Evaluation of ecological restoration effectiveness of Zoige grassland wetland in the upper reaches of the Yellow River

doi:10.21203/rs.3.rs-4942852/v1

In order to scientifically demonstrate the progress and effectiveness of ecological restoration in the Zoige grassland wetland, and to guide the standardized implementation, supervision, and management of ecological restoration projects in local or similar areas, this study selected multi-source remote sensing data from 2021 before ecological restoration and governance, and from 2023 during ecological restoration and governance. This enabled the accurate acquisition of the status quo and change information of ecological restoration, and the scientific construction of a monitoring index system and effectiveness evaluation model. The study focused on monitoring and evaluating the stage restoration effect, yielding the following results: (1) Utilizing multi-source remote sensing techniques including high-resolution satellite imagery, multi-spectral remote sensing, and 3D modeling, a scientifically constructed monitoring index system and evaluation model comprehensively, accurately, and chronologically obtained progress and effectiveness information of ecological restoration projects. (2) The area with a significant and good ecological restoration and management effect accounted for 9%, mainly located in the Heihe River basin, Hongyuan County, Baihe River basin, and Dadu River basin of Aba County. These areas showed significant improvements in water conservation, vegetation coverage, and a reduction in ecological and environmental problems such as land desertification and soil erosion. (3) The Zoige grassland wetland ecological restoration project has not been fully completed. The next steps include continuing to optimize the monitoring index system and evaluation model, and conducting further monitoring and evaluation research on the effectiveness of ecological restoration.

Caving

High resolution optical images

Stacking InSAR

Sentinel-1

Ecological restoration

The Ruoergai grassland wetland, located in the upper reaches of the Yellow River, is an important area for water conservation and recharge, designated as a national important wetland ecological function area. It holds a crucial strategic position in the ecological security of the Yellow River basin (Liu et al., 2023). To promote ecological protection and high-quality development in the Yellow River Basin, the state initiated the "Zoige Landscape Project" in 2022, encompassing comprehensive protection and restoration measures for mountains, water bodies, forests, farmlands, lakes, grasslands, sand areas, and glaciers in the Upper Yellow River region of Sichuan Province. By 2023, the project had fully commenced implementation. Monitoring the project's construction progress and restoration effects according to the planned schedule is a significant challenge for the management authorities. Consequently, technical research units and scholars have focused on methods to monitor the project's progress in real-time and assess the restoration effects, as well as later management and protection status (Yang et al., 2020, Zhen, 2020).

In recent years, both domestic and international research efforts have focused on monitoring, early warning systems, and effectiveness evaluations of ecological restoration projects. These studies have utilized various technical methods such as satellite remote sensing, UAV measurements, test analysis, modeling, and estimation (Roy et al., 2014, Liu et al., 2020, Wang, He, 2021, Xu, 2008). Significant progress has been made in constructing ecological security index systems (Mengyu et al., 2023, Yu et al., 2018), monitoring and early warning systems for ecological security (Li et al., 2023), enhancing ecosystem service functions (MEA, 2005, Ni et al., 2024), assessing social benefits of ecological restoration (Zhou et al., 2020, Zhang et al., 2024(b)), and estimating ecological values (Sloat et al., 2018, Xian, 2015, GOSCPRC, 2016, Guo et al., 2021, Ahirwal, Maiti, 2018). However, the lack of systematic monitoring indicators and unified estimation models has resulted in poor comparability of evaluation results across different regions. This issue is particularly pronounced in the monitoring and evaluation of ecological restoration in alpine grassland wet areas in the upper reaches of the Yellow River. Consequently, there is a significant challenge in meeting the rapid assessment needs for ecosystem restoration effectiveness in specific regions.

This paper utilizes high-resolution satellite imagery, multispectral remote sensing, 3D modeling, and other multi-source remote sensing technologies to accurately acquire ecological restoration information and data. It then scientifically constructs a monitoring index system and an effectiveness assessment model, taking into account relevant industry technical specifications and the specific characteristics of the Zoige landscape restoration and management. The study focuses on assessing the effectiveness of the restoration of the Zoige grassland wetland. The research results include estimated data on the improvement in ecological restoration effectiveness, an analysis of the differences in restoration effectiveness among different restoration units, subprojects, and governance measures. Finally, the paper proposes future research directions and application services based on these findings.

