NASA’s Cyclone Global Navigation Satellite System (CYGNSS) mission, launched in 2016, is a small satellite constellation designed to measure the ocean surface wind speed in hurricanes and tropical cyclones. To explore its additional capabilities for applications on the land surface, this study investigated the advantages and limitations of using CYGNSS data to monitor flood inundation during typhoon and extreme precipitation events in southeast China in 2017. The results showed that despite the lack of quantitative evaluation, the CYGNSS-derived surface reflectivity (SR) and flood inundation area was qualitatively consistent with the Global Precipitation Measurement (GPM)-derived precipitation and Soil Moisture Active Passive (SMAP)/Soil Moisture and Ocean Salinity (SMOS)-derived total brightness temperature at circular polarization ( ${\mathrm{T}}_{{\mathrm{b}}_{\mathrm{C}}}$ ). The results provide supporting evidence for further designation of Global Navigation Satellite System (GNSS) reflectometry (GNSS-R) constellations to monitor land surface hydrology.

Capturing high frequency water surface dynamics via optical remote sensing is important for understanding hydro-ecological processes over seasonally flooded wetlands. However, it is a difficult task due to the presence of clouds on satellite images. This study proposed the MODerate-resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) Minimum Value Composite (MinVC) algorithm to generate daily water surface data at a 250-m resolution. The algorithm selected pixelwise minimum values from the combined daily Terra and Aqua MODIS NDVI data within a 15-day moving window. Consisting mainly of cloud and water surface information, the MinVC NDVI data were segmented for water surfaces over the Poyang Lake, China (2000–2017) by using an edge detection model. The water surface mapping result was strongly correlated with the Landsat based result (R² = 0.914, root mean square error, RMSE = 223.7 km²), the cloud free MODIS image based result (R² = 0.824, RMSE = 356.7 km²), the recent Landsat-MODIS image fusion based result (R² = 0.765, RMSE = 403 km²), and the hydrodynamic modeling result (R² = 0.799). Compared to the equivalent eight-day MOD13 NDVI based on the Constraint View-Angle Maximum Value Composite (CV-MVC) algorithm, the daily MinVC NDVI highlighted water bodies by generating spatially homogenous water surface information. Consequently, the algorithm provided spatially and temporally continuous data for calculating water submersion times and trends in water surface area, which contribute to a better understanding of hydro-ecological processes over seasonally flooded wetlands. Within the framework of sensor intercalibration, the algorithm can be extended to incorporate multiple sensor data for improved water surface mapping.

The Three Gorges Dam (TGD) has received increasing attention with respect to its potential effects on downstream hydro-ecosystems. Poyang Lake is the largest freshwater lake downstream of the TGD, and it is not immune to these impacts. Here, we combine hydrological observations, remote sensing, a geographic information system (GIS), and landscape ecology technology to investigate the variability and spatial pattern of the hydro-ecological alterations to Poyang Lake induced by the operation of the TGD. It was found that the TGD caused significant hydro-ecological alterations across the Poyang Lake wetland. Specifically, the TGD operation altered the seasonal inundation pattern of Poyang Lake and significantly reduced the monthly inundation frequencies (IFs), which were especially notable (~30–40%) from September to November. Spatially, the declining IFs led to an increase in the mudflat area that is suitable for the growth of vegetation. The vegetation area increased by 58.82 km² and 463.73 km² in the low- and high-water season, respectively, with the most significant changes occurring in the estuary delta of the Ganjiang and Raohe rivers. The results also indicated that the changes in the inundation pattern and floodplain vegetation have profoundly altered the structure and composition of the wetland, which has resulted in increased landscape diversity and a gradual increase in the complexity of the ecosystem composition under the influence of regulation of the TGD. Such results are of great importance for policymakers, as they may provide a reference for wetland water resource planning and landscape restoration in an operational dam environment.

