Novel Framework for Exploring Human–Water Symbiosis Relationship: Analysis, Quantification, Discrimination, and Attribution

Abstract

There is an interdependent symbiotic relationship between humans and water; scientific and effective assessment of the human–water symbiosis relationship is of great significance for the promotion of sustainable development. This study developed a novel framework of the human–water symbiosis relationship under an integrated perspective, which included theoretical interpretation, quantitative assessment, pattern discrimination, and an attribution analysis. Based on the symbiosis theory, the theoretical analysis of the human–water relationship was carried out to analyze the three basic elements of the human–water system, and then the evaluation index system of the human–water symbiosis system was constructed to quantitatively assess the development level of the human system and the water system. The Lotka–Volterra model was used to identify the symbiotic pattern, and the human–water symbiosis index was calculated to characterize the health state of the human–water symbiosis system. The main influencing factors of the human–water symbiosis system were further identified through an attribution analysis. Finally, a case study was carried out with 18 cities in Henan Province. Results reveal that (a) the proposed method can effectively realize the quantitative characterization of the human–water symbiosis relationship, with good applicability and obvious advantages; (b) the human–water symbiosis pattern of cities in Henan Province is dominated by the “human system parasitizes water system (H⁺W⁻)” pattern, and more attention should be paid to the water system in the subsequent development of it; and (c) the main factors influencing the human system, the water system, and the human–water symbiosis system are the research and development (R&D) personnel equivalent full-time (H7), per capita water resources (W1), and proportion of water conservancy and ecological water conservancy construction investment (W6), respectively. The findings can provide theoretical and methodological support for the study of the human–water symbiosis relationship and sustainable development in other regions.

1. Introduction

Water is a fundamental natural resource and a strategic economic resource, and human survival and development have never been separated from water since the origin of human beings [1]. The human–water relationship refers to the interaction relationship between a “human” and “water” [2]. The human–water system is the object of study of the human–water relationship, including the complex system between the human system and the water system at the macro-level, and the system formed between the behavior of a specific human activity and the change in a parameter of the water system at the micro-level. The human–water relationship is the epitome of human–nature relations, and a harmonious human–water relationship is the prerequisite and foundation for the harmonious development of human beings and nature [3]. The 18th World Water Congress was held in Beijing, China, in September 2023, with the theme of “Water for All: Harmony between Humans and Nature”. As one of the most important relationships between human beings, the origin of the study of the human–water relationship can be traced back to the early Anthropocene [4], when human beings explored the human–water relationship from the early stage of recognizing the process of flooding and utilizing water resources. With global climate change and increasingly frequent human activities, on the one hand, increasingly frequent floods, droughts, and other water disasters constrain the development of the human system [5]. On the other hand, in response to the needs of socio-economic development, the escalating water demand, irrational water usage patterns, and outdated water resource management methods have resulted in a multitude of water issues [6]. The changes and challenges facing the human–water relationship are becoming increasingly complex [7,8]. The quality of the human–water relationship has become a core issue for the sustainable development of human society [9]. Maintaining healthy human–water relationships is a crucial guarantee for supporting sustainable development of the economy, society, and ecological environment [10]. Consequently, exploring the complex interaction between the human system and the water system, and quantitatively analyzing the human–water coupled system, is of significant importance for regulating the human–water relationship and promoting harmonious coexistence between humans and water.

As early as 1977, Falkenmark [11] suggested that the water system and the human system are a complex system that interact with each other. As a giant system with intricate interactions and different scales, the human–water system involves a wide range of research [2]. In terms of the study of the human system acting on the water system, it mainly includes the impacts of human activities such as water conservancy project construction [12], urbanization processes [13], and water resource management [14] on the exploitation, utilization, protection, and other engineering or non-engineering measures of the water system [15,16]. Research in the area of the water system affecting the human system has focused on the role of the water system in supporting or constraining the development of the human system, such as the evaluation of drought and flood risk [17,18], and the impacts of water quality on public health [19]. These studies cover numerous scales and multiple disciplines, with some favoring the natural water system and some favoring the human system. They reveal particular aspects of the intricate interactions between humans and water, and provide important perspectives and clues for a comprehensive understanding and effective management of the human–water relationship. In addition, there are fewer studies specifically focusing on the human–water relationship, but some representative research results have been produced, mainly focusing on two aspects. On one hand, there is the qualitative research on the human–water relationship, including the study of the theoretical basis of the human–water relationship framework, the process of change in the human–water relationship, and policy measures such as water resources management [20,21]. For example, Evers et al. [22] put forward a newly developed concept of pluralistic water research (PWR), arguing that it is necessary to integrate different paradigms, epistemologies, and methodologies of human–water research in order to coherently and comprehensively integrate the human–water dimension; Zuo [23] introduced the subdisciplines of the human–water relationship on the basis of briefly describing the disciplinary system and summarized the basic concept of the human–water relationship, and proposed the basic principles. On the other hand, quantitative research is aimed at the evaluation of the human–water complex system. For example, Ding et al. [24] constructed the human–water harmony index from the three dimensions of development, coordination, and satisfaction to assess the human–water relationship in five important cities in China; Zuo et al. [25] proposed a human–water relationship evaluation method based on the theory of harmony that includes harmony assessment, indicator identification, harmony balance constraints, and harmony regulation; Li et al. [26] proposed a hybrid framework based on driving force–pressure–state–response (DPSR) to quantitatively assess human–water harmony.

In conclusion, a large number of studies have been carried out on the human–water relationship, through which we can more comprehensively and deeply understand the human–water system, and it is of great significance to the effective management and regulation of the human–water relationship. But previous quantitative studies of the human–water system are mostly based on indicator evaluation methods to evaluate the integral state of the human–water system. However, in addition to studying the harmonious state and spatio-temporal evolution of the human–water system, it is more important to reveal the dynamic interdependence and interplay between the human system and the water system, so as to clarify the development trajectory of the human–water relationship [27,28]. The symbiosis theory and Lotka–Volterra model provide a possibility for further research and deeply exploring the interaction in the human–water system and reveal its symbiotic hypostasis. Currently, they have been gradually applied from the field of biology to the fields of economics, sociology, and resource environment studies [29,30], as well as in the studies of industrial development, regional coordination, and city–lake symbiosis [31,32,33]. These studies show that the symbiosis theory and Lotka–Volterra model can effectively explain the interaction between systems and identify the feedback state between subsystems [34]. Currently, academics have not yet systematically applied the symbiosis theory to the study of the human–water relationship. Though some scholars have put forward optimization proposals for water protection and water governance, the human–water landscape pattern, and other aspects based on the philosophy of human–water harmonious symbiosis [35,36], key research on quantitative methods of the human–water symbiosis relationship is still a gap.

