INTELLIGENT MANAGEMENT METHODS OF

WATER ENVIRONMENT RESOURCES IN

THE CONTEXT OF GREAT ECONOMY

Xiaoyun Ma

• Jiyang College of Zhejiang A&F University, Shaoxing, Zhejiang, 311800, China

•zhuyan10086@126.com

Yan Zhu*

• Ecology and Environmental Science Research & Design Institute of Zhejiang

Province, Hangzhou, Zhejiang, 310007, China

Reception: 20 February 2024 | Acceptance: 10 April 2024 | Publication: 21 May 2024

Suggested citation:

Ma, X. and Zhu, Y. (2024).Intelligent Management Methods of water

environment resources into the context of great economy. 3C Empresa.

Investigación y pensamiento crítico. 13(1), 252-271. https://doi.org/

10.17993/3cemp.2024.130153.252-271

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ABSTRACT

In this paper, under the background of big economy, firstly, we integrate the life

community of mountains, water, forests, fields, lakes and grasses, combined with the

construction of wastewater treatment and the supporting pipeline network, and

complete the architecture of the overall governance framework of the management

system. Secondly, based on information resources and infrastructure, design the

application functions and application system architecture of the intelligent

management system to realize the integrated management of the whole life cycle of

water environment resources. It also describes the attribute values of cloud computing

service processing capability, sets the feature item labels between sensing, and lays

the foundation for the clustering distribution of management function modules. Finally,

scientific and technological innovation is proposed as an important means to improve

the utilization efficiency of water environmental resources, to realize the mutual

promotion of high-quality economic development and total water consumption control,

industrial structure transformation and upgrading. The results show that the overall

situation of water environment resource intelligent development is very good, with

good satisfaction accounting for 84% of the overall, and the highest system evaluation

of 4.93 points, which proves the effectiveness of this paper's water environment

resource intelligent management system.

KEYWORDS

Big economic background; intelligent management; system architecture; cloud

computing; cluster distribution

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INDEX

ABSTRACT .....................................................................................................................2

KEYWORDS ...................................................................................................................2

1. INTRODUCTION .......................................................................................................4

2. INTELLIGENT MANAGEMENT SYSTEM DESIGN FOR WATER ENVIRONMENT

RESOURCES ...........................................................................................................6

2.1. Overall governance framework ..........................................................................6

2.2. Intellectualized service application system ........................................................8

2.3. Cloud Computing Service Attribute Values ......................................................10

2.4. Water Environment Resource Utilization Efficiency .........................................11

3. MODELING OF WATER ENVIRONMENT RESOURCE UTILIZATION EFFICIENCY

4. INTELLIGENT MANAGEMENT SYSTEM SIMULATION ANALYSIS ....................13

4.1. Questionnaire design .......................................................................................13

4.2. Analysis of Interview Results ...........................................................................15

4.3. Analysis of questionnaire results ......................................................................16

5. CONCLUSION ........................................................................................................18

ABOUT THE AUTHORS ...............................................................................................18

FUNDING ......................................................................................................................19

REFERENCES ..............................................................................................................19

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1. INTRODUCTION

Intelligent management of water environment resources is an important content to

promote the modernization of water environment governance system and governance

capacity, and a major change to promote the construction of ecological civilization,

modernization of governance system and modernization of governance capacity [1-2].

With the rapid development of social and economic development and industrialization,

people are increasingly aware of the importance of promoting green development,

strengthening the construction of water environment infrastructure and improving the

quality of water environment [3]. And it is of great significance to design intelligent

management methods for water environmental resources to reasonably determine the

scale of the project, improve regional water resources planning and rational allocation,

establish a strict water resources management system, and improve the efficiency of

water resources utilization [4-5]. At present, the research on water environment

management mainly focuses on the research and development of water environment

management related technologies, while the research on water environment resource

management ideas and their applications based on intelligent management is less [6].

Therefore, it is necessary to comprehensively sort out the engineering construction of

water environment resource management, search for the optimal management path,

provide conditions for comprehensively and efficiently implementing the intelligent

management of water environment resources, and design the intelligent management

system of water environment resources in the context of the large economy in order to

effectively achieve the management objectives [7].

