Abstract
The model was used to predict and analyze the future changes in the total ecological water demand of the Panjin wetland, with a view to providing some scientific reference for the optimal allocation of regional water resources and the sustainable development of wetlands. The results showed that (1) the quality of the habitat environment in the Panjin wetland has a great influence on the change of the total water demand, and the total ecological water demand in the Panjin wetland will continue to decrease in the future. (2) There is a clear correlation between landscape pattern and ecological water demand. (3) The distribution characteristics of the landscape pattern are greatly influenced by political factors, thus affecting the total ecological water demand of the Panjin wetland.
HIGHLIGHTS
The landscape pattern changes in the Panjin wetland from 1989 to 2017 were investigated.
The ecological water demand of the Panjin wetland was calculated.
The important factor affecting the ecological water demand security of the Panjin wetland was habitat quality.
The ecological water demand of the Panjin wetland was predicted and assessed to provide a basis for scientific wetland management.
Graphical Abstract
INTRODUCTION
For a long time, research on water supply, demand, and allocation has considered only the water needs of artificial ecosystems, ignoring the water needs of natural ecosystems, emphasizing only the water needs of production and life, and neglecting the water needs of the ecosystem itself, resulting in ecological imbalance and environmental degradation, and limiting sustainable socio-economic development. Located at the interface between land and sea, estuarine wetlands have a unique ecological structure and environmental characteristics, rich in biodiversity, sensitive to external disturbance and relatively fragile ecosystems (Mulamoottil et al. 1997; Keddy 2000). In recent years, with the development of aquaculture and accelerated urbanization, human activities have increasingly disturbed estuarine wetlands, causing serious water pollution and water scarcity problems in estuarine wetlands. As the problem of water pollution in wetlands intensifies, there is a growing concern about the ecological water security of estuarine wetlands (Finlayson et al. 2013; Zhang et al. 2017; Shamshirband et al. 2019). The ecological water demand of wetlands refers to the basic amount of water needed for wetlands to maintain their own development and ensure the performance of basic ecological functions, and a healthy wetland ecosystem requires an adequate amount of water to maintain (Zhao et al. 2015). Studying the ecological water demand of wetlands can make effective use of limited water resources, maximize the regulating effect of wetlands on the ecological environment, and achieve the synergistic development of ecological protection and economic construction.
Research on the wetland ecological water demand started in the 1990s, but the concept and calculation methods of the wetland ecological water demand are very different from those of riverine and terrestrial systems, and no unified standard has yet been developed (Zhang et al. 2019, 2021). The ecological water requirements of wetlands have been studied and estimated by various scientists. Common models used in the ecological water demand estimation process include mathematical models, water balance models, gray correlation models, and linear regression models (Gleick 1998, 2000; Schuluter et al. 2005; Palmer & Bernhardt 2006; Shokoohi & Amini 2014; Sajedipour et al. 2017). As scientists have used different models to study the water demand of wetland ecosystems for their own research purposes and perspectives, this may lead to differences in estimation results (Horne et al. 2017; Zhao 2020; Bayesteh & Azari 2021). Ecological, ecohydrological, and remote sensing-based simulation methods are commonly used to estimate ecological water demand (Shokoohi & Hong 2011; Kral et al. 2012; Agboola et al. 2016; Ehteram et al. 2018; Sharafati & Pezeshki 2020; Goorani & Shabanlou 2021). Different methods have their own advantages and disadvantages and should therefore be selected according to the actual situation in the study area. The ecological method is widely used and has good adaptability, but has the disadvantage of repeated calculations. The ecohydrological method requires high topographic data, has a limited scope and is more suitable for wetlands where the surface water level can be easily controlled. The remote sensing-based simulation analysis method has the advantages of high accuracy, real time, and wide monitoring area, and is more suitable for wetland ecological water demand calculation. With the development of RS and GIS technology, this method will be of greater value. Although some research has been conducted on ecological water demand in wetlands, the literature on ecological water demand in estuarine wetlands is less well documented. Balancing different ecological water demand objectives in estuarine wetlands and providing appropriate ecological water demand and flow processes is important to improve wetland habitat conditions, ameliorate water scarcity, and maintain biodiversity (Dong et al. 2011; Pan et al. 2015; Mao et al. 2016).
