Abstract

Ecological effect evaluation of water diversion is a difficult and long-term process requiring complex monitoring data and scientific evaluation method. Based on remote sensing data and the ecological investigation data of Yellow River delta, this study built a wetland ecology evaluation index system with the analytic hierarchy process (AHP) framework, which included 13 evaluation indices of three criteria as suitability, diversity, and functionality. Fuzzy-AHP comprehensive evaluation method was used to evaluate the ecological effect of water diversion at Diaokou River wetland restoration zone. The results show that the comprehensive evaluation index (CEI) of wetland ecology is 0.464 before water diversion, which belongs to the ‘poor’ level, while after five years of water diversion, the CEI increased to 0.737, which belongs to the ‘fine’ level. It represents that ecological water diversion has made prominent positive effects for the ecosystem of Diaokou River wetland restoration zone. The research result could give decision-makers a clear understanding about the ecological effect of wetland water diversion and provide scientific guidance for strategic decisions.

Introduction

Wetland is one of the most important ecosystems on the planet. It has abundant biodiversity and ecological landscapes. Wetland is closely linked to human survival, reproduction, and development, it provides a wide variety of services to humanity and plays an important role in flood control, drought relief, soil erosion control, and climate regulation (Camacho-Valdez et al., 2013). With the rapid development of the social economy, wetland ecological environment has deteriorated seriously. The natural wetlands continue declining; wetland species, especially the quantity of rare waterfowl have sharply reduced. The atrophia-degeneration of wetland results in a decline in its storage capacity, which further aggravates the water crisis (Turner et al., 2000). According to a survey of the State Forest Administration of China, from 2003 to 2013, the national wetland area reduced by more than 33.3 thousand km2. Wetland ecosystem is facing serious challenges, and the eco-reconstruction and protection of wetlands have drawn ever closer attention.

Ecological effect evaluation is the qualitative and quantitative statistics and description of ecology under the influence of projects (Ma et al., 2017). The ecological effect of wetland water diversion can be reflected in various aspects, such as wetland restoration, water and soil conservation, landscape restoration, vegetation and rare aquatic animal protection. There are more than 30 indices used in wetland ecology evaluation at home and abroad, among which, diversity, naturality, suitability, and vulnerability take place with high frequency (Jacobs et al., 2010; Qin et al., 2010; Howe et al., 2015). With the development of wetland science in the 21st century, researchers attempt to establish evaluation index systems of different research directions, but a systematic evaluation index system for ecological effect evaluation of water diversion has not been established so far. Fuzzy-AHP method is a quantitative scientific evaluation method proposed by Van Laarhoven & Pedrycz (1983). It combines analytic hierarchy process (AHP) model and fuzzy method by introducing the fuzzy membership functions into the analytic hierarchy framework, and this compositive method remedied the fuzzification or ambiguity in the evaluation criteria judgment process (Kaya & Kahraman, 2011), and it is especially suitable for the ecological effect evaluation of wetland water diversion.

The Yellow River delta wetland is one of the most important wetlands in China. Since the Yellow River changed its channel to the sea from Diaokou River to Qingshuigou River in 1976, wetland at Diaokou River estuary has degenerated unceasingly due to lack of water supply. With the aggravation of soil salinity and seawater intrusion, it is hard for the ecological aspect of Diaokou River wetland to function. In order to curb degradation trends of the wetland ecosystem at the Diaokou River estuary and also guarantee Diaokou River's basic water conditions as a reserved waterway of the Yellow River, in June 2010, the Yellow River conservancy commission launched the ecological water diversion of Diaokou River wetland restoration area during the period of an annual Yellow River water and sediment regulating experiment (Dong et al., 2013). By the end of 2015, the accumulated quantity of water diversion at Diaokou River wetland reached about 153.90 million m3.

The objective of this study is to evaluate the ecological effect of water diversion at Diaokou River wetland restoration area. For this purpose, remote sensing monitoring technique and field investigation method were applied to get valid data of evaluation indices, and fuzzy-AHP method was used to analyze the effect of water diversion of the wetland ecological system. The research results could provide decision support to the ecological restoration of wetlands and regional sustainable development.

