User:Amaiamarruedo/draft water remote sensing

Water Remote Sensing studies the color of water through the observation of the spectrum of water leaving light. From the study of this spectrum, the concentration of optically active components of the upper layer of the water body can be concluded via specific algorithms. Water quality monitoring by remote sensing and close-range instruments has obtain considerable attention since the founding of EU Water Framework Directive.

History
Development of water remote sensing techniques started in the early 1970s. These first techniques measured the spectral and thermal differences in the emitted energy from water surfaces. In general, empirical relationships were settled between the spectral properties and the water quality parameters of the water body. In 1974, Ritchie et al. (1974) developed an empirical approach to determine suspended sediments. This kind of empirical models are only able to use to determine water quality parameters of water bodies with similar conditions. In 1992 an analytical approach was used by Schiebe et al. (1992). This approach was based on the optical characteristics of water and water quality parameters to elaborate a physically based model of the relationship between the spectral and physical properties of the surface water studied. This physically based model was successfully applied in order to estimate suspended sediment concentrations.

Function
Water Remote sensing instruments allow to record the color of a water body, which provides information on the presence and abundance of optically active natural water components. The water color spectrum is defined as an apparent optical property (AOP) of the water. Thus, the value of this parameter will change with changes in the optical properties and concentrations of the optically active substances in the water (inherent optical properties or IPOS). There are two different approaches to determine the concentration of optically active water components by the study of the spectra. The first approach consist of empirical algorithms based on statistical relationships and the second approach consists of analytical algorithms based on the inversion of calibrate bio-optical model. Accurate calibration of the relationships/models used is an important condition for successful inversion on water remote sensing techniques and the determination of concentration of water quality parameters from observed spectral remote sensing data. Thus, these techniques depend on their ability to record these changes in the spectral signature backscattered from water surface and relate these recorded changes to water quality parameters via empirical or analytical approaches. Depending on the water component that wants to be measured, its concentration and the sensor properties, the wavelength that is used will change.

Contribution
By the use of Optical close range devices (e.g. spectrometers, radiometers) and satellites, the light reflected from the water bodies is measured. For instance, algorithms are used to induce parameters such as chlorophyll-a(Chl-a) and suspended particulate matter (SPM) concentration, the absorption by colored organic matter at 440nm (aCDOM) and secchi depth. The measurement of these values will give an idea about the water quality of the water body being studied. Thus, a very high concentration of green pigments like chlorophyll might indicate the presence of an algal grow, generally due to eutrophication processes, or the presence of submerged vegetation, which would indicate very clear water conditions. In addition, if it is possible to rule out the presence of submerged vegetation, the chlorophyll concentration could be used as a proxy or indicator for the trophic condition of a water body. In the same manner, other optical quality parameters such as suspended particles or Total suspended Matter (TSM) and Colored Dissolved Organic Matter (CDOM) can be used to monitor water quality.