How will SWOT How will SWOT observations inform observations inform hydrology models?hydrology models?

Eric Martin and Kostas Andreadis

SWOT Science Definition Team Meeting17-20 June 2014, Toulouse

BackgroundBackground

• Models developed with motivation of understanding the water cycleo Budget closureo Reproducing variability of processeso Impact and sensitivity studies

• Applications of water resources models can rangeo Long-term re-analyseso Prediction and forecasting at various scales (seasonal to decadal)o Earth system modeling components for climate change simulations

• Some disparity among models that depends on specific application

• Number of deficiencies that complicates reconciling models with observations

• Trade-offs between resolving processes and model area size

Global & regional water balanceGlobal & regional water balance

• Ability to close the water balance as a metric of model improvement

• How well do models perform over regional and global scales?

• What can we currently observe from remote sensing?

Observing each water balance Observing each water balance

termterm

• Uncertainties exist in each satellite observationo retrieval algorithms, representativeness of observations

• Observations of individual components do not close the water budget

GRACE

TRMM, GPM

SMOS, SMAP

MODIS

JASON, SENTINEL-3SARAL, MODIS

SWOT

Can models close the water Can models close the water

budget?budget?

• Models don’t agree with each othero even when forced by identical data

• Example comparison of runoff from PILPS-2

Role of river dischargeRole of river discharge

• Discharge acts as a basin-wide “integrator” of water fluxes

• Discharge dynamics vary both spatially and temporally

• Extensively used to calibrate & validate hydrology models

• Level 2.5 data product from SWOT• Indirectly estimated from SWOT observables• Number of candidate “direct estimation” algorithms

o Instantaneous estimates at a reach-averaged scale

• Through data assimilation into river hydraulic modelso Potentially continuous estimates across river network and between

observation times

State-of-the-art hydrology modelsState-of-the-art hydrology models

• Most large-scale hydrology models are essentially column models

• Flow routing schemes are rather simplified

Hydrodynamic modelsHydrodynamic models

• Water levels are usually not represented in hydrology models

• Need hydrodynamic models to accurately simulate processes in the river and floodplain

• Few models can be used to simulate large areaso Downscaling formulations could allow transforming 1-km to <100-m

scales

Example of downscaling

What can SWOT improve?What can SWOT improve?

• SWOT will provide observations of o Water storage changes in lakes and reservoirso Water inundation and surface elevationo River discharge

• Overview of improvements envisioned by SWOTo Model calibration and validationo Modeling and delineating lakes and wetlandso Deriving information on reservoir operationso Indirect estimation of water budget components (e.g. precipitation)o Forecasting using either hydrologic or hydrodynamic models

• As with every novel type of observation, there will probably be improvements in models that are not included hereo GRACE is a favorite example, especially in hydrology

At what scales can SWOT be At what scales can SWOT be

valuable?valuable?

• Spatial resolution of discharge observations will vary but on the order of few kilometers

• SWOT will provide observations at varying temporal frequencies (~7-10 days)

o Should be adequate for current state-of-the-art hydrologic models

o Hydrodynamic models usually have finer spatial resolution

o SWOT will only observe rivers wider than 50-100 m

o Should be adequate for model calibration

o It will be difficult to observe faster processes (e.g. flood wave propagation for most rivers)

o Higher latitudes will be better described

Spatial and temporal samplingSpatial and temporal sampling

• Example of the Garonne River over an orbit cycle

Model calibration and validationModel calibration and validation• Primarily hydrodynamic models• Water levels are usually used for model calibration

and validationo Many examples of using in-situ or altimeter measurements for calibration

• Use of SWOT water level observations would be seamlesso Spatially-distributed measurements should provide order-of-magnitude

improvement

• Discharge observations from SWOT can be directly used to calibrate hydrologic models

• Calibration for each sub-basin would lead to distributed parameters -> increased realism

Model calibration and validation Model calibration and validation

(cont’d)(cont’d)

• Despite coarser resolution of discharge relative to hydraulic modelso SWOT can provide boundary inflowso Provide a reach-averaged river channel bathymetry and roughness

• Adjust floodplain topography based on SWOT observations

• Water inundation observations have been used to calibrate against specific flood events

Model agreement with Observations

Model over- & under-prediction

Example from the Amazon main stem

Reducing errors in water budget Reducing errors in water budget

termsterms• Given the role of discharge, SWOT observations can be

assimilated to correct water budget imbalances

Unconstrained Constrained

• Example of Mississippi• Use of assimilation to

constrain water budget• Q from gauges – SWOT

should further improve technique

Water budget closure error

Lake water storage from SWOTLake water storage from SWOT

• Observations of water storage change

• Fine-scale determination of size and location of lakeso Especially important for Arctic lakes

• WSE and delineation of lakes is an indirect combination of the water budget and dynamics

• Ability to extend information on storage by developing area-storage relationships

• Interpretation of the measurements requires models that incorporate lake dynamics

• No generic parameterization for lakes exists

SWOT observations of reservoir SWOT observations of reservoir

storagestorage• Some large-scale models incorporate reservoirs in

their flow routingo Simple linear schemeso Optimizing releases according to reservoir typeo Coupling of hydrology models with dedicated water resources

management models

• Issues of trans-boundary rivers persist for models of these systems

• Forecasting and assessment hydropower production

• Observed WSE could be ingested directly or model parameters can be calibrated

Mapping changes in wetlandsMapping changes in wetlands

• Diversity and complexity of wetlands makes their modeling difficult

• Affect local water and energy exchanges due to relatively high ET

• Distributed versus areal modeling of wetlands• Probably need to explicitly include groundwater in

hydrologic models• Changes in water storage and inundation extent

can be used to calibrate model parameters• Inferred ET can be assimilated directly• Implications for eco-hydrologic models

Can SWOT help with forecasting?Can SWOT help with forecasting?

• When there is a SWOT overpass initial conditions for a forecast can be estimated

• Estimation can be direct or indirecto Direct example: flood forecastingo Indirect example: hydrologic forecasting by estimating soil moisture

that produced observed runoff

• Improvement in forecast skill by model calibration or identification of model biases

Example of forecast error reduction when assimilating satellite WSE over the Ohio River

Challenges: discrepancy between observations and Challenges: discrepancy between observations and

modelsmodels

• What SWOT observes does not necessarily match the model state variable

• Transforming WSE to water depth depends on accuracy (or assumption) of topography

• Reach-averaged properties are not directly represented in the modelso Need to validate assumptions of aggregation with finer scale

measurements and models

• Models lack or have simplistic representation of lakes and wetlands

• Do we need to modify existing model structures?• What is the best approach for resolving these

discrepancies?

Challenges: hyper-resolution Challenges: hyper-resolution

modelingmodeling

• New satellite missions including SWOT are starting to provide information at high spatial resolutions

• Grand challenge of developing models at 1-km scale globally

• Not as simple as changing the grid cell size…

• Data assimilation must play key role

• Perhaps models need to be restructured with satellite observations in mind

Challenges: how to move forwardChallenges: how to move forward

• Coupling of hydrology and hydrodynamic modelso Need to represent surface water inundation

• Leverage existing work or develop new schemes foro Consumptive useo Reservoir operationso Lake and wetland dynamics

• Perform model validation experiments• Continue work on data assimilation of SWOT and

AirSWOT observations into both hydraulic and hydrodynamic modelso State estimationo Model calibrationo Assess the feasibility of closing the water budget, in combination with

other satellite observationso Demonstrate value of approach in applications

Questions?Questions?