Materials and methods

Study area

The Yellow River delta wetland is located north of Dongying City, Shandong Province, the northeastern coast of the Bohai Sea, stretching between 37°35′–38°12′N and 118°33′–119°20′E. It is China's youngest and the most intact estuary wetland ecosystem of the warm temperate zone. It has unique ecological types and the estuarine region, which has developed a large area of shallow sea beaches and wetlands, makes the Yellow River delta wetland an important ‘transfer station’ and wintering grounds for the transoceanic migration of birds. In order to protect the wetland ecosystem, the Yellow River delta national nature reserve was established in 1992. It consists of two districts: the south district where the current flow path – Qingshuigou river estuary is located, and the north district where the old flow path – Diaokou River estuary is located. Diaokou River wetland restoration zone is located at the center of the north district wetland reserve, and is the main area of ecological water diversion in the Yellow River delta wetland (Figure 1).

Fig. 1.

Location of the study area.

Fig. 1.

Location of the study area.

Data sources

Remote sensing data

Two periods of remote sensing data were obtained from the United States Geological Survey (USGS), including images on June 7, 2010 from Landsat 5 ETM and June 5, 2015 from Landsat 8 ETM with 30 m resolution. Normalized difference water index (NDWI) was used to extract the water body from a remote sensing image (Figure 2) and visual interpretation methods were used to analyze the landscape pattern changes (Figure 3) using ENVI 5.3 and Arcgis 10.0 software (Behera et al., 2012; Huang et al., 2012). Simpson's landscape diversity index and patch richness was calculated by Fragstats 4.0 (Rocchini et al., 2013).

Fig. 2.

Normalized difference water index (NDWI) at Diaokou River wetland restoration zone.

Fig. 2.

Normalized difference water index (NDWI) at Diaokou River wetland restoration zone.

Fig. 3.

Landscape pattern at Diaokou River wetland restoration zone.

Fig. 3.

Landscape pattern at Diaokou River wetland restoration zone.

Ecological investigation data

In order to monitor the change of ecosystem along Diaokou River, the Yellow River Water Conservation Institution has conducted long-term monitoring work since 2010. The monitoring content involves vegetation, soil, water birds, and so on. In this study, data of 11 monitoring sites in June 2010 and June 2015 were used for ecological effect evaluation. The sampling sites are evenly distributed in the region (Figure 4). Because of the transformation of wetland landscapes, there are differences in sampling locations in the two periods. At each sampling site, the vegetation type and average height were measured in a 1 m × 1 m quadrate. Oven drying method was used to measure soil moisture, soil salinity, and soil organic matter.

Fig. 4.

Location of sampling sites in different periods.

Fig. 4.

Location of sampling sites in different periods.

Methods

Establishment of evaluation index system

The evaluation index system was established using AHP framework. The hierarchical framework includes three layers: the topmost layer is the objective of the wetland water diversion effect evaluation; the second layer is the criteria of indices; the last layer is the indices (Figure 5).

Fig. 5.

Structure of AHP framework.

Fig. 5.

Structure of AHP framework.

Based on the research fields, scientific literature, and experts' suggestions, in this study, 13 typical indices were selected under three representative criteria which were suitability, diversity, and functionality (Cvetkovic & Chow-Fraser, 2011; Klemas, 2013) (Table 1).

Table 1.

Evaluation index system for ecological effect of wetland water diversion.