1.1 General Situation

The study area of this research is defined by the implementation scope of the Zoige Landscape Project, primarily located in the upper reaches of the Yellow River in Sichuan Province. It includes the administrative regions of four counties: Zoige, Aba, Hongyuan, and Songpan, all part of the Aba Tibetan and Qiang Autonomous Prefecture within the Yellow River basin. The geographical coordinates range from east longitude 101°06'57"-104°15'14" and north latitude 31°51'57"-34°18'50", covering a land area of approximately 37,000 km2. Situated at the eastern edge of the Qinghai-Tibet Plateau, this region is close to the water division between the Yellow River and the Yangtze River. It belongs to a relatively independent fault basin on the plateau, surrounded by Dibu Mountain, Minshan Mountain, Qionglai Mountain, Bayankera Mountain Gorge, and Anyimachen Mountain, which form the peripelvic marginal mountains (Wang et al., 2022).

The research area is situated within the ecological barrier area of the Qinghai-Tibet Plateau, designated as part of the "three zones and four zones" in the Master Plan of Major Projects for the Protection and Restoration of National Important Ecosystems (2021–2035). Specifically, it is identified as the "Key Project for the ecological protection and restoration of water conservation of the Zoige Grassland Wetland" under the dual planning of the state.

The Zoige Landscape Project has established 132 sub-projects across 6 major restoration units (Fig. 1). These sub-projects primarily focus on grassland ecological restoration, wetland ecological restoration, forest ecological restoration, grassland rat control, mine geological control, sandy land control, soil erosion control, and water ecological protection and management.

1.2 Data source

1.2.1 Basic data source

Basic data on the natural ecological environment, including natural resources, rainfall, temperature, surface runoff, evaporation, soil conditions, landform, and geological structure, were collected for the study area. Additionally, relevant business data such as the implementation plan for the Ruoergai Landscape Engineering, restoration and management design of sub-projects, and sampling and testing analysis of project areas were also gathered.

1.2.2 Remote sensing data source

Multi-source remote sensing data were acquired to achieve regional 3D remote sensing monitoring objectives. To address the monitoring requirements for changes in restored land within the Ruoergai Mountain Water project area, high-resolution satellite remote sensing image data from similar time periods in 2021 (pre-restoration) and 2023 (post-restoration) were obtained (refer to Fig. 2). These data mainly included satellite data types such as Yuyuan No. 3, Gaofen No. 1, Gaofen No. 2, Gaofen No. 6, and Gaofen No. 7. Additionally, Landsat satellite images from similar time periods in 2021 and 2023 were acquired to meet the needs for estimating ecological and environmental restoration index information. UAV photogrammetry data from 2023 for typical treatment projects were also obtained.

This study takes 132 sub-projects in 10 categories of the Ruoergai Mountain Water Project as monitoring objects, and on the basis of fully collecting basic data such as ecological environment background, natural resources background, ecological restoration and protection in the research area, A complete set of technical and methodological processes such as data collection, monitoring index system, ecological restoration information extraction, field verification, data collection, and comprehensive assessment were established (Fig. 3).

2.1 Construction of monitoring and evaluation system

2.1.1 Monitoring index system

Within the scope of natural resource management responsibility, the Zoige Landscape Project's ecological restoration objectives, tasks, sub-project management measures, and performance target assessments were studied in detail. This was done by referencing natural resource management, ecological environmental protection, soil and water conservation, and other related industry technical specifications. The study also incorporated new technologies and methods such as ecological value assessment, ecological carbon sink analysis, and ecological function improvement. Comprehensive data collection, field verification, and the utilization of multi-source remote sensing (Luo et al., 2019, Liang et al., 2023) were employed as technical means. To enhance the accessibility of ecological protection and restoration information, a monitoring index system was developed for estimating the restoration effectiveness of the Zoige Landscape Project. This system was created through comprehensive analysis and expert discussions. As illustrated in Table 1, the monitoring index system consists of three primary indexes (improvement of ecosystem type, optimization of landscape pattern, and enhancement of ecological function) and 12 secondary indexes (related to the improvement of ecological function).

