Brainstorm session on remote sensing applications in hydrology

1. Brainstorm session onremote sensing applications in hydrology Jef Dams Brainstorm session on RS applications in hydrology

2. Table of content • Remote Sensing principles • Properties of RS measurements • Remote Sensing in hydrology Brainstorm session on RS applications in hydrology

3. Remote Sensing principles Remote sensing (RS) is the acquisition of information of an object or phenomenon, by the use of a device that is not in physical or intimate contact with the object Sun and Earth electromagnetic spectrum Brainstorm session on RS applications in hydrology

4. Remote Sensing principles "Atmospheric window" is the name of wavelengths where the atmosphere is "translucent" and where emission and reflection pass through almost unhindered. At other wavelengths the radiation is absorbed by various greenhouse gases Brainstorm session on RS applications in hydrology

5. Remote Sensing principles ‘spectral signature’ (A/B) B A Brainstorm session on RS applications in hydrology

6. Table of content • Remote Sensing principles • Properties of RS measurements • RS possibilities in hydrology Brainstorm session on RS applications in hydrology

7. Properties of RS measurements SENSORS e.g. ETM+ / MODIS / ASTER /... e.g. LIDAR / NEXRAD Brainstorm session on RS applications in hydrology

8. Properties of RS measurements PLATFORM The vehicles or carriers for remote sensors are called the platforms. Typical platforms are satellites and aircraft, but they can also include radio controlled aeroplanes, balloons kits for low altitude remote sensing, as well as ladder trucks or 'cherry pickers' for ground investigations. The key factor for the selection of a platform is the altitude that determines the ground resolution and which is also dependent on the instantaneous field of view (IFOV) of the sensor on board the platform. e.g. Landsat 5,7 / TERRA / IKONOS Brainstorm session on RS applications in hydrology

9. Properties of RS measurements 60 km 11 km 185 km IKONOS ASTER Landsat - Orbit - Swath width MODIS: 2330 km Brainstorm session on RS applications in hydrology

10. Properties of RS measurements SPECTRAL RESOLUTION • The spectral resolution is the ability of a sensing system to resolve or differentiate electromagnetic radiations of different frequencies.The more sensitive a sensor is for small spectral differences (small wavelength intervals) the higher is its spectral resolution. Spectral resolution depends on the setting of the optical filter which splits the incoming electromagnetic radiation in smaller spectral bands. • Panchromatic images • Multispectral images • Hyperspectral images Brainstorm session on RS applications in hydrology

11. Properties of RS measurements RADIOMETRIC RESOLUTION Radiometric Resolution: is determined by the number of discrete levels into which signals may be divided. e.g. 1 byte GROUND RESOLUTION In remote sensing, the images’ resolutions are expressed by the size of the area covered by a pixel. Each pixel in an image corresponds to a patch on the Earth’s surface. We thus talk about ‘ground resolution’. Brainstorm session on RS applications in hydrology

12. Properties of RS measurements TEMPORAL RESOLUTION • The temporal resolution is related ot the repetitive coverage of the ground by the remote-sensing system. For example, the temporal resolution of Landsat 4/5 is sixteen days. Orbit Swath-width Brainstorm session on RS applications in hydrology

13. Properties of RS measurements spatial resolution + cost / area spectral + temporal resolution e.g. Quickbird e.g. Landsat e.g. MODIS Brainstorm session on RS applications in hydrology

14. Table of content • Remote Sensing principles • Properties of RS measurements • Remote Sensing in hydrology Brainstorm session on RS applications in hydrology

15. Remote Sensing in hydrology • Hydrological state variables • Land Surface Temperature • Surface soil moisture • Snow cover / snow water equivalent • Surface roughness • Land cover/use (including vegetation cover) • Water quality • Hydrometeorological fluxes • Evapotranspiration • Snowmelt runoff • Rainfall Brainstorm session on RS applications in hydrology

16. Remote Sensing in hydrology LAND SURFACE TEMPERATURE • The observed radiance, often brightness temperature, in the thermal spectrum is influenced by the surface temperature (which we are looking for), the atmospheric loss of intensity and the emissivity. • The emissivity is the ratio of energy radiated by a particular material to energy radiated by a black body at the same temperature. • Methods to obtain LST: • ‘split window’ techniques • sensor specific methods based on the empirical relations between the range of emissivities and the minimum value from a set of multi-channel observations. • Used for: • evapotranspiration estimation • moisture • discovering bare soils Brainstorm session on RS applications in hydrology

