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Recent Hydrologic Developments in the SWOT Mission. Doug Alsdorf 1 , Nelly Mognard 2 , Jean-Francois Cretaux 2 , Stephane Calmant 3 , Dennis Lettenmaier 4 , and Ernesto Rodriguez 5

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Recent Hydrologic Developments in the SWOT Mission

Doug Alsdorf1, Nelly Mognard2, Jean-Francois Cretaux2, Stephane Calmant3, Dennis Lettenmaier4, and Ernesto Rodriguez5

1Byrd Polar Research Center, School of Earth Sciences, Ohio State University, 2LEGOS-CNES, Toulouse France, 3IRD-LEGOS, Toulouse France, 4Civil & Environmental Engineering, UW, 5NASA JPL

5. Transboundary River Flows

1. Abstract

3. AirSWOT

  • The core of AirSWOT is a multi-purpose Ka-band radar, KaSPAR(Ka-band SWOT Phenomenology Airborne Radar). This instrument will collect two swaths of across-track interferometry data, nominally, between nadir and 1 km and between 1km and 5 km, respectively, which can be used to obtain centimeter-level topographic maps of water surfaces and flood plains. KaSPAR also implements an along-track interferometer that can be used to measure the temporal decorrelation of water surfaces, as well as the water radial velocity. Additional instruments will include an IR camera system and precision IMU.

The Surface Water and Ocean Topography satellite mission (SWOT, http://swot.jpl.nasa.gov/) is designed to measure the elevations of the world’s water surfaces including both terrestrial surface waters and the oceans. CNES, NASA, and the CSA are partners in the mission as are hydrologists, oceanographers, and an international engineering team. Recent hydrologic and mission related advances include the following. (1) An airborne version of SWOT called AirSWOT has been developed to provide calibration and validation for the mission when on orbit as well as to support science and technology during mission development. AirSWOT flights are in the planning stage. (2) In early 2012, NASA and CNES issued calls for proposals to participate in the forthcoming SWOT Science Definition Team. Results are expected in time for a Fall 2012 start of the SDT. (3) A workshop held in June 2012 addressed the problem of estimating river discharge from SWOT measurements. SWOT discharge estimates will be developed for river reaches rather than individual cross-sections. Errors will result from algorithm unknowns of bathymetry and roughness, from errors in SWOT measurements of water surface height and inundation, from the incomplete temporal record dictated by the SWOT orbit, and from fluvial features such as unmeasured inflows and outflows within the reach used to estimate discharge. To overcome these issues, in-situ and airborne field data are required in order to validate and refine algorithms. (4) Two modeling methods are using the Amazon Basin as a test case for demonstrating the utility of SWOT observables for constraining water balances. In one case, parameters used to minimize differences between SWOT and model water surface elevations should be adjusted locally in space and time. In the other case, using actual altimetry data as a proxy for SWOT’s water surface elevations, it was determined that model water surface elevations were less than 1.6m different from the altimetry measurements: a considerable match given the lack of channel bathymetric knowledge. (5) The influence of the world’s managed reservoirs on the water cycle is difficult to assess given the abundance of dams and the relative lack of water level or storage change information. The downstream impacts, particularly for transboundary rivers, are similarly difficult to determine. The challenges for SWOT to overcome this lack hinge on the temporal sampling dictated by the mission’s orbital repeat cycle, on the accuracy of the height measurements, on the surface area, and on topography causing radar layover. (6) While SWOT’s orbit is designed to minimize errors from tidal aliasing, orbital sub-cycles can be adjusted to minimize hydrological errors. The impact of theses sub-cycles has been assessed using a hydrodynamic modeling of the last 1000 km reach of the Ob River, a West Siberian river draining a total area of around 3 million km2. Using a local ensemble Kalman smoother to assimilate virtual SWOT observations, similar results have been obtained for either a 1-day or 3-day sub-cycle when decreasing the differences between "true" and modeled water elevations. A key result is the necessity of using the smoother in the assimilation, at least for large rivers like the Ob.

Topex/Poseidon (triangles) 10-day forecast water elevation anomalies compare well with in-situ gauge (line) measurements in Bangladesh. Water levels measured by T/P in India are projected downstream and 10-days later. RMSE between 0.6m and 0.8m. SWOT will improve this by measuring smaller rivers, by providing more extensive geographic coverage, by having a better height accuracy, and by a having an improved temporal sampling.

  • We need to demonstrate the capability of Ka-band radar to penetrate vegetation canopies, thus key targets include inundated forest and grasses. We also need to test discharge algorithms, thus water heights and slopes along river channels as well as channel widths will be measured.

6. Orbit Analysis

Sacramento-Feather Conf.