Thus, focusing on three issues, (a) how to characterize the complex and dynamic interdependence of the human system and the water system; (b) how to identify the feedback states between the two systems; and (c) how to further quantify the overall state of the human–water symbiosis system, requires further in-depth exploration. Based on the above, this article proposed a framework for exploring the human–water symbiosis relationship between the human system and the water system by incorporating the symbiosis theory and the Lotka–Volterra model. The main contributions of this paper are as follows: we (a) analyzed the human–water relationship based on symbiotic theory, elucidating the fundamental elements of the human–water symbiosis system; (b) proposed a comprehensive framework for exploring the human–water symbiosis relationship; and (c) applied the proposed method to 18 areas in Henan Province, and validated the feasibility of the framework.

This paper is organized as follows: Section 2 presents the overall framework and primary research methodologies. Section 3 introduces the case study area of Henan Province, followed by Section 4, which analyzes the research results. Section 5 discusses the rationale of the framework, policy implications, and limitations. The conclusions are presented in Section 6. The research findings aim to provide insights for the study of the human–water symbiosis relationship and comprehensive water resource management in Henan Province and other regions.

2. Methodology

In order to realize the research objective, this paper proposes a novel framework for the study of the human–water symbiosis relationship. Figure 1 shows the overall research framework of this study, which mainly consists of four parts—(a) theoretical interpretation: analyzing the human system and the water system from a symbiotic perspective, and interpreting the human–water symbiosis system based on the three fundamental elements of symbiosis theory; (b) quantitative assessment: constructing the human–water symbiosis index system to measure the development index of the human system and the development index of the water system; (c) pattern discrimination: identifying the human–water symbiosis pattern based on the Lotka–Volterra model, and further calculating the human–water symbiosis index to characterize the health state of the symbiosis system; (d) attribution analysis: applying the influencing factor analysis method to diagnose the main influencing factors affecting the human system, the water system, and the human–water symbiosis system.

2.1. Theoretical Analysis of Human–Water Symbiosis

The concept of “symbiosis” was first proposed in 1879 by Anton Debary, a German mycologist, and originally meant “different species living together according to some material connection” [37]. The theory of symbiosis refers to symbiotic units interacting with each other in a specific symbiotic pattern within a defined symbiotic environment, ultimately forming a symbiotic coexistence relationship. The symbiotic unit, symbiotic environment, and symbiotic pattern are its three major basic elements [38]. Through the phenomenon of biological symbiosis, we realize that there is an interdependent, harmonious, and unified relationship of fate between humans and nature, and between the human system and the water system. We can further analyze the human–water symbiosis system based on the three basic elements (Figure 2).

(a) Symbiotic unit: The human system and the water system are fundamental symbiotic units in the human–water symbiosis system, serving as the basic entities for energy production and exchange. On one hand, water resources are foundational for human survival and development. They play a crucial role in various activities such as commercial endeavors, industrial manufacturing, agricultural irrigation, aquaculture, hydroelectric power generation, and transportation, providing essential support for the development of the human system. Simultaneously, droughts, floods, water pollution, and other water-related disasters constrain the development of the human system. On the other hand, humans implement both engineering and non-engineering measures to exploit and utilize water resources. However, in this process, human activities may lead to pollution and damage to the water system, resulting in negative impacts. Therefore, the human system and the water system engage in complex dynamic interactions including cooperation, competition, coexistence, convergence, and conflict.

(b) Symbiotic pattern: The symbiotic pattern is the symbiotic unit interaction or mutual combination of the form. It can demonstrate the manner in which symbiotic units interact with each other. The symbiotic pattern between the human system and water system in the human–water symbiosis system (referred to as human–water symbiosis pattern) is not static, but changes with the variations in symbiotic units and the symbiotic environment, demonstrating an overall trend of complex evolution. At different stages, as the interaction modes and intensities between the human system and water system change, the human–water symbiosis pattern also evolves accordingly. In essence, symbiotic patterns undergo complex dynamic interactions such as cooperation, competition, coexistence, convergence, and conflict during their development. Through continuous interaction and integration, they adapt to each other by making adjustments, thereby forming a closer symbiosis relationship.

(c) Symbiotic environment: The symbiotic environment encompasses the sum of factors that support symbiotic units and symbiotic patterns within a specific time and space, including both direct and indirect environments. The continuous transformation and updating of the symbiotic environment, such as ecological space, consciousness guiding, and policy orientation, can influence the development trajectory of the human system and the water system. The symbiotic environment is external, and exhibits fluctuation and uncertainty. An ideal symbiotic environment can actively facilitate energy exchange and material transformation among symbiotic units, as well as promote the transformation of the symbiotic pattern towards ideal trends.

2.2. Assessment Indicator System of Human–Water Symbiosis System

2.2.1. Establishment of Index System

The human system refers to a system centered around human development, consisting of numerous factors related to development such as social development, economic activities, and technological advancements. The water system is centered around water and composed of water resources, ecology, the environment, and other factors [39,40]. Therefore, the human system considers economic development (ED), social livelihood (SL), technological progress (TP), and culture and education (CE), while the water system considers water resources endowment (WRE), water resources security (WRS), water ecological protection (WEP), and water environment status (WES). Based on the reference of the relevant literature, following scientific, representative, and operational principles, a total of 11 indicators for the human system and 10 indicators for the water system were selected to construct an index evaluation system for the human–water symbiosis system (Table S1) to calculate the Human System Development Index (HDI) and the Water System Development Index (WDI).

2.2.2. Evaluation Method of HDI and WDI

Using “the single-indicator quantification, multiple-indicator synthesis, and multiple-criteria integration” (SMI-P) method, HDI and WDI were calculated according to the hierarchical relationship of the “target layer—criterion layer—indicator layer”, and study [41] can be referred to for the calculation steps. In the calculation of the affiliation degree of the kth indicator (${\mu }_k$), the thresholds were selected according to the various plans and standards in China [42]. The thresholds selected for each indicator are shown in Table S2.

The membership values of each indicator are weighted to obtain the evaluation results of various criteria layers. The calculation formula is as follows.

$$P_t={\displaystyle \sum _{k=1}^n{w}_k{\mu }_k}$$

(1)

In Equation (1), $P_t$ is the index of the criterion layer (i.e., ED, SL, TP, CE, WRE, WRS, WEP, and WES); n is the number of evaluation indicators; ${\mu }_k$ is the affiliation degree of the kth indicator; and $w_k$ is the corresponding weight of the first evaluation indicator. In this paper, the entropy weight method was used to calculate the weight of each indicator [43].

The integration of multiple-criteria layers by the weighted average of the above calculated indices for each criterion layer can be calculated to obtain the target layer index with the following formula.

$$DI={\displaystyle \sum _{i=1}^4{w}_i{P}_t}$$

(2)

In Equation (2), DI is the index of the target layer (i.e., HDI and WDI); $w_i$ is the corresponding weight of each criterion layer. In this paper, we consider that each criterion layer is equally important for the quantitative assessment of the human system and water system, so we take $w_1=w_2=w_3=w_4=1/4$.

