Evaluation of the Water Eco-Environmental Quality of a Typical Shallow Lake in the Middle and Lower Reaches of the Yangtze River Basin

Abstract

Intensified human activities in recent years, such as wastewater discharge and agricultural non-point source pollution have led to a decline in lake water quality, especially in the middle and lower reaches of the Yangtze River Basin, which threaten the stability of lake water ecosystems. Therefore, it is necessary to conduct a scientific assessment of the water eco-environmental quality of shallow lakes and implement targeted management measures. Considering the characteristics of shallow lakes, major ecological and environmental issues, and current standards and guidelines, an indicator system method was employed to establish a water eco-environmental quality evaluation system tailored for typical shallow lakes in the middle and lower reaches of the Yangtze River Basin. This evaluation system comprises three criteria layers (aquatic organism, habitat quality, and water quality) and 10 indicator layers. Using survey data from 2022 to 2024 for evaluation, the results showed that the water eco-environmental quality of Lake Gehu was rated as poor, with the lowest score for macrophyte coverage and the highest score for riparian vegetation coverage. This indicates that the shoreline restoration project in Lake Gehu was effective, while the lake water quality still needs improvement. Remedial measures include increasing aquatic vegetation coverage, reducing nitrogen and phosphorus pollution loads, and controlling the occurrence of algal blooms. This evaluation system combines field surveys with remote sensing monitoring data, fully considering historical and current conditions, and can guide local authorities in evaluating lake water environmental quality. The constructed evaluation system is applicable for the assessment of shallow lakes in the middle and lower reaches of Yangtze River Basin. It provides a scientific basis for the continuous improvement of eco-environmental quality and the construction of Beautiful Lakes Initiative, contributing to the management and protection of lake ecosystems.

1. Introduction

The middle and lower reaches of the Yangtze River Basin in China is the region with densely distributed freshwater lakes. Rapid urbanization and a series of other factors have led to lake eutrophication in recent years [1]. Because the region is a floodplain, there are high nutrient loads entering the lake via river water and surface runoff. Agricultural non-point source pollution is another pollution source to the lake. The combined effects of natural and anthropogenic factors have led to issues such as a reduction in lake area, degradation of the lakeside zone, and a decline in aquatic biological resources [2,3]. Since 2023, the Ministry of Ecology and Environment and collaborating agencies have enacted the “Evaluation Criteria for Water Ecological Assessment in the Yangtze River Basin”, which is an important measure to implement the “Yangtze River Protection Law of the People’s Republic of China”. Therefore, it is necessary to establish a water eco-environmental quality evaluation system applicable to shallow lakes in the middle and lower reaches of the Yangtze River Basin, to promote the continuous improvement of the eco-environmental quality of shallow lakes [1]. The Ministry of Ecology and Environment has proposed the “Action Plan for the Protection and Construction of Beautiful Rivers and Lakes (2025–2027)”, which focuses on improving water eco-environmental quality, coordinating the management of water resources, water environment, and water ecology, implementing comprehensive governance of lake eutrophication, and promoting the protection and construction of Beautiful Rivers and Lakes Initiative. Lake Gehu is a typical shallow lake in the middle and lower reaches of the Yangtze River Basin. It suffers from significant water pollution and eutrophication, has sparse macrophytes, and experiences frequent occurrences of algal blooms, all of which makes the ecosystem quite fragile. The eco-environmental status of Lake Gehu is representative of shallow eutrophic lakes in the middle and lower reaches of the Yangtze River Basin, which is an urbanized region containing thousands of shallow lakes [4]. These shallow lakes experienced ecosystem degradation and need a scientifically robust assessment framework for guiding lake restoration. Thus, a comprehensive water eco-environmental quality evaluation system for shallow lakes in the middle and lower reaches of the Yangtze River Basin is essential to guide ecological conservation and to provide transferable protocols for eutrophic lake restoration in similar climatic zones.

Water eco-environmental quality assessment is based on ecological theory and evaluates the overall status and changes in the constituent elements of water ecosystems [5]. China’s surface water environmental assessment commenced in the 1980s, with the enactment of the first Water Pollution Prevention and Control Law in 1984, which incorporated pollutant loads into the total control targets for rivers and lakes [6]. With rapid economic development and accelerated industrialization, water pollution has become an increasingly pressing issue, posing a threat to ecological security and public health. There is an urgent need to conduct water quality monitoring and assessment. The comprehensive index method is relatively mature in its application in China. It can be used to analyze pollution sources and provide a theoretical basis for the comprehensive management of water environment in river basins [7]. Biological indicators, as one of the environmental quality indicators, can be used to evaluate the health of water bodies by assessing the status and types of existing aquatic organisms [8]. During the 14th Five-Year Plan period, China has achieved significant improvements in water environmental quality. The Ministry of Ecology and Environment has proposed establishing a new system for the integrated management of water resources, water environment, and water ecology [9].

