Abstract

Wetlands play a critical role in the environment. With the impacts of climate change and human activities, wetlands have suffered severe droughts and the area declined. For the wetland restoration and management, it is necessary to conduct a comprehensive analysis of wetland loss. In this study, the Xiong’an New Area was selected as the study area. For this site, we built a new method to identify the patterns of wetland loss integrated the landscape variation and wetland elements loss based on seven land use maps and Landsat series images from the 1980s to 2015. The calculated results revealed the following: (1) From the 1980s to 2015, wetland area decreased by 40.94 km2, with a reduction of 13.84%. The wetland loss was divided into three sub stages: the wet stage from 1980s to 2000, the reduction stage from 2000 to 2019 and the recovering stage from 2009 to 2015. The wetland area was mainly replaced by cropland and built-up land, accounting for 98.22% in the overall loss. The maximum wetland area was 369.43 km2 in the Xiong’an New Area. (2) From 1989 to 2015, the normalized difference vegetation index (NDVI), normalized difference water index (NDWI) and soil moisture monitoring index (SMMI) showed a degradation, a slight improvement and degradation trend, respectively. The significantly degraded areas were 80.40 km2, 20.71 km2 and 80.05 km2 by the detection of the remote sensing indices, respectively. The wetland loss was mainly dominated by different elements in different periods. The water area (NDWI), soil moisture (SMMI) and vegetation (NDVI) caused the wetland loss in the three sub-periods (1980s–2000, 2000–2009 and 2009–2015). (3) According to the analysis in the landscape and elements, the wetland loss was summarized with three patterns. In the pattern 1, as water became scarce, the plants changed from aquatic to terrestrial species in sub-region G, which caused the wetland vegetation loss. In the pattern 2, due to the water area decrease in sub-regions B, C, D and E, the soil moisture decreased and then the aquatic plants grew up, which caused the wetland loss. In the pattern 3, in sub-region A, due to the reduction in water, terrestrial plants covered the region. The three patterns indicated the wetland loss process in the sub region scale. (4) The research integrated the landscape variation and element loss appears potential in the identification of the loss of wetland areas.

Highlights

  • Wetlands, formed in the transitional zone between land and water, are widely distributed worldwide [1]

  • The Great Artesian Basin wetland vegetation was analyzed by using MODIS normalized difference vegetation index (NDVI), and the results show that the vegetated wetland area declined from 2002 to 2009 [17]

  • Since each sub-region had different change trends in different periods, we proposed that the pattern of wetland loss in the Xiong’an New Area was integrated with the evolution of the wetland landscape and its elements (Figure 4)

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Summary

Introduction

Wetlands, formed in the transitional zone between land and water, are widely distributed worldwide [1]. Using Landsat images, China’s wetlands loss was detected by the land use matrix and the results proposed that China’s total wetland area decreased by 101,399 km from 1978 to 2008 [9]. These studies mainly used the land use data to analyze the wetland loss and were concentrated on separate periods. It was analyzed that the long-term change in surface water area in the Xiong’an New Area using dense Landsat time series images, which indicated that the wetland has degraded and that this degradation was driven by human activities [20]. Where x represents the land use types; w represents the wetland types; k represents the number of the wetland maps and S represents the maximum wetland extent

Calculation of Wetland Elements
Change Trend Analysis Method
The Pattern of Wetland Loss in the Landscape Integrated with Elements
The Pattern of Wetland Loss in A Landscape Integrated with Elements
Comparison of the Wetland Loss
Uncertainties and Prospects
Findings
Conclusions
Full Text
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