Criterion Index Explanation 
B1: Suitability C1: Water area The degree to which the area of surface water is sufficient for the ordinary performance of biological functions 
C2: Surface soil moisturea The degree to which the soil water content is suitable for the growth and development of vegetation 
C3: Soil organic matter The degree to which the soil organic materials is adequate for natural vegetation 
C4: Soil bulk density The degree to which the topsoil porosity is suitable for wetland vegetation growth 
C5: Vegetation cover The percentage of the vegetation coverage of sample area 
C6: Plant community height Reflects the vegetation characteristic and distribution of wetland plant community 
B2: Diversity C7: Patch richness The amount of patch types with various vegetation growth 
C8: Landscape diversity index The diversity of landscape elements in wetland structure and function 
C9: Vegetation abundance The number of wetland vegetation species 
C10: Species diversity index The degree to which an area is significant for the variety of life forms and communities 
B3: Functionality C11: Erosion control Measured by the speed of coastal erosion in coastal wetlands 
C12: Saline soil restoration Measured by the surface soil salinity 
C13: Habitat protection Measured by the quantity of waterfowls on the basis of waterbirds' surveillance 
Criterion Index Explanation 
B1: Suitability C1: Water area The degree to which the area of surface water is sufficient for the ordinary performance of biological functions 
C2: Surface soil moisturea The degree to which the soil water content is suitable for the growth and development of vegetation 
C3: Soil organic matter The degree to which the soil organic materials is adequate for natural vegetation 
C4: Soil bulk density The degree to which the topsoil porosity is suitable for wetland vegetation growth 
C5: Vegetation cover The percentage of the vegetation coverage of sample area 
C6: Plant community height Reflects the vegetation characteristic and distribution of wetland plant community 
B2: Diversity C7: Patch richness The amount of patch types with various vegetation growth 
C8: Landscape diversity index The diversity of landscape elements in wetland structure and function 
C9: Vegetation abundance The number of wetland vegetation species 
C10: Species diversity index The degree to which an area is significant for the variety of life forms and communities 
B3: Functionality C11: Erosion control Measured by the speed of coastal erosion in coastal wetlands 
C12: Saline soil restoration Measured by the surface soil salinity 
C13: Habitat protection Measured by the quantity of waterfowls on the basis of waterbirds' surveillance 

aSurface soil moisture, soil organic matter and soil bulk density data were taken at 10 cm depth. This is because soil conditions of 10 cm depth can well reflect the ecosystem characteristics of wetland because the root depth of typical wetland communities is universally at that depth.

Weights’ determination

The pair-wise comparison was used to determine the relative weights, and experts were asked to make comparisons between each two indices using a 1–9 preference scale (Saaty & Vargas, 2012) (Table 2), and each comparison was transformed to a quantitative value (Anselin et al., 2015). According to relative importance between each two indices, a pair-wise judgment matrix was further obtained, which was organized in the form of a matrix A as follows:  
formula
(1)
aij was governed by the following rules:  
formula
(2)
Table 2.

1–9 preference scale of relative importance.

Intensity of importance Definition Explanation 
Equal importance Two indices contribute equally to objective 
Weak importance Estimates slightly favor one index over another 
Essential or strong importance Estimates strongly favor one index over another 
Intensive importance Estimates intensively favor one index over another 
Absolute importance The evidence favoring one index over another is of the highest possible order of affirmation 
2, 4, 6, 8 Intermediate values between the two adjacent judgments  
Intensity of importance Definition Explanation 
Equal importance Two indices contribute equally to objective 
Weak importance Estimates slightly favor one index over another 
Essential or strong importance Estimates strongly favor one index over another 
Intensive importance Estimates intensively favor one index over another 
Absolute importance The evidence favoring one index over another is of the highest possible order of affirmation 
2, 4, 6, 8 Intermediate values between the two adjacent judgments  

The term represents a quantified judgment on pair-wise indices, the value of was represented with 1–9 preference scale, and n represents the number of criteria or indices.

The consistency index is used to determine whether and to what extent decisions violate the transitivity rule. The values were calculated by Equation (3). Values of the random index are shown in Table 3.  
formula
(3)
where n is the order of matrix A; is the largest eigenvalue of matrix A.
Table 3.

Random index .

10 11 12 
RI 0.58 0.9 1.12 1.24 1.32 1.41 1.45 1.49 1.52 1.54 
10 11 12 
RI 0.58 0.9 1.12 1.24 1.32 1.41 1.45 1.49 1.52 1.54 
The consistency ratio is used to determine the consistency of judgmental matrix, which is defined as follows:  
formula
(4)

When < 0.10, the pair-wise comparisons have reasonable level of consistency, when ≥ 0.10, the ratio indicates inconsistent judgments.

The weights of indices were calculated with the square-root method given by Equation (5):  
formula
 
formula
(5)
 
formula
The final value indicates the relative importance of each index and is computed as follows:  
formula
(6)
where is the weight for each index of the framework, is the weight of the criteria under the topmost layer, is the weight of the Cth indices under the Bth criteria.

Determination of the evaluation criteria and rules

The criteria are assumed as:  
formula
(7)
where n is the number of ranks.

