Discharge and water‐depth estimates for ungauged rivers: Combining hydrologic, hydraulic, and inverse modeling with stage and water‐area measurements from satellites. Issue 8 (3rd August 2015)

• Record Type: Journal Article
• Authors: Liu, Ganming; Schwartz, Franklin W.; Tseng, Kuo‐Hsin; Shum, C. K.
• Is Part Of: Water resources research. Volume 51:Issue 8(2015:Aug.)
• Page Start: 6017
• Page End: 6035
• Publication Date: 2015-08-03
• Subjects: Hydrology -- Periodicals; 333.91
• DOI: 10.1002/2015WR016971
• Languages: English
• ISSNs: 0043-1397

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p>Anticipating future global freshwater scarcity and providing mitigation require timely knowledge of spatiotemporal dynamics of discharge for gauged and, more challengingly, ungauged rivers. This study describes a coupled hydrologic (SWAT) and hydraulic (XSECT) modeling approach set in a genetic algorithm framework for estimating discharge and water depth for ungauged rivers from space. The method was tested in the Red River of the North basin by comparing simulated discharges and depths from 2006 to 2010 to in situ observations from across the basin. Results showed that calibration using only remotely sensed data (i.e., water levels from ENVISAT altimetry and water extents from LANDSAT) along the main stem of the Red River yielded daily and monthly estimates of river discharge, which correlated to measured discharges at three gaging stations on the main stem with <italic>R</italic><sup>2</sup> values averaging 0.822 and 0.924, respectively. The comparisons of modeled and measured discharges were also extended to smaller tributaries, yielding a mean <italic>R</italic><sup>2</sup> of 0.809 over seven gaging stations. The modeling approach also provided estimates of water depth that correlated to observations at four stations with an average <italic>R</italic><sup>2</sup> of 0.831. We conclude that the integrated modeling approach is able to estimate discharge and water depth from space for larger ungauged rivers. This study also implies that in situ discharge data may not be necessary for successful hydrologic model calibration.</p> </abstract>