The Panjin wetland is an important part of the Liaohe Delta, and has important scientific research value and economic value. An increasing number of scholars have paid attention to this wetland and have conducted in-depth research. The research results included the spatial and temporal monitoring of wetland (Wu & Zhang 2017; Zhou et al. 2021), evaluation of ecological suitability of wetland (Dong et al. 2014; Cheng & Zhou 2018), analysis of wetland landscape pattern evolution (Song et al. 2016), wetland ecological functions, and wetland ecological environment (Wang & Wei 2012). The above research provides a rich scientific basis for the conservation, restoration, and planning of the Panjin wetland. However, no studies have been conducted to assess the ecological water security of the Panjin wetland. It is hoped that the results of this study will enrich the Panjin wetland in the field of wetland water demand research.
The Panjin wetland is the largest estuarine wetland in China and plays an important role in climate regulation, optimal water resource management, and biodiversity conservation. In recent years, due to the increasing disturbance of human activities, the fragmentation trend of the Panjin wetland landscape pattern is obvious, and the water quality is deteriorating, posing a threat to regional water resources and water security. In order to protect wetland resources scientifically and effectively, ecological balance should be maintained and regional water resources should be allocated rationally, this study takes the Panjin wetland as the research object, takes 3S technology as the basis, combines landscape status, precipitation and evaporation and other basic data, and divides its ecological environment water demand into two parts: consumptive ecological environment water demand and non-consumptive ecological environment water demand.
MATERIALS AND METHODS
Study area
Data source and pre-processing
Landscape data
Year . | Reed . | Beach . | River . | Paddy land . | Dry land . | Residential land . | Farming pond . | Total . |
---|---|---|---|---|---|---|---|---|
1989 | 884.86 | 213.11 | 244.00 | 1,536.86 | 424.89 | 336.31 | 280.51 | 3,920.55 |
1999 | 830.31 | 154.14 | 275.42 | 1,620.18 | 319.65 | 413.21 | 307.64 | |
2009 | 842.50 | 200.83 | 152.19 | 1,699.94 | 259.58 | 462.52 | 302.99 | |
2017 | 684.77 | 152.76 | 116.88 | 1,784.64 | 359.03 | 540.78 | 281.69 |
Year . | Reed . | Beach . | River . | Paddy land . | Dry land . | Residential land . | Farming pond . | Total . |
---|---|---|---|---|---|---|---|---|
1989 | 884.86 | 213.11 | 244.00 | 1,536.86 | 424.89 | 336.31 | 280.51 | 3,920.55 |
1999 | 830.31 | 154.14 | 275.42 | 1,620.18 | 319.65 | 413.21 | 307.64 | |
2009 | 842.50 | 200.83 | 152.19 | 1,699.94 | 259.58 | 462.52 | 302.99 | |
2017 | 684.77 | 152.76 | 116.88 | 1,784.64 | 359.03 | 540.78 | 281.69 |
Precipitation
The hydrological data used in this study include precipitation, surface evaporation, local reed in Panjin wetland, and evaporation from paddy land (Hughes 2001; Tubiello et al. 2015). The precipitation data of the site were obtained from the observations of Antun and Wanghuiwobao stations between 1985 and 2017. The surface evapotranspiration was obtained from the observations of Jinzhou station between 1985 and 2017. The average annual evapotranspiration of the wetland was 1,086.63 mm, and the average annual precipitation was 623.90 mm (the high precipitation period was more concentrated in summer), and the evapotranspiration was 1.7 times the precipitation. The precipitation is less than evapotranspiration, which is the more obvious characteristic of the Panjin wetland. The evapotranspiration of paddy is 650 mm from April to September, and the evapotranspiration of reed is 700 mm from April to September, as shown in Table 2.
Month . | 4 . | 5 . | 6 . | 7 . | 8 . | 9 . |
---|---|---|---|---|---|---|
Paddy land | 55.99 | 86.3 | 116.43 | 164.79 | 141.37 | 85.12 |
Reed | 60.3 | 92.94 | 125.39 | 177.46 | 152.24 | 91.67 |
Month . | 4 . | 5 . | 6 . | 7 . | 8 . | 9 . |
---|---|---|---|---|---|---|
Paddy land | 55.99 | 86.3 | 116.43 | 164.79 | 141.37 | 85.12 |
Reed | 60.3 | 92.94 | 125.39 | 177.46 | 152.24 | 91.67 |
Landscape fragmentation model
In order to more clearly analyze the changes in landscape pattern characteristics and the degree of disturbance from the outside world in the Panjin wetland during 1989–2017, PD (Patch density index), S (Landscape separation index), and SHDI (Shannon's diversity index) were selected for the study of landscape fragmentation in the Panjin wetland in this study (Zhao et al. 2014; Dong et al. 2015).