17. Remote Sensing in hydrology SURFACE SOIL MOISTURE • At microwave frequencies (λ > 5 cm) the most striking feature of the emission form the earth’s surface is the large contrast between water and land. This is due to the high dielectric constants of water (around 80) while that of dry soils is smaller then 5. • The basic conclusion of a large number of research since the early 70’s is that it is possible to determine the moisture content of the surface layer of the soil about a ¼ of a wavelength thick (about 0-5 cm). • Main factors influencing the accuracy: • vegetation cover • soil properties • surface roughness e.g: European RS Satellite (ERS), RADARSAT (C-band), Japanese Earth Resource Satellite (JERS) and SMOS (L-band) Used for: - data assimilation Brainstorm session on RS applications in hydrology

18. Remote Sensing in hydrology SNOW COVER AND WATER EQUIVALENT Large difference in physical properties of snow and other natural surfaces: e.g. high albedo (+- 80% for new snow versus +-15% for snow free surfaces). Satellite VNIR observations: Landsat and SPOT (30m – 14d) / NOAA-AVHRR (1km – 12h) / MODIS (250m – 1d). Optimum image frequency during depletion: once a week. The sensitivity of the microwave radiation to a snow layer on the ground makes it possible to monitor snow cover using passive microwave remote sensing techniques to derive information on snow extent, snow depth, snow water equivalent and snow state. e.g: MODIS (VNIR) and AQUA (passive microwave) Used for: - snow runoff modelling Brainstorm session on RS applications in hydrology

19. Remote Sensing in hydrology LANDSCAPE ROUGHNESS Roughness refers to the unevenness of the earth’s surface due to natural processes (e.g. topography, erosion, vegetation) or human activities (e.g. buildings) Three complexities: - vegetation and urban roughness - transition roughness between landscape patches - topographic roughness e.g: LIDAR • Used for: • evapotranspiration estimation • estimation infiltration • estimation surface water velocity Brainstorm session on RS applications in hydrology

20. Remote Sensing in hydrology LAND COVER AND VEGETATION DYNAMICS Improved remote sensing based land cover observations can improve remote sensing parameterisation. Example: Imperviousness measurements (Landsat ETM+, ASTER, IKONOS,…) Vegetation dynamics can be derived from RS using for example vegetation indices (e.g. NDVI). High spatial versus high temporal resolution. (Landsat ETM+, MODIS, VEGETATION) • Used for: • Interception • Runoff Routing • Evapotranspiration Brainstorm session on RS applications in hydrology

21. Remote Sensing in hydrology WATER QUALITY • Substances in surface water can significantly change the backscattering characteristics of surface water. • Major factors affecting water quality in water bodies: • Suspended sediments • Dissolved organic matter • Thermal releases • Strong research need for understanding the effects of water quality on optical and thermal properties to be able to build physically based models. - Algae - Chemicals - … Satellites: SEAWIFS, EOS, MOS, IKONOS Brainstorm session on RS applications in hydrology

22. Remote Sensing in hydrology OTHER • Subsurface soil hydraulic properties (by repetitive measurements of microwave • brightness temperature) • Water level (LIDAR) • Lake extend / level • Cloud cover • Wind speed • Plant Species • … Brainstorm session on RS applications in hydrology

23. Remote Sensing in hydrology • Hydrological state variables • Land Surface Temperature • Surface soil moisture • Snow cover / water equivalent • Surface roughness • Land cover/use (including vegetation cover) • Water quality • Hydrometeorological fluxes • Evapotranspiration • Snowmelt runoff • Rainfall Brainstorm session on RS applications in hydrology

24. Remote Sensing in hydrology EVAPOTRANSPIRATION Indirect methods: Models (SVAT – ABL) Energy balance: Empirical methods Rn is the net radiation flux (W/m²), λE is the latent heat flux (W/m²), G is the soil heat flux (W/m²) and H is the sensible heat flux to air (W/m²) Semi-empirical methods including physical components e.g. SEBAL / SEBS / DisALexi Brainstorm session on RS applications in hydrology

25. Remote Sensing in hydrology RAINFALL Active ground based radars: - Doppler Radar - Dual-polarized Radar - Bistatic Radar Z=200*R^1.6 Z: This is the reflectivity factor of the precipitate. The number of drops and the size of the drops affect this value. R: This is the target range of the precipitate. • Active and passive microwave techniques (satellite based) • Tropical Rainfall Measuring Mission (TRMM) carrying different sensors including a passive microwave sensor (TMI) (ppt over oceans) and an active sensor: TRMM precipitation Radar (PR) (ppt over land) • Future: Global Precipitation Measurement (GPM) Brainstorm session on RS applications in hydrology

26. Thank you for your attendance! Brainstorm session on RS applications in hydrology

27. Brainstorm session on RS applications in hydrology