Wen-hui Jie, Chun-lei Xiao, Ce Zhang, En Zhang, Jing-yue Li, Bing Wang, Hai-wei Niu,Shuang-fa Dong

a Airborne Survey and Remote Sensing Center of Nuclear Industry, Shijiazhuang 050002, China

b Hebei Key Laboratory of Airborne Survey and Remote Sensing Technology, Shijiazhuang 050002, China

c China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, China Geological Survey, Beijing 100083, China

Keywords:Wetlands Environmental change Global climate change Remote sensing Dynamic monitoring Southern Mongolian Plateau

ABSTRACT The environmental change in the wetlands in the southern Mongolian Plateau has important impacts on the environment of North China and even the entire Northeast Asia, from which the global climate change can be understood on a large scale, especially the climate change in the Mongolian Plateau. This study extracted the information on the wetlands from three stages of remote sensing images (also referred to as RS images) of the study area, including Enhanced Thematic Mapper Plus (ETM+) images of 2000, TM images of 2010, and Landsat 8 Operational Land Imager (OLI) images of 2018. As indicated by the extraction results, the area of wetlands decreased from 796.90 km2 of 2000 to 666.24 km2 of 2018 at a rate of 7.26 km2/a. The reduced area is 130.66 km2, which is about 16.4% reduction. And the patch number of wetlands decreased from 731 of 2000 to 316 of 2018 in the study area, approximately 56.8% reduction(415 patches), and the decrease in the area of the wetlands mainly occurred in the northwest endorheic region. In terms of wetland types, the change of the wetlands was dominated by the decrease of lacustrine wetlands, of which the area and patch number decreased by 106.2 km2 and 242, respectively. Furthermore,the area of the lacustrine wetlands decreased at the highest rate of 8.70 km2/a in 2010‒2018. From the perspective of spatial distribution, the wetlands in the western part shrunk more notably than those in the eastern part as a whole in the study area. According to local meteorological data, the precipitation gently decreased and the temperature increased (about 1.7℃) from 1975–2018. Overall, the decrease in the area of the wetlands and the temperature rises in the study area were mainly driven by the Mongolian monsoon climate, reduction in precipitation, and human activities.

1. Introduction

Wetlands, also known as “Earth’s kidneys”, are ecosystems with multiple unique functions. They play a highly significant role in the protection of biodiversity and rare species, the maintenance of ecological balance, flooding and drought reduction by water storage, water source conservation, climate regulation, the control of soil erosion,and pollution degradation. Furthermore, they are important strategic resources in promoting national economic and social development and are rare resources in pushing forward human civilization and advancement (He Q and Xu LY, 2017; Wang Y, 2019; Zhu H et al., 2019; Liu HM et al., 2010). However,as much as 87% of the wetlands in the world have been lost over the past 300 years, with 54% of them having been lost since 1900, as reported by the Intergovernmental Science and Policy Platform on Biodiversity and Ecosystem Services(IPBES). With a decrease in the area and intensified fragmentation of wetland habitats, the biodiversity declined and the wetlands play an increasingly small role in water purification, hydrological regulation, and carbon sink capacity. Consequently, the ecological environmental quality of the wetlands has declined and their functions have gradually weakened or even lost. As revealed by the latest survey results, wetlands in China cover an area of more than 0.536×106km2, accounting for about 5.58% of the total land area of China. They have the characteristics of great variety,large area, and rich biodiversity and play a unique and irreplaceable role in the maintenance of national ecologic safety, freshwater safety, food safety, and climate safety.However, the ecological environmental quality and ecological functions of nearly 90% of major wetlands in China have declined due to the effects of human activities (Xiao DR et al.,2007).

