De toegevoegde waarde van remote sensing voor het bepalen van de verdamping

Through the ‘SAT-WATER’ partnership, the regional water authority ‘Groot Salland’ receives remotely sensed (RS) evaporation data, regarding the actual evapotranspiration and the evapotranspiration deficit, on a daily basis. However until now no research has been carried out into the possibilities of these evaporation data. The aim of this investigation is to assess the added value of these remotely sensed data, in comparison to the Makkink method for determining evapotranspiration, which is currently in use. In evaporation calculations a distinction is made between potential, actual and reference evapotranspiration. The potential evapotranspiration is the evapotranspiration for a well-watered crop. The actual evapotranspiration is the ‘real’ evapotranspiration which takes into account the water availability. The difference between these two, a measure for the amount of unevaporated water due to water shortage, is called the evapotranspiration deficit. The reference evapotranspiration, calculated among others by the Makkink and Penman-Monteith methods, is the evapotranspiration for well-watered grass. This is equal to the potential evapotranspiration for grass. The potential evapotranspiration for other crops is often calculated using the reference evapotranspiration an multiplying it by a crop factor. To gain a first insight into this added value, the quality of the data has been examined. Also the accuracy of the evaporation data has been investigated, by comparing the RS potential evapotranspiration (actual evapotranspiration + evapotranspiration deficit) with a reference. As a reference the Penman-Monteith method using meteorological variables, as discussed by Allen et al. (1998), was adopted. Besides this, the accuracy of the RS evapotranspiration deficit was determined by comparing it to the precipitation deficit calculated by the Royal Netherlands Meteorological Institute. Because the actual evapotranspiration is calculated by subtracting the evapotranspiration deficit from the potential evapotranspiration, both analyses together give an insight into the accuracy of the actual evapotranspiration. To get an indication of the possible differences that will arise from a transition to remotely sensed evapotranspiration data, a comparison is made between the RS actual evapotranspiration and the reference evapotranspiration calculated using the Makkink method. Lastly, the possible applications of the RS evaporation data have been investigated. From the first examination of the quality of the data, it turns out that a relatively small amount of remotely sensed data was used to calculate the evaporation data. The input data consists for the largest part of meteorological spot measurements. Also the resolution of the evaporation images is too low (250m) to draw conclusions about small areas. The investigation into the accuracy showed agreement between the RS potential evapotranspiration and the Penman-Monteith reference evapotranspiration. Although large deviations were observed for a colder period, the deviations remained small for the rest of the season. The cumulative deviation at the end of the season for grassland was only 3mm. For large areas the deviation also remained small, and the results were as expected. The comparison between the RS evapotranspiration deficit and the precipitation deficit showed agreement also. This was to be expected, because the soil moisture data used to derive the evapotranspiration (deficit) was based on meteorological variables. When a transition from the Makkink method to RS evapotranspiration data is made, the differences for grassland will be small. Here the cumulative RS actual evapotranspiration at the end of the season was only 16mm lower than the Makkink reference evapotranspiration. For areas with a more diverse land cover the actual evapotranspiration is roughly 50mm lower than the reference evapotranspiration. For areas largely covered by woods this deviation is smaller (35mm lower than Makkink), and for areas largely built-up it is higher (88mm lower than Makkink). From an analysis of the possible applications it became apparent that the data can only be used for purposes where a general insight in the evaporation is needed and that the data can only be used on larger areas. In conclusion the RS data can be looked upon as a good model for determining the evapotranspiration. Although the RS evaporation data can give an insight into the evapotranspiration in the area, users should be aware of the fact that drought is also affected by water supply and extractions that are not included in the evapotranspiration data. Also the data can only be used for larger areas. The main advantage of the RS evaporation data compared to Makkink, is that they give an accurate insight into the spatial differences in evapotranspiration. When using the data, users should be aware of its limitations, especially the fact that the effects water supply and extractions will not be shown accurately by the data. It is recommended that future investigations into new sources of evapotranspiration images will start by examining the lineage of the data, even before the deviations compared to other methods are explored. It is unlikely however that these new sources will display the effect of soil moisture effectively, because the current generation of soil moisture sensors on board of satellites have very low spatial resolutions (≥10Km). Suppliers of evapotranspiration data with a higher spatial resolution could be found, however because the resolution of the soil moisture information will be low, this element will have a lower level of detail.