Global rivers that will be observed by SWOT and their characteristics K. Andreadis 1, L. Clark 1, M. Durand 2, S. Biancamaria 4, E. Rodriguez 3, D. Lettenmaier 1, D. Alsdorf 2 SWOT Hydrology Workshop 9/15/2008, Columbus, OH 1 University of Washington 2 Ohio State University 3 NASA JPL 4 LEGOS

Motivation Obvious question on what rivers will SWOT be able to “see”  What are their characteristics?  How many times will they be observed per orbit cycle? What are the expected errors in discharge estimation?  How far upstream the drainage network can we estimate discharge with reasonable accuracy? Availability of global measurements of river discharge, width, depth etc?

General approach Power law relationships for river width and depth (functions of discharge)‏ Regional regression of mean annual discharge with drainage area Moody and Troutman, 2002 In-situ discharge measurements and global river dataset are required Estimate potential discharge errors from simple stage-discharge relationship

Datasets HYDRO1K  Topographically derived dataset based on GTOPO30  Aspect, flow direction/accumulation, stream lines, drainage basins GRDC (Global Runoff Data Center)‏  3,035 stations worldwide  Mean monthly discharges HYDROSHEDS  Based on SRTM at 3-arcsec resolution  Hydrologically conditioned dataset

Caveats Major limitations with existing datasets and power law relationships Peak versus mean annual flow Not looking at temporal variability here However, we need a consistent approach as a “first-cut” for evaluating the potential for SWOT observations We need a realistic dataset of river characteristics

Algorithm Q: discharge A: drainage area W: width D: depth σ z : height error σ Q : discharge error

SWOT orbital coverage 22-day repeat cycle 78-degree inclination Australia from HYDROSHEDS, rest from HYDRO1K

What kind of rivers would SWOT see? 1280 km km km km km 2 Drainage Area >10 SWOT Observations per 22-day orbit cycle Percentage of rivers belonging in bin 26 m35 m53 m88 m2740 m River Width

What kind of rivers would SWOT see? 1 Strahler Order >10 SWOT Observations per 22-day orbit cycle Percentage of rivers belonging in bin Gradient (Δh/ΔL)‏

Global river discharge Mean annual river discharge (m 3 /s)‏

Global river width Derived river width (m)‏

Global river depth Derived river depth (m)‏

Sanity check for derived characteristics Maximum river widths and mean annual discharge North America: Q=13600 m 3 /s, W=845 m South America: Q= m 3 /s, W=2740 m Africa: Q=32000 m 3 /s, W=1290 m Asia: Q=17400 m 3 /s, W=950 m Europe: Q=19900 m 3 /s, W=1020 m Oceania: Q=12450 m 3 /s, W=800 m

Calculating the expected error in river discharge We're using a simple stage-discharge relationship Need to take into account: i) measurement error and ii) model error (discharge)‏  Assuming model and measurement errors are independent Discharge fractional error

Amazon watershed (Branco River)‏ Small domain in the Amazon basin Example validation of methods River width in-situ measurements

Amazon watershed maps We can evaluate what order streams SWOT will observe (discharge) depending on required accuracy Discharge (m 3 /s)‏ River width (m)‏ River depth (m)‏ Monthly σ Q /Q σ Q /Q

Global river discharge errors Discharge fractional error σ Q /Q

Discharge errors with river characteristics Discharge (m 3 /s)‏Width (m)‏ Strahler OrderDepth (m)‏ σ Q /Q N. America S. America Africa Asia Europe Oceania Australia

Discharge errors with river characteristics Discharge (m 3 /s)‏Width (m)‏ Depth (m)‏ σ Q /Q N. America S. America Africa Asia Europe Oceania Australia

Global river discharge monthly errors Based on mean Q relationship fit from gauge measurements

Future work Swapping HYDRO1K with more accurate HYDROSHEDS dataset Improve discharge estimates by using additional in-situ datasets Perform analysis regionally on basins where in- situ width, depth, etc. measurements are available Incorporate other models of stage-discharge and other techniques of estimating discharge

Questions?