| 摘要: |
| 2022年鄱阳湖流域发生自1951年有记录以来的严重干旱。为充分利用高时空分辨率影像探究鄱阳湖湿地干旱及生态响应过程，本文采用STNLFFM时空信息融合模型，融合了MODIS与Sentinel-2影像数据，构建出鄱阳湖2021-2022年平均时间间隔为15天的10 m高时空分辨率NDVI影像序列，对比分析了不同年份水体面积以及NDVI时空变化，在此基础上探讨干旱可能造成的生态影响。结果表明：（1）2022年鄱阳湖干旱持续时间近3个月，退水时间比2021年提前约80天；2022年10月鄱阳湖最小水体面积为680 km2，较2021年同期减少约1,900 km2，较2021年枯水期最小水体面积减少约337 km2。2022年鄱阳湖湿地淹水时长小于90天的面积是2021年的3倍以上，约占总面积的30.77%。（2）2022年干旱过程中，湖区洲滩植被提前开始生长，NDVI均值在7月中旬之后迅速增大，较2021年同期最大相差0.27；到11月中旬，NDVI值小于0.2的面积为1,527 km2，较2021年同期增加561 km2；到12月份，NDVI值大于0.6的面积仅15 km2，不足2021年同期的3 %。（3）2022年鄱阳湖干旱引起的植被和水体变化改变了候鸟及长江江豚的栖息环境。湖区的碟形子湖具有较好的持水能力，对极端干旱具有较好的抵御作用。因此，本文建议在干旱期间，适当对湖区长势迅速的植被进行刈割，促使新芽萌发，保障候鸟的食源；开展高时空分辨率的水体连续变化过程监测和预测工作，以便及时救助非连通水体内被困的水生生物；对碟形子湖空间结构进行保护并适当给子湖补水，以保持碟形湖湿地生态系统的稳定性。 |
| 关键词: 鄱阳湖 湿地 干旱 时空信息融合 NDVI |
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| 基金项目:中国科学院战略性先导科技专项（A类）（编号：XDA23040201）、湖北省重点研发计划项目（编号：2023BCB104）和国家自然科学基金项目（编号：41901235）联合资助 |
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| Monitoring and analysis of the Poyang Lake wetland drought process in 2022 based on spatiotemporal information fusion model |
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luojiahuan,yan yi,xiao fei,cao shuhui,chen miaomiao,du yun
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Key Laboratory for Environment and Disaster Monitoring and Evaluation, Hubei, Innovation Academy for Precision Measurement Science and Technology, Wuhan
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| Abstract: |
| In 2022, the Poyang Lake Basin experienced the most severe drought since recorded observations began in 1951. The flat terrain of Poyang Lake makes wetland vegetation highly sensitive to fluctuations in water levels, and drought often causes rapid changes in surface conditions. To effectively utilize high temporal and spatial resolution imagery for investigating wetland drought and ecological response processes in Poyang Lake, this study employed the spatial and temporal nonlocal filter-based fusion model (STNLFFM). By integrating MODIS and Sentinel-2 satellite data, we established a 10-meter high temporal and spatial resolution NDVI image sequence with an average temporal interval of 15 days, spanning from 2021 to 2022. Through comparative analysis, we examined variations in water body area and NDVI spatiotemporal dynamics across different years, providing a foundation for exploring potential ecological impacts induced by drought. The results showed that (1) the drought in 2022 persisted for nearly 3 months, with water recession occurring approximately 80 days earlier than in 2021. In October 2022, the minimum water area of Poyang Lake was 680 km2, representing a reduction of about 1,900 km2 compared to the same period in 2021 and a decrease of approximately 337 km2 from the minimum water area during the dry season in 2021. The area with a water inundation duration of less than 90 days in 2022 was more than 3 times that of 2021, accounting for approximately 30.77% of the total area. (2) During the drought in 2022, the wetland vegetation began to grow earlier, and the NDVI mean value increased rapidly after mid-July, with a maximum difference of 0.27 compared with the same period in 2021. By mid-November, the Poyang wetland with an NDVI value less than 0.2 was 1,527km2, an increase of 561 km2 compared with the same period in 2021; By December, the area with an NDVI value greater than 0.6 was only 15 km2, less than 3% of the same period in 2021. (3) The alterations to the water body and vegetation resulting from the 2022 drought in Poyang Lake affected the habitat of migratory waterbirds with different diets and Yangtze Finless Porpoise. The Poyang sub-lakes have better water holding capacity and resistance to extreme drought. Therefore, to mitigate the impacts of extreme droughts, it is suggested that the fast-growing vegetation in the lake area be mowed appropriately to ensure that shoots sprout before the arrival of migratory birds. Meanwhile, timely monitoring and predicting of continuous processes in water bodies with high spatial and temporal resolution images and rescue of trapped aquatic organisms like Yangtze Finless Porpoises in unconnected waters. Additionally, the edge structure of the Poyang sub-lakes should be repaired and appropriately replenished the Poyang sub-lake with water to maintain the stability of the wetland ecosystem. |
| Key words: Poyang Lake Wetland Drought Spatiotemporal data fusion NDVI |
