Abstract
Abstract. The objective of this study is to evaluate the potential of large altimetry datasets as a complementary gauging network capable of providing water discharge in ungauged regions. A rating curve-based methodology is adopted to derive water discharge from altimetric data provided by the Envisat satellite at 475 virtual stations (VS) within the Amazon basin. From a global-scale perspective, the stage–discharge relations at VS are built based on radar altimetry and outputs from a modeling system composed of a land surface model and a global river routing scheme. In order to quantify the impact of model uncertainties on rating-curve based discharges, a second experiment is performed using outputs from a simulation where daily observed discharges at 135 gauging stations are introduced in the modeling system. Discharge estimates at 90 VS are evaluated against observations during the curve fitting calibration (2002–2005) and evaluation (2006–2008) periods, resulting in mean normalized RMS errors as high as 39 and 15% for experiments without and with direct insertion of data, respectively. Without direct insertion, uncertainty of discharge estimates can be mostly attributed to forcing errors at smaller scales, generating a positive correlation between performance and drainage area. Mean relative streamflow volume errors (RE) of altimetry-based discharges varied from 15 to 84% for large and small drainage areas, respectively. Rating curves produced a mean RE of 51% versus 68% from model outputs. Inserting discharge data into the modeling system decreases the mean RE from 51 to 18%, and mean NRMSE from 24 to 9%. These results demonstrate the feasibility of applying the proposed methodology to the continental or global scales.
Highlights
In the last decades, the hydrological sciences community has experienced significant advances in the understanding of water storage and transport over the continents using remote sensing data
This study evaluates a methodology where stage–discharge relations are based on rating curves derived from Envisat data and simulated discharges provided by the Hydrological Modeling and Analysis Platform (HyMAP) flow routing scheme (Getirana et al, 2012) coupled in off-line mode with the Interactions Sol-Biosphere-Atmosphere (ISBA) (Noilhan and Mahfouf, 1996) land surface model (LSM)
This study evaluates a methodology to predict water discharges from radar altimetry data with potential applications at the global scale
Summary
The hydrological sciences community has experienced significant advances in the understanding of water storage and transport over the continents using remote sensing data. Most applications have attempted to retrieve water discharges from stage– discharge relations derived from altimetric data and observed discharges from gauging stations located in the vicinity of the VS. These relations are commonly represented by rating curves and allow one to predict water discharges from observed water levels, with accuracy varying as a function of input data and flow regime characteristics. Other studies have taken advantage of radar altimetry data to make forecasts at gauges downstream of a virtual station. Coe and Birkett (2004) first suggested and applied this idea to forecast downstream discharges and levels in Lake Chad. Similar approaches have been applied in a few other studies to forecast downstream discharges in the Mekong River (Birkinshaw et al, 2010) and downstream water levels in the Ganges and Brahmaputra Rivers (Biancamaria et al, 2011)
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