Current methods for evaluating water eco-environmental quality include the Index of Biotic Integrity (IBI) method, predictive modeling method, European Union Water Framework Directive (WFD) method, and indicator system method. The IBI assessment method is used to protect the health of aquatic organisms and to characterize the integrity of aquatic ecosystem, while habitat quality and water quality are not included in the assessment [10,11,12]. The predictive modeling method can reflect the riverine eco-environmental quality and ecological degradation levels [13]. It uses macroinvertebrates as sole bioindicators to indicate the health status of rivers, and is suitable for rivers or streams with a small catchment area. However, it requires a large amount of data collection. The WFD evaluation method comprehensively considers three factors: hydrological conditions, aquatic organisms, and hydrochemical parameters [14]. The indicator system method, or objective-criterion-indicator model, establishes a comprehensive indicator system to evaluate the eco-environmental quality of water bodies [15]. The indicator system method consists of three hierarchical layers: the objective layer, criterion layer, and indicator layer [16]. It emphasizes evaluation parameters such as hydrological and physicochemical attributes and has been widely applied to assess aquatic ecosystem integrity [17,18]. Therefore, a multi-index assessment method that comprehensively integrates habitat quality, water physicochemical properties, and aquatic biological indicators has become the prevailing approach in water eco-environmental health assessment [19]. Dong et al. [20] proposed a lake ecological health evaluation index system for Lihu Lake and evaluated the health level, which can provide support for the ecological health evaluation of urban lakes. Sun et al. [21] established a health evaluation index system for the Xiangxi River and assessed the health status of the aquatic ecosystem. The indicator system method can be used to establish a set of evaluation indicators for specific areas, reflecting the strengths and weaknesses of lake water eco-environmental quality, thus guiding the implementation of lake water ecological restoration. This paper applies the indicator system method to establish a water eco-environmental quality evaluation system tailored for Lake Gehu, which is a shallow lake in the middle and lower reaches of the Yangtze River Basin. This evaluation system can be used to guide the restoration of water eco-environmental quality and to implement guidelines for the protection and construction of Beautiful Rivers and Lakes Initiative.

2. Establishment of an Eco-Environmental Quality Evaluation System for a Typical Shallow Lake

2.1. Site Description

Lake Gehu is an important part of the Taihu Lake Basin in the middle and lower reaches of the Yangtze River Basin, spanning Changzhou and Wuxi cities. The increased nutrient fluxes, including nitrogen and phosphorus from industrial wastewater, domestic sewage, and aquaculture into the lake, have resulted in water pollution and the decline of aquatic plants, ultimately making the lake ecosystem relatively fragile [22,23]. Lake Gehu has an average water depth of 1.27 m, which is typical of shallow lakes. The lake serves multiple functions, including navigation, irrigation, and aquaculture, and serves as a backup water source area for Changzhou City. The macrophyte coverage in Lake Gehu has decreased from 80~90% in the 1990s to less than 10% at present, with submerged plants being particularly scarce [24,25]. Chemical oxygen demand (COD_Mn) pollution loads in the region mainly come from urban non-point source pollution, while ammonia nitrogen (NH₃-N), total nitrogen (TN), and total phosphorus (TP) pollution loads mainly come from urban domestic sources, followed by industrial sources and urban non-point source pollution [26]. These pollution loads indirectly impact lake water bodies. Lake Gehu has enough water quantity to ensure water intake for the backup water source area, but the water quality cannot consistently meet the Class III level (TN = 1.0 mg/L and TP = 0.05 mg/L for lake water) according to the China Surface Water Environmental Quality Standard, with nitrogen and phosphorus concentrations exceeding the limits [27].

2.2. Establishment of an Evaluation System

In this paper, we applied the indicator system method, followed the principles of scientific soundness, comprehensiveness, and feasibility, and selected indicators that can best reflect the overall state of the components of the water ecosystem. We then constructed a water eco-environmental quality evaluation system for Lake Gehu, a representative shallow lake in the middle and lower reaches of the Yangtze River Basin. The construction of the indicator system first considered all applicable indicators for lakes according to the “Evaluation Criteria for Water Ecological Assessment in the Yangtze River Basin”, and referred to the evaluation contents in the “Technical Guidelines for Monitoring and Evaluation of Water Eco-environment Quality of Lakes and Reservoirs” and the “Technical Guidelines for River and Lake Health Assessment” [28]. Through expert consultation and verification, the final evaluation system can effectively guide the governance and improvement of the water eco-environment of Lake Gehu. The indicator system method is mature and has been applied in other lakes as well, such as Baiyangdian Wetland [9] and Lihu of Lake Taihu [20].