There are four ranks in the study: a, b, c, and d. Among the four ranks, a represents the best grade, following is b and c, and d means the worst grade.

The evaluation criteria employed in this study were determined according to the China Wetland System Protection and Restoration Program, overseas and domestic relevant researches (Zheng et al., 1994; Kentula et al., 2000; Kang et al., 2016) (Table 4).

Table 4.

Criteria for the ecological effect evaluation of water diversion.

Evaluation index Criteria
 
Water area a. ≥ 400 b. 100–400 c. 20–100 d. ≤ 20 
Surface soil moisture a. ≥ 30 b. 20–30 c. 10–20 d. ≤ 10 
Soil organic matter (10 cm) a. ≥ 20 b. 10–20 c. 5–10 d. ≤ 5 
Soil bulk density a. ≤ 1.15 b. 1.15–1.20 c. 1.20–1.25 d. ≥ 1.25 
Vegetation cover a. ≥ 70 b. 50–70 c. 30–50 d. ≤ 30 
Biocoenosis height a. ≥ 50 b. 30–50 c. 20–30 d. ≤ 20 
Patch richness a. ≥ 10 b. 8–10 c. 6–8 d. ≤ 6 
Landscape diversity index a. ≥ 2 b. 1.7–2 c. 1.4–1.7 d. ≤ 1.4 
Vegetation abundance a. ≥ 100 b. 60–100 c. 30–60 d. ≤ 30 
Species diversity index a. ≥ 2.4 b. 1.8–2.4 c. 1.4–1.8 d. ≤ 1.4 
Erosion control a. ≤ 0 b. 0–5 c. 5–10 d. ≥ 10 
Saline soil restoration a. ≤ 0.1% b. 0.1%–0.4% c. 0.4%–0.8% d. ≥ 0.8% 
Habitat protection a. ≥ 20,000 b. 10,000–20,000 c. 5,000–10,000 d. ≤ 50,00 
Evaluation index Criteria
 
Water area a. ≥ 400 b. 100–400 c. 20–100 d. ≤ 20 
Surface soil moisture a. ≥ 30 b. 20–30 c. 10–20 d. ≤ 10 
Soil organic matter (10 cm) a. ≥ 20 b. 10–20 c. 5–10 d. ≤ 5 
Soil bulk density a. ≤ 1.15 b. 1.15–1.20 c. 1.20–1.25 d. ≥ 1.25 
Vegetation cover a. ≥ 70 b. 50–70 c. 30–50 d. ≤ 30 
Biocoenosis height a. ≥ 50 b. 30–50 c. 20–30 d. ≤ 20 
Patch richness a. ≥ 10 b. 8–10 c. 6–8 d. ≤ 6 
Landscape diversity index a. ≥ 2 b. 1.7–2 c. 1.4–1.7 d. ≤ 1.4 
Vegetation abundance a. ≥ 100 b. 60–100 c. 30–60 d. ≤ 30 
Species diversity index a. ≥ 2.4 b. 1.8–2.4 c. 1.4–1.8 d. ≤ 1.4 
Erosion control a. ≤ 0 b. 0–5 c. 5–10 d. ≥ 10 
Saline soil restoration a. ≤ 0.1% b. 0.1%–0.4% c. 0.4%–0.8% d. ≥ 0.8% 
Habitat protection a. ≥ 20,000 b. 10,000–20,000 c. 5,000–10,000 d. ≤ 50,00 

Determination of the fuzzy relationship matrix

The fuzzy relationship matrix is expressed as:  
formula
(8)
where is the membership of the ith index belonging to the jth level.

The membership functions indicate the degree to which the indices belong to the fuzzy system (Haider et al., 2015). The membership degrees of evaluation indices at each criterion can be described quantitatively by a set of formulae as follows:

For positive indexes:  
formula
 
formula
(9)
 
formula
For negative indexes:  
formula
 
formula
(10)
 
formula

Calculation of the overall evaluation result

Combining the fuzzy membership matrix with overall weights by fuzzy arithmetic operator, a evaluation vector is obtained:  
formula
 
formula
(11)
 
formula

In Equation (11), represents the degree of membership of the four ranks in the wetland ecological evaluation.

