaborative organization structure (Lin, 2007;Jiang, 2007;Wang, 2008;Liu 2018).The reconstruction idea lies in: First, build a crossregional and cross-departmental marine disaster monitoring and early warning collaborative organization system, and design it as a network-based dynamic collaborative organization; second, establish a multi-agent cooperative Figure 7 shows a cross-regional, low-level dynamic collaborative organization structure.marine disaster monitoring and early warning command center of the whole region is mainly responsible for the collection, processing, and analysis of monitoring information, as well as marine disaster early warning and forecasting, and is responsible for the allocation of resources for monitoring and early warning of marine disasters and the allocation of personnel, and the coordination and command of monitoring and early warning of marine disasters.The leaders of the marine administrative departments of the provinces (municipalities and autonomous regions) are the constituent members, mainly responsible for the command, coordination and cross-regional coordination of the region.All coastal cities are divided into several regions according to the level of synergy, and the municipal and county-level maritime departments and monitoring stations in each region are responsible for the execution and implementation of policies of specific monitoring and early warning work, and responsible for coordination and collaboration with other regions, and responsible for transmitting monitoring and early warning information to the higher-level marine administrative departments in the jurisdiction and other regions.All participating departments and subjects are linked through the network to form a dynamic network structure with dynamic management across the domain, a high degree of command uniformity, and close cooperation between regions, through effective operating procedures and scientific operating mechanisms, the coordination of monitoring and early warning of marine disasters in coastal  (1) It can effectively realize the unified command of the monitoring and early warning of marine disasters in the whole region.In terms of organizational structure, the global marine disaster monitoring and early warning command center negotiates and deploys monitoring and early warning work of whole region to ensure its leadership and command position; In terms of work content, the command center can carry out unified handling around information sharing, resource exchange, monitoring information processing, monitoring and early warning resource integration, early warning and forecasting decision-making, and information release to ensure the unity of command and the authority of information and decision-making (Zhou, 2018).(2) Conducive to the formation of a regional information sharing mechanism.Under the localized management system, monitoring information is carried out in accordance with administrative subordination and administrative hierarchy, which can ensure the vertical transmission of monitoring information.
For horizontal or cross-domain, monitoring information cannot be effectively shared and transmitted, resulting in emergency coordination between cities.By establishing a monitoring and early warning collaborative organization structure based on a network structure, it can effectively strengthen the information sharing between horizontal and crossdomain departments.(4) Conducive to the practice of territorial management and unified command principles.Dividing the whole area into several management areas, each area in accordance with the principle of territorial management, is conducive to the implementation and implementation of the monitoring and early warning tasks in the area.At the same time, in accordance with the administrative affiliation, it can also command and act in a unified manner in the region.(5) It can effectively realize the upper and lower docking and regional linkage.The members of the command center are composed of the leaders of the provincial ocean bureau, which mainly communicate and make decisions through joint meetings, which is conducive to mutual consultation and communication among various regions; The municipal and county-level maritime bureau-level monitoring stations in each region, in addition to the leaders of the provincial marine department in their respective regions, have formed a cooperation mechanism for information sharing and mutual communication, which is conducive to the upper and lower docking and regional linkage of monitoring and early warning work.(6) It is conducive to the participation of multiple subjects and cooperation and co-governance.This kind of monitoring and early warning collaborative organizational structure based on the network structure has good compatibility and can incorporate social subjects into the organizational structure, which can make full use of social resources to serve the monitoring and early warning of the whole region, and can realize a collaborative network structure of cooperation and co-governance with active participation of multiple subjects (Wu 2011).

Conclusions
In this paper, we focus on evaluating the coordination of marine disaster monitoring and early warning and reconstructing the organizational structure of marine disaster monitoring and early warning in coastal cities in China.based on the synergy theory, this paper focuses on the five dimensions of marine disaster in coastal cities including: monitoring and early warning subject decision-making, monitoring and early warning resource exchange, monitoring and early warning organization guarantee, monitoring and early warning response process, and monitoring and early warning information sharing.an indicator system for evaluating monitoring and early warning synergy has been constructed in coastal cities; The multi-level gray correlation evaluation method is used to empirically verify the monitoring and early warning synergy of 24 coastal cities in China.The empirical results show that the level of synergy in each dimension of the 24 coastal cities is unevenly distributed, and the overall distribution of synergy in the five dimensions is at the middle and low level; The evaluation results show that the level of coordination in monitoring and early warning of marine disasters in 24 coastal cities is not high, and the level of economic development is positively correlated with the level of coordination in monitoring and warning.Finally, based on the evaluation results and the development status of coastal cities' marine disaster monitoring and early warning synergy development, we propose a network structure-based coastal city monitoring and early warning synergy organization structure; it provides a realistic basis for China's coastal cities to build a full-scale marine disaster monitoring and early warning synergy capability.However, this article uses expert grading method to obtain data for some qualitative indicators, the reliability of the evaluation results needs to be verified; this article does not consider the sensitivity of indicators, which to some extent restricts the rational understanding of key factors in the system.

Fig. 2
Fig. 2 Distribution map of disaster prevention capabilities of coastal cities in China, Green means ''good'', yellow means ''average'', and red means ''poor'' Source:Huang X, Jin HD, Bai H. 2019.Vulnerability assessment of China's coastal cities based on DEA cross efficiency model.International Journal of Disaster Risk Reduction,(36): 1-11.

Fig. 3
Fig. 3 Collaboration ranking of various dimensions of marine disaster monitoring and early warning in coastal cities

Fig. 4
Fig. 4 Overall distribution of synergy in each dimension

Fig. 5
Fig. 5 Distribution of coordination of marine disaster monitoring and early warning in coastal cities (3) Conducive to the realization of global resource sharing and mutual coordination.Constructing a coordinated organization structure for global monitoring and early warning can integrate all coastal cities into an overall management, which is conducive to the overall planning of global monitoring and early warning resources, realizes resource sharing and mutual coordination, and achieves the purpose of resource optimization and overall planning.

Fig. 7
Fig. 7 Cooperative organizational structure for marine disaster monitoring and early warning in coastal cities

Table 2
Evaluation index system of coordination of marine disaster monitoring and early warning in coastal cities

Table 3
Survey of related work

Table 5
Classification standards for coordination of marine disaster monitoring and early warning in coastal cities

Table 6
Evaluation results of 5 subsystems in coastal city marine disaster monitoring and early warning synergy