Atchafalaya Wetlands

Sacramento River Delta

4. Discharge Algorithms

SWOT Simulated Discharge Along the Kanawha River

Mike Durand's “instantaneous discharge algorithm” is the most promising pathway towards estimating discharge from SWOT. It needs to be tested using a combination of AirSWOT and ground-based data in a range of environments as soon as possible. The algorithm uses continuity, i.e., assumes no change in discharge along a given reach and sets the upstream discharge equal to the downstream discharge. Equating upstream Q to downstream Q, yields unknown depths expressed as functions of water slope and channel width. Requires temporal variations in slope in order to work correctly. A hydrodynamic model was set-up with stream gauge data as boundary conditions and known river bathymetry to continuously yield water heights. These were sampled with SWOT orbit and measurement characteristics and errors. The samples are then used in the discharge algorithm to estimate discharge (dots) and bathymetry which are then compared to “truth”.

Day 2

Day 4

2. Phase A and the Science Definition Team

Day 3

In the Fall of 2012, SWOT passed two important milestones and has now entered "Phase A" in the NASA mission development lifecycle. The milestones are common to all NASA satellite missions and include the Mission Concept Review (MCR) and Key Decision Point A (KDP-A). For SWOT, the MCR was a two-day process wherein mission science and the associated flight and ground mission design are evaluated to determine if they meet certain maturity criteria. KDP-A is a NASA-HQ programmatic review that follows MCR that provides direction for an official project to be formed and enter the formulation phase (A). SWOT very favorably passed both reviews such that the mission is now in Phase A. Phase A will last for about 18 months and then progress towards subsequent milestones leading to Phases B, C, and D. The Launch Readiness is currently targeted for October 2020 with planned three year primary science operations phase (E).

The SWOT Science Definition Team (SDT) has been formed and has work to do. Mission development during Phase-A includes a number of trade-off studies ("trades") that are crucial to the design of the instrument and satellite in a way that meets science requirements while keeping costs to a minimum. We have a number of key decisions that need to be made by early 2013. These include narrowing the range of orbit possibilities including sub-cycles and the fast-phase; reviewing the mission science requirements and ensuring that these are correct; and helping to implement the AirSWOT field acquisitions and related data analysis.

Day 1

Upstream

Floodwave moving downstream

Durand et al., 2010

Because of oceanographic considerations, SWOT will use a non-sun synchronous orbit that minimizes tidal aliasing. Because of hydrologic considerations, SWOT will extend to at least 78N. Both sciences require global coverage with essentially no spatial gaps. A few candidate orbits are available, all having a 22-day repeat cycle but with 1-day and 3-day sub-cycles that fill-in the spatial coverage in different ways. The figures show examples of a 1-day (left) and 3-day (right) sub-cycle across the Niger River basin. The 1-day fills-in using immediately adjacent swaths. The 3-day fills-in using a leap-frog step-wise non-adjacent pattern.

Biancamaria, Yamazaki, and Pedinotti analyzed the impact of these differing sampling patterns on discharge. Results suggest that the temporal sampling of all candidate orbits have essentially similar errors when considering the monthly discharge averages: 8.2% to 7.0% when comparing SWOT 1-day and 3-day sub-cycle overpasses, respectively, of 216 somewhat globally distributed gauges. When comparing orbital sampling to model derived discharge, errors are similar 14.5% to 14.8%.

Amazon

The SWOT Satellite

SWOT consists of two Ka-band SAR antennae at opposite ends of a 10m boom (blue are the solar panels). Like SRTM, this is a one-pass interfero-metric system. Unlike SRTM it will operate at near-nadir incidence angles (which will be further tested by AirSWOT). Given this geometry, SWOT will be at least an order of magnitude more accurate than SRTM. Samplings as fine as 2mx10m are possible with +/-50cm height accuracy. When multiple samples are averaged, the height accuracy will be better than 10cm.

References

  • Durand, M., E. Rodriguez, D. E. Alsdorf, and M. Trigg, Estimating River Depth From Remote Sensing Swath Interferometry Measurements of River Height, Slope, and Width, IEEE JSTARS, 2010, vol. 3, issue 1.
  • Biancamaria, S., F. Hossain and D. P. Lettenmaier, Forecasting transboundary river water elevations from space, Geophysical Research Letters, 38, L11401, doi:10.1029/2011GL047290.
  • Yamazaki, D., H. Lee, D. Alsdorf, E. Dutra, H. Kim, S. Kanae, AND T. Oki, Analysis of the water level dynamics simulated by a global river model: a case study in the Amazon River, Water Resources Research, 48, W09508, doi:10.1029/2012WR011869, 2012.

Congo

During Phase A, the SDT will address important science questions. While SWOT is designed to address the global and regional water balances, additional science drivers are also evident. For example, what are the impacts of hydrology and hydraulics on sediment, nutrient, and carbon fluxes in large tropical wetlands? From a few radar altimetry passes, we suggest that the Amazon and Congo wetlands differ significantly in terms of their hydrodynamics. Water levels on the Amazon wetlands are well timed with and are at the same elevation as the nearby mainstem river. In contrast, Congo wetland water levels are always higher in elevation compared to the nearby river. Clearly, the river water cannot flow into the wetlands, rather water flow is one-way, from the wetland to the river. SWOT will measure water levels everywhere throughout these two wetlands to determine flow patterns and water exchange, hence giving a clearer indication of the importance of hydraulics on sediment, nutrient, and carbon fluxes.