The research on wetlands is gradually systematic and internationalized. The theoretical system of wetlands as a discipline is being gradually improved and expanded,contributing to the establishment and rapid development of new branch disciplines. Meanwhile, wetland science is covering increasing content and extending to increasing fields. It is an interdiscipline of ecology, hydrology,environmental science, and geography and mainly focuses on the research of the formation and evolution of wetlands, the regularity, and mechanisms of the ecological processes of wetlands, and the assessment of wetland ecosystem (Han M,2012). In the 1990s, Liu HT (1995) firstly studied the classification of the wetlands in China by referring to foreign experience in distinct accordance with the guideline of“gradual improvement from simple to specific classification”.Yin ZQ et al. (2006) explored and analyzed the relationship of the formation and evolution of the Zhalong Wetland with the Nenjiang River and sandy lands by analyzing remote sensing(RS) images and samples. They discovered that the ecological environment in the Zhalong Wetland area will be significantly affected once the wetland disappears, leading to the salinization and desertification of land. Li HY et al. (2012),Wu CD et al. (2005), and Xu ZG et al. (2007) studied the effects of the water quality changes and hydrological situation of wetlands on the structure and functions of wetland ecosystem and the role that wetlands play in the purification of water pollutants. Huang XY et al. (2019) researched the wetland ecosystem in the Liaohe Delta and revealed that coastal wetlands are greatly significant for the filtration of heavy metal elements and the abatement of environmental pollution. Based on years of investigation and research of the wetlands in Panjin, Tian H et al. (2018) evaluated the ecological environment of the wetlands using the analytic hierarchy process (AHP). The results indicate that the wetlands in Panjin enjoy a good ecological environment overall. Meanwhile, they play an important role in flood equalization, climate regulation, tourism, and the protection of biodiversity and ecosystem stability, which serve as an important factor in determining the value of the wetlands.

Wetlands are widely distributed and some swamps cannot be directly investigated on the ground. Furthermore, wetlands mostly feature short vegetation and have high optical reflectivity waters (Lin J et al., 1997). Therefore, remote sensing technology can be relied on to conduct efficient,timely, accurate, and long-term monitoring of wetlands since it enjoys the following advantages. Remote sensing can be used to dynamically monitor a broad range of wetlands on both spatial and temporal scales in a real-time and straightforward manner, can reflect macroscopic laws, and can largely save human, material, and financial resources (Jie WH et al., 2020). At present, the studies on wetlands gradually increase with an increase in the understanding of the importance of wetland resources. Moreover, remote sensing technology has become a hot spot in wetland research in the world owing to its great advantages in wetland research (Han M et al., 2003). Based on three stages of RS images of the study area, including Enhanced Thematic Mapper Plus(ETM+) images of 2000, TM images of 2010, and Landsat 8 Operational Land Imager (OLI) images of 2018, this paper obtained the spatial distribution characteristics and temporalspatial evolution patterns of the wetlands in the study area in 2000‒2018 and summarized the temporal-spatial evolution patterns of the wetlands in different parts of the study area.

2. Overview of the study area

The study area is located on the southern margin of the Mongolian Plateau and in the northwest of Hebei Province,with geographical coordinates of 40°56′N‒42°51′N and 112°54′E ‒117°10′E. It is a typical grassland ecosystem and the wetlands in the study area involve nine counties (banners),namely Shangdu County, Xinghe County, Huade County,Chahar Right Back Banner, and Taibus Banner in Inner Mongolia, and Zhangbei County, Kangbao County, Shangyi County, and Guyuan County in Hebei Province (Fig. 1). The Mongolian Plateau is a relatively closed arid and semi-arid inland plateau with an extremely fragile ecological environment. The environmental change in the wetlands in the southern Mongolian Plateau has important impacts on the environment of North China and even the entire Northeast Asia, from which the global climate change can be understood on a large scale, especially the climate change in the Mongolian Plateau. However, the area of the wetlands in the study area has greatly decreased since 2000, with numerous lakes and swamps scattering in the area have largely shrunk and dried up. This will result in marked changes in the ecological and geological environments in the study area.