Patch density index
Landscape separation index
Shannon's diversity index
Ecological water demand calculation model
Dry land and residential land in the study area are mainly distributed in the test area, which are damages caused by human activities to the wetland and are not included in the calculation of ecological environment water demand. In this study, the ecological environmental water demand is divided into two parts: consumptive ecological environmental water demand and non-consumptive ecological environmental water demand. Consumptive ecological environmental water demand refers to the water consumed by the wetland, including evaporation from the water surface, plant evaporation, and seepage. Non-consumptive ecological environment water demand refers to the surface water storage to maintain the ecological balance and its normal function, including soil water demand and biological habitat water demand, the integration of the above five parts of water demand is the ecological environment water demand of the whole wetland.
Water demand of consumptive ecosystem
- (1)
Water demand from surface evaporation
- (2)
Evaporative water demand of vegetation
- (3)
Water requirements for groundwater recharge
Non-consumptive ecosystem water demand
- (1)
Soil water demand
- (2)
Biological habitat water demand
Total water demand of the Panjin wetland
Gray prediction model
Gray system theory was proposed by Chinese scholar Deng Julong in the 1980s to extract valuable information by regenerating part of the known information to obtain the system's evolutionary pattern and trend (Deng 1987; Chen 2012). Traditional gray system theory stipulates that the modeling sequence must be an equally spaced univariate first-order gray model. However, in real life, due to some irresistible factors that make the acquired data non-equally spaced, if the prediction is carried out according to the equally spaced gray model, it will disrupt the regularity of the original data and cause large deviations, which will affect the prediction results. Therefore, a non-equally spaced GM(1,1) model is used in this paper (She et al. 2013).
- (1)
- (2)
- (3)
- (4)
The evaluation results of 1989, 1999, 2009, and 2017 were used as the original data to construct a GM(1,1) gray prediction model to complete the prediction of the ecological and environmental quality status of the study area for the next 20 years.
RESULTS AND DISCUSSION
Analysis of landscape fragmentation
As shown in Table 3, the patch density, Shannon diversity, and separateness indices generally showed a decreasing trend, indicating that from 1989 to 2017, with the further establishment of the Panjin wetland and the successive introduction of relevant conservation policies for the reserve, the landscape pattern status of the study area was gradually restored, the landscape fragmentation was gradually improved, the ecological functions of the wetland were gradually restored, and the self-regulating capacity of the wetland was increasingly enhanced. In this study, 2017 was the year in which the ecological environment of the wetland was in the best condition during this period.
Year . | PD . | SHDI . | S . |
---|---|---|---|
1989 | 76.5 | 1.674 | 4.155 |
1999 | 64.5 | 1.649 | 3.940 |
2009 | 65.7 | 1.601 | 3.979 |
2017 | 52.3 | 1.576 | 3.678 |
Year . | PD . | SHDI . | S . |
---|---|---|---|
1989 | 76.5 | 1.674 | 4.155 |
1999 | 64.5 | 1.649 | 3.940 |
2009 | 65.7 | 1.601 | 3.979 |
2017 | 52.3 | 1.576 | 3.678 |
Calculation of water demand for the Panjin wetland consumptive ecosystem
- (1)
Surface evaporation water demand calculation
Combined with the actual situation, the types of landscapes that meet this condition in the Panjin wetland in this study are farming pond, beach, and river, and combining the rainfall, evaporation, and the corresponding total landscape area to obtain the surface evaporation ecological water demand of the reserve, as shown in Table 4.
- (2)
Vegetation water demand calculation
Year . | Farming pond . | Beach . | River . | Total . |
---|---|---|---|---|
1989 | 0.130 | 0.099 | 0.113 | 0.341 |
1999 | 0.142 | 0.071 | 0.127 | 0.341 |
2009 | 0.140 | 0.093 | 0.070 | 0.304 |
2017 | 0.130 | 0.071 | 0.054 | 0.255 |
Year . | Farming pond . | Beach . | River . | Total . |
---|---|---|---|---|
1989 | 0.130 | 0.099 | 0.113 | 0.341 |
1999 | 0.142 | 0.071 | 0.127 | 0.341 |
2009 | 0.140 | 0.093 | 0.070 | 0.304 |
2017 | 0.130 | 0.071 | 0.054 | 0.255 |
The Panjin wetland has a wide range of vegetation species and key species should be selected when calculating vegetation water demand. The reed and paddy land occupy a large area and are the key plants, so these two species were selected for the calculation (Li et al. 2021; Zhang et al. 2021). The calculated results are shown in Table 5.
