Remote sensing for surface water hydrology

1. Remote sensing for surface water hydrology • RS applications for assessment of hydrometeorological states and fluxes • Soil moisture, snow cover, snow water equivalent, evapotranspiration, vegetation cover and water content, land surface energy balance, water quality • The above parameterize numerous physical, conceptual, and empirical models of surface water dynamics, such as runoff, infiltration, and streamflow • Can runoff/streamflow be directly observed and quantified with RS? Not with any current technology

2. } = CurveNumber NRCS* Curve number method • Data and Parameters • Digital Elevation model • Watershed delineation • Land use / land cover • Soil hydrologic group • Precipitation data • Streamflow record • Stream baseflow estimation • Antecedent moisture condition * NRCS – Natural Resources Conservation Service

3. RS direct quantification Soil moisture RS proxy characterization Passive microwave methods Landscape state and energy flux Infiltration Essential observations of a surface water system Precipitation (rainfall) Runoff Streamflow Infiltration very coarse spatial resolution poor temporal resolution expensive data moderate spatial resolution excellent temporal resolution free data

4. Data and Methodology • Remote Sensing Data MODIS NASA’s Moderate Resolution Imaging Spectroradiometer • Surface temperature (LST) • Albedo • Vegetation state • NDVI (Normalized Difference Vegetation Index) • EVI (Enhanced Vegetation Index) • User derived MSI (Moisture Stress Index) and others AMSR-EAdvanced Microwave Scanning Radiometer • Soil Moisture (resolution issues?) • Vegetation water content and roughness

5. http://malibusurfsidenews.com/blog/uploaded_images/ USGS_Pic2488r-764415.jpg General methodology Model parameterization based on: • MODIS time-series landscape biophysicals • High temporal resolution (daily but composited as 8 and 16 day products) • Moderate spatial resolution (0.25 - 1km2 pixel dim) • NEXRAD radar (Stage III, MPE) precipitation estimates • USGS gauged streamflow records

6. NEXRAD MPE radar estimate of hourly precipitation rate for 4 July 2006 (21:00 GMT) for Sandies Creek watershed and surrounding region. Rates ranged from 0.0 mm/hr (black pixel) to 14.6 mm/hr (white pixel) for cells within the watershed

7. Daytime LST (8 day composite) for the Sandies Creek watershed for the period 18 - 25 February 2002. Mean temperatures for this period ranged from 24.9 C (dark pixels) to 29.3 C (light pixels).

8. NDVI (16 day composite) image of the Sandies Creek watershed for the period 18 February – 6 March 2002. Dark-toned and light-toned pixels represent low and high NDVI values (stressed vegetation vs healthy), respectively.

11. How is LST coupled to soil moisture (or vice versa) • Heat flux from the earth’s surface • Radiative flux (long wave thermal 9-13 μm) • Sensible heat flux (convection and conduction) • Latent heat flux (phase change) • Is soil surface emissivity affected by soil moisture? would this affect radiative, sensible, or latent heat loss? • Would a loss or gain of near-surface soil moisture likely impact sensible or latent heat flux?

12. From: http://upload.wikimedia.org/wikipedia/en/6/69/LWRadiationBudget.gif

13. visible near infrared middle infrared Leaf water content Leaf structure Leaf chemistry Coupling vegetation to soil moisture

14. red nir

15. Band 6 Band 7 Band 2

16. Development of a benchmark model (CN) for Sandies Creek for 2004

17. Final equation: where Q = streamflow, P = precipitation, T = LST, and I = EVI All β1,2,3 estimates significant at P < 0.0001 β0 estimate significant at P < 0.04 RS Model Development (2004) • 6 MODIS parameters (LSTday, LSTnight, NDVI, EVI, NDWI, MSI) x 2 states (raw, deseasoned) x 3 antecedent offsets (0, 8, 16 days) = 36 regressors evaluated (plus precipitation) • Streamflow log transformed (normality assumptions) • Final model: Prec, LSTdayr(1), EVIr(0)

18. 2002 – 07* time series of daytime LST and precipitation

19. Sandies Creek calibration and validation results * Exclusion of July 2002 flood event Validation Calibration

20. Sandies Creek validation results (linear space)