2.3. Lotka–Volterra Model

2.3.1. Construction of Human–Water Symbiosis Model

In the early 20th century, Lotka [44] and Volterra [45] proposed the Lotka–Volterra model for the study of biological population relationships, the basic form of which is shown below. When two species in the biological realm share space, the Lotka–Volterra model can be utilized to simulate and analyze their symbiosis relationship.

$$\{\begin{array}{l}{\displaystyle \frac{d{N}_1\left(t\right)}{dt}}=r_1{N}_1\left(t\right){\displaystyle \frac{K_1-N_1\left(t\right)-\alpha N_2\left(t\right)}{K_1}}\\ {\displaystyle \frac{d{N}_2\left(t\right)}{dt}}=r_2{N}_2\left(t\right){\displaystyle \frac{K_2-N_2\left(t\right)-\beta N_1\left(t\right)}{K_2}}\end{array}$$

(3)

In Equation (3), $N_1\left(t\right)$ and $N_2\left(t\right)$ represent the population sizes of species S₁ and S₂ in time t, respectively; r₁ and r₂ are the growth rates of populations S₁ and S₂, respectively; K₁ and K₂ are the maximum environmental capacities of populations S₁ and S₂, respectively; α is the competition intensity coefficient of species S₂ on S₁; and β is the competition intensity coefficient of species S₁ on S₂.

Based on the theoretical analysis of human–water symbiosis presented earlier, we considered that the Lotka–Volterra model was also applicable for determining the human–water symbiosis pattern and constructed the model between the human system and the water system. The specific forms are as follows.

$$\{\begin{array}{l}{\displaystyle \frac{dH\left(t\right)}{dt}}=r_{H}H\left(t\right){\displaystyle \frac{K_H-H\left(t\right)-\alpha W\left(t\right)}{K_H}}\\ {\displaystyle \frac{dW\left(t\right)}{dt}}=r_{H}W\left(t\right){\displaystyle \frac{K_W-W\left(t\right)-\beta H\left(t\right)}{K_W}}\end{array}$$

(4)

In Equation (4), H represents the development level of the human system, while W represents the development level of the water system; K_H and K_W, respectively, denote the maximum development levels of the human system and the water system; r_H and r_W represent the growth rates of the human system and the water system, respectively; and α and β are the competition coefficients.

Referring to previous studies [46], the discretization solution for Equation Set (4) can be obtained as follows:

$$\{\begin{array}{l}{S}_H\left(k\right)=-\alpha =-{\displaystyle \frac{\left[\left(1-r_H\left(t+1\right)/r_H\left(t\right)\right)\times K_H-H\left(t\right)\right]}{W\left(t\right)}}\\ S_W\left(k\right)=-\beta =-{\displaystyle \frac{\left[\left(1-r_W\left(t+1\right)/r_W\left(t\right)\right)\times K_H-W\left(t\right)\right]}{H\left(t\right)}}\end{array}$$

(5)

In Equation (5), $S_H\left(k\right)$ and $S_W\left(k\right)$ represent the symbiotic stress indexes, where $S_H\left(k\right)$ represents the symbiotic pressure index that the human system experiences from the water system, and $S_W\left(k\right)$ represents the symbiotic pressure index that the water system experiences from the human system. The human–water symbiosis pattern can be determined based on the positive and negative values of S_H and S_W (

Table 1. Discrimination of human–water symbiosis pattern.

Symbiotic Pattern	SH > 0	SH < 0	SH = 0
SW > 0	Mutualism symbiosis (H+W+)	Water system parasitizes human system (H−W+)	Partially beneficial symbiotic pattern of water system (H0W+)
SW < 0	Human system parasitizes water system (H+W−)	Mutual-harm symbiosis (H−W−)	Partially harmful symbiotic pattern of water system (H0W−)
SW = 0	Partially beneficial symbiotic pattern of human system (H+W0)	Partially harmful symbiotic pattern of human system (H−W0)	Irrelevant symbiosis (H0W0)

).

2.3.2. Calculation of Human–Water Symbiosis Index

Although we can determine the symbiotic pattern based on S_H and S_W, it is still impossible to quantitatively ascertain the degree of superiority or inferiority of the state of the human–water symbiosis system under a certain pattern. Therefore, we constructed a comprehensive characterization index of the human–water symbiosis system, i.e., the human–water symbiosis index S, as a way to further quantify the health state of the human–water symbiosis system, building upon previous studies [47].

$$S\left(k\right)={\displaystyle \frac{S_H\left(k\right)+S_W\left(k\right)}{\sqrt{{S_H}^2\left(k\right)+{S_W}^2\left(k\right)}}}$$

(6)

In Equation (6), as both $S_H\left(k\right)$ and $S_W\left(k\right)$ are not equal to 0, it can be deduced that $S\left(k\right)\in \left[-\sqrt{2},\sqrt{2}\right]$. Drawing on the research findings of Wang et al. [48], this study further categorizes the health status of the human–water symbiosis system into six intervals, healthy, sub-healthy, risky, high-risk, dangerous, and recovery, as illustrated in Figure 3.

Description—(1) Healthy interval: when S_H > 0, S_W > 0, and 1 < S ≤ √2, the human system and the water system are in a mutually beneficial symbiotic pattern, promoting each other and realizing a win–win situation. (2) Sub-healthy interval: S_H < 0, S_W > 0, 0 < S ≤ 1. The health of the water system is improved, but the development of the human system is hindered. (3) Risk interval: S_H < 0, S_W > 0, −1 < S ≤ 0. The health condition of the water system is slightly improved, but the development level of the human system is significantly reduced. (4) High-risk interval: S_H < 0, S_W < 0, −√2 < S ≤ −1. Both the human system and the water system have been damaged, and the competition between them has increased. (5) Dangerous interval: S_H > 0, S_W < 0, −1 < S ≤ 0. The degree of destruction of the water system is much larger than the degree of development of the human system in the dangerous interval. (6) Recovery interval: S_H > 0, S_W < 0, 0 < S ≤ 1. With the development of the human system, the damage to the water system is gradually reduced.

2.4. Influencing Factor Identification Method

2.4.1. Obstacle Degree Model

The obstacle factors are key factors limiting further development of the system. The obstacle degree model was used to identify the key obstacle factors influencing the human system and the water system [49].

$$O_{i,j}={\displaystyle \frac{\overline{w_j}\times I_{i,j}}{{\displaystyle {\sum }_{j=1}^m\overline{w_j}\times I_{i,j}}}}$$

(7)

$$I_{i,j}=1-{\mu }_{i,j}$$

(8)

In Equations (7) and (8), I_i,j represents the deviation degree of indicator j; $\overline{w_j}$ stands for the maximum weight of indicator j; and O_i,j denotes the obstacle degree of indicator j. A higher obstacle degree for indicator j indicates a greater impact on the human–water symbiosis index.