The study area is in a middle temperate sub-arid zone with an East Asian continental monsoon climate. The spring features changeable but arid weather with little rain. The summer has humid weather with a large amount of precipitation since warm and humid air blows in as the western Pacific subtropical high (WPSH) extends westward and advances northward. In autumn, it is sunny and gradually gets colder as dry and cold northwest wind becomes gradually strong again while warm and humid southeast air grows increasingly weak. In winter, cold waves prevail and the study area is frequently struck by a sharp temperature drop and consequent wind and snow under the control of the strong Mongolian cold high. Rainfall is mostly concentrated from June to August, with total precipitation of 220‒340 mm,accounting for 64%‒69% of the total annual precipitation in the study area. The annual precipitation in the Batou Mountain area in the south is 350‒550 mm. There are numerous rivers and lakes in the study area. Among them, the Luanhe River is the largest exorheic river and the other rivers are mostly typical endorheic rivers. Most of the rivers originate from the Batou Mountain and flow in the NS trending, with the atmospheric precipitation serving as their main recharge source.

Fig. 1. Schematic map of the study area.

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3. Data sources and information extraction

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3.1. Data sources

To obtain unified RS images to extract the data on the wetlands in the study area scientifically and accurately, the RS images collected by Landsat satellites were selected given the factors such as the long period of this study and the update period and resolution of RS images (Zhu YN et al., 2019; Li CL et al., 2019; Nie XR et al., 2018; Zhao R et al., 2019;Cheng PG et al., 2018; Ai JQ, 2020; Sun N et al., 2017). This study collected three stages of remote sensing images, namely ETM+ images of 2000, TM images of 2010, and Landsat 8 OLI images of 2018 (Table 1).

3.2. Extraction of wetland information

Two methods are mainly employed to extract wetland information at present, namely manual visual interpretation and computerized automatic interpretation (Mc Feeters SK,1996; Luo JC et al., 2009). The latter primarily relies on the spectrum information of RS images to identify wetland information. It is characterized by a high degree of automation, high speed, and low workload. However, it imposes high requirements for the quality of RS images and the threshold for the information extraction is difficult to determine. Therefore, it is unfeasible to extract wetland information by this method given the current conditions. As for the method of manual visual interpretation, wetland information is mainly extracted by the visual judgment of false-color composites of RS images. This method enjoys the advantages of simple operation and high interpretation precision but is time-consuming and requires a heavy workload (Li XF et al., 2018). In this study, the advantages of both manual visual interpretation and computerized automatic extraction were combined by man-machine interaction to improve the extraction speed and precision. Furthermore, a certain amount of field verification was performed to ensure the accuracy of the information extraction.

In this study, the Ramsar wetland type classification(Davidson NC, 2018) was adopted to divide the wetlands in the study area into four types according to their genesis,namely fluvial wetlands, lacustrine wetlands, swamps, and human-made wetlands. Among them, the fluvial wetlands can be further divided into permanent rivers, seasonal/intermittent rivers, and floodplain wetlands; the lacustrine wetlands can be subdivided into permanent freshwater lakes and seasonal freshwater lakes; the swamps include marshes, shrub swamps,and salt meadows, and the human-made wetlands consist ofreservoirs, freshwater aquaculture ponds, ponds, rice fields,urban artificial landscapes, and recreational waters.

Table 1. Information on the remote sensing images of 2000, 2010, and 2018 selected in this study.

4. Results and discussion

4.1. Spatial distribution of wetlands

The information on the wetlands in the study area was extracted through man-machine interactive interpretation of the RS images of 2000, 2010, and 2018 of the wetlands in the study area, as well as field verification. The results are as follows.

Table 2 shows the wetlands in the study area in 2000. It can be seen from the table that the wetlands covered an area of 796.90 km2and consisted of 731 wetland patches in total.They were dominated by swamps, followed by lacustrine wetlands, fluvial wetlands, and human-made wetlands successively. As indicated by the interpretation results, the swamps covered an area of 347.66 km2, accounting for 43.63% of the total wetland area. Meanwhile, they were relatively concentrated and were comprised of 50 wetland patches, which accounted for 6.84% of the total wetland patch number. The lacustrine wetlands were 276.17 km2in area,accounting for 34.66% of the total wetland area. They were dispersed in the study area and consisted of 641 wetland patches, accounting for 87.69% of the total wetland patch number. The fluvial wetlands covered an area of 155.60 km2,accounting for 19.53% of the total wetland area. They werecomprised of 32 wetland patches, accounting for 4.38% of the total wetland patch number. The human-made wetlands covered a relatively small area of 17.47 km2, accounting for 2.19% of the total wetland area. They consisted of eight patches, accounting for 1.09% of the total wetland patch number.

