Exploiting CryoSat-2 altimetry for surface water monitoring and modeling

Abstract

Water shortages, floods, and droughts pose global challenges. The past decade saw severe water scarcity and flooding. The world’s population continues to soar and temperature is ever rising, meaning that the freshwater we have is under severe pressure. However, we have poor knowledge of the spatial and temporal dynamics of freshwater at large scales. Remote sensing has proven useful in water resources monitoring as well as hydrological and geomorphological modeling. This is the main motivation of this research: monitoring water resources from space. Satellite altimetry allows us to measure water surface elevation, its slope, and temporal variation. Most satellite altimetry missions (Jason series, ERS/Envisat/SARAL, etc.) have a short repeat period, i.e. 10 to 35 days while CryoSat-2 has a 369-day long repeat (geodetic orbit). However, short-repeat altimeters miss too many water bodies due to their coarse ground track spacing. Thanks to its geodetic orbit, CryoSat-2 allows a high number of water bodies to be monitored. This also provides a more highly resolved water surface elevation profile of rivers that have not been well sampled before. In the meantime, these benefits come at the cost of long repeat cycle. This particularly poses challenges to derive time series of water level at virtual stations, which are commonly used for short-repeat altimeters. Therefore, one research question is “Can we use distributed CryoSat-2 data for river modeling beyond the ‘virtual station’ concept?” The contributions of this PhD project are to exploit CryoSat-2 for surface water resources monitoring in China at national scale and for hydrodynamic modeling. The aim is to understand spatiotemporal variations of freshwater resources as well as hydrodynamic modeling without precise knowledge of bathymetry. How do lakes and reservoirs change and how can CryoSat-2 help to understand these variations? This motivates the study of water level variation of water bodies. This work demonstrates the great spatial coverage of CryoSat-2. Over 1000 lakes and reservoirs, and 6 large rivers were investigated. RMSE of CryoSat-2 over lakes is around 20 cm, and around 40 cm for most rivers, except the Yangtze and Pearl rivers. Most lakes in the Tibetan Plateau, especially those in the northern part, maintained the rising trend seen by ICESat during 2003 - 2009. Moreover, water bodies in the Junggar Basin and Huai River Basin showed a dominant declining trend. In contrast, those in the Songnen Plain, lower Yangtze River basin showed a marked rising trend. To understand surface water storage dynamics and its contribution to total water storage change, we estimated both surface and total water storage change by combining CryoSat-2 with water extent maps and GRACE total storage change estimates. The estimated surface water storage changes in the Tibetan Plateau, and Inner Mongolia-Xinjiang are 35.5 and 25.9×108 m3/yr, respectively. On the contrary, the northeast China zone exhibited a decline. Changes in volume indicate that surface water variation contributes significantly to total storage variation, especially in the Qaidam Basin and the Tibetan Plateau, and should therefore not be omitted in land surface models. Finally, calibration of a 1D hydrodynamic model (MIKE HYDRO River) was carried out in the Songhua River, where no bathymetry information is available. CryoSat-2 data and data from other short-repeat satellite altimeters were used to calibrate distributed river morphological parameters, i.e. roughness and river datum jointly. Clearly, CryoSat-2 by far outperforms other altimeters in both synthetic and real-world experiments. The results also show that a higher accuracy of observations does not proportionally decrease parameter uncertainty for all cross sections. Instead, high spatial sampling density (such as CryoSat-2 and Envisat) helps to identify the spatial variability of morphological parameters. The results from this project shed light on the added value of CryoSat-2 for surface water monitoring and river modeling over China. This dataset shows the spatiotemporal variation of surface water resources at continental scale with the unique sampling pattern of CryoSat-2. This is valuable for water resource monitoring in an efficient and cost-effective way, especially for sparsely gauged or ungauged regions. Moreover, the dataset is valuable for hydrodynamic modeling considering the lack of bathymetry information for many rivers. In addition, this work is timely because the upcoming Surface Water and Ocean Topography mission will significantly improve spatial and temporal resolution of spaceborne observations of water surface elevation, and hydraulic models need to be prepared for the uptake of these data.