Poyang Lake is the largest freshwater lake in China and is well known for its ecological function and economic importance. However, due to the influence of clouds, it is difficult to dynamically monitor the changes in water surface areas using optical remote sensing. To address this problem, we propose a novel method to monitor these changes using Sentinel-1A data. First, the Sentinel-1A water index (SWI) was built using a linear model and a stepwise multiple regression analysis method with Sentinel-1A and Landsat-8 imagery acquired on the same day. Second, water surface areas of Poyang Lake from 24 May 2015 to 14 November 2016 were extracted by the threshold method utilizing time-series SWI data with an interval of 12 days. The results showed that the SWI threshold classification method could be applied to different regions during different periods with high quantity accuracy (approximately 99%). The water surface areas ranged between 1726.73 km² and 3729.19 km² during the study periods, indicating an extreme variability in the short term. The maximum and average values of the changed areas were 875.57 km² (with a change rate of 35%) and 197.58 km² (with a change rate of 8.2%), respectively, after 12 days. The changes in the mid-western region of Poyang Lake were more dramatic. These results provide baseline data for high-frequency monitoring of the ecological environment and wetland management in Poyang Lake.

Land use and sediment alluviation/deposition are the main factors influencing the vertical distributions of particles with different sizes and soil organic carbon (SOC) forms. Based on field investigation, experimental analysis, data analysis, soil particle characteristics, and the relationships with SOC compositions are studied in the typical alluviation/deposition area of Kaifeng–Zhoukou. In the soil profile, the particulate matter is mainly 10–50 μm and 50–250 μm in size with an average content of approximately 65%, the content difference within the same size particle range is small. There is a large content range of D_{F(farmland in the flooded area)} and D_{NW(woodland in the nonflooded area)} > D_{W(farmland in the nonflooded area)}. The contents of particles smaller than 50 μm have a positive effect on D, and the particles exceeding 50 μm have a negative effect. The contents of 10–50 μm, <2 μm, 2–5 μm, and 5–10 μm particles and their dynamic variances are the root causes of the D differences in the farmland/woodland soil in the FA (the flooded area) and NFA (the nonflooded area). SOC components combine to a greater extent with silt and clay that are <10 μm in size in the NF, and the stability is relatively high. The contents of the 10–50 μm and <10 μm particles are the main reasons for the differences in the soil active and nonactive organic carbon (AOC and NOC, respectively) contents in the FA and the NFA. The difference in D can reflect the change in SOC and its components and can be used as an index to characterize the variance in soil properties and quality. This study revealed the influences of the different particle sizes in the SOC components, which will expand and enrich the current area of study and further provide a basis to increase SOC and improve soil quality.