Water ecological security assessment and spatial autocorrelation analysis of prefectural regions involved in the Yellow River Basin

Water ecological security evaluation results of Yellow River Basin

Index weight analysis

This study selects the index weights in 2009, 2014, and 2019 for comparative analysis. As shown in Table 3, in terms of space, in the pressure layer, indicator A₆ (Water area) has the most prominent weight, and indicator A₃ (Natural population growth rate) has the most negligible weight; in the state layer, indicator B₆ (Proportion of wetland area to total area) has the most prominent weight, and B₁ (COD emissions per 10,000 yuan GDP) has the most negligible weight; in the response layer, indicator C₃ (Green area rate of built-up area) has the most prominent weight, and indicator C2 (Centralized treatment rate of urban domestic sewage) has the most negligible weight. In summary, water area, wetland area, and built-up green space are the key indicators affecting the water ecology of the Yellow River Basin, including natural factors and economic and social factors.

In terms of time, indicators A₆ and B₆ have equal weights in three years and have always been in an important position. The weight of indicator C₁ (the rate of stable compliance of wastewater discharge by industrial enterprises) has fallen for three consecutive years, from 0.38 to 0.09. It shows that after years of environmental management in various cities, the rate of compliance with wastewater discharge standards of industrial enterprises has been continuously increasing. It plays a positive role in the construction of water ecological security. The weight of indicator C₃ has increased significantly in three years, from 0.31 in 2009 to 0.90 in 2019, indicating that with the continuous development of urbanization, the built-up area has become larger and larger, which has a massive impact on water ecological security. Therefore, the green area in the built-up area is vital, which is the key to ensuring the urban ecological environment. It is also a critical factor in maintaining the water ecological security.

Trend analysis of water ecological security

This study is based on Eq. (4) to calculate the WESI of the nine provinces in the past ten years, as shown in Fig. 3. From the perspective of the changes in WESI from 2009 to 2019, the overall trend is slowly increasing. Compared with 2009, WESI increased by 5.96% in 2019, but the average annual growth rate was only 0.59%. The sharp rise stage was in 2009–2012, with an average annual growth rate of 1.84%. Since 2009, there has been no inferior V water in the main stream of the Yellow River, and the water quality has been improving year by year. During this period, the nine provinces implemented the Yellow River Basin Flood Control Plan under the guidance of The State Council. The plan calls for strengthening infrastructure construction in the Yellow River Basin and conducting work such as river improvement and soil and water conservation. Therefore, we will promote the restoration of water ecology in the river basin and improve the safety of water ecology. From 2012 to 2019, WESI showed a trend of ups and downs. This is because the provinces have gradually shifted their development focus to the economy after achieving significant results in restoring water ecology in the river basin. The rapid economic development has brought more significant pressure to environmental governance and hindered water ecological safety improvement.

Criterion layer quantitative results

To further study and appraise the water ecological security of the study area, this paper quantifies the criteria layers (i.e., pressure, state, response) on account of the SMI-P method. It selects 2009, 2014, and 2019 for comparative analysis. As shown in Fig. 4, the criterion layer has undergone specific changes over time. First of all, the distribution of pressure in 62 cities has not changed much in three years. The areas with more tremendous pressure on water ecological security are mainly concentrated in eastern cities, including Shuozhou, Taiyuan, Jinzhou, Luliang, Linfen, Jincheng, and Changzhi, Anyang, Hebi, Jiaozuo, Puyang, Liaocheng, and other cities. Areas with less pressure are mainly concentrated in western and eastern cities, including Guoluo Tibetan Autonomous Prefecture, Hainan Tibetan Autonomous Prefecture, Haibei Tibetan Autonomous Prefecture, Ordos, Bayannaoer, Yulin, and other cities. In 2009, the precipitation in spring and winter in Lanzhou is less, the degree of drought is serious, and the flood disaster is more severe in flood season, which brings tremendous pressure to the water ecological security. After 2015, Lanzhou continued to implement the Action Plan for Prevention and Control of Water Pollution and then the river chief system was implemented. In 2019, The Work Plan of Lanzhou Municipal Water Pollution Prevention and Control Action in 2019 was issued and implemented. All these measures and actions have laid a foundation for water ecological security. On the contrary, with the rapid development of urbanization and economy and society, the pressure of water ecological security in Jinan has increased.

The larger the value of the status layer, the better the aquatic ecological status. On the contrary, the worse the aquatic ecological security. The overall spatial distribution of the status layer has not changed significantly in the past three years, and the changes are mainly concentrated in some cities. For example, the water ecological security status of Wuhan and Ulan Chab has gradually deteriorated in three years. The reason is that the urban population is becoming denser and sewage discharge is increasing, but related management and measures have not been fully implemented. In Dongying, the water ecological security status improved in 2014 and 2019. According to the Environmental Status Bulletin, in 2014, Dongying deepened its drainage basin pollution control system, continuously strengthened the restraint mechanism to improve river water quality, and carried out a pilot wetland ecological restoration.

