SWOT Hydrology Virtual Mission, Sept. 22, 2010, Paris

Aaron Boone

CNRM-GAME Météo-France

Results from: Augusto Getirana (CNRM), Jhan-Carlo Espinoza (LMTG, IPH, CNRM) and Vanessa Pedinotti (CNRM)

Collaborations with: LEGOS (N. Mognard, J.-F. Cretaux, S. Biancamaria), LMTG (M.-P. Bonnet, S. Calmant), LERMA (C.

Prigent), LTHE (L. Descroix, T. Vischel), CNRM (B. Decharme), IPH

Funding: CNES (TOSCA Grant), Midi-Pyrénées Region

SWOT Hydrologic Modeling Activites: A Large Scale Niger Application and towards a global Hydrodynamic-

Hydrological system

SWOT Hydrology Virtual Mission, Sept. 22, 2010, Paris

Vanessa Pedinotti: Thesis directors: A. Boone (CNRM-GAME, Météo-France) and N. Mognard (CNES/LEGOS)

Collaborations: Bertrand Decharme (CNRM-GAME), Luc Descroix (LTHE), Jean-François Cretaux (CNES/LEGOS), C. Prigent (LERMA), T. Vischel (LTHE)

Thesis: Preparation for the Surface Water Ocean Topography mission: The use of wide-swath altimetry for modeling hydrological and hydrodynamic

processes in West Africa as a part of the AMMA Project

Resumé 2010: • Set up SURFEX model configuration (using ISBA and TRIP) over the Niger bassin• Evaluation of different forcing inputs (rainfall: TRMM, CMORPH, PERSIANN), evaluation of simulated flood extent using satellite data, discharge evaluation…• Use TRIP-Offline (classic configuration) to simulate discharge from ALMIP (10 LSM models)• Simulations and sensitivity tests using fully coupled floodplain and simple aquifer representation• Results presented at the AGU of the Americas, Foz, Brazil, July, 2010

ISBA/TRIP modeling of the Niger basin

SWOT Hydrology Virtual Mission, Sept. 22, 2010, Paris

ISBA/TRIP modeling of the Niger basin

0.5 deg resolution, 2002-2007

ISBA

TRIP

ISBA/TRIP (Oki et al., 1999)

Niamey, Niger« delta region » ISBA/TRIP coupling: Decharme et al., 2007

Niamey

SWOT Hydrology Virtual Mission, Sept. 22, 2010, Paris

Water extent developed from a classification based on MODIS data: fraction represent coverage over delta region

Satellite Product: Flooded Zones (from J.-F. Cretaux, LEGOS)

ISBA/TRIP modeling of the Niger basin

Max extent

Min extent

SWOT Hydrology Virtual Mission, Sept. 22, 2010, Paris

ISBA/TRIP modeling of the Niger basin

• Using TRIP alone (offline) with LSM runoff: overestimate of discharge, rapid recession

• Coupled system: better timing and volume

Perspectives 2011:- Use GRACE to better estimate/constrain water budget components, and additional water fractional coverage product (Prigent)

- Perform more sensitivty tests towards parameter estimation optimization

- Use MGB simulation by Jhan-Carlo as « SWOT observation » to develope assimilation

SWOT Hydrology Virtual Mission, Sept. 22, 2010, Paris

PreviousWorkdischarge,waterlevelandfloodinundationinSolimõesRiversimulationresultsfromMGB-IPHhydrodynamicmodel:

- Full Saint Venant equations

- Simple storage model for flood inundation

Rio

Rio AmazonasRio Negro

Rio Ta

pajó

s

Rio Xingu

Rio

Ara

guai

a

Rio

Toc

antin

s

Rio Mad

eira

Rio

Rio Ju

ruá

Rio Solimões

Puru

s

Rio Japurá

Solimões

Rio U

cayali

45° W

45° W

50° W

50° W

55° W

55° W

60° W

60° W

65° W

65° W

70° W

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75° W

80° W

80° W

5° N 5° N

0° 0°

5° S 5° S

10° S 10° S

15° S 15° S

20° S 20° S

SWOT Hydrology Virtual Mission, Sept. 22, 2010, Paris

Estimationofdischarge:2004-2005

Largeriver smallriver

*SWOT–MGB-IPH

ComputedischargeusingManningequation:

