Oberflächenabflussbestimmung mittels photogrammetrischer Bildauswertung
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Sara Hamah Said, Elisabeth Schnöll. (30/4/2016). Oberflächenabflussbestimmung mittels photogrammetrischer Bildauswertung. Vienna, Austria: Universitaet für Bodenkultur Wien, Center for Development Research (BOKU - CDR).
This bachelor thesis " Surface runoff determination by means of photogrammetric image analysis" was conducted in the Gumara-Maksegit drainage area in the highland dry areas of north-western Ethiopia, which covers around 54 km². The region is affected by severe land degradation due to intense rainfalls in the raining season between June and September, which lead to soil erosion and loss of fertile top soil. These circumstances make the local farmers very vulnerable to climate change and in turn endanger their livelihood. The objective of this thesis was to find the surface runoff at an installed measuring weir. Originally sensors were installed to measure the water level, but difficulties led to missing or flawed information. For this reason a camera was installed to automatically take pictures of the weir with the corresponding water level. Because of the prolonged time of the raining season and the amount of photos, a manual analysis would consume an enormous amount of time. Therefore an automatic method for the evaluation of the photos had to be found. This was done with the help of two different programs. ArcGis was used to analyse the differences in colours between the flood markers, which were manually depicted on the weir, and the water via a specifically developed algorithm. Subsequently Excel was used to convert this information into depictions of water levels. This automatic method of photo analysis was partly successful. The quality of the pictures is at times too poor for any program to analyse, which led to flaws in the final appraisal in Excel. Fortunately it is possible to eliminate the inconsistent data, but this has to be done manually. Additionally the position of the camera was repeatedly altered by the employees in Ethiopia as well as by wind and rain. This had to be taken into consideration while working with ArcGis and the analysis had to recurrently and manually be adjusted.