2.4.2. Neural Network Model

Referring to the study of Yuan et al. [50], this paper used the neural network model to identify the influencing factors of the human–water symbiosis index. The method can use the dataset to obtain a nonlinear continuous function that conforms to the basic characteristics of the variations in the human–water symbiosis index, and calculate the weight coefficients between neurons. The input layer used the 21 indicators of the indicator system of the human–water symbiosis system shown in Table S1, the output layer was the human–water symbiosis index, and the hidden layer was set according to the input and output conditions.

The correlation significance coefficient h_ql can be calculated as

$$h_{ql}={\displaystyle \sum _{k=1}^K{\omega }_{kq}\left(1-e^{-{\omega }_{lk}}\right)/\left(1+e^{-{\omega }_{lk}}\right)}$$

(9)

In Equation (9), q is the input unit of the neural network, i = 1, 2, …, Q; l is the output unit of the neural network, l = 1, 2, …, L; K is the hidden layer unit of the neural network, k = 1, 2, …, K; ${\omega }_{kq}$ is the weight coefficient between the input layer q and the hidden layer k; and ${\omega }_{lk}$ is the weight coefficient between the output layer l and the hidden layer k.

The correlation coefficient H_ql can be calculated as

$$H_{ql}=\left|\left(1-e^{-h_{ql}}\right)/\left(1+e^{-h_{ql}}\right)\right|$$

(10)

Finally, the indicator factor contribution S_ql can be calculated.

$$S_{ql}=H_{ql}/{\displaystyle \sum _{q=1}^Q{H}_{ql}}$$

(11)

3. Case Study

3.1. Overview of the Study Area

Henan Province is located in east-central China and the middle and lower reaches of the Yellow River (31°23′–36°22′ N, 110°21′–116°39′ E), with a total area of 167,000 square kilometers (Figure 4). The terrain is high in the west and low in the east. The plains and basins, mountains, and hills account for 55.7%, 26.6%, and 17.7% of the total area, respectively. Henan Province has a unique location spanning four major river basins, namely the Haihe River, the Yellow River, the Yangtze River, and the Huaihe River, each of which accounts for 9.2%, 21.7%, 16.3%, and 52.8% of the total area of the province. Henan Province is a continental monsoon climate in the transition from the northern subtropical zone to the warm temperate zone, with an annual average temperature from south to north of 10.5–16.7 °C, an annual average precipitation of 407.7–1295.8 mm, and an annual average of total water resources of 40.5 billion cubic meters. At the end of 2022, the overall resident population of Henan Province was 98.72 million, the urbanization rate was 57.07%, and the annual per capita GDP was CNY 62,106. Henan Province is a crucial national energy center and a vital transportation nexus. The advantages of location have contributed to the rapid development of Henan Province in recent years, but also brought about the contradiction between humans and water. The contradiction between socio-economic development and water resources utilization has become a major constraint to the realization of the goal of high-quality development in the region. Above all, this paper selected 18 cities in Henan Province as the case study to explore the current situation of the human–water relationship.

3.2. Data Source

The research period of this paper is from 2007 to 2022, and the relevant data of the human system and water system involved are mainly from The China Statistical Yearbook, Henan Provincial Statistical Yearbook, Henan Environmental Statistical Yearbook, Henan Urban and Rural Construction Statistical Yearbook, Yearbook of Henan Water Resources, and Henan Water Resources Bulletin, as well as statistical yearbooks and water resources bulletins of various cities (https://www.stats.gov.cn/ and https://www.henan.gov.cn/). In addition, the research data in this paper were strictly checked to ensure the accuracy and authenticity of the data. Missing data were supplemented by linear interpolation to ensure that the research data are a continuous time series.

4. Results

4.1. Spatial and Temporal Evolution Analysis of HDI and WDI

Figure 5 shows the variations in HDI and WDI in 18 cities in Henan Province from 2007 to 2022. The figure demonstrates a consistent upward trajectory in the HDI values of these cities, indicating a continual enhancement in the developmental status of the human system over the years. Specifically, the annual average values of HDI in Henan Province during this period range from 0.383 to 0.706. Among these, only Zhengzhou and Luoyang have surpassed the threshold of 0.6, boasting annual averages of 0.706 and 0.633, respectively. As the “double engine” of development in Henan Province, the socio-economic development in Zhengzhou and Luoyang has remained stable for several years, propelling the growth of neighboring cities through the robust competitiveness of the dual-core development mode.

While the WDI also showed an improvement trend from 2007 to 2022, its fluctuations were more obvious. In certain years (e.g., 2010, 2012, 2019, and 2021), the WDI value of each city has a relatively obvious inflection point, which makes the WDI show an unstable fluctuation and increased state. This volatility can be attributed to the significant impact of abrupt changes in precipitation on the WDI. The years 2012 and 2019 marked exceptionally dry periods in Henan’s history, with annual precipitation plummeting to 605.2 mm and 529.1 mm, respectively. Conversely, 2010 and 2021 were characterized by excessive rainfall, with the latter experiencing the devastating “21·7” (17–22 July 2021) severe torrential rain event that resulted in a record annual precipitation of 1127.7 mm [51]. Additionally, both Zhoukou and Shangqiu exhibit lower HDI and WDI rankings in Henan Province, securing the 16th and 18th positions in both categories. These rankings can be attributed to the predominant agricultural focus of these cities, serving as key food production hubs within Henan Province [52]. Zhoukou is located in the hinterland of the Yellow–Huaikou Plain, with flat terrain, favorable climatic and geographical conditions, a long history of farming culture, and a stable perennial grain sowing area of more than 20 million acres. The high demand for irrigated agriculture has caused it to face serious water shortages, and intensive agricultural practices, including chemical fertilizer and pesticide usage, have contributed to the deterioration of the local water ecological environment, imposing further constraints on the development of its human system [53].

In terms of developmental disparities between the human system and the water system, Xinyang exhibits the most significant gaps. Its annual average WDI is 0.740, ranking first, while HDI is only 0.396, ranking 17th out of 18 cities. This stark contrast results in a substantial 0.345 difference between HDI and WDI values in Xinyang. Situated at the southernmost tip of Henan Province, Xinyang lies within the Yangtze River and Huai River water systems, endowed with abundant water resources such as the Huaihe River. The region enjoys plentiful precipitation, ensuring ample water resources and a relatively stable ecological water supply, nurturing a robust water system. While the human system appears to be trailing the water system in development, the pressure on water resource conservation is relatively low, presenting considerable growth potential. However, care should be taken to avoid embarking on the dangerous path of “pollute first, treat later”.