Influenced by climate change, human activities and socio-economic development,

water resources management in river basins is facing more and more uncertainty and

complexity. On this basis, Wang, Y et al. proposed a GIS-based water resources

visualization knowledge map to visualize and quantify the knowledge base, domains

and structures of water resources management by applying bibliometrics and

knowledge mapping to safeguard the health and integrity of the ecosystems from the

perspectives of sustainable and adaptive development, and by applying bibliometrics

and knowledge mapping methods. The results of the study show that the research on

water resources management in watersheds is on the rise [8]. With the acceleration of

economic and industrialization processes, more and more chemical substances are

emitted into the environment, and these chemical pollutants are potentially harmful to

human health, especially prolonged exposure to the atmosphere can cause lipid

metabolism disorders. Therefore, Zheng, S et al. found a positive correlation between

NAFLD and long-term exposure to pollutants by analyzing the results of population

and toxicological studies, and the study will help to better understand the mechanism

of liver damage caused by pollutants in the water environment [9]. Acciarri, M. F et al.

proposed a set of integrated solutions of water resources management and renewable

energy development for ecologically fragile areas based on the summary of the

existing research results. Renewable energy development in ecologically fragile

areas. Firstly, the main research content of the project is presented, then the main

research content of the project is introduced and the feasibility study of the project is

conducted. Finally, in each alternative, water homogenization cost and water

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homogenization emission were calculated separately [10]. Soil moisture information is

an important basis for understanding global climate change, and the validity of soil

moisture information is very limited by the limitation of field observation means,

especially in the mountains. Osenga, E et al. took the Southern Rocky Mountains of

Colorado, USA as the research object, and by constructing a set of new set of

interactive roaring bifurcation observation network based on multi-disciplines, such as

climate, soil, and ecology, etc., the preliminary study was carried out. Through the

implementation of the project, it can provide new ideas for mountain ecological

meteorological research, and it can provide a reference for long-term monitoring work

[11]. Literature [12] adopts a scientific and efficient way to enable everyone and

anyone in the organization to participate in personnel management. Big data analytics

and information technology (IT) are used to explore how IT can be utilized to solve the

current problems faced by companies. Through the application of data mining theory,

human resource management theory, the process of data mining and analysis

methods, and its intrinsic connection is deeply analyzed, and the problems are

discussed in depth, so as to provide a reference for improving the management level

of human resource managers. With the management of water resources and

environment, the reliability of medium- and long-term hydrological prediction has been

put forward higher requirements. Bogner, K et al. Based on the previous work, they

carry out the research on hydrological prediction method of watersheds based on

numerical simulation and apply it to the monthly meteorological observation data to

analyze the value of its application in hydrological prediction. Taking four catchments

with real measurement data as an example, post-processing techniques were used to

eliminate bias and diffuse errors, and they were validated and evaluated [13]. The

problem of water scarcity has become a prominent issue in economic and social

development, in order to ensure the supply of water resources, on the basis of the

survey results, LI, W et al. planned six emergency water sources, and discussed the

amount of water withdrawn from each source and the corresponding management

countermeasures. In the long term, the utilization of aquifers as reservoirs and the

joint utilization of surface water and groundwater are of great significance in ensuring

water security and sustainable management of water resources [14].

In the context of large economy, intelligent management of water environment

resources is particularly important. In order to improve the utilization efficiency of

water environmental resources, the key elements such as the overall governance

framework, the intelligent service application system, the value of cloud computing

service attributes and the utilization efficiency of water environmental resources are

fully considered. A framework that organically integrates the resources and strengths

of all parties is established to ensure the full implementation of the intelligent

management system. This includes the participation of the government, enterprises,

research institutions and other parties to form a cooperative and win-win governance

model. Second, the design of the intelligent service application system is the core of

improving management effectiveness. Combining advanced technologies such as the

Internet of Things and big data, a real-time monitoring, prediction and scheduling

system for water environment resources is established to realize data sharing and

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intelligent processing of information, and to enhance the scientific and precise nature

of decision-making. The intrinsic relationship between data is deeply excavated, and

the utilization efficiency assessment model of water environment resources is

established to realize the scientific, efficient and sustainable development of intelligent

management of water environment resources in the context of big economy.

