References Alsdorf, D. E., E. Rodriguez, and D. P. Lettenmaier (2007), Measuring surface water from space, Rev. Geophys., 45(2). Bates, P. D., and A. P. J. De Roo (2000), A simple raster-based model for flood inundation simulation, J. Hydrol., 236(1-2), 54–77. Beighley, R. E., K. G. Eggert, T. Dunne, Y. He, V. Gummadi, and K. L. Verdin (2009), Simulating hydrologic and hydraulic processes throughout the Amazon River

Basin, Hydrol. Process., 23(8), 1221–1235, doi:10.1002/hyp.7252. Collischonn, W., D. G. Allasia, B. C. Silva, C. E. M. Tucci, (2007), The MGB-IPH model for large-scale rainfall-runoff modelling. Hydrological Sciences Journal, v.

52, p. 878-895, 2007. David, C. H., D. R. Maidment, G.-Y. Niu, Z.-L. Yang, F. Habets and V. Eijkhout, (2011) River network routing on the NHDPlus dataset, Journal of

Hydrometeorology, 12(5), 913-934, DOI: 10.1175/2011JHM1345.1 David, C. H., J. S. Famiglietti, Z.-L. Yang, and V. Eijkhout (2015), Enhanced fixed-size parallel speedup with the Muskingum method using a trans-boundary

approach and a large sub-basins approximation, Water Resources Research, 51(9), 1-25, DOI: 10.1002/2014WR016650 Decharme, B., R. Alkama, F. Papa, S. Faroux, H. Douville, and C. Prigent (2012), Global off- line evaluation of the ISBA-TRIP flood model, Clim. Dyn., 38(7-8),

1389–1412, doi:10.1007/s00382-011-1054-9. Fry, L. M. et al. (2014), The Great Lakes Runoff Intercomparison Project Phase 1: Lake Michigan (GRIP-M), J. Hydrol., 519, Part D(0), 3448–3465, doi:10.1016/

j.jhydrol.2014.07.021. Kouwen, N. (2010), WATFLOOD / WATROUTE Hydrological Model Routing & Flow Forecasting System, Department of Civil Engineering, University of

Waterloo, Waterloo, ON, Canada. Oki, T., Y. C. Sud (1998), Design of Total Runoff Integrating Pathways (TRIP)—A Global River Channel Network, Earth Interactions, 2, 1-36. Pedinotti, V., A. Boone, S. Ricci, S. Biancamaria, and N. Mognard (2014), Assimilation of satellite data to optimize large-scale hydrological model parameters: a case

study for the SWOT mission, Hydrol Earth Syst Sci, 18(11), 4485–4507, doi:10.5194/hess-18-4485-2014. Rodell, M. et al. (2004), The Global Land Data Assimilation System, Bull. Am. Meteorol. Soc., 85(3), 381–394. Yamazaki, D., S. Kanae, H. Kim, and T. Oki (2011), A physically based description of floodplain inundation dynamics in a global river routing model, Water Resour.

Res., 47(4), W04501. Acknowledgments This work was supported by the U.S. National Aeronautics and Space Administration under NASA Research Announcement NNH15ZDA001N (SWOT Science Team). C. H. David, K. M. Andreadis, J. S. Famiglietti and E. Rodriguez are supported by the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA.

Preparing for the ingestion of SWOT data into continental-scale river models

INTRODUCTION

Giventhelackofexis1ngSWOT-likeobserva1onsatcon1nentaltoglobalscales,macroscalehydromodels are currently our bestway of es;ma;ng the spa;otemporal varia;ons ofsurfacewaterfeaturesthatshouldbeobservedbySWOTatcon;nentalscaleandatsub-monthly;mesteps. Addi1onally,onecouldhopethattheunprecedentedobserva1onswillhelp improvingourunderstandingandmodelingcapabili1es for theglobal terrestrialwatercycle and of the climate system, although therewill remain spa1otemporal gaps betweenSWOT retrievals. The ability of SWOT land measurements to directly contribute to ourunderstanding of terrestrial hydrology and of the climate systemwill therefore likely bedemonstratedthroughtheirintegra;onwithinmodels.

OBJECTIVES

INTEGRATIONANDINTER-COMPARISON

Cédric H. David1, Konstantinos M. Andreadis1, James S. Famiglietti1, R. Edward Beighley2, Aaron A. Boone3, Dai Yamazaki4, Hyungjun Kim5, Etienne Gaborit6, Ernesto Rodriguez1, Sylvain Biancamaria7, Rodrigo Paiva8, Guy J.-P. Schumann9

PRELIMINARYRESULTS

Weare combining an inter-comparison framework consis1ng of a series ofeighthorizontalwatertransferschemes:CaMa-Flood[Yamazakietal.,2011],HRR[Beighleyetal.,2009], ISBA-TRIP [Decharmeetal.,2012],LISFLOOD-FP[BatesanddeRoo,2000],MGB-IPH[Collischonnetal.2007],RAPID[Davidetal.,2011],TRIP [OkiandSud,1998],andWATFLOOD[Kouwenetal.,1993].ThesemodelswillbefedbyrunoffproducedbythefourlandsurfacemodelsofNASA’sGlobalLandDataAssimila1onSystem[Rodelletal.,2004].