Table 1

Monitoring indicator system
Serial number	Primary index	Secondary index	Data acquisition mode	Index score
1	Ecosystem type improvement	Evaluate the increase in the area of forest, scrubland, grassland, wetland, farmland (non-ecological land conversion), and other ecosystems in the area.	Remote sensing	15
2	Landscape pattern optimization	Landscape connectivity evaluation model information	Remote sensing; Verify	5
3		Landscape fragmentation evaluation model information	Remote sensing; Verify	5
4		Landscape diversity assessment model information	Remote sensing; Estimate	5
5	Ecological function enhancement	Vegetation coverage evaluation model information	Remote sensing; Verify	10
8		Biological abundance evaluation model information	Remote sensing	10
6		Water network density evaluation model information	Remote sensing	5
7		Water conservation evaluation model information	Comprehensive calculation	10
9		Soil conservation evaluation model information	Comprehensive calculation	10
10		Information of evaluation model for windbreak and sand fixation	Comprehensive calculation	10
11		Net initial productivity estimation model information	Comprehensive calculation	10
12		Ecological carbon sequestration evaluation model information	Comprehensive calculation	5

2.1.2 Comprehensive evaluation method

In accordance with the assessment criteria for ecological restoration projects, necessary information and data are collected through methods such as data collection, 3D measurement of the actual scene, identification of remote sensing information, estimation, and analysis. Each indicator is assigned and calculated based on a kilometer grid as the benchmark, following specific rules for assigning monitoring indicators. These calculations result in the estimation results.

Based on the evaluation scores of various indicators, the project restoration effectiveness index is calculated according to the following formula:

$$\:{S}_{T}=\sum\:_{i=1}^{n}{S}_{i}$$

$\:{S}_{T}$ —— Evaluation index of restoration effectiveness of ecological governance projects;

$\:{S}_{i}$ —— Score of item i;

$\:i$ ——Index serial number;

$\:n$ ——The number of indicators;

According to the calculation results of the ecological governance project restoration effectiveness evaluation index, the effectiveness improvement level is determined, as shown in the following table:

Table 2

Ecological restoration effectiveness improvement evaluation grading table
Index score range	Effectiveness evaluation grading
90≤$\:{S}_{T}$≤100	Remarkable
80≤$\:{S}_{T}$<90%	Preferably
60≤$\:{S}_{T}$<80%	Normal
$\:{S}_{T}$<60%	Weaker

2.3 Ecological restoration information acquisition

2.3.1 Management engineering information extraction

Using high-resolution remote sensing images from 2023 after ecological restoration and 2021 before ecological restoration, ArcGIS software was employed as the primary platform for identifying and extracting ecological restoration information. This was done through analogy, literal translation, exclusion, and prediction methods. Reference was made to relevant technical standards such as the "Guidelines for Ecological Protection and Restoration Projects of Mountains, Rivers, Forests, Fields, Lakes, and Grasslands" (MEE PRC, 2020), "Technical Specifications for Remote Sensing Monitoring of Mine Environment" (MNR PRC, 2022), and "Technical Requirements for Ecological Geological Survey (1:50,000)" (Ni et al., 2024).The study focused on identifying and extracting information such as changes in land type area, scope, and measures generated by restoration projects within the region. This approach aimed to capture improvement data of the ecosystem following the implementation of regional restoration and management projects.。

2.3.2 Ecological environment state information estimation

Based on collected data on land cover, biological species, and other relevant information, and in conjunction with remote sensing data extraction, the study referenced technical guidelines such as the "Technical Guidelines for the Assessment of Ecological Protection and Restoration Effectiveness" (MEE PRC, 2022), "Technical Specifications for the National Ecological Status Investigation and Assessment" (MEE PRC, 2021), and "Technical Specifications for the Assessment of Ecological Environment Status" (MEE PRC, 2015). The aim was to obtain estimation information regarding the improvement of landscape pattern function, enhancement of ecological function, and mitigation of ecological stress.

