Transcript NASA Working Group on Hydrologic Processes of Rivers and

The Need for Satellite Based
Observations of Global Surface
Waters
Funded by the Terrestrial
Hydrology Program at NASA
D. Lettenmaier, D. Alsdorf,
C. Vörösmarty, C. Birkett
www.swa.com/hydrawg/
Amazon Floodplain (L. Hess photo)
Outline

The Lack of Discharge and Water
Storage Change Measurements

Resulting Science Questions

Why Satellite Based Observations
Are Required to Answer These
Questions

Potential Spaceborne Solutions

Your Participation is Welcomed
(please see our web page for a list of
participants)
www.swa.com/hydrawg/
Lack of Q?
Keep these measuring approaches in mind
Lack of Q and ΔS Measurements: An example
from Inundated Amazon Floodplain
Singular gauges are incapable of measuring
the flow conditions and related storage
changes in these photos whereas complete
gauge networks are cost prohibitive. The
ideal solution is a spatial measurement of
water heights from a remote platform.
How does water flow through these
environments?
100% Inundated!
(L. Mertes, L. Hess photos)
Example: Braided Rivers
It is impossible to measure discharge along these
Arctic braided rivers with a single gauging station.
Like the Amazon floodplain, a network of gauges
located throughout a braided river reach is
impractical. Instead, a spatial measurement of
flow from a remote platform is preferred.
Globally Declining Gauge
Network

“Many of the countries whose hydrological networks are in the worst
condition are those with the most pressing water needs. A 1991 United
Nations survey of hydrological monitoring networks showed "serious
shortcomings" in sub-Saharan Africa, says Rodda. "Many stations are
still there on paper," says Arthur Askew, director of hydrology and water
resources at the World Meteorological Organization (WMO) in Geneva,
"but in reality they don't exist." Even when they do, countries lack
resources for maintenance. Zimbabwe has two vehicles for maintaining
hydrological stations throughout the entire country, and Zambia just has
one, says Rodda.”

“Operational river discharge monitoring is declining in both North
America and Eurasia. This problem is especially severe in the Far East
of Siberia and the province of Ontario, where 73% and 67% of river
gauges were closed between 1986 and 1999, respectively. These
reductions will greatly affect our ability to study variations in and
alterations to the pan-Arctic hydrological cycle.”
Stokstad, E., Scarcity of Rain, Stream Gages Threatens Forecasts, Science, 285, 1199, 1999.
Shiklomanov, A.I., R.B. Lammers, and C.J. Vörösmarty, Widespread decline in hydrological monitoring threatens Pan-Arctic
research, EOS Transactions of AGU, 83, 13-16, 2002.
Resulting Science Questions

How does this lack of measurements limit our
ability to predict the land surface branch of
the global hydrologic cycle?

Stream flow is the spatial and temporal integrator
of hydrological processes thus is used to verify
GCM predicted surface water balances.

Unfortunately, model runoff predictions are not in
agreement with observed stream flow.
Model Predicted Discharge vs. Observed
1.25
1.00
0.75
0.50
0.25
0.00
OBS
Runoff (mm/day)
J
F
M
A
REAN2
M
J
J
GSM
A
REAN2: NCEP/DOE
AMIP Reanalysis II
GSM, RSM: NCEP
Global and Regional
Spectral Models
ETA: NCEP
Operational forecast
model
OBS: Observed
S
RSM
O
N
D
ETA
Mouth of Mississippi: both timing and magnitude errors (typical of many locations).
Within basin errors exceed 100%; thus gauge at mouth approach will not suffice.
Similar results found in global basins
Roads et al., GCIP Water and Energy Budget Synthesis (WEBS), J. Geophysical Research, in press 2003. Lenters, J.D., M.T. Coe, and J.A. Foley, Surface
water balance of the continental United States, 1963-1995: Regional evaluation of a terrestrial biosphere model and the NCEP/NCAR reanalysis, J.
Geophysical Research, 105, 22393-22425, 2000. Coe, M.T., Modeling terrestrial hydrological systems at the continental scale: Testing the accuracy of an
atmospheric GCM, J. of Climate, 13, 686-704, 2000.
Resulting Science
Questions

For 2025, Relative to 1985
What are the implications for global
water management and
assessment?