Additionally, Zhengzhou closely follows Xinyang in terms of human–water system development differentials. With annual averages of HDI and WDI of 0.706 and 0.500, respectively, Zhengzhou demonstrates a 0.206 difference. Its HDI ranks first among the 18 cities, indicating high development levels, yet its WDI falls below the municipal average. As the capital of Henan Province, an industrial hub, and a national commercial center, Zhengzhou possesses a solid foundation for human system advancement. However, the rapid economic and social growth amplify the demand for water resources, leading to challenges like groundwater overexploitation, environmental water sacrifices, excessive sewage discharge, and water inefficiencies, posing threats to the development of the water system [54]. Furthermore, per capita water resources of Zhengzhou amount to only half of the provincial average, coupled with an uneven distribution of precipitation, rendering its water system intrinsically fragile. Consequently, the stronger negative effects resulting from human activities exacerbate the developmental disparities between the two systems [55].

Figure 6 shows the spatial distribution of HDI and WDI in Henan Province from 2007 to 2022. From the viewpoint of spatial distribution, there are obvious regional differences in the spatial distribution of HDI and WDI. The HDI is influenced by the natural endowment, topography, transportation, economic level, and other factors, exhibiting a pattern where the west and north regions have higher values than the east and south. This conclusion is consistent with the findings of previous studies [25]. Zhengzhou and Luoyang in central Henan are densely populated and industrialized, boasting higher HDI values, while cities such as Zhumadian, Shangqiu, Zhoukou, and Xinyang in the east and south have lower HDI scores (0.431, 0.408, 0.396, and 0.383, respectively). Regarding WDI distribution, the southwest of Henan Province shows superior values compared to the northeast due to differences in water resources. The hilly southwest has more water compared to the plain northeast, affecting water availability. The eastern and northern plains, crucial for grain production, face water scarcity, impacting local economic sustainability.

A further analysis of the criterion layer results clearly reveals (Figures S1 and S2) that the water system exhibits greater uncertainty compared to the human system. The uncertainty is particularly pronounced in the results of the WRE criterion layer. Fluctuations and regional differences in water resources are influenced by factors such as topography, climate, and human interventions. According to the 2022 Water Resources Bulletin and 2023 Statistical Yearbook of Henan Province, the population of 13 cities in northern, eastern, and central Henan (Anyang, Hebi, Jiaozuo, Jiyuan, Puyang, Xinxiang, Zhengzhou, Xuchang, Pingdingshan, Luohe, Kaifeng, Shangqiu, and Zhoukou) accounted for 67.8% of the total population, yet their total water resources were only 10.51 billion cubic meters, accounting for 42.2% of the total. Conversely, the five cities in southern and western Henan (Nanyang, Xinyang, Zhumadian, Luoyang, Sanmenxia) account for only 32.2% of the province’s population, but possess around 14.41 billion cubic meters of total water resources, accounting for 57.8% of the province’s total water resources.

4.2. Analysis of Comprehensive Characteristic Index of Human–Water Symbiosis System

4.2.1. Discriminant of Human–Water Symbiosis Pattern

To clearly present the human–water symbiosis pattern of each city based on the calculation results of S_H and S_W, Figure 7 plots the frequency distribution of symbiosis patterns of each city in Henan Province during the period of 2008–2021. There are four types of symbiosis patterns in Henan Province, which are the human–water mutualism symbiosis (H⁺W⁺) pattern, human–water mutual-harm symbiosis (H⁻W⁻) pattern, human system parasitizes water system (H⁺W⁻) pattern, and water system parasitizes human system (H⁻W⁺) pattern.

As can be seen from the figure, except for Zhengzhou, Luohe, Shangqiu, and Xinyang, the human–water symbiosis pattern in most of the cities in Henan Province was dominated by the “H⁺W⁻” pattern. It can be seen that the development of the human system in Henan Province has been accompanied by a one-sided pursuit of economic and social gains, potentially neglecting the safeguarding of the water system. If this development pattern continues, it will pose a significant threat to the future development of the water system. The human–water symbiosis pattern of Shangqiu was mainly dominated by the “H⁻W⁻” pattern, with a frequency of 42.86%. And from the development status of Shangqiu, its HDI fluctuated and grew from 0.234 in 2007 to 0.541 in 2022, with its annual average growth rate of about 205%, while the WDI grew with fluctuation from 0.480 in 2007 to 0.415 in 2022, with an annual average growth rate of −0.41%. The level of development of the human system showed a trend of improvement, but in terms of the symbiosis relationship, both systems were subject to a certain amount of pressure and showed a competitive pattern of mutual inhibition. Although this pattern does not occur continuously, the development of the human system will bring damage to the water system in the long run, and the aggravation of water problems will in turn further inhibit the development rate of the human system, which is not conducive to the sustainable development of the symbiosis system [48]. In contrast, the human–water symbiosis pattern in Zhengzhou and Xinyang was dominated by the “H⁺W⁺” pattern, with frequency ratios of 35.71% and 42.86%, respectively. The human–water symbiosis system under the pattern presents a harmonious state of mutual promotion and benefit, which is the most ideal human–water symbiosis pattern. Despite notable disparities between HDI and WDI in these locales, the internal interactions within their symbiosis systems showcase a reinforcing feedback loop between the human system and water system, fostering positive development prospects.

4.2.2. Analysis of Human–Water Symbiosis Index

Table 2. Calculation results of human–water symbiosis index S.