Table 2. Statistics of the area and patch number of the wetlands in the study area in 2000.

The wetlands in the study area in 2000 are shown in Table 3.As can be seen from this table, the wetlands covered an area of 750.99 km2and consisted of 493 patches in total. They were dominated by swamps, followed by lacustrine wetlands,fluvial wetlands, and human-made wetlands successively. As indicated by the interpretation results, the swamps covered an area of 334.96 km2, accounting for 44.60% of the total wetland area. Meanwhile, they were relatively concentrated and were comprised of 48 wetland patches, which accounted for 9.74% of the total wetland patch number. The lacustrine wetlands were 239.58 km2in area, accounting for 31.90% of the total wetland area. They were dispersed in the study area and consisted of 399 wetland patches, accounting for 80.93%of the total wetland patch number. The fluvial wetlands covered an area of 144.05 km2, accounting for 19.18% of the total wetland area. They were comprised of 29 wetland patches, accounting for 5.88% of the total wetland patch number. The human-made wetlands covered a relatively small area of 32.40 km2, accounting for 4.31% of the total wetland area. They consisted of 17 wetland patches, accounting for 3.45% of the total wetland patch number.

Table 3. Statistics of the area and patch number of the wetlands in the study area in 2010.

Table 4. Statistics of the area and patch number of the wetlands in the study area in 2018.

Table 4 shows the wetlands in the study area in 2018. It can be seen from this table that the wetlands covered an area of 666.24 km2and consisted of 316 wetland patches in total.They were dominated by swamps, followed by lacustrine wetlands, fluvial wetlands, and human-made wetlands successively. As indicated by the interpretation results, the swamps covered an area of 320.84 km2, accounting for 48.16% of the total wetland area. Meanwhile, they were relatively concentrated and were comprised of 50 wetland patches, which accounted for 15.82% of the total wetland patch number. The lacustrine wetlands were 169.97 km2in area, accounting for 25.51% of the total wetland area. They were dispersed in the study area and consisted of 217 wetland patches, accounting for 68.67% of the total wetland patch number. The fluvial wetlands covered an area of 144.05 km2,accounting for 21.62% of the total wetland area. Meanwhile,they were comprised of 29 wetland patches, accounting for 9.18% of the total wetland patch number. The human-made wetlands covered a relatively small area of 31.38 km2,accounting for 4.71% of the total wetland area. They consisted of 20 wetland patches, accounting for 6.33% of the total wetland patch number.

4.2. Temporal-spatial evolution patterns of wetlands

Based on the extracted information on the wetlands in the study area in 2000, 2010, and 2018, the variations in the quantity of the wetlands and their percentages were analyzed and studied using the spatial analysis tool ArcGIS. In this manner, the change characteristics of the wetlands in the study area in 2000‒2018 were obtained. The changes of the wetlands in 2000‒2010 were achieved using the Erase tool of ArcGIS, as shown in Fig. 2. In detail, the zones with decreased wetlands can be achieved by erasing the extracted wetland information of 2000 from that of 2010, and similarly,the zones with increased wetlands can be determined by erasing the extracted wetland information of 2010 from that of 2000. Likewise, the changes of the wetlands in the study area in 2010‒2018 and 2000‒2018 can be obtained from the extracted wetland information of 2000, 2010, and 2018, as shown in Fig. 3 and Fig. 4.

