As a significant hydrological parameter, the water level of complex and shallow river-lake wetland has important implications for a number of hydrological, biological, physical and chemical processes. Current in-situ and satellite-based methods both have disadvantages in capturing water levels over smaller surface water bodies with spatial heterogeneity or complexity. Interferometric imaging radar altimeter (InIRA) is a latest generation of Ku-band radar altimeter onboard Tiangong-2 (TG-2), the Chinese space laboratory, launched in 2016. Similar to the design idea of NASA’s SWOT, it is expected to improve this situation through wide-swath altimetry. However, the capacity of the TG-2 InIRA to measure water levels within small surface water bodies remains unexamined. To explore these performances, particularly their potential impact on hydrology research, an assessment and comparison between in-situ and TG-2 derived measurements was performed over the largest river-lake wetland in China. The results showed that the TG-2 InIRA, with a broad range of coverage, was able to effectively capture most of the surface water at its elevation. For the focused shallow depressions, a relatively good correlation was observed between the in-situ and InIRA-derived water surface elevations (WSEs), with an R2 of 0.97, RMSE of 0.29 m, and absolute difference ranging from 3 to 55 cm. The accuracy of InIRA-derived WSEs was highly controlled by the depression sizes, and the absolute biases broadly increased in a power law fashion as the size of the depression decreased. In addition, surface water profiles along the Ganjiang and Xiushui River channels indicated that the TG-2 InIRA could also measure river WSEs, with absolute differences below 0.43 m. Although differences were observed, the results of the river gradient distribution were consistent with the practical situation and showed overall slopes of 18.72 cm/km and 12.43 cm/km for the Xiushui and Ganjiang Rivers, respectively. Such results demonstrated that TG-2 InIRA measurements can satisfactorily capture spatial patterns of the surface water gradient, which is useful for accurately estimating river discharge. This study will not only bridge the gap between in-situ measurements and forthcoming SWOT products but also contribute to water resource management and hydrologic service assessments over data-sparse regions of river-lake systems within the study area.
Read full abstract