- (3)
Groundwater recharge water demand calculation
Year . | Reed . | Paddy land . | Total . |
---|---|---|---|
1989 | 0.999 | 0.619 | 1.618 |
1999 | 1.053 | 0.581 | 1.634 |
2009 | 1.105 | 0.590 | 1.695 |
2017 | 1.160 | 0.479 | 1.639 |
Year . | Reed . | Paddy land . | Total . |
---|---|---|---|
1989 | 0.999 | 0.619 | 1.618 |
1999 | 1.053 | 0.581 | 1.634 |
2009 | 1.105 | 0.590 | 1.695 |
2017 | 1.160 | 0.479 | 1.639 |
In this study, the wetland groundwater recharge water demand of the paddy land was mainly investigated, where Φ was taken as 0.001 m/d and T was taken as 120 days, to obtain the groundwater recharge demand of the Panjin wetland in 1989, 1999, 2009, and 2017 as shown in Table 6.
Year . | Total . |
---|---|
1989 | 0.184 |
1999 | 0.194 |
2009 | 0.204 |
2017 | 0.214 |
Year . | Total . |
---|---|
1989 | 0.184 |
1999 | 0.194 |
2009 | 0.204 |
2017 | 0.214 |
Calculation of the water demand of non-consumptive ecological environment in the Panjin wetland
- (1)
Soil water demand calculation
According to the relevant data, it is known that the soils of the Panjin wetland can be classified as rice soils and swamp soils according to the characteristics of moisture content and nutrients. The main part of the paddy soil is the paddy field, whose volume percentage reaches 60–70%, and in this study, the data were selected as 65%, and the soil thickness of its root system was selected as 1.2 m for calculation. The reed is the main species in the swamp soil and its volume percentage reaches 45–55%, and in this study, the data were selected as 50%, and the soil thickness of the plant root system can be determined according to the relevant literature, and its calculation data was selected as 0.8 m. The calculations were carried out to obtain the soil water demand of the Panjin wetland in 1989, 1999, 2009, and 2017, as shown in Table 7.
- (2)
Biological habitat water demand calculation
Year . | Swampy soil . | Rice soil . | Total . |
---|---|---|---|
1989 | 0.354 | 1.199 | 1.553 |
1999 | 0.332 | 1.264 | 1.596 |
2009 | 0.337 | 1.326 | 1.663 |
2017 | 0.274 | 1.392 | 1.666 |
Year . | Swampy soil . | Rice soil . | Total . |
---|---|---|---|
1989 | 0.354 | 1.199 | 1.553 |
1999 | 0.332 | 1.264 | 1.596 |
2009 | 0.337 | 1.326 | 1.663 |
2017 | 0.274 | 1.392 | 1.666 |
The calculation of the biological habitat water demand in Panjin wetland is mainly based on various necessary biological activities of fish, birds, and other organisms in the area, and the amount of water required by them for these activities is the biological habitat water demand in the area. Black-billed gulls, cranes, and other national key protected animals mainly inhabit the reed and beach, where the water depth is around 0.5–1.0 m, and 0.8 m was chosen for this calculation. As for fish, shrimps, and plankton, they mainly live in farming pond and river, and 1.5 m was chosen for this calculation, the water demand of biological habitats in Panjin wetland in 1989, 1999, 2009, and 2017 can be obtained, as shown in Table 8.
Year . | Reed and beach . | Farming pond and river . | Total . |
---|---|---|---|
1989 | 0.878 | 0.787 | 1.665 |
1999 | 0.788 | 0.875 | 1.662 |
2009 | 0.835 | 0.683 | 1.517 |
2017 | 0.670 | 0.598 | 1.268 |
Year . | Reed and beach . | Farming pond and river . | Total . |
---|---|---|---|
1989 | 0.878 | 0.787 | 1.665 |
1999 | 0.788 | 0.875 | 1.662 |
2009 | 0.835 | 0.683 | 1.517 |
2017 | 0.670 | 0.598 | 1.268 |
Total water demand of the Panjin wetland
The total water demand of the Panjin wetland ecosystem is the sum of five types of ecological water demand, and the calculation results are shown in Table 9.
