Using modelled discharge to develop satellite-based river gauging: a case study for the Amazon Basin

Abstract

Abstract. River discharge measurements have proven invaluable to monitor the global water cycle, assess flood risk, and guide water resource management. However, there is a delay, and ongoing decline, in the availability of gauging data and stations are highly unevenly distributed globally. While not a substitute for river discharge measurement, remote sensing is a cost-effective technology to acquire information on river dynamics in situations where ground-based measurements are unavailable. The general approach has been to relate satellite observation to discharge measured in situ, which prevents its use for ungauged rivers. Alternatively, hydrological models are now available that can be used to estimate river discharge globally. While subject to greater errors and biases than measurements, model estimates of river discharge do expand the options for applying satellite-based discharge monitoring in ungauged rivers. Our aim was to test whether satellite gauging reaches (SGRs), similar to virtual stations in satellite altimetry, can be constructed based on Moderate Resolution Imaging Spectroradiometer (MODIS) optical or Global Flood Detection System (GFDS) passive microwave-derived surface water extent fraction and simulated discharge from the World-Wide Water (W3) model version 2. We designed and tested two methods to develop SGRs across the Amazon Basin and found that the optimal grid cell selection method performed best for relating MODIS and GFDS water extent to simulated discharge. The number of potential river reaches to develop SGRs increases from upstream to downstream reaches as rivers widen. MODIS SGRs are feasible for more river reaches than GFDS SGRs due to its higher spatial resolution. However, where they could be constructed, GFDS SGRs predicted discharge more accurately as observations were less affected by cloud and vegetation. We conclude that SGRs are suitable for automated large-scale application and offer a possibility to predict river discharge variations from satellite observations alone, for both gauged and ungauged rivers.

Reply on RC1

“…To distinguish the respective influences of human activity and climate variability on reservoir dynamics, greater collaboration and public sharing of in situ data on reservoir storage, water release and downstream water use would be requireed. In some basins, satellite-derived upstream and downstream river discharge dynamics (Hou et al 2020;Hou et al 2018) and changes in irrigation area or evaporation (Van Dijk et al 2018) may be able to provide additional information to better understand the drivers of reservoir water security. The algorithm from Zhao and Gao (2018) could in principle be used to calculate reservoir surface water extent time series beyond 2015, but is reliant on the availability of Landsat-derived GSWD (Pekel et al 2016).…”

Hydromorphological attributes for all Australian river reaches derived from Landsat dynamic inundation remote sensing

“…climate change. The dataset developed here may also be useful in providing fundamental information for understanding hydrological, biogeochemical, and ecological processes in floodplain-river systems; describing river width features in hydrological modelling; estimating river depth and discharge; assessing river conveyance capacity; identifying flooding-prone areas, and determining potential locations for satellite-based river gauging (Hou et al, 2018).…”

A Review of Earth Observation-Based Analyses for Major River Basins

“…Accordingly, estimation of river discharge is possible using indirect EO-based approaches [204]. Regarding river basins, studies are performed the Amazon [205,206], Brahmaputra [207,208], Congo [209], Mekong (e.g., [210,211]), and Yangtze river (e.g., [212]). Here, common methods to retrieve river discharge are rating curves (e.g., [213]) or the Manning's equation (e.g., [214]).…”