The status of wetland ecology can be reflected by comprehensive evaluation index (CEI). It translates multiple indicators into a comprehensive index which can reflect the ecological situation of the wetland. CEI was calculated with multi-objective linear weighting function as follows:  
formula
(12)

With reference to the CEI classification standard (Liang & Ren, 2007; Zhang et al., 2011; Zhang et al., 2013; Sun et al., 2016), wetland ecological status can be divided into five grades (Table 5).

Table 5.

CEI classification standard.

CEI Ecological status 
0.85 ≤ CEI ≤ 1.00 Good 
0.7 ≤ CEI < 0.85 Fine 
0.55 ≤ CEI < 0.7 Acceptable 
0.4 ≤ CEI < 0.55 Poor 
CEI < 0.4 Bad 
CEI Ecological status 
0.85 ≤ CEI ≤ 1.00 Good 
0.7 ≤ CEI < 0.85 Fine 
0.55 ≤ CEI < 0.7 Acceptable 
0.4 ≤ CEI < 0.55 Poor 
CEI < 0.4 Bad 

Results

Weights of the indices

The overall weights of indices were calculated by Equations (1)–(6), and the results are shown in Table 6. In the ecological effect evaluation index system, water area is the most important index, whose weight is 0.219, the next is habitat protection index, whose weight is 0.170, the surface soil moisture index takes third place with a weight of 0.097, and species diversity index, vegetation cover, and saline soil restoration have similar weights, which is about 0.085. Among the 13 indices, five of them have a weight below 0.05, of which, soil organic matter index possesses the least weight.

Table 6.

Overall weight of the evaluation index.

Index B1 B2 B3 Overall weight Rank 
0.539 0.164 0.297 
C1 0.406   0.219 
C2 0.180   0.097 
C3 0.070   0.038 11 
C4 0.079   0.043 
C5 0.153   0.083 
C6 0.111   0.060 
C7  0.133  0.022 12 
C8  0.067  0.011 13 
C9  0.267  0.044 
C10  0.533  0.087 
C11   0.143 0.042 10 
C12   0.286 0.085 
C13   0.571 0.170 
Index B1 B2 B3 Overall weight Rank 
0.539 0.164 0.297 
C1 0.406   0.219 
C2 0.180   0.097 
C3 0.070   0.038 11 
C4 0.079   0.043 
C5 0.153   0.083 
C6 0.111   0.060 
C7  0.133  0.022 12 
C8  0.067  0.011 13 
C9  0.267  0.044 
C10  0.533  0.087 
C11   0.143 0.042 10 
C12   0.286 0.085 
C13   0.571 0.170 

Comprehensive evaluation results

The fuzzy relationship matrix and the CEI results are shown in Table 7. In 2010, the CEI is 0.464 and the comprehensive ecological status of Diaokou River wetland restoration zone belongs to ‘poor’ level, while in 2015, the CEI has increased to 0.737, which belongs to the ‘fine’ level. From the results of CEI of three criteria, wetland suitability, diversity, functionality belong to ‘acceptable’, ‘poor’, and ‘bad’ level, respectively, in 2010, while in 2015, the CEI of the three criteria all belong to ‘fine’ level. It means that ecological water diversion has had a positive and great impact on the ecological status of wetland. After five years of water diversion, the CEI of Diaokou River wetland restoration zone increased by 37.04%. Suitability, diversity, and functionality criteria have different degrees of improvement, and the increase rate is 24.36%, 26.09%, and 65.26%, repectively.

Table 7.

Fuzzy relationship matrix.