Year . | Vegetation . | Soil . | Surface evaporation . | Biological habitats . | Groundwater recharge . | Total . |
---|---|---|---|---|---|---|
1989 | 1.618 | 1.553 | 0.341 | 1.665 | 0.184 | 5.362 |
1999 | 1.634 | 1.596 | 0.341 | 1.662 | 0.194 | 5.428 |
2009 | 1.695 | 1.663 | 0.304 | 1.517 | 0.204 | 5.383 |
2017 | 1.639 | 1.666 | 0.255 | 1.268 | 0.214 | 5.042 |
Year . | Vegetation . | Soil . | Surface evaporation . | Biological habitats . | Groundwater recharge . | Total . |
---|---|---|---|---|---|---|
1989 | 1.618 | 1.553 | 0.341 | 1.665 | 0.184 | 5.362 |
1999 | 1.634 | 1.596 | 0.341 | 1.662 | 0.194 | 5.428 |
2009 | 1.695 | 1.663 | 0.304 | 1.517 | 0.204 | 5.383 |
2017 | 1.639 | 1.666 | 0.255 | 1.268 | 0.214 | 5.042 |
As shown in Table 9, the overall upward trend in the total ecological water demand between 1989 and 1999 was due to the arrival of large numbers of people in the area, resulting in the increased demand for agricultural land and the development of some of the reed into paddy land. In addition, people were driven by economic interests and the increasing number of small-scale individual ponds resulted in continuous encroachment and pollution of the beach resource, which led to the continuous deterioration of the ecological environment within the wetland, the degradation of ecological functions, the reduction of autogenous supply capacity and the increasing demand for ecological water. This phenomenon was alleviated after 1999, with the completion of the second phase of the Panjin wetland restoration project and the introduction of related conservation measures and policies, the ecological environment of the Panjin wetland has been improved to a certain extent and its internal ecological functions have been enhanced.
Correlation analysis between landscape pattern index and total ecological water demand
Panjin wetland water demand risk assessment
In this study, MATLAB software was used for predictive analysis, and the total ecological water demand of the Panjin wetland in 1989, 1999, 2009, and 2017, 5.362 × 109 m3, 5.428 × 109 m3, 5.383 × 109 m3, and 5.042 × 109 m³, respectively, were used as raw data for the predictive analysis. The total ecological water demand of the Panjin wetland in 2027, 2037, 2047, and 2057 is 4.913 × 109 m3, 4.738 × 109 m3, 4.570 × 109 m3, and 4.408 × 109 m3, respectively. Simulated values and simulation errors are shown in Table 10.
Serial number . | Actual data . | Simulation data . | Residuals . | Relative simulation error . |
---|---|---|---|---|
1 | 5.362 | 5.362 | 0 | 0 |
2 | 5.428 | 5.476 | −0.048 | 0.886% |
3 | 5.383 | 5.282 | 0.101 | 1.885% |
4 | 5.042 | 5.094 | −0.052 | 1.028% |
Serial number . | Actual data . | Simulation data . | Residuals . | Relative simulation error . |
---|---|---|---|---|
1 | 5.362 | 5.362 | 0 | 0 |
2 | 5.428 | 5.476 | −0.048 | 0.886% |
3 | 5.383 | 5.282 | 0.101 | 1.885% |
4 | 5.042 | 5.094 | −0.052 | 1.028% |
CONCLUSION
In this study, the Panjin wetland was selected as the research object, and the landscape pattern of the Panjin wetland was analyzed based on the landscape classification data in 1989, 1999, 2009, and 2017, with patch density, Shannon diversity index, and separation degree as indicators. The results showed that the landscape fragmentation and ecological functions of the Panjin wetland have been improved between 1989 and 2017, and the whole ecosystem is developing in a better direction. This study also used the ecological water demand calculation model to calculate the total ecological water demand for 1989, 1999, 2009, and 2017 for Panjin wetland as 5.362 × 109 m3, 5.428 × 109 m3, 5.383 × 109 m3, and 5.042 × 109 m3, respectively, based on the landscape pattern classification data. A gray prediction model was used to obtain the future. The ecological water demand of the Panjin wetland in 2027, 2037, 2047, and 2057 is 4.913 × 109 m3, 4.738 × 109 m3, 4.570 × 109 m3, and 4.408 × 109 m3, which shows an overall decreasing trend and indicates that the overall ecological environment of the Panjin wetland is improving.
This study investigated the ecological water demand of the Panjin wetland and used gray models to predict the future ecological water demand of the Panjin wetland, enriching the research results in the field of ecological assessment of the Panjin wetland, providing a basis for scientific management of wetlands, and providing a scientific reference for other regional estuarine wetlands research. However, the low resolution of the remote sensing images, with a resolution of only 30 m, can have an impact on the analysis results. In addition, the small number of samples chosen to carry out the prediction analysis will also have a certain bias on the prediction results. There are many factors affecting the ecological environment of wetlands, and in the process of practical application, the impact of social and economic factors on the ecological water demand security of wetlands should also be taken into account.
FUNDING
This study was funded and supported by the National Natural Science Foundation of China (No. 31570706).
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.
CONFLICT OF INTEREST
The authors declare there is no conflict.