| Résumé: |
Rainfall has been measured since the 17th century in Europe, and there are several instruments used to do it. From local scale, using rain gauges, to regional or continental scale, with radar or satellites. In addition, rainfall measurement is complex due, in particular to the strong spatio-temporal variability of rainfall. Another point is the resolution (spatial and temporal), which is not always enough. Instruments used allow knowledge in their specific scale.
Lidar is an active remote sensing instrument, which sends a laser beam and measures the returning signal. Its range can be from some meters to several kilometers. It used in several field, like to do accurate Digital Elevation Model (DEM), but not only. As there is not only one type of lidar, there are several field using it, such as geological or atmosphercial to cite only two possible applications. Over the years we have seen the development of low-cost lidar. In general lidar uses several wavelengths from visible to infrared (IR). One of water's properties is to absorb infrared. Theoretically, it should be possible to estimate rainfall, using a lidar working in IR.
This Master thesis, investigates the possibilities offered by a low-cost terrestrial lidar and how it could be used for rainfall studies. This research has two objectives: 1) having a simple theoretical framework; 2) test theory with measurements.
Results show that it is possible to estimate rainfall using a low-cost lidar. However, the reliability of them depends on the intensity of rainfall. In fact, when the rainfall intensity does not exceed 10 mm/h, the lidar / rainfall relation is less visible; it is explained by a linear function. In addition, it stands out that at low rainfall intensities, lidar signal is more sensitive to noise. Although when the rainfall intensity exceeds 10 mm/h, the presence of extremes brings more information. In this case, the relation is clearer and is similar to the one observed with radars, this is a power-law function, which explains it. |
Mémoire [18 Mo]