Ability to globally forecast
freshwater availability is critical for
population sustainability.

Water use changes due to
population are more significant than
climate change impacts.

Predictions also demonstrate the
complications to simple runoff
predictions that ignore human
water usage (e.g., irrigation).
Vörösmarty, C.J., P. Green, J. Salisbury, and R.B. Lammers, Global water resources: Vulnerability from climate change and
population growth, Science, 289, 284-288, 2000.
Resulting Science Questions

What is the role of wetland, lake, and
river water storage as a regulator of
biogeochemical cycles, such as
carbon and nutrients?

Rivers outgas as well as transport C.
Ignoring water borne C fluxes, favoring
land-atmosphere only, yields
overestimates of terrestrial C
accumulation

Water Area x CO2 Evasion = Basin Wide
CO2 Evasion
(L. Hess photos)
Richey, J.E., J.M. Melack, A.K. Aufdenkampe, V.M. Ballester, and L.L. Hess, Outgassing from Amazonian rivers and wetlands as a
large tropical source of atmospheric CO2, Nature, 416, 617-620, 2002.
CO2 Evasion in the Amazon
(0,72W)
(8S,72W)



(0,54W)
(8S,54W)
Over 300,000 km2 inundated area, 1800+ samples of CO2 partial pressures, 10 year time
series, and an evasion flux model
Results: 470 Tg C/yr all Basin; 13 x more C by outgassing than by discharge
But what are seasonal and global variations? If extrapolate Amazon case to global wetlands,
= 0.9 Gt C/yr, 3x larger than previous global estimates; Tropics are in balance, not a C Sink?
Richey, J.E., J.M. Melack, A.K. Aufdenkampe, V.M. Ballester, and L.L. Hess, Outgassing from Amazonian rivers and wetlands as a
large tropical source of atmospheric CO2, Nature, 416, 617-620, 2002.
Global Wetlands




Wetlands are distributed
globally, ~4% of Earth’s
land surface
Current knowledge of
wetlands extent is
inadequate
Amazon wetlands are much larger than thought in
this view [Melack et al, in review ]
Putuligayuk River watershed on the Alaskan north
slope: studies with increasing resolution
demonstrate a greater open water area (2% vs.
20%; 1km vs. 50m) and as much as 2/3 of the
watershed is seasonally flooded tundra [Bowling et
al., WRR in press].
Matthews, E. and I. Fung, Methane emission from natural wetlands: global distribution, area, and environmental characteristics of
sources, Global Biochemical Cycles, v. 1, pp. 61-86, 1987. Prigent, C., E. Matthews, F. Aires, and W. Rossow, Remote sensing of
global wetland dynamics with multiple satellite data sets, Geophysical Research Letters, 28, 4631-4634, 2001.
Saturated extent from RADARSAT Putuligayuk River, Alaska
2
0
0
0
Inundated area (km 2)
= wet
400
300
= dry
a.
200
b.
c.
1999
2000
d.
e.
100
0
6/10
6/30
7/20
8/9
8/29
Why Use Satellite Based Observations
Instead of More Stream Gauges?

Wetlands and floodplains have non-channelized flow, are
geomorphically diverse; at a point cross-sectional gauge
methods will not provide necessary Q and ΔS.

Wetlands are globally distributed (cover ~4% Earth’s land;
1gauge/1000 km2 X $40,000 = $ 230M)

Declining gauge numbers makes the problem only worse.
Political and Economic problems are real.