	Index	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
ZZ	S	1.25	0.93	−1.07	1.32	0.89	1.15	1.40	1.38	0.03	0.54	−0.77	−1.31	0.87	−1.41
	Level	I	II	IV	I	VI	I	I	I	VI	VI	V	IV	II	IV
KF	S	−1.00	1.28	1.02	−0.94	0.52	−0.98	0.72	1.26	−0.70	−1.07	0.97	0.85	−0.99	0.52
	Level	IV	I	I	V	VI	V	VI	I	V	IV	VI	II	III	VI
LY	S	−1.11	1.38	−0.06	−0.98	1.39	−0.46	0.73	1.18	−0.88	0.86	−1.02	−1.41	1.39	−1.30
	Level	IV	I	V	V	I	V	VI	I	V	VI	IV	IV	I	IV
PDS	S	0.00	0.93	−1.01	1.29	1.41	−0.06	−0.17	−0.98	1.03	0.18	0.34	0.80	−0.57	−1.41
	Level	V	II	IV	I	I	V	V	V	I	VI	VI	II	III	IV
AY	S	−0.64	−0.80	0.45	−1.03	0.01	−0.77	−1.39	−1.37	−1.41	0.90	0.85	0.77	0.93	0.50
	Level	V	V	VI	IV	VI	V	IV	IV	IV	VI	II	VI	II	VI
HB	S	−0.44	−0.96	0.99	0.76	−1.35	0.96	0.72	−0.85	0.74	0.49	1.40	−1.39	−0.35	−0.63
	Level	V	V	VI	II	IV	VI	II	III	II	VI	I	IV	III	V
XX	S	1.36	1.37	0.39	1.41	1.09	−0.94	−0.42	−0.77	0.87	−0.86	1.07	−0.93	1.41	−1.24
	Level	I	I	VI	I	I	V	V	V	VI	V	I	V	I	IV
JZ	S	0.93	−0.87	−0.96	−0.32	0.64	−0.63	1.40	1.20	1.13	1.41	−0.02	−0.93	1.13	−0.98
	Level	VI	V	V	V	VI	V	I	I	I	I	V	V	I	V
PY	S	0.80	−0.84	−0.80	1.41	−0.32	−0.35	−1.32	−0.96	0.82	1.15	−0.13	−0.55	1.08	−0.87
	Level	II	III	V	I	V	V	IV	III	II	I	V	V	I	V
XC	S	0.01	0.81	0.23	1.37	0.33	−0.95	−0.63	0.01	−0.30	0.97	−0.54	−1.31	−0.87	−1.03
	Level	II	VI	VI	I	VI	V	V	VI	V	VI	V	IV	III	IV
LH	S	−0.97	1.01	−1.36	−1.41	1.40	1.41	−0.73	0.07	1.26	−0.95	1.41	−0.99	−0.95	−1.20
	Level	V	I	IV	IV	I	I	V	VI	I	V	I	V	III	IV
SMX	S	−0.99	1.09	0.94	−1.00	1.21	−1.07	0.96	−1.26	1.13	0.38	1.07	1.10	−0.70	0.50
	Level	V	I	VI	V	I	IV	VI	IV	I	VI	I	I	V	VI
NY	S	0.68	1.00	0.19	0.12	0.71	0.68	0.98	1.02	1.02	1.09	−0.86	−1.30	−0.92	−0.83
	Level	VI	I	VI	II	II	VI	II	I	I	I	V	IV	III	V
SQ	S	−1.14	−1.04	−1.08	1.01	−1.30	−0.68	0.96	−0.85	0.81	1.32	−0.97	−1.38	−1.15	−0.78
	Level	IV	IV	IV	I	IV	V	II	III	VI	I	V	IV	IV	III
XY	S	0.99	−0.72	−0.97	1.11	1.04	−1.00	1.41	1.02	1.41	−0.27	1.17	−1.33	−1.03	0.99
	Level	II	V	V	I	I	V	I	I	I	V	I	IV	IV	II
ZK	S	0.71	0.57	−0.77	−0.51	1.27	−0.85	−1.41	0.68	1.30	0.80	−1.00	0.25	−1.19	−1.22
	Level	II	VI	V	III	I	V	IV	II	I	VI	V	VI	IV	IV
ZMD	S	1.37	−0.92	−0.95	−0.26	−0.92	−0.71	−0.78	1.05	1.10	−1.40	1.00	0.58	−1.40	−1.13
	Level	I	V	V	V	V	V	V	I	I	IV	I	VI	IV	IV
JY	S	−0.51	−1.40	−1.00	−1.03	1.41	−0.42	1.39	−0.88	0.72	−0.39	0.40	0.92	0.17	−1.36
	Level	V	IV	IV	IV	I	V	I	V	VI	V	VI	II	II	IV

Notes: “I” refers to “Healthy”, “II” refers to “Sub-healthy”, “III” refers to “Risky”, “IV” refers to “High-risk”, “V” refers to “Dangerous”, “VI” refers to “Recovery”. The corresponding health status zoning diagram is shown in Figure S3 in the Supplementary Materials.

shows the human–water symbiosis index S and health state levels of various cities in Henan Province calculated by Formula (6). It can be observed that there were 68 occurrences of a dangerous status, 61 occurrences of a healthy status, 45 occurrences of a high-risk status, 43 occurrences of a recovery status, 23 occurrences of a sub-healthy status, and 12 occurrences of a risky status during the sample period. Overall, the aforementioned results align with the reality of the escalating contradiction between rapid socio-economic development and water utilization in Henan [56]. This indicates that the overall health state of the human–water symbiosis system in Henan Province is not optimistic, which is consistent with the research results of Liu et al. [57]. The prevalence of frequency data in harmful zones of the water system underscores the pronounced inhibitory impact of the human system on water resources. When steadily advancing the healthy development of the human system in the future, more attention must be paid to and efforts made to ensure the health state of the water system, to minimize disturbances and damages caused by economic and social activities to the water system.

Figure 8 further shows the distribution of the health state of the human–water symbiosis system in 18 cities in Henan Province during the sample period, plotted with S_W as the vertical axis. In 2021, as many as 9 out of 18 cities in Henan Province were in a high-risk status of the human–water symbiosis system, which was the worst year for the health state of the symbiosis system. This may be the result of the influence of unfavorable external symbiotic environments [58]. The year 2021 was the critical and complex period of COVID-19 pandemic prevention and control, when economic and social development faced a near standstill. Additionally, it was a once-in-a-millennium year of flooding, further leading to detrimental changes in the interaction patterns within the human–water symbiosis system.

From the perspective of individual cities, the cities with a frequency of distribution of the human–water symbiosis system in the safe zone (consisting of healthy, sub-healthy, and risky) greater than 0.6 during the sample period include Zhengzhou, Nanyang, and Sanmenxia. Taking Zhengzhou as an example, we found that its human–water symbiosis system was under a relatively stable state from 2011 to 2017, during which there were four years in a healthy state, and 2012, 2016, and 2017 were in a period of a recovery interval in transition to a healthy one. However, this state was not sustainable, and the human–water symbiosis relationship began to deteriorate after 2017. High-risk status even manifested twice, indicating a shift towards mutual competition within the human–water symbiosis system. Comparing the conclusion of Zuo et al. [25], there seems to be an inconsistency. The reason for this appearance is that the focus of our study is on the feedback state between the symbiotic units within the human–water symbiosis system, that is, to study whether the interaction between the human system and water system is positively facilitated or negatively inhibited [47]. Therefore, a good symbiosis relationship does not mean that the development level of the human–water system must be high. If the development level of the human system and water system is low, and the feedback relationship within the symbiosis system is in the ideal pattern of mutualism symbiosis, only when this state can exist stably for a long time, the development level of the two systems will improve year by year with a sustainable development mode.