Estimationofdischarge:2004-2005

MGB-IPHhydrologicalandhydrodynamicsimulationonPurusriverbasinModelparameterscalibratedusingstreamgaugedata1) Synthetic SWOT data using the calibrated

MGB-IPH model2) Automatic calibration of MGB-IPH modelusing the previously simulated SWOT data

SWOT Hydrology Virtual Mission, Sept. 22, 2010, Paris

Estimationofdischarge:2004-2005

Largeriver smallriver

*SWOT–MGB-IPH

ComputedischargeusingManningequation:

Estimationofdischarge:2004-2005

MGB-IPHhydrologicalandhydrodynamicsimulationonPurusriverbasin

1) Generate Synthetic SWOT data using the calibrated MGB-IPH model

2) Automatic calibration of MGB-IPH model using the previously simulated SWOT data

SWOT Hydrology Virtual Mission, Sept. 22, 2010, Paris

NigerRiver:4,180 km

Area:2,117,700km2

HydrodynamicsimulationofNigerRiverusingMGB-HDmodel

MGB-HDPre-processingisnowcompletedFirstestofMGB-IPH

Preparation of forcing and physiographic parameters

River Network

Vegetation and Soils from ECOCLIMAP

Segmentation: HRUs

SWOT Hydrology Virtual Mission, Sept. 22, 2010, Paris

SRTM500m

12HRU

Minibasins1982~1000km2

NigerRiver:4,180 km

Area:2,117,700km2

HydrodynamicsimulationofNigerRiverusingMGB-HDmodel

MGB-HDPre-processingisnowcompletedFirstestofMGB-IPH

Preparation of forcing and physiographic parameters

River Network

Vegetation and Soils from ECOCLIMAP

Segmentation: HRUs

SWOT Hydrology Virtual Mission, Sept. 22, 2010, Paris

River Routing Network: Ouémé basin, BeninALMIP2: Benin meso-square

2

one, A., AA. Boone, A. C. V. Getirana, J. Demarty, B. Cappelaere, S. Galle, M. Gosset, M. Grippa, T. Lebel, E. Mougin, C. Peugeot, G. Quantin, L. Seguis, J. Viarre and T. Vischel +

others!!!GEWEX News, November, 19(4), 2009

Goal: Develop a simple routing scheme for the mesoscale which can be used to transfer LSM runoff through a river network.

Used to evaluate and intercompparehydrology from multiple LSMs (Météo-France, NCEP, ECMWF, UKmetOff etc…) and compare to « pure » hydrological models (e.g. TOP-AMMA etc.)

SWOT Hydrology Virtual Mission, Sept. 22, 2010, Paris

0

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1/1/2005 1/1/2006 1/1/2007 1/1/2008

obs

ISBA+MC

Nash=0.89

R=0.94

Bias=-3.6%Discharge simulated by ISBA 2005-2008 at Beterou, BeninAfter calibration of 3 MC parameters

Perspectives for SWOT:• Use the same model towards a global scale approach (post-doc 2010-2011, CNES)• Designed to be rapid, automatic (as possible) determination of river network(see next talk)

2

SWOT Hydrology Virtual Mission, Sept. 22, 2010, Paris

Perspectives:1) Finalize large scale modeling of the Niger using ISBA-TRIP

• Improve simple aquifer representation, use GRACE to try to better quantify large scale storage

• Evaluate flooded fraction of delta region with additional datatset (Prigent)

• Perform a parameter optimization (using discharge): try to obtain more discharge data

• Examine impact of improved vegetation datatbase (including annual cycle)

• Test uncertainties related to meteoroloigcal forcing: notably precipitation: TRMM, PERSIANN, CMORPH

2) Begin optimization/assimilation work è SWOT preparation

• Inter-Compare ISBA-TRIP results with more detailed approach using MGB (Jhan Carlo, Marie-Paul Bonnet, Stéphane Calmant)

l Develop assimilation scheme/strategy (first test, use MGB simulation as « SWOT measurement »)

3) Begin working on global methodology for SWOT (see next talk)