2.4 Analysis of typical ecological engineering

Selecting typical ecological restoration and management sub-projects, the study employed UAV tilt photography to construct a 3D model of the actual scene. This model was then verified and analyzed on-site to achieve a precise 3D measurement of key landscape engineering projects. This measurement included parameters such as height, length, area, angle, slope, quantity, material, and type, providing comprehensive spatial information. This approach allowed for an intuitive understanding of the current status and changes in ecological restoration projects, enabling the correction and supplementation of global ecological restoration information. Figure 4 illustrates the analysis of the implementation progress and effectiveness of ecological restoration in the Yellow River Emergency Bend project and the sandy land management sub-project under the Zoige Mountain Water Project. Through 3D remote sensing and comparison monitoring of the actual scene, information regarding the restored land area, type, measures, specifications, and vegetation growth state was effectively captured. These findings serve as typical examples for similar sub-projects and contribute to the enhancement and supplementation of global ecological restoration information data.。

3.1 Ecological type improvement

Based on the remote sensing monitoring data of the area evolution of forest land, grassland, cultivated land, wetland and other ecosystems within the scope of the implementation of the Ruoergai Mountain water Project, a single monitoring and evaluation model was introduced to estimate the area growth efficiency assessment results of important ecosystems (Fig. 5a).

3.2 Landscape pattern optimization

The optimization, monitoring and evaluation of landscape pattern of ecological restoration projects (Wu, 2000) was carried out with reference to the Technical Guide for Assessment of Ecological Protection and Restoration Effectiveness.

3.2.1 Landscape connectivity

The landscape pattern reflects the extent of human influence on the landscape to a certain degree (Wan et al., 2015). Using multi-source remote sensing identification information and referring to monitoring and evaluation data from ecological environment departments, natural resources departments, implementing units, or evaluation units, Conefor software was employed for calculation. Scores were assigned based on the improvement in the overall connectivity degree of the ecosystem within the evaluation range. The evaluation results are illustrated in Fig. 5b.

3.2.2 Landscape fragmentation

It represents the fragmentation degree of landscape segmentation and reflects the degree of human disturbance to the landscape to a certain extent (Wang, 2011). Scores are assigned based on the improvement in the overall fragmentation degree of the ecosystem within the assessment range, and the assessment results are shown in Fig. 6a.

3.2.3 Landscape diversity

The Simpson's landscape diversity index (SHDI) can effectively reflect landscape heterogeneity and is particularly sensitive to the unbalanced distribution of various patch types within the landscape. Furthermore, in a landscape system, the greater the diversity of land use, the higher the degree of fragmentation, and consequently, the higher the SHDI value (Zhang et al., 2020). The evaluation results are illustrated in Fig. 6b.

3.3 Ecological function enhancement

Based on the natural ecological background and the goals and tasks of the Zoige Mountain Water Project, and with reference to the existing monitoring and evaluation system, key ecological function improvement indicators were identified. These include vegetation coverage, biological abundance, water network density, water source conservation, soil conservation, wind prevention and sand fixation, ecological carbon sequestration, and net primary productivity.The monitoring and evaluation of these indicators are conducted in accordance with the "Technical Specifications for National Ecological Status Investigation and Evaluation" and "Technical Specifications for Ecological Environment Status Evaluation".

3.3.1 Vegetation coverage and biological abundance increased

Improvement in Vegetation Coverage: The evaluation assessed the degree of improvement in vegetation coverage within the region resulting from the implementation of the restoration project (Zhang et al., 2024(a)). This was quantified using the estimated change value of the Normalized Difference Vegetation Index (NDVI) per unit area in the evaluation area. The evaluation results are presented in Fig. 7a.。

Increase in Biological Abundance: The evaluation assessed the degree of increase in biological abundance and diversity in the restoration project area, expressed using the Biodiversity Change Index (Zhang, 2023). The evaluation results are presented in Fig. 7b.

3.3.2 The density of water network and water source conservation are improved

Water Network Density Improvement: The evaluation utilized current status and change data regarding water area range, length, and water resource volume per unit area (Liu et al., 2010) to analyze and estimate the regional improvement in water network density. The evaluation results are depicted in Fig. 8a.

Water Conservation Improvement: Focusing on the critical goal of enhancing water conservation in the upper reaches of the Yellow River, this study comprehensively estimated ecosystem area, quality, water resources, and climate (Lin et al., 2020). This analysis aimed to determine the increase in available water resources within the restoration and treatment project area. The assessment results are presented in Fig. 8b.

3.3.3 Soil conservation, windbreak and sand fixation capacity improved

Improvement in Soil Conservation Ability: The enhancement of soil conservation ability, including the reduction of rainwater erosion and soil loss, as well as the prevention of sediment accumulation through ecosystem protection and treatment measures, was calculated using the modified Revised Universal Soil Loss Equation (RUSLE) (Yue et al., 2023). The evaluation results are presented in Fig. 9a.