In the three years of 2009, 2014, and 2019, the response layer has changed more significantly than the pressure and status layers. It can be seen that the degree of response scarcity has gradually shifted from western cities to eastern cities. The reason can be understood as that due to their superior natural conditions, western cities have relatively weak awareness of water ecological protection and governance, and their ability to respond to emergencies is insufficient. However, with the increasingly prominent ecological and environmental problems, the awareness of maintaining water ecological safety is increasing, and the protection and governance measures are constantly improving. For example, Guoluo Tibetan Autonomous Prefecture, Hainan Tibetan Autonomous Prefecture, and Haibei Tibetan Autonomous Prefecture. Eastern cities are densely populated, urbanization development is faster than western cities, and environmental problems occur more frequently. Therefore, the awareness of ecological and environmental protection is more substantial, the governance system is relatively complete, and responsiveness is relatively good. However, as time progresses, some cities have somewhat slackened their ecological environment governance, and therefore their responsiveness has also weakened. For example, Shuozhou, Jinzhou, Lvliang, Linfen, and other places.

Final quantitative results

In order to show the water ecological security status of 62 cities more intuitively, this paper shows the water ecological status level in Table 2 through the GIS spatial distribution map (Fig. 5).

Looking at the overall situation in the past three years, the water ecological security status is relatively stable, with little overall change. The reasons mainly include natural geographical location and economic and social development. In terms of physical geography, the safer areas are concentrated in the upper reaches of the Yellow River Basin, all of which have the characteristics of large land and sparsely populated areas and relatively superior natural conditions. They provide good conditions and foundations for the construction of water ecological security. The moderate warning cities are primarily located in the Loess Plateau and the North China Plain, where water resources are scarce, and the dense population, posing a threat to water ecological security. In terms of economic and social development, relatively safe areas are located in remote areas with inconvenient transportation. The region is dominated by agriculture and animal husbandry, with relatively backward economic development and a low level of urbanization. In addition, the threat to water ecological security is relatively tiny. Residents in the moderate warning area have a significant living demand, and the over-exploitation and utilization of natural resources have led to the destruction of the ecological environment. Therefore, it poses a more significant threat to water ecological security.

Combining Fig. 5 and Table A.2 of appendix, it can be seen that in 2009, there were 8 safer cities, 22 with early warning level, and 32 with moderate warning. Relatively safe cities are concentrated in the southwest and north of the Yellow River Basin; cities with moderate warning level are distributed in the central and eastern areas. In 2014, the number of safer cities increased to 10, and the number of cities with moderate warning level decreased to 30. The means that water ecological security has received more and more attention, and cities have consciously strengthened the protection and governance of water ecology to maintain water ecological security. In 2019, there are 11 relatively safe cities, 21 cities with warning level, and 30 cities with moderate warning level. The overall situation has not changed much, and some cities have changed significantly. For example, Erdos had increased from an early warning status in 2009 to a safer status in 2014, and its safety index has risen from 0.57 to 0.65. Wuzhong has been upgraded from the warning level in 2009 (0.39) to the relatively safe in 2014 (0.44), and the safety index (0.47) in 2019 has also increased. Binzhou had improved from its early warning status (0.60) in 2009 to a relatively safe level (0.64) in 2014, and its safety index (0.66) has also increased in 2019, but the increase is not significant. On the contrary, Jinan has deteriorated from the early warning level in 2009 and 2014 to the moderate warning level in 2019, indicating that the water ecological security of Jinan has been seriously threatened in the process of rapid development.

Spatial autocorrelation analysis of 62 cities in the Yellow River Basin

Global spatial autocorrelation analysis

This paper selects 2009, 2014 and 2019, and analyzes the global spatial autocorrelation based on GeoDa. Combining Table 4 and Fig. 6, the Moran index for these three years was 0.298, 0.359, and 0.334 respectively, which were all in the [0,1] interval, indicating the water ecological security of 62 cities in the past three years showed significant spatial autocorrelation. Moreover, there is a positive spatial correlation, and the spatial autocorrelation is strong. The four quadrants of the scatter chart are high-high (i.e., first quadrant) aggregation area, low–high (i.e., second quadrant) aggregation area, low-low (i.e., third quadrant) aggregation area, and high-low (i.e., fourth quadrant) aggregation area. After testing, z-value > 1.96, p-value < 0.05, the study area has significant clustering, proving the strong spatial positive autocorrelation of water ecological security in 62 cities.