Criterion Index 2010 2015 
B1 C1 0.000 0.676 0.324 0.000 0.664 0.336 0.000 0.000 
C2 0.000 0.330 0.670 0.000 0.230 0.770 0.000 0.000 
C3 0.000 0.000 0.000 1.000 0.000 0.000 0.000 1.000 
C4 0.000 0.000 0.400 0.600 0.000 0.200 0.800 0.000 
C5 0.000 0.250 0.750 0.000 0.000 0.500 0.500 0.000 
C6 0.000 0.000 0.755 0.245 0.000 0.270 0.730 0.000 
CEI of B1 0.556 0.736 
B2 C7 0.000 0.500 0.500 0.000 0.500 0.500 0.000 0.000 
C8 0.000 0.233 0.767 0.000 0.067 0.933 0.000 0.000 
C9 0.000 0.000 0.000 1.000 0.000 0.400 0.600 0.000 
C10 0.000 0.650 0.350 0.000 0.033 0.967 0.000 0.000 
CEI of B2 0.541 0.732 
B3 C11 0.000 0.000 0.080 0.920 0.000 0.925 0.075 0.000 
C12 0.000 0.000 0.000 1.000 0.000 0.000 0.075 0.925 
C13 0.000 0.000 0.000 1.000 0.887 0.113 0.000 0.000 
CEI of B3 0.256 0.737 
CEI 0.464 0.737 
Criterion Index 2010 2015 
B1 C1 0.000 0.676 0.324 0.000 0.664 0.336 0.000 0.000 
C2 0.000 0.330 0.670 0.000 0.230 0.770 0.000 0.000 
C3 0.000 0.000 0.000 1.000 0.000 0.000 0.000 1.000 
C4 0.000 0.000 0.400 0.600 0.000 0.200 0.800 0.000 
C5 0.000 0.250 0.750 0.000 0.000 0.500 0.500 0.000 
C6 0.000 0.000 0.755 0.245 0.000 0.270 0.730 0.000 
CEI of B1 0.556 0.736 
B2 C7 0.000 0.500 0.500 0.000 0.500 0.500 0.000 0.000 
C8 0.000 0.233 0.767 0.000 0.067 0.933 0.000 0.000 
C9 0.000 0.000 0.000 1.000 0.000 0.400 0.600 0.000 
C10 0.000 0.650 0.350 0.000 0.033 0.967 0.000 0.000 
CEI of B2 0.541 0.732 
B3 C11 0.000 0.000 0.080 0.920 0.000 0.925 0.075 0.000 
C12 0.000 0.000 0.000 1.000 0.000 0.000 0.075 0.925 
C13 0.000 0.000 0.000 1.000 0.887 0.113 0.000 0.000 
CEI of B3 0.256 0.737 
CEI 0.464 0.737 

Discussion

Weight analysis of indices

The results of index weight are basically consistent with the actual situation of the wetland ecosystem at Diaokou River wetland restoration zone. In the criterion layer of the index system, suitability took first priority by reason of the suitability criterion reflecting the basic environmental conditions for the restoration of degraded wetland ecological environment. Among the six indices of suitability criterion, water area had the highest weight, in accordance with the situation that water is the fundamental and urgent need after long-term water shortage at Diaokou River wetland restoration zone. The functionality criterion reflects the normal exertion of specific wetland ecological functions of the study area; the display of wetland ecology function is under the premise of suitability, so it is reasonable that the functionality criterion has an inferior priority. Under functionality criterion, the habitat protection index had the highest weight. This is in line with the important position of the Yellow River delta wetland reserve as one of the most important habitats for migrating and wintering water birds in China. The weight of diversity criterion obtained the lowest priority compared with other criteria. It largely depends on the formation of species diversity which needs complicated and long-term accumulation, thus the diversity indices cannot reflect the effect of wetland water diversion in a very intuitive way.

Analysis of application of the method

Compared with other ecological evaluation methods, the fuzzy-AHP method enhances the systematicness and effectiveness of the evaluation process by combining qualitative and quantitative analysis. It overcomes the disadvantage of using a certain value to determine the class and decreases the uncertainty of the evaluation result, which was proved to be an adequate method for incorporating decision-makers' judgments into complex decision-making processes. Moreover, the application of remote sensing monitoring technique in the data acquisition process fills in the gaps in the deficiency of field survey data innovatively and enhances the veracity of the evaluation results. It was proved to be an effective way to get essential data in specific regions, and this method can be used in similar studies.

Sensitivity analysis

Sensitivity analysis is an uncertainty analysis technique. It conducts research about the degree of influence of research conclusions when a factor or some factors have a certain degree of change (Xu et al., 2004). In this study, sensitivity analysis is used to analyze how a certain change of an index influences the final evaluation result. The sensitivity coefficient was computed as follows:  
formula
(13)
where S is sensitivity coefficient; is original evaluation result; is the evaluation result after the change of a specific index value; V is the relative increment of evaluation indices. The relative increment of evaluation index value was defined as ±20% (+20% for negative indices; −20% for positive indices) on the basis of data in 2015.

