The Western States Water Mission

CUAHSI Hydroinformatics meeting 16 July 2015

Jet Propulsion Laboratory, California Institute of Technology

Water Cycle and Freshwater Availability

CLOUDS

AIRS, MLS, GPS-ROTempest (2017)

WATER VAPOR

SMAPSOIL MOISTURE Aquarius

EVAPORATION

Jason Series, SWOT (2020)

WATER STORAGEIN OCEANS

GPMRainCube (2017)

PRECIPITATION

Airborne Snow Observatory (ASO)

FRESHWATER STORAGE IN ICE AND SNOW

GRACE, GRACE-FO (2017)GROUND-WATER

CloudSat, MODIS

SWOT (2020)RIVERS & LAKES

ECOSTRESS (2017)EVAPOTRANSPIRATION

Next Challenge : Adding Integrated Value to the Measurements

- There is some best-estimate of water state based on a combination of models and data

- Beyond scientists and to user friendly applications for water managers and the public

- Active operational assimilation of all current products

- Remove obstacles in downloading, aggregating and interpreting outputs

- Advancing to the management spatial scale

- Including robust uncertainties!!!

Towards an optimized management information product

The Western States Water Mission: An example of a systems approach to hydrology Observations

CA

Tot

al U

sabl

e Fr

eshw

ater

(m

illion

acr

e-fe

et)

1month

ago

1season

ago

1yearago

1020

3040

Retrospective Record

(Notional)

(Prospective customers)

Estimates with Uncertainties

Coupled and Validated Models

Stakeholders/Customers

Colorado Water Conservation Board

Operational, high-resolution assimilation of satellite, airborne, in situ products

State Estimation with Uncertainties Near-Real Time, plus 1979-present Western US 3km2 catchment-grid with river routing Decision support for Western States

RHEAS

A. Konstantinos/JPL

ASO

R2O path for process modeling & optimal assimilation practices for

GRACE, SMAP, ASO, SWOT, etc

The Western States Water Mission: A robust effort to improve state estimates of water availability

Precipitation measurement missionGPM

Core satellite launched in February 2014

Really a constellation of many satellites

Like TRMM but at all latitudes

Measures light, heavy, frozen

Global coverage

2-4 hour frequency

~5-km resolution

Soil Moisture Active-PassiveSMAP

Launched January 2015

Beta product due October 2015

Soil moisture and freeze-thaw state

Global coverage

3-km radar and 9-km combined active-passive

2-3 day latency for level-3

Gravity Recovery and Climate ExperimentGRACE and GRACE-FO

Launched 2002

Still flying and returning data, with periodic outages to conserve power

Monthly, global TWSA

Measures total integrated water storage change beneath the satellites

~2-3 degree resolution

JPL-RL05m [Watkins, 2015]

1. Dozier, J., Painter, T.H., Rittger, K., & Frew, J.E. (2008). Time-space continuity of daily maps of fractional snow cover and albedo from MODIS. Advances in Water Resources, 31, 1515-1526, doi: 10.1016/j.advwatres.2008.08.011.

2. Painter, T.H., Rittger, K., McKenzie, C., Slaughter, P., Davis, R.E., & Dozier, J. (2009). Retrieval of subpixel snow covered area, grain size, and albedo from MODIS. Remote Sensing of Environment, 113, 868-879, doi: 10.1016/j.rse.2009.01.001.

3. Rittger, K., Painter, T.H., & Dozier, D. (Submitted). Assesment of methods for mapping snow cover from MODIS. Advances in Water Resources, Anniversary Issue.