In the “Evaluation Criteria for Water Ecological Assessment in the Yangtze River Basin”, the lake water ecological assessment indexes include the number of fish species, the number of protected aquatic species, the number of macroinvertebrate species, the proportion of algal bloom area, macrophyte coverage, zooplankton community structure, natural shoreline ratio, the human activity impact index on aquatic habitats, the ecosystem quality of water source conservation areas, the comprehensive trophic state index, and the ecological flow attainment rate. Among them, the number of protected aquatic species, the human activity impact index on aquatic habitats, and the ecosystem quality of water source conservation areas are not applicable to shallow lakes in Changzhou and are thus excluded from the evaluation system. The evaluation of fish, macroinvertebrates, and zooplankton refers to the “Technical Guidelines for Water Ecological Monitoring: Monitoring and Evaluation of Aquatic Organisms in Lakes and Reservoirs” [29]. The Shannon–Wiener diversity index (H) and evenness index (J) are used, and these two indicators are applicable to all lakes. In addition, the aquatic organism criterion layer of this evaluation system includes an evaluation of fish species diversity. Two indicators, including the proportion of algal bloom area and macrophyte coverage, belong to the habitat quality criterion layer. The shoreline of Lake Gehu has undergone projects such as returning farmland to lake and water ecological restoration. Therefore, the evaluation of the lake’s shoreline primarily uses small- and medium-scale habitat indicators (including lake shoreline stability and riparian vegetation coverage) and macroscale habitat indicators to evaluate the growth status of riparian vegetation, replacing the traditional evaluation of natural shoreline ratio. The comprehensive trophic state index belongs to the water quality criterion layer. The ecological flow attainment rate was evaluated based on the proportion of lake area shrinkage using macroscale habitat indicators. Thus, the water eco-environmental quality evaluation system for Lake Gehu comprises one objective layer and three criterion layers. The target layer is the water eco-environmental quality index (A), while the three criteria layers include aquatic organism (B1), habitat quality (B2), and water quality (B3). The indicator layer primarily evaluates aspects such as phytoplankton, zooplankton, macroinvertebrates, fish diversity, small- and medium-scale habitat, macroscale habitat, water quality, and trophic status index. The components of the evaluation system for Lake Gehu and their reference basis were shown in

Table 1. The water eco-environmental quality evaluation system and reference basis for Lake Gehu.

Objective Layer	Criterion Layer	Indicator Layer	Reference Basis
The water eco-environmental quality index (A)	Aquatic organism (B1)	Phytoplankton diversity index (C1)	[29]
		Zooplankton diversity index (C2)
		Macroinvertebrate diversity index (C3)
		Fish diversity index (C4)
	Habitat quality (B2)	Small- and medium-scale habitat indicators (C5)	[30]
		Riparian vegetation coverage index (C6)	[31]
		The algal bloom area ratio (C7)	[32]
		The lake area shrinkage ratio (C8)
		Macrophyte coverage index (C9)
	Water quality (B3)	Water quality and trophic status index (C10)	[28,32]

.

2.3. Selection of Indicators and Scoring Method

Each indicator is converted to a score ranging from 1 to 5, and the water eco-environmental quality index (WEQI) is being calculated. The evaluation results of WEQI are classified into five grades: excellent (WEQI = 5), good (5 > WEQI ≥ 4), moderate (4 > WEQI ≥ 3), poor (3 > WEQI ≥ 2), and very poor (2 > WEQI ≥ 1). The scoring criteria for each indicator are shown in

Table 2. The scoring criteria for each indicator.

Criterion Layers	Indicator Layers		Score
			5 (Excellent)	4 (Good)	3 (Moderate)	2 (Poor)	1 (Very Poor)
Aquatic organism	Biodiversity index	Shannon–Wiener index (H)	H ≥ 3.0	2.0 ≤ H < 3.0	1.0 ≤ H < 2.0	0 < H < 1.0	H = 0
		Evenness index (J)	0.8 < J ≤ 1	0.5 < J ≤ 0.8	0.3 < J ≤ 0.5	0 < J ≤ 0.3	J = 0
Habitat quality	The small- and medium-scale habitat		150 < HS	120 < HS ≤ 150	90 < HS ≤ 120	60 < HS ≤ 90	HS ≤ 60
	Macroscale habitat	Riparian vegetation coverage	75~100% (Very high density)	40~75% (High density)	10~40% (Moderate density)	0~10% (Sparse)	0 (No vegetation)
		The algal bloom area ratio (P)	P = 0% (No algal bloom)	0% < P ≤ 10% (No significant algal bloom)	10% < P ≤ 30% (Mild algal bloom)	30% < P ≤ 60% (Moderate algal bloom)	60% < P ≤ 100% (Severe algal bloom)
		Lake area shrinkage ratio	0 (No shrinkage)	0~10% (No significant shrinkage)	10~20% (Moderate shrinkage)	20~30% (Significant shrinkage)	>30% (Severe shrinkage)
		Macrophyte coverage (Historical data comparison method)	≤5% (Close to historical data)	5~10% (Slight difference from historical data)	10~25% (Moderate difference from historical data)	25~50% (Significant difference from historical data)	>50% (Substantial difference from historical data)
		Macrophyte coverage (Direct scoring method)	>75% (Very high density)	40~75% (High density)	10~40% (Moderate density)	0~10% (Sparse coverage)	0% (No coverage)
Water quality	Physico-chemical water quality index	Water quality status	Class I-II	Class III	Class IV	Class V	Inferior to Class V
		Trophic status index	Oligotrophic	Mesotrophic	Light eutrophic	Moderate eutrophic	Severe eutrophic

.