Improvement in Windproof and Sand-fixing Ability: The restoration and treatment projects aimed to increase the soil's resistance to wind and reduce wind erosion and sand damage. The Revised Wind Erosion Equation (RWEQ) model (Huang et al., 2022) was utilized for budget prediction. The evaluation results are shown in Fig. 9b.

3.3.4 Net primary productivity and ecological carbon sequestration were improved

Increase in Net Primary Productivity: This refers to the amount of organic matter accumulated per unit area per unit time by green vegetation after deducting its own respiratory consumption. The classical Carnegie-Ames-Stanford Approach (CASA) model (Yuan et al., 2022) was adopted for prediction and estimation based on remote sensing monitoring and collected data. The evaluation results are presented in Fig. 10a.

Improvement in Ecological Carbon Sequestration: Carbon sequestration serves as an evaluation index of ecosystem carbon sequestration function, obtained by subtracting soil respiration (RS) consumption from net primary productivity (NPP). The evaluation results are depicted in Fig. 10b.。

3.4 Evaluation results and analysis

Based on the estimated monitoring index values of the Zoige Mountain Water Project and utilizing the comprehensive assessment method model calculations, the evaluation results of ecological restoration effectiveness were derived, as illustrated in Fig. 11. By 2023, the area demonstrating a significant ecological restoration effect will constitute 1.21% of the total study area. These areas are predominantly located in the grassland and wetland ecological protection and restoration unit of the Heihe River Basin in Ruoergai County, as well as the land comprehensive regulation and forest ecological protection and restoration unit of the Bailong River basin. These areas are mainly within the management scope of sub-projects such as water conservation improvement comprehensive management, wetland protection improvement, desertification land management, and rat wasteland comprehensive management. These efforts have notably enhanced regional water conservation and vegetation coverage while reducing ecological and environmental issues such as land desertification and soil erosion.Areas exhibiting a good ecological restoration effect account for 7.79% of the total study area. These areas are mainly distributed in the water conservation and grassland ecological protection and restoration unit of the Baihe River basin in Hongyuan County and the Dadu River basin in Aba County. They are mostly within the management scope of sub-projects such as grassland ecological protection, historical mine ecological restoration, small watershed comprehensive management, and grassland ecological carbon sink. These efforts have significantly improved vegetation coverage rates and mitigated trends of soil erosion and grassland degradation.The general ecological restoration effect area encompasses 36.82% of the total study area. These areas are primarily distributed in the forest grassland and water ecological protection and restoration unit of the Minjiang River basin in Songpan County and the water source conservation and grassland ecological protection and restoration unit of the Baihe River basin. They are mostly within the management scope of sub-projects such as forest protection and protection, grassland sealing and protection, and ecological river embankment construction. However, the restoration methods of forest protection and grassland sealing and protection sub-projects are relatively straightforward, and the restoration effects have not been significant. Regarding the subproject of ecological embankment construction, conventional embankment engineering measures are primarily adopted. Although this approach eliminates the problem of embankment erosion, the overall ecological improvement effect is moderate.The area with weak ecological restoration effect encompasses 54.17% of the total study area. These areas are mainly located outside the scope of the ecological restoration and governance sub-project area and have not directly produced ecological environment improvement effects at present.

Building upon an exploration of regional natural environmental conditions and the characteristics of the restoration project, this study identified the improvement of ecosystem type, optimization of landscape pattern, and enhancement of ecological functions as the primary monitoring and evaluation objectives. Subsequently, a monitoring index system was established, and the monitoring and evaluation model were optimized to quantitatively assess the phased ecological restoration effectiveness of the Zoige Landscape Project. The main conclusions are as follows:

1༉ Based on a comprehensive collection of natural environment data and related business data, and utilizing multi-source remote sensing technologies such as high-resolution satellite imagery, multispectral remote sensing, and three-dimensional modeling, this study accurately obtained data on the area, type, measures, specifications, and ecological parameters estimation of ecological restoration projects. These findings can provide detailed and robust basic data for monitoring the implementation progress of ecological restoration projects, identifying performance targets, and evaluating restoration effectiveness.