Need a global dataset of Q and ΔS concomitant with other
NASA hydrologic missions (e.g., soil moisture, precipitation).
Q & ΔS verify global hydrologic models.
Solutions from Radar Altimetry
Topex/POSEIDON tracks crossing the
Amazon Basin. Circles indicate locations
of water level changes measured by T/P
radar altimetry over rivers and wetlands.
Presently, altimeters are configured for
oceanographic applications, thus lacking
the spatial resolution that may be
possible for rivers and wetlands.
Water surface heights, relative to a
common datum, derived from
Topex/POSEIDON radar altimetry.
Accuracy of each height is about the
size of the symbol.
Birkett, C.M., Contribution of the TOPEX NASA radar altimeter to the global monitoring of large rivers and wetlands, Water
Resources Res.,1223-1239, 1998.
Birkett, C.M., L.A.K. Mertes, T. Dunne, M.H. Costa, and M.J. Jasinski, Surface water dynamics in the Amazon Basin: Application of
satellite radar altimetry, accepted to Journal of Geophysical Research, 2002.
Lakes, wetlands and reservoirs in Africa
Total lake area = 844145 km2
(2.3 % of total land area)
Lakes & Wetlands from UMd land cover
classification based on AVHRR (~1 km): JERS-1
Mosaics may show greater area, like the Amazon
Topex/POSEIDON heights x area = storage changes
Mean interannual variability for 5 lakes is
~200 mm; averaged over all of Africa is 5
mm, about 1/10th the equivalent value for soil
moisture. What is the effect of all smaller
water bodies? Not negligible and maybe 1/2
that of soil moisture.
Sridhar, V., J.Adam, D.P. Lettenmaier and C.M. Birkett, Evaluating the variability and budgets of global water cycle components, 14th Symposium on Global Change and
Climate Variations, American Meteo. Soc., Long Beach, CA, February, 2003.
Solutions from Interferometric SAR for Water Level
Changes
0 km 20
These water level
changes, 12 +/- 2
cm, agree with
T/P, 21 +/- 10++
cm.
JERS-1 Interferogram spanning February 14 – March 30, 1997. “A” marks
locations of T/P altimetry profile. Water level changes across an entire lake have
been measured (i.e., the yellow marks the lake surface, blue indicates land).
BUT, method requires inundated vegetation for “double-bounce” travel path of
radar pulse.
Alsdorf, D.E., J. M. Melack, T. Dunne, L.A.K. Mertes, L.L. Hess, and L.C. Smith, Interferometric radar measurements of water level
changes on the Amazon floodplain, Nature, 404, 174-177, 2000.
Alsdorf, D., C. Birkett, T. Dunne, J. Melack, and L. Hess, Water level changes in a large Amazon lake measured with spaceborne
radar interferometry and altimetry, Geophysical Research Letters, 28, 2671-2674, 2001.
Existing
Instruments

Water Surface Area:



Water Surface Heights:



Low Vertical & Spatial, High Temporal (>
10 cm accuracy, 200+ km track spacing):
Topex/POSEIDON
High Vertical & Spatial, Low Temporal
(180-day repeat): ICESat
Water Volumes:



Low Spatial/High Temporal: Passive
Microwave (SSM/I, SMMR), MODIS
High Spatial/Low Temporal: JERS-1, ERS
1/2 & EnviSat, RadarSat, LandSat
Very Low Spatial, Low Temporal: GRACE
High Spatial, Low Temporal:
Interferometric SAR (JERS-1, ALOS, SIRC)
Topography:

SRTM (also provides some information on
water slopes)
River Velocity & Width & Slope
Measurements
Concept by Ernesto Rodriguez of JPL
Measure -Doppler Velocity
Measure Topography
Measure +Doppler Velocity
Example of measurement of the
radial component of surface velocity
using along-track interferometry
Basic configuration of the satellite
Conclusions:



Lack of Q and ΔS measurements cannot be
alleviated with more gauges (e.g., wetlands =
diffusive flow).
This lack leads to poorly constrained global
hydrologic models.
Potential exists for a satellite-based solutions to
these problems.
www.swa.com/hydrawg/
Also of interest at this meeting:


Session HS15: “Satellite observations of
rivers and wetlands ..” (Gallieni 3, 14:1516:45 today)
NASA surface water working group
meeting (immediately following session
HS15; check with Doug Alsdorf for
location)