2.3.1. Aquatic Organism Criterion Layer

The aquatic organism criterion layer includes diversity indices of phytoplankton (C1), zooplankton (C2), macroinvertebrates (C3), and fish (C4). The evaluation and scoring of these biological indicators refer to the guidelines provided in “Technical Guidelines for Water Ecological Monitoring: Monitoring and Evaluation of Aquatic Organisms in Lakes and Reservoirs” [29] and the “Technical Guidelines for Monitoring and Evaluation of Water Eco-Environment Quality of Lakes and Reservoirs” [30]. The diversity indices of phytoplankton, zooplankton, macroinvertebrates, and fish are evaluated using the Shannon–Wiener diversity index (H) and the evenness index (J). The average scores of H and J are used as the final score for each aquatic biodiversity index. The H index reflects the complexity of biological community structure. A higher H index indicates better eco-environmental conditions, while a lower H index indicates deteriorating water quality. The J index reflects the uniformity of individuals in a biological community. A higher J index indicates a more complex community structure, whereas a lower J index indicates a more uniform and simplified community structure. The scoring criteria for aquatic biodiversity indicators are shown in Table 2. The scores range from 1 to 5, with higher scores indicating better water eco-environmental quality.

2.3.2. Habitat Quality Criterion Layer

(1)

Small- and medium-scale habitat indicators

The small- and medium-scale habitat indicator (C5) was evaluated using the habitat scoring method described in the “Technical Guidelines for Monitoring and Evaluation of Water Eco-environment Quality of Lakes and Reservoirs” to assess the habitat conditions of biological habitats in the littoral zones and water bodies of lakes and reservoirs [33]. Survey points are evenly distributed along the water body shoreline, with each point representing a section of the littoral zone without overlap between two sections. Each point was scored for various small- and medium-scale habitat elements, including substrate conditions, habitat elements, littoral zone stability, water quantity status, and riparian vegetation coverage. Each item scored on a scale of 0–20 points. The total score of all habitat elements represents the small- to medium-scale habitat elements at that point. The average score of all survey points is then converted to a score ranging from 1 to 5 (Table 2), where 5, 4, 3, 2, and 1 point represent undisturbed, slightly disturbed, moderately disturbed, severely disturbed, and extremely disturbed of the physical habitat, respectively.

(2)

Macroscale habitat indicators

The macroscale habitat indicator includes the growth status of riparian vegetation, algal bloom conditions, water supply security, and macrophyte coverage. The scoring criteria for each indicator are shown in Table 2. Among them, riparian vegetation coverage (C6) represents the growth status of littoral vegetation. Referring to the “Technical Specifications for Eco-environmental Status Evaluation” [31], the maximum normalized difference vegetation index (NDVI) of the riparian zone during the period of maximum vegetation coverage within the year is calculated based on satellite remote sensing images. The range of the riparian zone is defined according to the lake area and extends 500 m to 1 km inland.

The algal bloom area ratio (C7) represents the ratio of the maximum single-event algal bloom area to the total lake area within a year, as specified in [32]. This index is intended to guide local efforts in algal bloom management. The method for calculating algal bloom area follows the “Technical Specifications for Remote Sensing and Ground-Based Monitoring and Evaluation of Algal Blooms” [34].

The lake area shrinkage ratio (C8) indicates the water supply security status of lakes. It is calculated as the relative reduction ratio of lake surface area in the assessment year compared to the historical reference year. The scoring criteria are shown in Table 2.

The macrophyte coverage index (C9) refers to the percentage of the total lake area occupied by emergent plants, floating-leaved plants, and submerged plants that are within the lake boundary. The index is used to assess the importance of restoring aquatic vegetation in lakes. The evaluation method combines direct scoring and comparison with historical data.

2.3.3. Water Quality Criterion Layer

The water quality criterion layer is represented by the physicochemical water quality index (C10), which includes water quality status and the trophic status index of lakes and reservoirs. Among them, the evaluation elements for water quality status include nine parameters: dissolved oxygen (DO), water temperature, electrical conductivity, pH, NH₃-N, TP, TN, COD_Mn, and five-day biochemical oxygen demand (BOD₅).

Water quality evaluation is conducted according to the “Environmental Quality Standards for Surface Water” [35] and the “Technical Regulations for the Assessment of Surface Water Resources Quality” [36]. The single-factor evaluation method is employed. For each sampling point, the score was determined by the lowest-scoring parameter among all indicators within the evaluation period. When multiple monitoring results were available, the average value of the monitoring results was used.

The trophic status evaluation of lakes and reservoirs refers to [37], using the comprehensive trophic level index (TLI) [38]. The TLI integrates five parameters: TP, TN, chlorophyll-a (Chl-a), COD_Mn, and water transparency (SD).

The scoring criteria for water quality status and trophic status of lakes and reservoirs are shown in Table 2. The water quality criterion score is determined by the minimum value between the physicochemical water quality index, and the trophic status index of lakes and reservoirs.

2.4. Determination of Index Weights and Calculation of Objective Criterion

The score for the criterion layer is calculated using Formula (1):

$$\mathrm{Z}={\sum }_{\mathrm{j}=1}^{\mathrm{M}}({\mathrm{F}}_{\mathrm{j}}\times {\mathrm{W}}_{\mathrm{j}}),$$

(1)

among them, Z is the score of the criterion layer, ${\mathrm{W}}_{\mathrm{j}}$ is the weight of the j-th evaluation indicator in the criterion layer, ${\mathrm{F}}_{\mathrm{j}}$ is the score of the j-th evaluation indicator, and M is the number of evaluation indicators in each criterion layer.