2༉ Based on a comprehensive analysis of the ecological restoration objectives, tasks, governance measures, and performance objectives of the Zoige Landscape Project, and with reference to relevant industry technical specifications, this study investigated and developed the main monitoring and evaluation indicators. These indicators focus on the improvement of ecosystem type, optimization of landscape pattern, and enhancement of ecological functions. Additionally, 12 secondary support monitoring indicators were established. The study scientifically and reasonably assigned weight scores to these indicators and constructed a threshold summation evaluation model. This model accurately evaluates the effectiveness of ecological restoration improvement in different areas within the scope of the Zoige Mountain Water Project.

3༉ Based on a comprehensive analysis of the monitoring and evaluation results, as of 2023, the area exhibiting significant and favorable ecological restoration effects from the Zoige Landscape Project accounts for 9%. These areas are primarily located in the Heihe River basin of Zoige County, the Baihe River basin of Hongyuan County, and the Dadu River basin of Aba County. They are mainly situated in the upper reaches of the Yellow River, focusing on comprehensive management for water conservation improvement, wetland protection enhancement, desertification land management, historical mine ecological restoration, and other sub-projects.These efforts have notably enhanced regional water conservation, increased vegetation coverage, and reduced land desertification, soil erosion, and grassland degradation. However, for sub-projects related to forest protection and grassland conservation, the restoration methods are relatively straightforward, and the restoration effects have not been significantly demonstrated. Similarly, the subproject involving ecological embankment construction primarily utilizes conventional embankment engineering measures. Although this approach addresses embankment erosion issues, the overall ecological improvement effect is less pronounced.

4༉ The Zoige Landscape Project is scheduled to be implemented from 2022 to 2024. According to public reports from relevant departments, as of October 2023, the completion rate of the landscape project stands at 84%. However, some ecological restoration subprojects have not yet been completed. Given that improvements in ecological indicators such as vegetation growth, soil restoration, and water conservation are gradual processes, the governance goals outlined in the implementation plan have not yet been fully achieved.Therefore, based on this study, there is a need to further optimize and enhance ecological information identification and estimation methods. This includes the development of a more scientifically sound monitoring indicator system and evaluation model. These efforts are crucial for continuing to assess and study the progress and effectiveness of ecological restoration and governance. Additionally, this will provide technical support for the national project's performance evaluation, effectiveness analysis, method model summary, and case demonstration and promotion.。

CRediT authorship contribution statement

YANG Xianhua: Writing-review & editing, Writing - original draft, Validation, Methodology, Investigation, Formal analysis, Data curation, E-mail: [email protected].

WEN hui: Supervision, Validation, Methodology, Resources, Project administration, Funding acquisition, Conceptualization, E-mail: [email protected].

ZHANG lv: Supervision, Validation, Methodology, Resources, Project administration, Funding acquisition, Conceptualization, E-mail: [email protected].

WANG yu: Validation, Software, Resources, Cartography, E-mail: [email protected].

HAN rubing: Cartography, E-mail: [email protected].

ZHANG mengyao: Cartography, E-mail: [email protected].

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data availability

The authors do not have permission to share data.

Funding Declaration

The authors gratefully acknowledge the financial supports by the Sichuan Provincial Natural Science Foundation Project(Project No.: 2022NSFSC0184), as well as theResearch Project of Sichuan Geological Survey and Research Institute( Project No.: SCIGS-CZDXM-2024014).

Ethical Approval (applicable for both human and/ or animal studies. Ethical committees, Internal Review Boards and guidelines followed must be named. When applicable, additional headings with statements on consent to participate and consent to publish are also required)

These declarations listed are not relevant to the content of my submission, this declaration is “not applicable”.

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No competing interests reported.

Evaluation of ecological restoration effectiveness of Zoige grassland wetland in the upper reaches of the Yellow River

Status:

Version 1

Abstract

Figures

0 Introduction

1 Study area overview and data acquisition

2 Research method

3 Monitoring and evaluation results

4 Conclusion

Declarations

References

Additional Declarations

Status:

Version 1

Index score range	Effectiveness evaluation grading
90≤\(\:{S}_{T}\)≤100	Remarkable
80≤\(\:{S}_{T}\)<90%	Preferably
60≤\(\:{S}_{T}\)<80%	Normal
\(\:{S}_{T}\)<60%	Weaker