Background Interferometric Synthetic Aperture Radar (InSAR) has become a promising technique for monitoring wetland water levels. However, its capability in monitoring wetland water level changes with Sentine-1 data has not yet been thoroughly investigated. Methods In this study, we produced a multitemporal Sentinel-1 C-band VV-polarized SAR backscatter images and generated a total of 28 interferometric coherence maps for marsh wetlands of China’s Momoge National Nature Reserve to investigate the interferometric coherence level of Sentinel-1 C-VV data as a function of perpendicular and temporal baseline, water depth, and SAR backscattering intensity. We also selected six interferogram pairs acquired within 24 days for quantitative analysis of the accuracy of water level changes monitored by Sentinel-1 InSAR. The accuracy of water level changes determined through the Sentinel-1 InSAR technique was calibrated by the values of six field water level loggers. Results Our study showed that (1) the coherence was mainly dependent on the temporal baseline and was little affected by the perpendicular baseline for Sentinel-1 C-VV data in marsh wetlands; (2) in the early stage of a growing season, a clear negative correlation was found between Sentinel-1 coherence and water depth; (3) there was an almost linear negative correlation between Sentinel-1 C-VV coherence and backscatter for the marsh wetlands; (4) once the coherence exceeds a threshold of 0.3, the stage during the growing season, rather than the coherence, appeared to be the primary factor determining the quality of the interferogram for the marsh wetlands, even though the quality of the interferogram largely depends on the coherence; (5) the results of water level changes from InSAR processing show no agreement with in-situ measurements during most growth stages. Based on the findings, we can conclude that although the interferometric coherence of the Sentinel-1 C-VV data is high enough, the data is generally unsuitable for monitoring water level changes in marsh wetlands of China’s Momoge National Nature Reserve.

Connectivity metrics for surface water are important for predicting floods and droughts, and improving water management for human use and ecological integrity at the landscape scale. The integrated use of synthetic aperture radar (SAR) observations and geostatistics approach can be useful for developing and quantifying these metrics and their changes, including geostatistical connectivity function (GCF), maximum distance of connection (MDC), surface water extent (SWE), and connection frequency. In this study, we conducted a geostatistical analysis based on 52 wet and dry binary state (i.e., water and non-water) rasters derived from Sentinel-1 A/B GRD products acquired from 2015 to 2019 for China’s Momoge National Nature Reserve to investigate applicability and dynamics of the hydrologic connectivity metrics in an ungauged (i.e., data such as flow and water level are scarce) multi-lake system. We found: (1) generally, the change of GCF in North–South and Northeast–Southwest directions was greater than that in the West–East and Northwest–Southeast directions; (2) MDC had a threshold effect, generally at most 25 km along the W–E, NW–SE and NE–SW directions, and at most 45 km along the N–S direction; (3) the flow paths between lakes are diverse, including channelized flow, diffusive overbank flow, over-road flow and “fill-and-merge”; (4) generally, the values of the three surface hydrological connectivity indicators (i.e., the MDC, the SWE, and the conneciton frequency) all increased from May to August, and decreased from August to October; (5) generally, the closer the distance between the lakes, the greater the connection frequency, but it is also affected by the dam and road barrier. The study demonstrates the usefulness of the geostatistical method combining Sentinel-1 SAR image analysis in quantifying surface hydrological connectivity in an ungagged area. This approach should be applicable for other geographical regions, in order help resource managers and policymakers identify changes in surface hydrological connectivity, as well as address potential impacts of these changes on water resources for human use and/or ecological integrity at the landscape level.