2. INTELLIGENT MANAGEMENT SYSTEM DESIGN FOR

WATER ENVIRONMENT RESOURCES

2.1. OVERALL GOVERNANCE FRAMEWORK

Follow the governance policy of prioritizing protection, integrating water and land,

adapting to local conditions, focusing on practicality, overall planning, step-by-step

implementation, rational design, organic integration, clear responsibility, division of

labor, broadening channels, and multiple inputs, and integrating the intelligent

management of the community of life of mountains, water, forests, fields, lakes, and

grasses [15]. Through the construction of sewage treatment and supporting pipeline

network, rainwater and sewage diversion renovation, urban point and surface source

pollution management, comprehensive improvement of rivers and building water

ecosystems and other measures, to effectively cut down the river pollution in the

watershed. To build a smart watershed, comprehensively improve the water

environment monitoring and early warning and risk prevention capabilities, and

provide scientific auxiliary decision-making for scientific water transfer, response to

environmental emergencies and comprehensive environmental remediation in the

watershed [16-17]. The overall governance framework is shown in Figure 1, and the

overall governance of intelligent management of water environment resources mainly

contains interception and pollution control project, landscape enhancement project,

water ecology project and intelligent watershed management system.

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Figure 1. Overall governance framework for smart management

It makes full use of existing intelligent technologies such as Internet of Things, big

data, cloud computing, artificial intelligence, etc., and combines basic information

resources and scientific and technological means to realize visual management,

simulation, prediction and analysis of daily water environment resource management

work in the watershed. Based on B/S+MI/S architecture and integrated GIS

development technology, it realizes the interconnection of mobile terminal and web

terminal, and consists of four horizontal and two vertical structural layouts of business

application, basin brain, information network, perception system, security system and

cooperative management mechanism. Among them, the main function of the business

application is to realize the basin water resources management, water ecological

restoration, water environmental protection, water disaster prevention and control,

government services and public services in the river basin brain to provide strong data

support and computing power, the above business information and data to carry out

comprehensive supervision, forming the water environment resources intelligent

service application system.

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Intelligent water treatment is an important part of the construction of intelligent

management of water environment resources. Compared with the traditional water

treatment method relying on chemicals and physical filtration, which has high cost and

the effect is difficult to guarantee, the adoption of information technology and

intelligent equipments can realize automatic monitoring and automatic regulation of

water quality, so as to accurately control the effect of water quality treatment, avoid

the over-standard of water quality and the wastage of resources as well as to reduce

the treatment cost. Intelligent equipment can automatically record water quality data

and upload it to the cloud to realize the sharing and interaction of water quality data.

Through the analysis of water quality data, we can understand the trend and law of

water quality changes, optimize the water treatment process, and improve the

effectiveness and stability of water quality treatment. Intelligent water treatment has

four obvious features: intelligent management, cost saving, high-efficiency water

treatment and data analysis.

2.2. INTELLECTUALIZED SERVICE APPLICATION SYSTEM

The intelligent service application system is based on information resources and

infrastructure, and according to the business requirements of water conservancy

functional departments, the application functions and application system architecture

of intelligent management are designed to realize intelligent perception, intelligent

simulation, intelligent diagnosis, intelligent early warning, intelligent scheduling,

intelligent disposal, intelligent control and intelligent service of intelligent management

of water environment resources, so as to serve the water-related businesses such as

flood control, drought mitigation and water resources management, water ecology

management, and water environment management. Management of water

environment management and other water-related businesses.

The functional architecture of the intelligent service application system for water

and environmental resources is shown in Figure 2. Through the construction of the

intelligent service application system, it realizes the integrated management of

intelligent perception intelligent simulation, intelligent diagnosis, intelligent early

warning, intelligent scheduling intelligent disposal intelligent control and intelligent

service for the whole life cycle of water services. It provides technical support for the

protection of water resources security, water environment security, water ecological

security and engineering security, serves the four major business areas of flood

control management, water resources management, water environment management

and water ecological management, provides different feedbacks for the situation of

daily status and emergency status, and comprehensively supports the management

business.