As shown in Table 5, the area and patch number of the wetlands in the whole study area decreased by 45.91 km2(5.76%) and 238 (32.56%), respectively in 2000‒2010.Among them, the area and patch number of the lacustrine wetlands decreased the most, with the decreased values of 36.59 km2(13.25%) and 242 (37.75%), respectively. In contrast, the human-made wetlands increased both in the area and patch number in this period. The changes of various types of wetlands in 2000‒2010 are shown in Fig. 2. The area and patch number of the wetlands in the whole study area decreased by 84.75 km2(11.29%) and 177 (35.90%),respectively in 2010‒2018, which were dominated by decreased area and patch number of the lacustrine wetlands—69.61 km2(29.06%) and 182 (45.61%),respectively. Meanwhile, the human-made wetlands increased in patch number but decreased in the area during this period.The changes of various types of wetlands in 2010‒2018 are as shown in Fig. 3. The area and patch number of the wetlands in the whole study area decreased by 130.66 km2(16.40%) and 415 (56.77%), respectively in 2000‒2018. Among them, the area and patch number of the lacustrine wetlands decreased the most, with decreased values of 106.20 km2(38.45%) and 424 (66.15%), respectively. Meanwhile, the area and patch number of human-made wetlands increased to a certain extent in this period, indicating that human activities had invaded the wetlands and produced increasing effects on the wetlands.The changes of various types of wetlands in 2000‒2018 are shown in Fig. 4. According to comprehensive analyses, the areas of the fluvial wetlands, lacustrine wetlands, and swamps all decreased in 2000‒2018. Among them, the area of the lacustrine wetlands decreased the most, followed by the areas of the fluvial wetlands and swamps. In comparison, the area of human-made wetlands increased, but their total area and increased area were both relatively small.

Fig. 2. Changes of the wetlands in the study area in 2000‒2010.

Fig. 3. Changes of the wetlands in the study area in 2010‒2018.

Fig. 4. Changes of the wetlands in the study area in 2000‒2018.

Table 5. Statistics of the changes in the wetlands in the study area in 2000‒2018.

Table 6 shows the change rates of the various wetlands in the study area in the three periods. It can be seen from this table that the area of each type of wetlands decreased at a rate higher in 2010‒2018 than in the other two periods, except for the fluvial wetlands, whose area remained unchanged. During this period, the annual decrease rates of the area were in the order of lacustrine wetlands, swamps, and human-made wetlands, which were 8.70 km2/a, 1.77 km2/a, and. 0.13 km2/a,respectively. Furthermore, the area of the human-made wetlands only decreased in 2010‒2018, which decreased by 1.02 km2at a rate of 0.13 km2/a. Overall, the decrease of thewetland area in the study area was dominated by the decrease in the surface area of lakes, and meanwhile, the changes of the wetlands in the study area were mainly reflected by the changes of the lacustrine wetlands in the area.

Table 6. Statistics of change rates of various wetlands in the study area in different periods (km2/a).

4.3. Temporal-spatial evolution patterns of wetlands in different regions

The study area can be divided into three regions, namely,the northwest endorheic region, the endorheic region in Wulannaoer, and the exorheic region of the Luanhe River from west to east. As can be seen from the changes of the wetlands in the study area in 2000‒2018 extracted based on analyses, the western part of the study area shrunk more than the eastern part of the study area overall (Fig. 5).

As can be seen from Table 7, the area and patch number of the wetlands in the study area decreased mainly under the influence of the northwest endorheic region in 2000‒2018,with the decreased values of 130.66 km2and 415, respectively in total in 2000‒2018. Among them, the area and patch number of the wetlands in the northwest endorheic region decreased by 97.86 km2and 366, respectively, accounting for 74.90% and 88.19% of the total decreased wetland area and the total decreased wetland patch number, respectively.Meanwhile, the area and patch number of the wetlands in the endorheic region in Wulannaoer decreased by 3.93 km2and 16, respectively, accounting for 3.01% and 3.86%,respectively, and the area and patch number of the wetlands in the exorheic region of the Luanhe River decreased by 28.87 km2and 33, respectively, accounting for 22.09% and 7.95%,respectively.

Fig. 5. Changes of the wetlands in different regions in the study area in 2000‒2018.

Table 7. Statistics of changes in the wetlands in different regions of the study area in 2000‒2018.