The comprehensive evaluation index for the water eco-environmental quality of Lake Gehu is calculated using Formula (2):

$$\mathrm{W}\mathrm{E}\mathrm{Q}\mathrm{I}={\sum }_{\mathrm{i}=1}^{\mathrm{m}}{\mathrm{Z}}_{\mathrm{i}}{\times \mathrm{W}}_{\mathrm{i}},$$

(2)

among them, WEQI is the score for lake water eco-environmental quality, ${\mathrm{Z}}_{\mathrm{i}}$ is the score of the i-th criterion layer, ${\mathrm{W}}_{\mathrm{i}}$ is the weight of the i-th criterion layer, and m is the number of criterion layers.

The weights of criterion layer B relative to objective layer A, and the weights of indicator layer C relative to criterion layer B, are both determined using a subjective assignment method, namely the expert scoring method. Specifically, each indicator within a criterion layer is scored according to its importance, and then the average score of each indicator is converted into the weight of that indicator layer. Similarly, each criterion layer within the objective layer is scored according to its importance, and then the average score of each criterion is converted into the weight of that criterion layer. The expert scoring method invites experts with extensive experience in the research scope to score each index. These experts are familiar with shallow lakes in Changzhou and have rich experience in river and lake health evaluation. They refer to existing water environment evaluation standards and specifications, ensuring the final scoring results are scientific and reliable [39].

3. Data Collection and Processing

3.1. Sample Collection

We set up eight sampling points in Lake Gehu and collected data from 2022 to 2024, collecting water samples and measuring aquatic organisms and water quality of the lake. Locations of the sampling points in Lake Gehu are shown in Figure 1. Aquatic organisms were sampled and identified in June and October, while water quality parameters were monitored during the wet season (June) and dry season (December). Water pH, DO (in mg/L), water temperature (°C), and electrical conductivity (EC, in µS/cm) were measured in situ with a portable multi-parameter water quality analyzer (YSI ProQuatro, Columbus, OH, USA). Water transparency was estimated by Secchi depth (SD) using a Secchi disk. All water samples were stored in polypropylene bottles after filtration and measured in the National Engineering Laboratory for Lake Pollution Control and Ecological Restoration, Chinese Research Academy of Environmental Sciences [40]. COD_Mn, NH₃-N, TP, TN, BOD₅, and Chl-a were measured in accordance with [41]. The sample collection and quantitative identification of phytoplankton, zooplankton, and macroinvertebrates referred to [42,43,44]. Fish diversity indices, specifically the Shannon–Wiener diversity index and Pielou’s evenness index, were analyzed using the number of reads obtained from environmental DNA (eDNA) [45].

3.2. Collection and Processing of Other Data

Macroscale habitat indicators were extracted from remote sensing imagery using data from the Landsat series of multispectral remote sensing satellites (https://earthexplorer.usgs.gov/; accessed in 10 October 2024) for June to September in 2022 and 2023 to extract the algal bloom area, macrophyte coverage, and riparian vegetation coverage of Lake Gehu, removing the influence of cloud cover. The months of June to September represent the period of peak values for algal bloom area, macrophyte coverage, and riparian vegetation coverage. The riparian vegetation coverage is defined as the proportion of riparian vegetation coverage to the total land area within a 1 km-width extending inland from the lake shore. Additionally, the small- and medium-scale habitat indicator of Lake Gehu was surveyed in June 2024.

3.3. Determination of the Weights of Evaluation Indicators

The weights for the criterion layer and indicator layer were determined using an expert scoring method. A total of five experienced experts were invited, whose research backgrounds involved ecology, environmental science, hydrology, lakeshore zone restoration and other fields. The scoring process referred to existing water environment evaluation standards and specifications. After statistical processing of the scores, the weights were obtained as shown in

Table 3. The factor weights of water eco-environmental quality evaluation for Lake Gehu.

Objective Layer (A)	Criterion Layers and Assigned Weights		Indicator Layers and Assigned Weights
	Criterion Layers (B)	The weight of B Relative to A	Indicator Layers (C)	The Weight of C Relative to B	The Weight of C Relative to A
The water eco-environmental quality index (A)	Aquatic organism (B1)	0.3333	Phytoplankton diversity (C1)	0.2692	0.0897
			Zooplankton diversity (C2)	0.1923	0.0641
			Macroinvertebrate diversity (C3)	0.1923	0.0641
			Fish diversity (C4)	0.3462	0.1154
	Habitat quality (B2)	0.2121	The small- and medium-scale habitat indicator (C5)	0.1744	0.037
			Riparian vegetation coverage (C6)	0.186	0.0395
			The algal bloom area ratio (C7)	0.2442	0.0518
			The lake area shrinkage ratio (C8)	0.2326	0.0493
			Macrophyte coverage (C9)	0.1628	0.0345
	Water quality (B3)	0.4546	Water quality and trophic status index (C10)	1	0.4546

. The water quality criterion layer has the highest weight, indicating its highest importance. According to the suggested weights from the Ministry of Ecology and Environment, the weights of aquatic organism, habitat quality, and water quality criterion layers are 0.4, 0.2, and 0.4, respectively.