MODIS snow-covered areaMODSCAG

Snow area and grain size

Most accurate MODIS snow products (Rittger et al., 2013)

Monthly, global fractional area

Based on 500m MODIS tiles

~24-hour turn around

snow water equivalent (SWE)

snow albedo

NASA/JPL, in partnership with the California Department of Water Resources

imaging spectrometer and scanning lidar

Airborne Snow ObservatoryASO

Surface Water and Ocean TopographySWOT

Launching 2020

Wide-swath interferometery

River, lake and reservoir heights globally

2x per 21-days

~100-m spatial imaging

~1-cm @1-km precision

Subsidence rate, 2007-2011

Subsidence rate, May-October 2014

Mapping Groundwater Induced Subsidence Rates Near El Nido, CA

Slide courtesy of Tom Farr, NASA JPL

Regional Hydrologic Extremes Assessment System (RHEAS)

Built by Kostas Andreadis at JPL

Variable Infiltration Capacity (VIC) hydrology model

Ensemble Kalman Filter

Has been successfully applied and validated in the CONUS

Due to data latency: we will conduct provisional (~7-days) and stable (~3 months) hindcasts

Like a reanalysis for land surface hydrology

TWS: GRACE, (GRSS)Snow: MODSCAG, ASOSM: SMAP, (AMSR-E, SMOS)(ET: MODIS, UCB)GRACE-FO, SWOT

(Precip: TRMM, CMORPHPERSIANN, CCS, etc.)

(Topo: SRTM)

Ingest

Surface storageStream gaugesWell levelSnow pillowsInSAR subsidence (w/ uncert.)GPSSnow surveysFisher ETECOSTRESS

Input

Assimilate

RHEASDatabase

Model(VIC)

Stored valuesor links

Pass-through

(all w/ uncertainty)Total waterGroundwaterSWESnow depthSnow cover %Soil moistureFreeze/thawETSnowmeltSublimationPrecipitationForecasts

VisualizationAggregation

Avg/Min/MaxUnit

conversion

Web interface

Surface storageSubsidence (w/ uncer.)Well level

Dynamicinteractive

map

Plots

Animations

Tables

Regional Hydrologic Extremes Assessment System (RHEAS)

Ingestion Module (IM)

User Interface (UI)

Hydrological Input, Estimation, and Prediction Resource (HIEPR)

(w/ uncertainty)RunoffModel

(RAPID) (w/ uncertainty)

Surface flow

User guide

Data Analytics Center Architecture

Data sources from space, airborne, ground sensorsDistributed Computation, workflow, vizualization

Interactive user interfaceCourtesy: aso.jpl.nasa.gov

Photo by Peter McBride

Q1 Q2 Q3 Q4

FY15

Q1 Q2 Q3 Q4

FY16

Q1 Q2 Q3 Q4

FY17

Q1 Q2 Q3 Q4

FY18

Lower-level requirements develop, architecture development, stakeholder engagement, development of an initial show and tell model, and coordination with the NASA Water Center

FormulationConcept Studies Implementation

Pre-Phase A Phase A Phase B Phase C Phase D Phase E

General project/mission implementation plan and top-level requirements development

Component Development

Component Test

System Integration & Test

Deployment/Operations

Western States Water Mission

The Western States Water Mission (WSWM) Will provide key stakeholders in California and the Western U.S. with actionable

information beginning in 2017

Planning for 2 data products : RHEAS VIC near-real-time preliminary product [~1-week latency] RHEAS VIC 3km2 catchment stable product [1979 to ~3-months ago]

Project personnel: James Famiglietti (Project Scientist), Ralph Basilio (Project Manager), Amy Trangsrud (Systems Engineer), Kostas Andreadis, Cedric David, JT Reager, Paul Ramirez, Dan Crichton, Duane Waliser, Michael Gunson,

Provides a tremendous opportunity for cooperation, synergy, and collaboration with CUAHSI:

Leveraging years of CUAHSI experience in water data sharing Specifically CUAHSI HIS for data downloading (e.g. USGS streamgages) WaterML to serve our results (catchment IDs, web mapping?) Links to Hydroshare, Hydrodesktop?

Questions, suggestions, discussion?

John.Reager@jpl.nasa.gov

Slide Number 1Slide Number 2Slide Number 3Slide Number 4Slide Number 5Slide Number 6Slide Number 7Slide Number 8Slide Number 9Slide Number 10Slide Number 11Mapping Groundwater Induced Subsidence Rates Near El Nido, CASlide Number 13Slide Number 14Data Analytics Center ArchitectureSlide Number 16Slide Number 17Slide Number 18