Global Drought and Flood. Группа авторов

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Global Drought and Flood - Группа авторов


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there is a strong agreement between the Landsat based RAFI and U.S. Geological Survey observed elevation values at Lake Whitney (Texas). By developing drought indices from the remotely sensed reservoir area, true global monitoring capability can be achieved. Furthermore, the decades of available Landsat data can offer insightful information for long‐term planning.

Graphs depict the comparison of remotely sensed surface area with observed storage/elevation for nine reservoirs.

      (Source: From Zhao, G., & Gao, H. (2018). Automatic Correction of Contaminated Images for Assessment of Reservoir Surface Area Dynamics. Geophysical Research Letters. 45(12), 6092–6099. © 2018, John Wiley & Sons.)

      In contrast, the physically based, distributed LHMs, which do not have a reservoir component, have been well adopted for monitoring agricultural drought at the continental and global scales. Examples include (but are not limited to) the North American Land Data Assimilation System (NLDAS) Drought Monitor (http://www.emc.ncep.noaa.gov/mmb/nldas/drought/), the Princeton United States and Global Drought Monitor (http://hydrology.princeton.edu/forecast/current.php), and the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) (http://drought.eng.uci.edu/). Although some of these drought monitors also use modeled streamflows as indicators, they are often biased because they do not consider the effects of reservoir flow regulations in their routing scheme. The most reliable streamflow based monitor is the U.S. Geological Survey Water Watch (https://waterwatch.usgs.gov), which collects national scale observed gauge data. However, it is impossible to set up monitors of this kind over most of the world due to the lack of gauge data (Kugler & De Groeve, 2007). Indeed, as pointed out by Wada et al. (2017) and other studies (Fekete et al., 2015; Lawford et al., 2013), there is a critical need for comprehensive data for purposes of calibrating and evaluating hydrological models over continental to global scales.

Schematic illustration of (a) monthly average precipitation and SPI with a 6-month timescale for the upstream area of Lake Whitney, Texas. (b) Comparison of RAFI with U.S. Geological Survey monitored elevation for Lake Whitney.

      (Source: From Li, Y., Gao, H., Jasinski, M. F., Zhang, S., & Stoll, J. D. (2019). Deriving High‐Resolution Reservoir Bathymetry from ICESat‐2 Prototype Photon‐Counting Lidar and Landsat Imagery. IEEE Transactions on Geoscience and Remote Sensing, 57(10), 7883–7893. © IEEE.)

      Second, the number of VIS/NIR/SWIR sensors in orbit has been increasing drastically, and high‐resolution imagery is now being collected more frequently than ever. For instance, the twin satellites Sentinel‐2A (since 2015)


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