2012 AGU Chapman Conference on Remote Sensing of the ...

esearch and applications projects enabled by GRACE. Theseinclude the following: 1) global monitoring of interannualvariability of terrestrial water storage and groundwater; 2)water balance estimates of evapotranspiration over severallarge river basins; 3) NASA’s Energy and Water Cycle Study(NEWS) state of the global water budget project; 4) droughtindicator products now being incorporated into the U.S.Drought Monitor; 5) GRACE data assimilation over severalregions.Rodriguez, ErnestoThe Measurement of Reach-Averaged Discharge bythe SWOT MissionRodriguez, Ernesto 1 ; Neal, Jeffrey 2 ; Bates, Paul 2 ;Biancamaria, Sylvain 3 ; Mognard, Nelly 31. Jet Propulsion Laboratory/Cal Tech, Pasadena, CA, USA2. School of Geographical Sciences, University of Bristol,Bristol, United Kingdom3. LEGOS, Toulouse, FranceThe proposed NASA/CNES Surface Water and OceanTopography (SWOT) mission will collect globalmeasurements of elevation and extent for all continentalwater bodies, as well as floodplain topography. From thesedata, the calculation of storage change will bestraightforward, and the prime hydrology objective for themission. In addition to storage change, globally distributedestimates of discharge can contribute significantly to theunderstanding of the water cycle and its geographicalvariability. There are two primary routes for obtainingdischarge from the SWOT measurements: 1) assimilation ofelevations and water extent into a dynamic model; or, 2)estimation of discharge using the SWOT observables andManning’s equation, to obtain an estimate of the dischargeat the time of observation. The second approach has theadvantage that it is less contaminated by limitations in thedynamic models, mostly due to the SWOT temporalsampling pattern, and we will examine it here. In the firstpart, we show how from the SWOT measurements, estimatescan be obtained for the terms in Manning’s equation: slope,river cross-section, and width. We also show that stableestimates can be obtained by averaging along the river reach.(A part of the channel bathymetry will not be measured bySWOT directly, and its estimation from SWOT time series isaddressed by Rodriguez and Durant in a separatepresentation in this conference). We next show that, giventhe noise level in the SWOT measurements, a naïveapplication of Manning’s equation will result in estimates ofdischarge that have unacceptable distributions, includinglarge relative biases and variances. To overcome thislimitation, we introduce the concept of reach averaging theSWOT observables, and show that, after sufficient averaging(from 1 km to 10 km), Gaussian estimates with acceptablenoise can be obtained by replacing these reach averagedquantities in Manning’s equation. However, due to thenonlinear relation between the SWOT observables and thedischarge, it will certainly be the case that using the reachaveragedSWOT observables will not result in a validestimate of the reach averaged discharge. However, byexamining the effects of averaging on the St Venantequations, we show that a functionally identical relationshipexists between the reach averaged discharge and the reachaveraged parameters: the only change that needs to be madeis an adjustment of the friction coefficient to account forthe fluctuations ignored by the reach averaging. We obtainan analytic expression for the scaled friction coefficient. Thisanalytic expression is then validated by comparison againstthe results from numerical models for a set of different rivertypes. We conclude that the estimation of reach-averagedriver discharge at the time of observation is viable using theSWOT data alone, independent of an underlying dynamicmodel. These globally distributed estimates of instantaneousdischarge, which can be obtained every