Table 8 shows the sensitivity analysis results. The species diversity index takes the highest sensitive coefficient of 0.437, which means vegetation is the most important factor for the restoration of Diaokou River wetland restoration zone, as wetland ecology will degenerate distinctly in the case of vegetation coverage reduction. The next is water area index, which has the second highest sensitive coefficient of 0.429, which indicates the decrease of water area can significantly lead to the degradation of wetland. Habitat protection index has a sensitive coefficient of 0.416, and indicates that the numbers of rare waterfowl have an obvious response to the degradation of eco-environmental quality at Diaokou River wetland restoration zone. Soil bulk density and surface soil moisture have the sensitive coefficient of 0.396 and 0.382, which indicates soil degradation is also a factor that cannot be ignored.

Table 8.

Sensitivity analysis result.

Index Variation Fuzzy evaluation vector CEI Sensitivity coefficient 
C1 ± 20% 0.260 0.469 0.156 0.117 0.719 0.429 
C2 0.311 0.397 0.177 0.117 0.726 0.382 
C3 0.333 0.396 0.156 0.117 0.737 0.314 
C4 0.333 0.387 0.121 0.160 0.724 0.396 
C5 0.333 0.362 0.189 0.117 0.728 0.367 
C6 0.333 0.379 0.166 0.122 0.731 0.348 
C7 0.322 0.398 0.164 0.117 0.732 0.345 
C8 0.332 0.385 0.166 0.117 0.734 0.332 
C9 0.333 0.383 0.168 0.117 0.734 0.333 
C10 0.330 0.324 0.230 0.117 0.717 0.437 
C11 0.333 0.393 0.158 0.117 0.736 0.318 
C12 0.333 0.396 0.149 0.123 0.735 0.324 
C13 0.269 0.460 0.156 0.117 0.721 0.416 
Index Variation Fuzzy evaluation vector CEI Sensitivity coefficient 
C1 ± 20% 0.260 0.469 0.156 0.117 0.719 0.429 
C2 0.311 0.397 0.177 0.117 0.726 0.382 
C3 0.333 0.396 0.156 0.117 0.737 0.314 
C4 0.333 0.387 0.121 0.160 0.724 0.396 
C5 0.333 0.362 0.189 0.117 0.728 0.367 
C6 0.333 0.379 0.166 0.122 0.731 0.348 
C7 0.322 0.398 0.164 0.117 0.732 0.345 
C8 0.332 0.385 0.166 0.117 0.734 0.332 
C9 0.333 0.383 0.168 0.117 0.734 0.333 
C10 0.330 0.324 0.230 0.117 0.717 0.437 
C11 0.333 0.393 0.158 0.117 0.736 0.318 
C12 0.333 0.396 0.149 0.123 0.735 0.324 
C13 0.269 0.460 0.156 0.117 0.721 0.416 

Conclusion

This paper evaluates the ecological effect of water diversion at Diaokou River wetland restoration zone in the Yellow River delta wetland with remote sensing technology and fuzzy-AHP evaluation method. The results demonstrate that the CEI increased from 0.464 to 0.737 after five years of water diversion and the comprehensive ecological status has been promoted from ‘poor’ level to ‘fine’ level. Wetland water diversion has the greatest benefits on functionality criterion, diversity criterion takes second place followed by the suitability criterion. Among the indices of the evaluation system, species diversity, water area, soil bulk density, and surface soil moisture are the most sensitive indices of ecological status at Diaokou River wetland restoration zone.

This paper believes that the remote sensing technology and fuzzy-AHP evaluation method are effective ways to evaluate wetland ecological status. They remedied the lack of mensurable wetland ecological indicators and enhanced the veracity and integrity of the evaluation results, which could provide references for policy making as well as similar studies.

Acknowledgment

The authors acknowledge the National Key Research and Development Program of China (2016YFC0401401), Major Research Plan of the National Natural Science Foundation of China (91547209), the National Natural Science Foundation of People's Republic of China (51579101, 51709111, 51709112), Distinguished Young Scholar of Science and Technology Innovation (184100510014) and the Science-tech Innovation Talents in University of Henan Province (15HASTIT044). The authors would like to express their sincere gratitude to the anonymous reviewers for their constructive comments and useful suggestions that helped us improve our paper.

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