4. Results and Discussions

4.1. Evaluation Results

The evaluation results showed that in the aquatic organism criterion layer of Lake Gehu, the biodiversity scores of phytoplankton, zooplankton, and macroinvertebrates during the wet season were 3.75, 2.88, and 3.44 points, respectively. During the dry season, the biodiversity scores were 2.94, 3.56, and 3.69 points, respectively. The biodiversity score of fish was 3.63 points. Overall, the scores of phytoplankton (C1), zooplankton (C2), macroinvertebrates (C3), and fish diversity (C4) were 3.345, 3.22, 3.565, and 3.63 points, respectively.

The small- and medium-scale habitat indicator (C5) was applied to evaluate the riparian condition. A total of 10 monitoring sites were set along the littoral zone of Lake Gehu. The scores ranged from 97 to 134, with an average value of 114.2. The evaluation grade suggested “mild disturbance”, which was converted to 3 points according to Table 2. According to the remote sensing monitoring data, the average value of riparian vegetation coverage (C6) of Lake Gehu was 42.09%, with a score of 4 points. The algal bloom area in Lake Gehu peaked in September 2022 and 2023 within the year, accounting for 39% and 20.02% of the total area, respectively (Figure 2b). The evaluation score of the algal bloom area ratio (C7) was 2.5 points. The water surface area of Lake Gehu was 160–168 km² in the 1970s, while the water surface area was 146 km² in 2020, indicating a slight shrinkage of lake area compared to the historical period. The score of the lake area shrinkage ratio (C8) was 3.5 points. The macrophyte coverage in Lake Gehu reached its annual peak value of 9.24% in September 2023, while in the historical period of September 1981, the macrophyte coverage ratio was 51.65%. Compared with 1981, macrophyte coverage decreased by 42.41% in 2023. By combining the direct scoring method and the historical data comparison method, the evaluation score of macrophyte coverage (C9) was 2 points. The spatial distributions of riparian vegetation coverage (C6) and macrophyte coverage (C9) of Lake Gehu were shown in Figure 2a.

The water quality monitoring data of Lake Gehu from 2022 to 2024 showed that DO was in Class I to II, COD_Mn was in Class II to III, and BOD₅ was in Class I except for site S6, which was in Class III. NH₃-N was in Class I to II, TP was in Class V except for a few sites classified as Class IV and inferior to Class V, and TN was distributed in Class II to inferior to Class V. According to the indicator with the worst water quality category, the score for TP was 2.13 points. The comprehensive TLI of Lake Gehu ranged from 50.49 to 63.72 during the dry season. In the wet season, it increased from 54.15 in the northeast to 62.55 in the northwest (Figure 2c), with an average value of 58, indicating a mildly eutrophic state. The average score of the comprehensive TLI across all monitoring sites was 2.63 points. The score of the water quality and trophic status index (C10) was calculated based on the lowest score of water quality and trophic state, which was 2.13 points.

The radar chart of the criterion layer and indicator layer showed the scores for the comprehensive evaluation of the water eco-environmental quality of Lake Gehu (Figure 3). In the indicator layer, macrophyte coverage had the lowest score, while water quality and algal bloom area ratio also had relatively low scores (below 3 points). Riparian vegetation coverage had the highest score, followed by fish diversity and macroinvertebrate diversity indicators. The scores of each criterion layer, including aquatic organism, habitat quality, and water quality, were 3.462, 3.017, and 2.13 points, respectively. The final score of the water eco-environmental quality index was 2.762 points, which corresponds to the evaluation grade of poor. According to the recommended weights of the criterion layers by the Ministry of Ecology and Environment, the score of the water eco-environmental quality index was 2.84 points. The evaluation result was similar to the result of this weight setting, indicating that the result obtained by the expert scoring method was reasonable.

4.2. Validation of Results

In the aquatic organism criterion layer, the evaluation score for phytoplankton diversity was the highest, followed by fish diversity, while the evaluation score for zooplankton diversity was the lowest. Previous studies on phytoplankton survey in Lake Gehu have found that the H index ranged from 2.78 to 3.29 and the J index ranged from 0.60 to 0.69 across different months, which were slightly higher than the results obtained in this study. This discrepancy may be attributed to different years and sampling sites. Overall, the central part and the northern part of the lake were more severely polluted. The main factors affecting algal bloom occurrence are water temperature and TP [41]. Therefore, the high TP concentrations in Lake Gehu may be one of the reasons for the relatively good phytoplankton diversity and the occurrence of mild algal blooms. In addition, the reduction in the number of rotifer species among the zooplankton in Lake Gehu was closely related to the decrease in submerged plant coverage and the deterioration of water quality [46]. The aquatic organism criterion layer of this indicator system has added a fish diversity index, considering that one of the main functional uses of Lake Gehu is aquaculture. The fish diversity index was scored at 3.63 points, with a good evaluation grade. Chlorophyta was the dominant phytoplankton group, followed by Bacillariophyta and Cyanobacteria. Merismopedia tranquilla was the dominant species in the lake in summer, indicating that the lake was in moderate eutrophication state, and TN rather than TP was the main influencing factor of its growth [25]. Nutrient inputs from agricultural and domestic sewage were the key driver of phytoplankton growth. Microcystis aeruginosa was another dominant species, which was commonly found in eutrophic freshwater lakes, indicating high nutrient levels and low water transparency.