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Figure 2. Functional architecture of intelligent service application system

The intelligent service application system is designed based on the software-as-a-

service of cloud computing, and the intelligent management business of water

environmental resources is constructed through each different service module, and

each module builds a business application that meets its own needs according to the

characteristics of the business requirements, and the design of the application module

is shown in Figure 3. The construction mode can effectively avoid repetitive

construction of the system, easy system upgrade and transformation, and realize the

openness and dynamic sustainable development of the system. In the process of

system upgrade and transformation, only the functional modules need to be

upgraded, and a unified upgrade can be carried out for the common modules.

Software as a service can easily access a variety of application components, and

ultimately exposed to the user in the form of interfaces to call, and at the same time,

through a unified portal single sign-on, unified authentication and other technical

means, to achieve a single portal, a variety of services, and future access to the

system is also the same through the registration of the service to achieve, rapid

deployment of applications. Application of cloud computing to take a modular

construction model that is the water information service module, water business

management function module, water decision support function module and water

emergency management function module.

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Figure 3. Application module design of intelligent service application system

2.3. CLOUD COMPUTING SERVICE ATTRIBUTE VALUES

Cloud service in the cloud computing operating model is denoted as:

(1)

where is the number of sensing services on the cloud platform and is the rd

cloud service. Attribute which reflects the service level and processing capability in

the cloud service is denoted as:

(2)

where is the attribute dimension of the cloud service, is the functional attribute

that reflects the sensing level of the service, is the non-functional attribute of the

cloud service, and is the th dimensional attribute of the sensing cloud service. As

a result, the th sensing cloud service can be expressed as:

(3)

Where is the value of the functional attribute of the nd cloud service , is

the value of the non-functional attribute, and is the value of the attribute of the th

sensing cloud service on the th dimensional attribute .

For non-functional attributes such as sensing time and sensing speed, the sensing

services on the cloud platform need to be divided into batch number ranges in

advance when clustering, and set up different grades, and the service provider needs

to give the sensing time and speed of the sensing services of this class for different

batch grades [18-20]. The triangular fuzzy number is used for description, and its

mathematical expression is:

S={S1,S2,⋯,Si,⋯,Sn}

S={SF,SN}={S1,S2,⋯,Sk,⋯,Sm},k∈[1, m]

Si={xF

i,xN

i}={xi,1,xi,2,⋯,xi,k,⋯,xi,m},k∈[1, m]

xi,k

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(4)

Where and are the upper and lower bounds on the values of the non-

functional attributes, i.e., the maximum and minimum values of sensing time, or the

slowest and fastest values of service speed, required by the service provider to

complete the service at the corresponding batch level. is the most likely value of

the non-functional attribute, i.e., the sensing time and the sensing speed that the

service provider most often employs to provide this type of service at the

corresponding batch level. By describing the values of the cloud computing service

processing capability attributes and setting the labels of the feature items between

sensing, a foundation can be laid for managing the clustering distribution of the

functional modules.

2.4. WATER ENVIRONMENT RESOURCE UTILIZATION

EFFICIENCY

As an important means to improve the utilization efficiency of water environment

resources, the mechanism of science and technology innovation in the context of big

economy can be expressed as the mechanism of influence on the utilization efficiency

of water environment resources, which can be expressed as the science and

technology innovation in the context of big economy accelerates the promotion and

application of water-saving technology, effectively controls the total amount of water

consumption and reduces the total consumption of water environment resources.

Science and technology innovation optimizes the water consumption structure by

promoting the innovation of the development mode of traditional industries,

accelerating the transformation of the production mode, and promoting the

transformation and upgrading of the industrial structure. Science and technology

innovation in the context of the big economy promotes the high-quality development of

the economy, realizes the mutual promotion of high-quality development of the

economy and the control of the total amount of water consumption, the transformation

and upgrading of the industrial structure, and ultimately improves the efficiency of the

utilization of water environment resources, and the influence mechanism is shown in

Figure 4. Due to the differences in the level of regional science and technology

innovation, the application scope of water-saving technologies and key industries are

different, and the degree of transformation and upgrading of industrial structure is

different, so the effect of the level of innovation on the utilization efficiency of water

environment resources in the context of the big economy is not the same. The level of

science and technology innovation in the context of large economy significantly

improves the utilization efficiency of water environment resources, and there are

significant spatial differences in the effect of the level of innovation on the utilization

efficiency of water environment resources in the context of large economy.