The area and patch number of the wetlands in the study area decreased by 45.91 km2and 238, respectively in total in 2000‒2010. Among them, the area and patch number of the wetlands in the northwest endorheic region decreased by 27.27 km2and 191, respectively, accounting for 59.41% and 80.25% of the total decreased wetland area and the total decreased wetland patch number in 2000‒2010, respectively.Meanwhile, the area and patch number of the wetlands in the endorheic region in Wulannaoer decreased by 2.86 km2and 12, respectively, accounting for 6.23% and 5.04%,respectively, and the area and patch number of the wetlands in the exorheic region of the Luanhe River decreased by 15.78 km2and 35, respectively, accounting for 34.36% and 14.71%,respectively.

The area and patch number of the wetlands in the study area decreased by 84.76 km2and 177, respectively in total in 2010‒2018. Among them, the area and patch number of the wetlands in the northwest endorheic region decreased by 70.59 km2and 175, respectively, accounting for 83.29% and 98.87% of the total decreased wetland area and the total decreased wetland patch number in 2010‒2018, respectively.Meanwhile, the area and patch number of the wetlands in the endorheic region in Wulannaoer decreased by 1.07 km2and 4,respectively, accounting for 1.27% and 2.26%, respectively.As for wetlands in the exorheic region of the Luanhe River in 2010‒2018, the area decreased by 13.09 km2, accounting for 15.45% of the total decreased area in 2010‒2018, and the wetland patch number increased by two.

Therefore, the changes of the wetlands in the whole study area mainly depended on the changes of the wetlands in the northwest endorheic region.

4.4. Discussion

4.4.1. Effects of monsoon change in the southern Mongolian Plateau on wetlands

The study area began to develop from a warm and wet climate into a cold and dry climate around 500014C BP in the Middle Holocene. It showed low-temperature and dry climate as a whole and exhibited notable human activities in the Late Holocene. Afterward, it has been a cold and dry climate since 3100 BP as a consequence of environmental deterioration,that is, the gradual change of the environment from the original forest steppes to desert steppes (Yang QL, 2007).Meanwhile, the study area is under the control of strong northwest arid air due to the global warming trend, which inevitably leads to the decrease of the wetlands.

4.4.2. Effects of temperature and precipitation on wetlands

Fig. 6. Annual precipitation trend in 1975‒2018 monitored at Duolun station.

Fig. 7. Annual average temperature trend in 1975‒2018 monitored at Duolun station.

Fig. 8. Annual precipitation trend in 1975‒2018 monitored at Zhangbei station.

Fig. 9. Annual average temperature trend in 1975‒2018 monitored at Zhangbei station.

Meteorological data were collected from four meteorological stations in the study area, namely the Duolun station in the east, the Zhangbei station in the middle, and the Jining and Huade stations in the west. To clearly exhibit the changing trend of the climate data in the study area, this study obtained the meteorological data in 1975‒2018. These data showed the same trend, that is, the precipitation decreased(Figs. 6, 8, 10, 12), but the temperature increased (Figs. 7, 9,11, 13), year by year overall in 1975‒2018. The average temperture rise is about 1.7℃.

Fig. 10. Annual precipitation trend in 1975‒2018 monitored at Jining station.

Fig. 11. Annual average temperature trend in 1975−2018 monitored at Jining station

Fig. 12. Annual precipitation trend in 1975‒2018 monitored at Huade station.

Fig. 13. Annual average temperature trend in 1975‒2018 monitored at Huade station.

4.4.3. Effects of human activities on wetlands

(i) Human activities have constantly increased in the study area with continuous social development. Many reservoirs have been built in the upper reaches of the northwest endorheic region mainly for irrigation and flood control. As revealed by relevant data, the upstream recharge channels of the wetlands have been interrupted since 1998 as the reservoirs retained and stored surface runoff. The area of the wetlands in the study area had continuously decreased according to the extracted changes in 2000‒2010. Therefore,upstream water retention is an important reason for the decrease in the area of the wetlands in the study area.