The scores of water quality parameters of Lake Gehu were relatively low, with TP concentrations in most monitoring sites classified as Class V, and TP and TN concentrations in some sites classified as inferior to Class V. Xia et al. [47] investigated the distribution of macrophytes in Lake Gehu and their relationship with environmental factors, indicating that Lake Gehu was in a moderately eutrophic state. TN and BOD₅ were the primary environmental factors influencing the growth and distribution of dominant macrophytes. Gao et al. [48] found that the growth of macrophytes in the northern part of Lake Gehu can affect nutrient concentrations, hydraulic conditions, and light exposure in the water body, thereby altering the original ecological structure of phytoplankton. Areas with no macrophyte coverage have a greater variety of phytoplankton species, and are more prone to algal blooms. Former studies have shown that the TLI of Lake Gehu in 2019 was 59.9–64.5, indicating a moderately eutrophic state [27]. TN and TP concentrations in the water exceeded the standards. Therefore, it is necessary to effectively control TN and TP contents in the lake. TLI ranged from 50.49 to 63.72 in winter, and TLI ranged from 54.15 to 62.55 in summer. The average TLI of Lake Gehu in this evaluation was 58, indicating a mildly eutrophic state, which demonstrated that the eutrophication status has improved compared with that before 2020. Nutrient concentrations and TLI values were higher in the western part of the lake area than in the eastern part, due to higher elevation in the west and inflowing rivers carrying nutrients. The higher TN and TP levels in the western and northwestern areas of the lake may be due to these areas area close to urban industrial zone and receives agricultural non-point source pollution inputs. The water quality of the lake has improved in the eastern part of the lake area, suggesting that the lake plays an important role in purifying water quality. Thus, the water quality of the rivers flowing out of the lake has been improved.

In the habitat quality criterion layer, the score for riparian vegetation coverage was the highest, followed by the lake area shrinkage ratio, while the score for macrophyte coverage was the lowest. Xu et al. [22] evaluated the lake wetlands in the Taihu Lake Basin and found that Lake Gehu had a low coverage of submerged plants, a limited variety of plant species, low restoration potential, and a high degree of eutrophication. This indicates that the ecological health of Lake Gehu was significantly affected by factors such as cage aquaculture, algal blooms, and the distribution of submerged vegetation. The evaluation results of this indicator system are consistent with conclusions in former studies. It is necessary to take measures to reduce TN and TP concentrations in the lake, restore the distribution of zooplankton and macrophytes, and improve the water environmental quality of Lake Gehu.

4.3. Applicability of the Evaluation System and Management Measures

Currently, there are two types of evaluations, i.e., ecosystem health assessment and eco-environmental quality evaluation. Ecosystem health is a multi-faceted, sustainable condition where resilience, biodiversity, balance, and functional integrity coexist. An eco-environmental quality evaluation includes a comprehensive evaluation of the overall condition of a water body across environmental, biological, and habitat dimensions, with a focus on the impacts of anthropogenic activities/stressors on the aquatic system. Some applications of water eco-environmental quality/health evaluations in other areas around the world are shown in

Table 4. Applications of water eco-environmental quality/health evaluations in other areas around the world.

Study Area	Objective	Evaluation Factors	Main Findings	Source
Baiyangdian Wetland, China	Comprehensive evaluation of water eco-environment quality.	Water environment, aquatic organism, and aquatic habitat.	WEQI = 3.6, indicating good water eco-environment quality. The evaluation system can reflect the pressures and challenges and propose corresponding recommendations for promoting the conservation and restoration of its ecological environment.	[9]
Ulansuhai Lake, China	Ecosystem health assessment of the lake.	Hydrological, physical, chemical, biological, and social services aspects.	The analytic hierarchy process-Entropy weight comprehensive assignment evaluation method is reliable and practical. The ecological health assessment results across different periods align with the actual conditions of the lake.	[50]
Sansha Bay, China	Ecosystem health assessment index system for aquaculture bays.	The comprehensive disturbance index of sea use, the proportion of industrial discharge outlets, the density of total discharge outlets, and the regional environmental risk index.	Rigorous endeavors in aquatic ecology are paramount to ensure the enduring sustainability of aquaculture.	[51]
Lake Taihu Basin, China	Ecological health assessment.	Pressure indicators (e.g., socio-economic and human activity-related metrics), state indicators (physicochemical characteristics of water environment), and response indicators (aquatic organisms).	The evaluation index system can reflect the impact of socioeconomic conditions on the ecological environment of lake water bodies.	[49]
Lakes in northwestern Byelorussia	Analyze the development state of lake ecosystems.	Thermodynamic indices, such as the ratio between the entropy produced and the exergy stored by the biological component of an ecosystem.	The ratio is an appropriate indicator of ecosystem maturity.	[52]
Lake Chao, China	Lake ecosystem health assessment.	A set of comprehensive ecological indicators including structural, functional, and system-level aspects.	The direct measurement method and ecological modeling method gave similar results in terms of the lake’s actual trophic state, suggesting that the evaluation system is effective and reliable.	[53]
Erhai Lake, China	Ecosystem health assessment.	Phytoplanktonic index of biotic integrity (P-IBI).	The P-IBI based ecological health assessment system shows strong concordance with water-quality categories, and provides an accurate evaluation of the lake’s ecosystem health.	[11]
The Pearl River Estuary of China	Ecosystem health assessment.	Biotic structure, habitat structure, supporting services, provisioning services, and regulating services index.	Ecosystem health degradation manifested as significant decreases in structure/services. The assessment could improve the understanding of the mechanism of marine ecosystem change and facilitate effective restoration of ecosystem health.	[54]
Minnesota lakes	Ecological health assessment of lakes.	Macrophyte-based index of biotic integrity (IBI).	It adapts the traditional IBI framework to aquatic macrophyte communities. Macrophyte community composition strongly correlates with lake trophic status and human disturbance gradients.	[55]
Vembanad Lake, India	Assessment of ecosystem health.	Water quality parameters at micro-level.	The aquatic ecosystem studied was characterized as good, moderate, fair and poor. The results can help the policymakers to make appropriate decisions for better management.	[56]
Ganjiang River System, China	Assessment of aquatic ecosystem health.	Indices of biotic integrity (IBIs), including fish, benthic macroinvertebrate, and phytoplankton.	The comprehensive assessments based on multiple groups rather than a single group can better characterize the impacts of environmental pressures on water ecosystems.	[57]