xi,k=

[

xNL

k,xNM

k,xNU

]

, 0 < xNL

k≤xNM

k≤xN

xNU

i,k

xNL

i,k

xNM

i,k

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Figure 4. Mechanisms affecting resource utilization efficiency in the water environment

3. MODELING OF WATER ENVIRONMENT RESOURCE

UTILIZATION EFFICIENCY

Spatial econometric modeling is used to construct a model of the effect of the level

of innovation on the efficiency of water environment resource use in the context of the

large economy [21-22]. The formula is expressed as:

(5)

Where denotes the degree of industrial upgrading in region in year ,

denotes the intensity of water environment regulation in region in year , denotes

the constant term, denotes the elasticity coefficient of

respectively, and is the random error term.

Construct the generalized production function model, which can be expressed as:

(6)

where denotes the environmental constant and denotes the random error

term. Taking logarithms for both sides of Eq. (6) yields:

(7)

According to Equation (7), the elasticity coefficients of the variables in the model

are estimated using Equation (5) to find the difference, which can be presented in the

form of growth rate of the function model:

Wit =β0+β1Iit +β2Uit +β3Rit +εit

Uit

Rit

β0

β1、β2、β3

Iit,Uit,Rit

Wit =AIβ

it Uβ

it Rβ

it eu

uit

lnWit = lnA+β1lnIit +β2lnUit +β3lnRit /Rit

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(8)

According to Equation (8), divide both sides by

at the same time and

multiply by 100% to get:

(9)

Then Equation (9) represents the contribution of the level of science and

technology innovation, the degree of industrial upgrading, and the intensity of water

environment regulation to the efficiency of water environment resource utilization in

Region in Year in the context of large economy.

4. INTELLIGENT MANAGEMENT SYSTEM SIMULATION

ANALYSIS

4.1. QUESTIONNAIRE DESIGN

This paper adopts a combination of questionnaire survey method and interview

method to conduct an in-depth investigation and research on the development of

intelligent management of water environment resources in the context of J Group's

large economy. In order to ensure that the information obtained from the interview is

more comprehensive and objective, the interview adopts in-depth interview, according

to the outline of the interview content and the interviewee one by one, the outline of

the interview content adopts open-ended questions in order to obtain more in-depth

details of the problem. In the interview process, in order to seek the effectiveness of

the results of the interview, and the interviewees to clarify the meaning of each

question, and basically control the content of the interview and the guidance of the

interview questions. The main content of the interview includes how to feel about the

use of the intelligent management of water environment resources in the context of

the use of the big economy, what are the satisfactory and unsatisfactory aspects of

the Group's intelligent management of water environment resources, and what

optimization suggestions are put forward in the light of their own use. In order to

ensure the effectiveness of the interview results, the interview subjects were selected

from employees and managers related to the intelligent management of the

company's water environment resources, and relevant scholars who understand the

operation of the intelligent management system, and sampling was carried out

according to different classifications, and a total of 10 people were selected to conduct

open-ended question interviews. After the interviews with the 10 selected subjects, the

contents of the interviews were organized and summarized.

Details of the questionnaire survey design are shown in Table 1, and the

questionnaire content contains two parts, a total of 29 questions. The first part is about

the basic situation of employees and managers of J Group, with a total of 5 questions,

and the second part is a survey on the development of intelligent management of the

ΔWit /Wit =β1ΔIit /Iit +β2ΔUit /Uit +β3ΔRit /Rit

ΔWit /Wit

100

%=β1

ΔI

ΔWit /Wit

×100% + β2

ΔU

ΔWit /Wit

×100% + β3

ΔR

ΔWit /Wit

×100

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group's water and environmental resources, including the overall situation of the

group's intelligent development of water and environmental resources, intelligent

management, operation and maintenance, intelligent planning and management,

intelligent talent system, intelligent protection, with a total of 24 questions. The survey

questionnaire was issued in 1 month, during which 200 questionnaires were issued

and 187 valid questionnaires were retrieved, with a recovery rate of 93.5%, the

questionnaire validity is good, and the data is relatively perfect.