During the sample period, the cities of Shangqiu, Puyang, and Zhumadian had a frequency of human–water symbiosis index distribution in the warning zone (consisting of risky, high-risk, and dangerous) exceeding 0.6. Among them, Shangqiu had the highest frequency of high-risk occurrences during the sample period, indicating that its symbiotic state was less than ideal and in the warning zone. Additionally, Kaifeng and Hebi exhibited all six health statuses, which showed significant interannual variability. This variability suggests that external environmental fluctuations significantly impacted the human–water symbiosis patterns, leading to an unstable developmental phase devoid of a dominant symbiotic pattern. In contrast, Jiaozuo only showed three states, healthy, risky, and recovery, and risky status occurred seven times, making it the dominant symbiotic state. This indicates that the development of the water system in Jiaozuo has been significantly inhibited by the human system, slowing down the progress of the water system. Jiaozuo is a typical resource-based city, heavily reliant on industries such as coal mining that have a high water consumption. Over the years, it had faced challenges including economic structural imbalances, increasing social burdens, and escalating environmental damage to water ecosystems [59].

4.3. Attribution Analysis

4.3.1. Analysis of Influencing Factors in Human System and Water System

In this study, the obstacle degree model was used to identify the main obstacle factors affecting the development level of the human system and the water system, respectively, and the results are shown in Figure 9. From the overall situation of each city in Henan Province, the research and development (R&D) personnel equivalent full-time (H7) and per capita GDP (H1) have a greater impact on the human system, with the mean value of the obstacle degree of 0.24 and 0.16, respectively. Meanwhile, the water supply coverage rate (H5) and greening coverage rate of built-up area (H6) have a lower obstacle degree, with the mean value of 0.03 solely. The main influencing factors of HDI are geographically different from city to city, with the proportion of the tertiary industry in GDP (H2) and water consumption per acre for farmland irrigation (H9) having the greatest influence on Jiyuan, H2 and H7 on Xuchang, and H1 and H7 on Nanyang. For the water system, the per capita water resources (W1) and the rate of flood control and drainage up to the standard (W3) have a high obstacle degree, with mean values of 0.23 and 0.16, respectively. Meanwhile, the water resources development and utilization rate (W4) and sewage treatment rate (W8) have a lower obstacle degree, with a mean value of only 0.03. The main influencing factors of WDI also differ geographically across cities, with the proportion of water conservancy and ecological water conservancy construction investment (W6) and the proportion of ecological water consumption (W7) having the greatest influence on Xinyang, W3 and W1 on Pingdingshan, and W1 and carbon dioxide emissions per unit of water consumption (W9) on Zhengzhou.

As the main factors affecting the human system and water system, respectively, H7 and W1 need to be used as the main starting point in the process of improving the HDI and WDI in Henan Province [60]. For example, for Zhengzhou, Puyang, and other areas with poor water resources endowment, it is necessary to give full play to the role of the South-to-North Water Diversion Project, the Yellow River Diversion Project, and the supporting water conservation facilities in Henan Province to alleviate the pressure of a local water resources shortage with the help of external water transfers, and adjust the scale of economic development and the structure of industry, and construct a sustainable management mode [54]. For Nanyang, Xinyang, Sanmenxia, and other areas with better water resources endowment conditions, the industrial structure should be optimized under the premise of maintaining the stability of local water resources and habitat systems, and the scale of economic and social development should be increased in an orderly manner. In addition, for cities such as Zhoukou, Zhumadian, Nanyang, and Shangqiu, where food production is the mainstay, the adoption of innovative water-saving appliances and irrigation technologies is crucial. This initiative aims to strengthen water conservation measures in the region while reducing the risk of the overexploitation of groundwater.

4.3.2. Analysis of Influencing Factors in Human–Water Symbiosis System

Table 3. The degree of influence of various indicators to the human–water symbiosis index. (Sort in descending order by the indicator factor contribution S_ql. The value indicates the extent to which a change in a single indicator contributes to the overall change).

Index	Sql	Index	Sql	Index	Sql	Index	Sql	Index	Sql	Index	Sql	Index	Sql
W6	0.106	W5	0.068	H7	0.056	W8	0.043	H5	0.038	W4	0.033	H8	0.027
H1	0.083	H8	0.064	H10	0.052	H9	0.042	H4	0.035	W7	0.031	W2	0.026
W1	0.068	W3	0.058	W9	0.051	H2	0.039	W10	0.034	H6	0.027	H11	0.019

shows the contribution rate of the indicators affecting the human–water symbiosis index. It can be statistically obtained that the total contribution ratio of water system indicators is 0.518, while that of the human system is 0.482. Water system indicators have a greater contribution to the health status of the human–water symbiotic system. Therefore, in efforts to improve the human–water symbiotic condition in Henan Province, greater attention should be paid to the water system to expedite its improvement. In addition, the top five indicators that have the greatest impact on the health of the human–water symbiosis system are the proportion of water conservancy and ecological water conservancy construction investment (W6), per capita GDP (H1), per capita water resources (W1), proportion of groundwater supply (W5), and water consumption per CNY 10,000 of industrial value added (H8), with their indicator factor contributions of 0.106, 0.083, 0.068, 0.064, and 0.058, respectively.

5. Discussion

5.1. Comparison and Contribution of the Framework

The research framework of human–water symbiosis constructed in this study includes theoretical interpretation, quantitative assessment, pattern discrimination, and an attribution analysis, which is a complete framework with clear structure and strong theoretical foundation. From a theoretical perspective, this paper comprehensively discussed the symbiotic relationship between the human system and water system based on the three elements of symbiosis theory, i.e., the symbiotic unit, symbiotic pattern, and symbiotic environment. Additionally, the selection of indicators for measuring the development level of the human system and water system was based on existing research achievements [2,23], combined with concepts and theories related to the human–water relationship.

Methodologically, this paper adopted the Lotka–Volterra model to measure the human–water symbiosis relationship. The model has been widely applied and practiced in the study of symbiosis relationships between systems [29,30,31,32,33], and has been rigorously derived and demonstrated. Furthermore, compared with traditional methods for quantifying the human–water relationship [25,40], the framework proposed in this study was more advantageous in portraying the interaction relationship between systems. For example, a harmony-based approach for assessing and regulating the human–water relationship was proposed by Zuo et al. [25] and applied in Henan Province. Its quantitative evaluation of the human–water relationship considered the health degree of the water system (HED), the development degree of the human system (DED), and the coordination degree of the human–water system (COD) three criterion layers. The coordination degree of human–water harmony (HWHD) was obtained by weighting HED, DED, and COD, and HWHD was adopted to quantify the human–water relationship in Henan Province. Although the comprehensive evaluation method based on the indicator system can effectively evaluate the overall status of the human–water relationship from multiple perspectives, the interactions between human–water systems still need to be further revealed [61]. There are other methods available for characterizing the interactions between systems, such as the coupling coordination degree method and the matching degree method. However, their calculation results cannot reflect the overall state of the coupled system [62,63].