. Similar evaluation methods and indicators have been applied to assess the water eco-environment quality of Baiyangdian Wetland [9]. Dong et al. [49] constructed an evaluation index system based on the Pressure State Response model and applied to evaluate the ecological health status of Lake Taihu Basin. Their evaluation index system chose 1999 and 2007 as the historical control years, while different historical years may influence the evaluation results. The evaluation indicators in our study are reasonable and feasibly set, with improvements in several aspects. For example, the aquatic organism criterion layer has added fish diversity, as fish is an important aquatic organism at a high trophic level in Lake Gehu. We also use habitat quality criterion layer instead of pressure indicators, while the former of which are more objective and feasible to achieve. The habitat quality criterion layer combines field surveys and remote sensing imagery data to verify with each other, making the evaluation results more scientific and accurate. Our constructed evaluation system centers on “aquatic ecosystem health” and simultaneously assesses aquatic organisms, habitat quality, and water quality, serving as an essential prerequisite for the implementation of Beautiful Rivers and Lakes Initiative. The evaluation system is applicable for the assessment of shallow lakes in the middle and lower reaches of Yangtze River Basin, due to similar characteristics and pollution status in this area. If necessary, additional indicators can be added and applied to other lakes as well.

The application of this evaluation system to Lake Gehu can comprehensively reflect the current status of the water eco-environmental conditions and the key directions for management, without the need for reference points. The radar chart of indicators showed that riparian vegetation coverage had the highest score, suggesting that restoration projects in the lakeside zone such as returning farmland to lakes have increased the density of riparian vegetation coverage. The score for macrophyte coverage was the lowest. Studies have proved that macrophytes can reduce TN and TP concentrations in lake water and inhibit the growth of harmful algae [25]. It is necessary to restore the growth of macrophytes, reduce the input of nitrogen and phosphorus loads, decrease the occurrence of algal blooms, and restore the diversity of aquatic organisms to improve the water eco-environmental quality of Lake Gehu. More ecological measures will promote lake ecosystems recovery, such as submerged vegetation restoration projects and biological manipulation. Lefcheck et al. [58] evaluated the relationship between nutrient pollution and submerged aquatic vegetation using aerial surveys spanning thirty years of data and found that the successful recovery of submerged aquatic vegetation and biodiversity conservation can lead to effective nutrient management. Biological measures, such as stocking filter-feeding fish to control algae, could effectively remove cyanobacteria cells while reducing the contribution of cyanobacteria blooms to phosphorus levels in the lake’s water column [25].

5. Conclusions

This study focuses on the prominent ecological and environmental issues of Lake Gehu, a shallow freshwater lake in the middle and lower reaches of the Yangtze River Basin, and establishes a water eco-environmental quality evaluation system for this lake. The evaluation system can be used to guide the improvement of water environmental management and to implement the construction and protection of local Beautiful Lakes Initiative. The evaluation results showed that the water eco-environmental quality grade of Lake Gehu was rated as poor. The evaluation of the eco-environmental quality of Lake Gehu aligns closely with existing research findings, thus supporting the conclusions of this evaluation. The low score of macrophyte coverage and the high score of riparian vegetation coverage indicate that measures such as farmland-to-lake conversion in recent years have increased riparian vegetation coverage. The lake area of Lake Gehu has not shown significant shrinkage, suggesting that large-scale engineering measures such as the Xinmeng River water diversion project have a crucial role in ensuring water supply. By taking ecological measures, such as the restoration of submerged vegetation, biological manipulation, and the stocking of filter-feeding fish to control algae, local communities can effectively improve the water environment of Lake Gehu. The comprehensive evaluation system is rigorous and feasible. The aquatic organism criterion layer has added a fish diversity index, and the habitat quality criterion layer combines field survey and remote sensing monitoring data, fully taking into account both historical and current situations. This evaluation system can be applied to shallow freshwater lakes in the middle and lower reaches of the Yangtze River Basin. It has good practicality and can intuitively reflect the lake’s water eco-environmental quality, management direction, and the effectiveness of management measures. In addition, the evaluation of water eco-environmental quality requires long-term follow-up. Future efforts should prioritize establishing sustained, long-term monitoring programs and conducting time-series assessments of ecosystem quality.