Specifically, in 2009, 40 cities were showing positive spatial autocorrelation, accounting for 64.52% of the entire study area. In 2014, 4 more cities were showing positive spatial autocorrelation than in 2009. In 2019, 47 cities showed positive spatial autocorrelation, an increase of 3 from 2014. It shows that the cities showing positive spatial autocorrelation are increasing, but the increase is slight.

Local spatial autocorrelation analysis

The global spatial autocorrelation analysis reflects the trend and degree of correlation between different regions in the entire study area. The local spatial autocorrelation analysis can clearly express the concentration and significance of specific areas.

1. (a)

   Target layer analysis

   As shown in the Fig. 7 that the significant areas of high-high and low-low are mainly distributed in the upper reaches of the Yellow River Basin and at the junction of the middle and lower reaches. It shows that water ecological security is more important for cities in the upper reaches and middle and lower reaches cities, and the impact is more significant. The upstream contains the river source area and canyon area, rapids, many lakes, swamps, grass beaches, large water yield, rich water resources; the junction of middle and lower reaches is a place where floods occur frequently, and there are lots of dikes, which has a significant impact on water ecology. Therefore, water ecological security is essential for the border area’s upstream, middle, and lower reaches.

   (a) LISA cluster map of water ecological safety in 62 cities in 2009, 2014, and 2019, (b) LISA significance map of water ecological security of 62 cities in 2009, 2014, and 2019. Note This was created by Geoda, version 1.18.0. https://geodacenter.github.io/.

   Full size image

   In combination with Table 5, it can be seen that the proportions of cities with positive spatial correlation (high-high, low-low) in the entire study area in the past three years are 16.13%, 17.74%, and 16.13%. Cities showing negative spatial correlation (low–high, high-low) accounted for 4.84%, 1.61%, and 3.23%. Comparing the two regions, it can be seen that the proportion of spatially positively correlated regions is higher than that of spatially negatively correlated regions, and the number of high-low agglomeration regions in 2014 and 2019 is 0.

   Full size table

2. (b)

   Criterion layer analysis

Pressure, state, and response have varying degrees of impact on the water ecological security of each city, so this article summarizes its characteristics through cluster analysis. In terms of pressure, the overall distribution of the degree of influence by the pressure indicators is stable, and the concentrated areas are in the western, northern, and eastern cities of the Yellow River Basin (Fig. 8a). Cluster distribution and significant changes appeared in very few regions. The main change was that in 2014, Ordos became a high-high area, and the significance of the Huangnan Tibetan Autonomous Prefecture increased.

In terms of state, as shown in Fig. 8b, the concentrated areas are mainly distributed in western and eastern cities, and the main changes are in Baoji, Liaocheng, and Kaifeng. In 2014, Liaocheng was more affected by the status indicators and became more significant. In 2019, the impact of state indicators on Baoji weakened, and the sign changed to insignificant. On the contrary, the influence of status indicators on Kaifeng increased, and its significance increased.

Compared with the pressure and the state, the changes in response are more significant. As shown in Fig. 8c, the concentration area has increased from the west and east to the west, east, and north, and the significance of the concentration area has also changed significantly. In 2009, 21 cities with positive spatial correlation in the study area were distributed in the westernmost and easternmost cities. Among them, 14 cities are highly significant. 4 cities are showing negative correlation, including Zhongwei, Yuncheng, Kaifeng, and Puyang, which are highly significant. In 2014, Aba Tibetan and Qiang Autonomous Prefecture and Xining changed from a positive to a negative correlation, which was very significant. Yuncheng, Kaifeng, etc., have become insignificant. Some areas in the west, such as Haibei and Hainan, have increased significantly, while some areas in the east have decreased significantly, such as Binzhou and Jinan. In 2019, Bayannaoer, Ordos, and Shizuishan were newly concentrated areas in the northern region, which are highly significant and are greatly affected by response indicators. Among them, Ordos and Shizuishan are positively correlated, and Bayannaoer is negatively correlated. At the same time, the number of cities in concentrated areas in the west has decreased, such as Haibei, Hainan, and Xining.

From the above changes, it can be seen that with the continuous development of society and the different needs of ecological environment governance, the attitudes and response intensity of ecological, environmental protection and governance vary from place to place. Therefore, the geographical environment, economy, and population environment are prominent. Cities are more spatially related to stress, state, and response factors.

Combined with Table A.3 of appendix, from an overall point of view, the pressure, state, and response presented in the study area have significant spatial autocorrelation. The proportion of cities with positive correlations presented by the three is more significant than that of negative correlations. Among them, the response layer is more prominent, reaching 33.87%, 25.8%, and 20.97%, respectively, in three years. It can also be seen that the proportion is declining, indicating that with the gradual improvement of environmental problems, some cities have weakened corresponding response measures. And relevant supervision has been relaxed.

Source: Ecology - nature.com