Estimating water discharge from large radar altimetry datasets

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)(2003)(2004)(2005) and evaluation (2006)(2007)(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.

Monitoring Water Levels and Discharges Using Radar Altimetry in an Ungauged River Basin: The Case of the Ogooué

“…This technique have been successfully applied to estimate river discharge using altimetry-based water levels when it was possible to derive the rating curve a common period of observation. It permits to derive river discharge with accuracy better than 20% (e.g., [18][19][20]22,[46][47][48]).…”

Application of an automated LSPIV system in a mountainous stream for continuous flood flow measurements

“…Conventionally, discharge measurements of rivers without an established gauging station can be conducted using current metres (i.e. mechanical devices such as impellers or rotating cups; Rantz, 1982), acoustic Doppler velocimeters (Muste et al, 2007), acoustic Doppler current profilers (Gordon, 1989;Oberg and Mueller, 2007;Simpson, 2001;Yorke and Oberg, 2002), remote sensing methods (Birkinshaw et al, 2014;Costa et al, 2006;Getirana and Peters-Lidard, 2013) or estimation by postevent dendrogeomorphic evidence analysis (Ballesteros Cánovas et al, 2011;Ruiz-Villanueva et al, 2010). It is, however, not only time consuming and labour intensive, but also unsafe and technically difficult to extend intrusive techniques to conduct field measurements during high flow events.…”

Assimilation of radar altimetry to a routing model of the Brahmaputra River

“…Getirana et al . [2009] and Getirana and Peters‐Lidard [] developed rating curves based on altimetric level measurements and modeled discharge from a hydrological model and a routing scheme, respectively, in order to estimate river discharge.…”