In contrast, in the framework of the human–water symbiosis relationship proposed in this study, we used the HDI and WDI measured based on the comprehensive evaluation method only as inputs to the Lotka–Volterra model. Based on the model, we could derive the symbiotic stress indexes (S_W and S_H) to characterize the interactions between the human system and the water system, and the human–water symbiosis index (S) could be used to reflect the overall health status of the human–water symbiosis system. Compared with the above methods, our framework synthesizes the advantages of previous methods and provides a new way to study the human–water symbiosis relationship from a symbiotic perspective. This study applied the proposed method to Henan Province, and the research results obtained aligned with the real situation in Henan Province. In addition, the method is a generalized method exploring the human–water symbiosis relationship, which has a broad application promise. Not only can it be applied to different spatial scales, such as national, provincial, urban, and watershed scales, but it can also capture the changing characteristics of the human–water symbiosis relationship in time series. In conclusion, the framework of the human–water symbiosis relationship proposed in this study demonstrates strong rationality and applicability.

5.2. Policy Implication

Although the development level of the human system and water system in Henan Province shows a trend of gradual improvement in general, individual cities still face many challenges such as the prominent contradiction between the supply and demand of water resources, the imbalance between the development of the resource-environmental system and the socio-economic system, and the unhealthy human–water symbiosis relationship, which will constrain the high-quality development of Henan Province [64]. In response to these problems, some practical suggestions are put forward from the three dimensions of the symbiotic unit, symbiotic pattern, and symbiotic environment by combining the research results of Henan Province.

As the basic units composing the symbiosis system, the human system and water system need to take tailored measures according to the development levels of individual cities. For regions with lower levels of human development (e.g., Shangqiu, Xinyang, and Zhoukou), it is recommended to adjust the industrial development structure and focus on promoting the development of the tertiary industry. Simultaneously, leveraging the transportation advantages of central urban clusters (such as Zhengzhou and Luoyang) of Henan Province and their pivotal role in regional coordinated development is essential [32]. Cities with lower rankings in water system development, such as Luohe and Pingdingshan, could promote the optimal allocation of water resources among cities through water diversion projects, thereby alleviating competitive water pressure in time and space [29].

To shift from the current predominance of the “H⁺W⁻” pattern in Henan Province, the enhancement in the human–water symbiosis relationship should primarily focus on alleviating the inhibitory effects of the human system on the water system. On the premise of ensuring the stable development of the human system, Henan Province should focus on improving the condition of the water system through effective water resources management, water ecological protection, and environment restoration. In addition, for cities where the current distribution of human–water symbiosis patterns is dominated by safety zones (e.g., Zhengzhou, Sanmenxia, and Nanyang), the current human–water symbiosis systems in these cities are in a relatively qualified state of health, but the overall health of these cities is not stable. Despite the symbiosis system in the safe zone, they are in the safe transition zone in most years, and they should always be alerted to the risk of transitioning to the non-safe zone [65].

Creating a conducive symbiotic environment for the development of the human–water system is equally indispensable. For instance, the proportion of investment in water conservancy construction for water protection and ecology (W6) as a primary influencing factor of the human–water symbiosis index is crucial for improving the human–water symbiosis relationship [50]. Promoting major ecological projects such as water environment protection and returning farmland to forests and grasslands will help enhance water conservation functions and create a symbiotic environment conducive to socio-economic development. Moreover, promoting the application of high-tech achievements, developing new quality productive forces, implementing the most stringent water resources management system, harnessing water recycling technologies, enhancing water utilization efficiency, and promoting water saving and emission reduction can effectively alleviate resource and environmental pressures on symbiotic systems [48].

5.3. Limitations and Prospects

This study introduced a novel symbiotic perspective on the human–water relationship, but it also has several limitations that remain to be improved and explored. Firstly, this study constructed a human–water symbiosis system evaluation index system with the human system and water system as symbiotic units. However, the human–water system is an intricate, complex, and intertwined system involving all aspects of the human system and the water system [2]. Influenced by the availability of data, only some representative indicators were selected in this paper. Although the indicator system constructed in this study has relatively good applicability, the appropriate indicators are not necessarily optimal, which may affect the comprehensiveness of the evaluation indicator system to a certain extent [31,47]. Secondly, this paper describes and analyzes the dynamics of the interaction between the human system and the water system based on the Lotka–Volterra model and identifies the main influencing factors of the human–water symbiosis system, but it lacks a specific portrayal of the mechanism of the role between the two subsystems within the human–water symbiosis system, as well as an in-depth analysis of the mechanism of the influence of the driving factors [50]. Finally, the framework proposed in this paper contains an analysis, quantification, discrimination, and attribution, but on the basis of recognizing and quantifying the human–water symbiosis relationship, how to further carry out practical regulation methods to promote the harmonious symbiosis between humans and water still needs in-depth exploration in the future.

6. Conclusions

This study used the proposed research framework of human–water symbiosis to comprehensively understand and evaluate the human–water relationship from the perspective of symbiosis, taking Henan Province as a case study. Specifically, the human–water relationship was analyzed based on the symbiosis theory, and the human–water symbiosis system indicator evaluation system was constructed to measure the development level of the human system and the water system in 18 cities in Henan Province from 2007 to 2022 using the SMI-P method. Then, the symbiotic pattern of the human–water system was identified based on the Lotka–Volterra model, and the human–water symbiosis index was calculated to characterize the health of the human–water symbiosis system. Finally, the obstacle degree model and neural network model were used to identify the influencing factors of the human system, the water system, and the human–water symbiosis system. The main conclusions are as follows.

(a) The framework of the human–water symbiosis relationship proposed in this study has obvious advantages and applicability. The framework is a generalized and novel framework for exploring the human–water symbiosis relationship, and it integrates the advantages of previous methods. It can not only describe the interactions between the human system and water system, but also characterize the overall health of the human–water symbiosis system. The framework has been effectively applied in Henan Province, demonstrating significant potential and promise.

(b) During the period 2007–2022, there are obvious spatial differences in the development levels of the human system and the water system in Henan Province, with HDI showing stable growth year by year, while WDI shows a slow and fluctuating growth trend, and the development status of the water system is more unstable. During the sample period, Henan is characterized by the “human system parasitizes water system (H⁺W⁻)” pattern, and the symbiosis relationship between the human system and the water system is not optimistic, so it is necessary to take appropriate measures to mitigate the inhibiting effects of the human system on the water system.

(c) Through an attribution analysis, we found that the main indicators affecting the human system are H1, H2, and H7, while affecting the water system are W1, W3, and W6, but there are also some geographical differences in different cities. In addition, the indicator with the largest contribution to the indicator factors of the human–water symbiosis system is the proportion of water conservancy construction investment for water conservation and ecology (W6). Based on the results of this study in Henan Province, we put forward recommendations for strengthening the development symbiotic units, improving the undesirable human–water symbiosis pattern, and creating a symbiotic environment suitable for the development of symbiotic units.