Table 1. Basic information about Group J's survey sample

Category Characteristics Frequency Percentage

Age

20-30 31 16.6

31-40 103 55.1

41-50 30 16

Above 50 (not

including 50)

23 12.3

Academic

qualifications

Below Bachelor's

Degree

18 9.6

Undergraduate 131 70.1

Postgraduate

(Masters)

26 13.9

Graduate student

(PhD)

12 6.4

Monthly income

Below 5000 89 47.6

5000-7000 53 28.3

7001-10000 34 18.2

10000 above 11 5.9

Length of service

Less than 5 years 61 32.6

5 to 10 years 63 33.7

11-20 years 43 23

More than 20 years

(excluding 20)

20 10.7

Department

Group Headquarters 12 6.4

Water Supply 31 16.6

Drainage 51 27.3

Engineering

department

26 13.9

Water sales

department

14 7.5

Dispatch Center 31 16.6

Others 20 10.7

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From the samples of this questionnaire survey, most of them are in the age of

31-40 years old, with bachelor's degree and 5 to 10 years of working experience. This

indicates that the main users of the intelligent management system of water

environment resources are mainly technicians who have certain working experience

as well as cultural level.

4.2. ANALYSIS OF INTERVIEW RESULTS

The result of the research is the internal opinion of Group J on the application of

intelligent management system of water environment resources, which shows that

there are three representative problems in the development process of intelligent

management of water environment resources in Group J. One of them is that there is

no unified intelligent water underlying architecture in terms of technology, so that the

intelligent management of water environment resources within the group is restricted

to deal with only their own water operation data, without interoperability between the

management, which also leads to valuable data can not be efficiently transmitted,

stored, converted into formats, and so on. Intelligent management at all levels can not

be interoperable, but also led to the imperfect function of the pipe network geographic

information system, there is no unified intelligent management, resulting in the level of

safety and security of intelligent management at all levels is uneven. Therefore, using

the intelligent management system of water environment resources in the context of

the big economy designed in this paper, the use of feelings, satisfaction and

optimization suggestions are summarized, and the effectiveness of the intelligent

management system of water environment resources in this paper has been verified.

Table 2 for the intelligent management system adoption rate interviews, the

industry scholars relatively high requirements for the Group's intelligent management

system for water environmental resources of the basic functions of higher recognition,

but some aspects of the existence of a greater space for development, and that its

functionality is targeted, the system structure is relatively simple and stable. At the

same time, they gave optimization suggestions, thinking that it is necessary to seek

cooperation with a third party, increase the scale of management, and focus on

improving the technical level of the staff, so as to guarantee the stable operation of

the intelligent management system. From the comprehensive analysis of the internal

and external parts of the interviews, the intelligent management system of water

environmental resources in the context of the big economy designed in this paper has

a complete system architecture, and the interoperability between the various system

operations forms a stable data source. However, with the process of intelligent

development in the context of a large economy, the traditional system of talent

introduction and training can not meet the needs of intelligent development of water

and environmental resources, resulting in the Group for the intelligent management

system for the actual use of personnel did not reach the expected level, but also

indirectly affects the level of technical support to continue to develop. The

development of intelligent management system of water environment resources is

mainly based on its own intelligent construction, adding a collaborative management

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mechanism to achieve win-win cooperation, but still need to cooperate with third

parties to strengthen the intelligent management of water environment resources.

Comprehensively, the intelligent management system of water environment resources

in the context of the big economy designed in this paper is very effective in the overall

intelligent management benefits, but it still needs to be combined with optimization

suggestions for improvement, so as to accelerate the speed of intelligent

development.

Table 2. Intelligent management system adoption rate

4.3. ANALYSIS OF QUESTIONNAIRE RESULTS

According to the questionnaire results statistics to get the overall situation of the

development of water environment resource intelligence, the statistical results are

shown in Figure 5. Most of the investigators think that the overall situation of the

development of water environment resource intelligence in the context of the big

economy is very good, accounting for 60%, 24% of those who think that the

development is very good, 3% of those who think that the development is not good,

2% of those who think that the development is very bad, and 84% of those who have

a good degree of satisfaction in the whole, which proves the validity of this paper's

design of the intelligent management method.

Interview Title Managers Technical staff

Water Industry

Scholars

Feeling of use

Save time.