Poyang Lake and Dongting Lake are the two largest freshwater lakes in China. The lakes are located approximately 300 km apart on the middle reaches of the Yangtze River and are differently connected through their respective tributary systems, which will lead to different river–lake water exchanges and discharges. Thus, differences in their morphological and hydrological conditions should induce individual lake spatio-temporal inundation patterns. Quantitative comparative analyses of the dynamic inundation patterns of Poyang Lake and Dongting Lake are of great importance to basic biogeochemical and ecological studies. In this study, using Moderate Resolution Imaging Spectoradiometer (MODIS) satellite imagery and a geographic information system (GIS) analysis method, we systematically compared the spatio-temporal inundation patterns of the two river-connected lakes by analyses of the lake area, the inundation frequencies (IFs) and the water variation rates (WVRs). The results indicate that there was a significant declining trend in the lakes’ inundation area from 2000 to 2011. The inundation areas of Poyang Lake and Dongting Lake, decreased by 54.74% and 40.46%, with an average annual decrease rate of 109.74 km²/y and 52.37 km²/y, respectively. The alluvial regions near Dongting Lake expressed much lower inundation frequencies, averaged over multiple years, than the alluvial regions near Poyang Lake. There was an obvious spatial gradient in the distribution of water inundation for Poyang Lake; the monthly mean IF slowly increased from north to south during the low-water, rising, and high-water periods. However, Dongting Lake expressed a clear zonal distribution of water inundation, especially in the low-water and rising periods. In addition, the WVRs of the two lakes differently changed in space throughout the year, but were in good agreement with the changing processes of water expansion or shrinkage. The different inundation frequencies and water variation rates in the two lakes may possibly depend on many intrinsic factors, including surface discharges from their respective tributaries, river–lake water exchanges and the lakes’ topographical characteristics. These findings are valuable for policymakers because they may lead to different decisions and policies for these two complex river–lake systems.

The saucer-shaped depressions located at the river deltas of Poyang Lake are typical floodplain shallow sub-lakes subject to river-lake connection or isolation. The hydrological connectivity between these depressions and the main lake has a major influence on the hydrologic function and ecological integrity of the lake-floodplain and associated wetland habitats. This study explored the water level fluctuations and water exchange processes between the Poyang Lake and three typical saucer-shaped depressions, using a 30-min temporal resolution of water level observations during 2015–2016. Our results showed that the water level correlation and hydrological connectivity between the main lake and its depressions displayed a strong seasonal and spatial signal. Temporally, the rainfall significantly influences the seasonality and frequency of water level fluctuations both in the main lake and the depressions. The correlation coefficient of the water level ordered from high to low occurred during the high-water period, the rising-water period, the falling-water period and the low-water period, respectively. Spatially, depressions with a shorter connection duration to the main lake are located at higher local elevation and at larger geographical distance from the main lake. Finally, we also discussed the implications of these findings and possible factors that could have caused these particular water regime characteristics and water exchange processes.

The availability of water surface inundation with high spatial resolution is of fundamental importance in several applications such as hydrology, meteorology and ecology. Medium spatial resolution sensors, like MODerate-resolution Imaging Spectroradiometer (MODIS), exhibit a significant potential to study inundation dynamics over large areas because of their high temporal resolution. However, the low spatial resolution provided by MODIS is not appropriate to accurately delineate inundation over small scale. Successful downscaling of water inundation from coarse to fine resolution would be crucial for improving our understanding of complex inundation characteristics over the regional scale. Therefore, in this study, we propose an innovative downscaling method based on the normalized difference water index (NDWI) statistical regression algorithm towards generating small-scale resolution inundation maps from MODIS data. The method was then applied to the Poyang Lake of China. To evaluate the performance of the proposed downscaling method, qualitative and quantitative comparisons were conducted between the inundation extent of MODIS (250 m), Landsat (30 m) and downscaled MODIS (30 m). The results indicated that the downscaled MODIS (30 m) inundation showed significant improvement over the original MODIS observations when compared with simultaneous Landsat (30 m) inundation. The edges of the lakes become smoother than the results from original MODIS image and some undetected water bodies were delineated with clearer shapes in the downscaled MODIS (30 m) inundation map. With respect to high-resolution Landsat TM/ETM+ derived inundation, the downscaling procedure has significantly increased the R² and reduced RMSE and MAE both for the inundation area and for the value of landscape metrics. The main conclusion of this study is that the downscaling algorithm is promising and quite feasible for the inundation mapping over small-scale lakes.