LargestriversexpectedtobeseenbySWOT,andrestofthenetworkinpartoftheMissouriRiverBasin

Thelargestbasinsstudiedwithmodels:1)theMississippi[Davidetal.,2015],b)Saint-Lawrence[Fryetal.,2014],c)Niger[Pedino`etal.,2014],d)Amazon[Beighleyetal.,2009]. ExpectednumberofSWOToverlaysperrepeatcycleonthe

largestriversoftheMississippiRiverBasin,usingrivernetworkofDavidetal.[2015]

P re l im inary work has sub - sampledcon1nental-scale model outputs based on atenta1veSWOTtrajectory.

This endeavorwas performed as communityeffortandisopenlyaccessibletoall.

(1)   Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States (2)   Northeastern University, Irvine, Boston, MA, United States (3)   CNRM-GAME Meteo-France, Toulouse, France (4)   Japan Agency for Marine-Earth Science and Technology, Yokosuka, Kanagawa, Japan (5)   University of Tokyo, Tokyo, Tokyo, Japan (6)   Environment Canada, Montreal, Canada (7)   LEGOS, Toulouse, France (8)   Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil (9)   Remote Sensing Solutions Inc., Pasadena, CA, USA

Theprimaryobjec1vesofthisprojectaretoshedlightontheexpectedSWOTobserva;onsat con;nental to global scaleand to inves;gate the integra;on of SWOTmeasurementsintoaseriesofglobalhydromodels.WewillestablishaSWOT-friendlycon1nental-to-globalscalemodeling frameworkand focusouranalysisusing sixhydromodelsappliedover fourcon1nental-scale river basins spanning various climate zones and driving hydrologicprocesses. Our research will focus on answering the following two sets of relatedfundamentalscienceques1ons:1.  How canwe best prepare for the expected SWOT con1nental to globalmeasurements

before SWOT even flies? That is, how can we understand the rela1onships betweenexis1ngsurfacewatervaria1onsandexpectedSWOTlarge-scaleobservingcapabili1es?

2.  What is theaddedvalueof includingSWOT terrestrialmeasurements intoglobalhydromodels for enhancing our understanding of the terrestrialwater cycle and the climatesystem?ArecurrentglobalhydrologicmodelsreadytoingestexpectedSWOTdata?WhatSWOTvariable(s)orSWOT-derivedproduct(s)offerthebestpromiseforintegra1onandfordataassimila1on?

Scheduleofproposedtasks.Colorscorrespondtothestudydomains:Mississippi(blue),Niger(green),Saint-Lawrence(skin),andAmazon(purple)

Summaryofkeycharacteris1csofbasinsstudiedandpublishedmodelingapproaches

Theelementaryscriptsallowingtoperformtheabovetasksweredevelopedaspartofacommunityeffort

Experimentaldesign

Fouroftheworld’slargestbasinsinfouryearsTheSurfaceWaterandOceanTopography(SWOT) Mission [Alsdorf et al., 2007] istenta1vely scheduled for launch in 2021a n d i s e x p e c t e d t o p r o v i d eunprecedented observa;ons of width,heightandslopeforthelargestterrestrialwaterbodies,fromspace.

However, the waterscape features thatSWOT should unveil at sub-monthlyresolu;on and con;nental to globalscales currently remainmostlyunknown,especially the spa1al characteris1cs offlowwavepropaga1on.

SWOTlook-alikeatcon@nentalscale

Modelsimula@ons

MaximumflooddepthassimulatedbyCaMa-Flood(leg)andMGB-IPH(right)

We build on ongoing research in several ins1tu1ons to establish an interna1onalcollabora1on that focuses on understanding the best integra;on methods betweenexpectedSWOTterrestrialretrievalsandexis;ngglobalhydrologic/hydrodynamicmodels.

ThelargestriversandreservoirsoftheMississippiRiverBasin,fromDavidetal.[2015].

SWOTdatainthecontextofcon1nentaltoglobalscalehydromodeling

EventAmerican Geophysical Union FallMee1ng, San Francisco, CA, 12-16December2016.PosternumberH21F-1477SessionnumberH21F: Science and Applica1ons inPrepara1on for the SurfaceWaterand Ocean Topography (SWOT)SatelliteMissionIIPosters

Dischargesimula1onsfortheOhioRiveratMetropolis,ILusingRAPID(leg),MGB-IPH(center),andHRR(right)

Copyright2016.Allrightsreserved.Referencehereintoanyspecificcommercialproduct,process,orservicebytradename,trademark,manufacturer,orotherwise,doesnotcons1tuteorimplyitsendorsementbytheUnitedStatesGovernmentortheJetPropulsionLaboratory,CaliforniaIns1tuteofTechnology.