(ii) According to relevant statistics, the population,industrial output value, grain yield, and most especially, the area of irrigable lands in the study area increased by 2.3 times,170 times, 1.5 times, and 190 times in 1949−2004. The water consumption in the study has increased by 11 times from the water conservancy construction of “100 reservoirs, 1000 ponds, and 10000 pumping wells” in the 1970s to the “the movement of drilling 10000 pumping wells” in the 1990s to the “industrialization of off-season vegetables” in recent years. The groundwater level has dropped by 3‒5 m and even more than 10 m in some areas with concentrated pumping wells since 1998. The drought and little rain in the study area result in the difficult recharge of water sources. Meanwhile,serious overexploitation of groundwater affects the water source conservation in the study area. All these block the recharge channels of groundwater runoff in the wetlands, thus leading to the decrease in the area of the wetlands in the study area.

(iii) The study area is located in the staggered zone between agricultural areas and grazing regions. Excessive land reclamation and grazing induced low coverage of ground vegetation and consequent serious land desertification in the area. As indicated by investigations, the study area still suffers severe ecological deterioration despite the ecological protection programs implemented in recent years, such as returning farmland to the forest (grass) program and the Beijing-Tianjin-Hebei sand sources control project.Specifically, the area of lands suffering salinity-related desertification increased by about 174 km2from the late 1970s to the late 1980s and further increased by about 119 km2from the late 1980s to the early 21st century. The aggravation of salinity-related desertification of the lands in the study area is the inevitable result of the notable shortage of surface water and groundwater supply and excessive land reclamation and grazing in the study area. It also reflects that water source conservation in the study area is weakening. Therefore, it contributes to the decrease in the area of the wetlands in the study area.

5. Conclusions

This study obtained the spatial distribution characteristics and temporal-spatial evolution patterns of the wetlands in the study area in 2000‒2018 using the advanced remote sensing technology and the method of man-machine interactive interpretation. Furthermore, it summarized the temporalspatial evolution patterns of the wetlands in different regions in the study area as well as the changes of the ecological environment in the study area and their driving factors.

(i) In 2000‒2018, the area of the wetlands in the study area decreased from 796.90 km2in 2000 to 666.24 km2in 2018 and the wetland patch number decreased from 731 in 2000 to 316 in 2018. Therefore, the area and patch number of the wetlands decreased by 130.66 km2and 415, respectively over the 18 years, with a decrease rate of 7.26 km2/a.

(ii) As revealed by comprehensive analyses of the changes in the wetlands and environment in the study area, the decrease in the lacustrine wetlands prevailed in the study area.Moreover, the wetlands in the study area shrunk more and at a higher rate in 2010‒2018 than in 2000‒2010. Meanwhile, the human-made wetlands in the study also decreased in the area in 2010‒2018.

(iii) In terms of spatial change characteristics, the study area can be divided into the northwest endorheic region, the endorheic region in Wulannaoer, and the exorheic region of the Luanhe River from west to east. Meanwhile, the western part of the study area shrunk more than the eastern part of the study area overall. That is, the three regions shrunk in the order of the northwest endorheic region > the endorheic region in Wulannaoer > the exorheic region of the Luanhe River.

(iv) Overall, the decrease in the area of the wetlands and the temperature rises (about 1.7℃) in the study area was mainly driven by the Mongolian monsoon climate, reduction in precipitation, and human activities.

CRediT authorship contribution statement

Wen-hui Jie and Chun-lei Xiao conceived of the presented idea. Wen-hui Jie developed the theory and performed the computations. Ce Zhang, En Zhang, and Jing-yue Li verified the analytical methods. Ce Zhang encouraged Wen-hui Jie to investigate meteorological data and supervised the findings of this work. All authors discussed the results and contributed to the final manuscript.

Declaration of competing interest

The authors declare no conflicts of interest.

Acknowledgment

This study was funded by the project initiated by the China Geological Survey entitled“Remote Sensing Geological Survey of National Key Earth Zones”(DD20190536). The authors would like to extend their sincere gratitude to the project team members for their hard work and reliable data. Thanks also go to Professor Fei Xia from the East China University of Technology for his strong assistance in the preparation and review of this manuscript.