The interface is

perfect and neat

Data storage time is

shorter.

Operation is more

complicated.

System response is

rapid.

Not much different from

the industry's leading

edge systems.

Data interoperability,

easy to share.

Flexible functions and

strong calculation

ability.

Small differences, easy

to operate.

Satisfaction

Replace manual work. Saving time.

The system structure is

stable.

Relatively stable, not

easy to fail.

Simple process. High simulation degree.

Decision construction.

Huge memory, easy to

operate

Low cost.

Dissatisfaction

Less update. Transmit the same

data over and over

Shortage of talents

Single operator

interface.

Limited funds.

Optimization

Suggestions

Optimize the operation

interface.

Optimize interface flow

Seek cooperation with

the third party.

Timely update Increase memory Improve personnel

skills

Strengthen hardware

construction

Add storage

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Figure 5. Satisfaction statistics of the development of water environment resource intelligence

Based on the questionnaire results, Figure 6 shows a comparison between the

original data and the survey results on the intelligent development of water

environmental resources. The samples agree on the effectiveness of implementing

the intelligent management system for water environmental resources in the context

of the big economy. The system comprehensively improves the efficiency of water

environmental resource operations, reduces workload, aids in decision-making, and

accelerates economic development. Based on the scores of very compliant, basically

compliant, general, partially non-compliant, and very non-compliant (ranging from 5 to

1), it is evident that the original management method, with the aid of management

decision-making, scored a minimum of 2.71 points. It accelerated economic

development by 3.13 points, achieved a comprehensive score of 3.35 points, and

scored the highest in improving operational efficiency with 3.82 points. This paper

evaluates the implementation of an intelligent management system for water and

environmental resources in the context of a large economy. The system's intelligent

development scored 4.76 points, while its impact on operational efficiency and

workload reduction scored 4.89 and 4 points, respectively. The intelligent development

of water and environmental resources contributed 4.62 points to decision-making

management, and 4.93 points to economic development. The economic development

score was 4.93. Thus, this paper demonstrates that the intelligent management

system for water and environmental resources in the context of a large economy has

improved overall development, operational efficiency, and management decision-

making while reducing the workload of management, ultimately contributing to

economic development.

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Figure 6. Comparison of the development of water environment resource intelligence

5. CONCLUSION

This paper presents the governance framework for the intelligent management

system of water environmental resources. The framework is structured around

information resources and infrastructure, and utilizes existing intelligent technologies

such as the Internet of Things, big data, cloud computing, and artificial intelligence. By

combining basic information resources and scientific and technological means, the

framework enables visualization management, simulation, prediction, and analysis of

water environmental resources management work. The application system for

intelligent management of water environment resources is designed to lay the

foundation for clustering distribution of management function modules. Finally, the

questionnaire and interview methods were combined with research to simulate

experimental verification. The results showed that the implementation of the system

described in this paper comprehensively improved the intelligent development of

water environmental resources, operational efficiency, and reduced workload. It also

aided in management decision-making and accelerated economic development. The

scores were 4.76, 4.89, 4.85, 4.62, and 4.93, respectively. It is evident that the original

management methods scored the lowest at 2.71 points under the management

decision-making score. However, there was an improvement of 1.91 points in the

management system's effectiveness after the application. This proves the

effectiveness of the intelligent management system for water environment resources

in the context of the big economy.

ABOUT THE AUTHORS

Xiaoyun Ma was born in Shanxi, China, in 1983. From 2001 to 2008, she studied in

Zhejiang University of Technology and received her bachelor's degree in 2005 and

Master's degree in 2008. Currently, she works in Zhejiang A&F University. She has

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published a total of nine papers. Her research interests are included Resource and

Environment Management.

Yan Zhu was born in Hangzhou, China, in 1983. From 2002 to 2009, he studied in

Zhejiang University of Technology and received his bachelor's degree in 2006 and

Master's degree in 2009. Currently, he works in Ecology and Environmental Science

Research & Design Institute of Zhejiang Province. His research interests are included

Environmental Policies and Standards.

FUNDING

This research was supported by the Research and development fund project of

Jiyang College of Zhejiang A&F University “Research on the impact of social capital

on farmers' participation in rural public goods supply” (JYYY201601).

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