A team of five students: Hugo van Meijeren, Janna Jilesen, Michiel Oliemans, Vera van Zoest and Michiel Blok, worked during their Academic Consultancy Training course on a case: Amsterdecks, which aims to improve the image of the canals in Amsterdam by good communication and visualisation of the water quality.
In the nineteenth and twentieth century, the canals of Amsterdam were used as a sewerage system. Although the water quality has improved since, the canals still suffer from a bad image. Amsterdecks, a project by Rademacher De Vries Associates (RDVA), Waternet, and Waag Society, aims to improve the image of the canals by good commu-nication and visualisation of the water quality. The water quality is partly determined by water flow (here defined as water speed and water direction). However, information about the water flow in the canals of Amsterdam is limited as data is only available from sensors at a few static locations, and calculated with the SOBEK model at other loca-tions. Global Navigation Satellite Systems (GNSS) tracking devices can possibly be used as low-cost dynamic flow sensors and have the potential to obtain a large amount of data in a short period of time.The objective of this study is to obtain data about the water flow in the canals of Amsterdam, at multiple locations and multiple points in time, using low-cost sensors. This data will be used for visualizing the water flow in the ca-nals of Amsterdam in such a way that patterns in the water can be explained to inhabitants and recreationists. Two specific research questions have been formulated in relation to the kind of data required: What are the similarities and differences in water flow between the measurements by Waternet (flow sensors) and measurements using floats mounted with GPS trackers? And what patterns can be found in the water flow?Floating rods equipped with GPS trackers were used for deriving water speed and direction at different locations and different points in time in the canals of Amsterdam. The tracking devices sent their location at a time inter-val of two minutes to a server, which was set up specifically for this study. Measurements were done during two different sessions. The first session took place on the 10th and 11th of June 2015. A total of 18 floating rods was dropped in the water and left there for 24 hours. The second session took place from the 15th till the 17th of June 2015, when a total of 17 floating rods was used. The locations and times sent to the server were stored in log files, and imported in Excel . ArcMap and CartoDB were used to visualize the data. Some of the floating rods showed interesting patterns. For example, the velocity of one of the measurement devic-es was compared with the velocity of the Amstel according to the static flow sensor at Amstel Omval (Berlagebrug). The measurements of the tracking device followed approximately the same pattern as the measurements of the static flow sensor. The largest differences were found when the velocity of the tracking device was 0. In this case, the device was stuck in the water for some time. The correlation between the two types of measurement is tested using correlation tests. A Spearman’s rank correlation test resulted in a correlation of ρ(283)=0.290 (p=0.000), which indicates that the measurements of the tracking devices correspond to the measurements of the static water flow sensor. Concerning the water flow, specific attention has been paid to exploring the influence of the tide at sea (near IJmuiden) on the water flow in the canals of Amsterdam. A Spearman’s rank correlation test was performed using the height of the tide and water flow measured by the static water flow sensor as inputs, showing a strong and significant correlation (ρ(283)=0.637 P=0.000). A Spearman’s rank correlation test was also done using the wa-ter flow measured by the tracking device, in relation to height of the tide. This test however showed no significant correlation between the measurements and tide height (ρ(283)=0.097 P=0.103). This result is remarkable, since a significant correlation between the measurements with the tracking devices and measurements with the static flow sensor was already found. This result may be caused by the device being stuck at some moments in time and therefore having a velocity of 0 for a while.
A large part of the tracking devices got stuck behind houseboats, in reed, or in shallow water. However, the tracking devices that did not get stuck too quickly, show patterns in water flow similar to the patterns observed in the data of the static water flow sensor at Amstel Omval. Even the influence of pseudo-tide can be seen in the water flow measured by the tracking devices, although no significant correlation was found.In short, the tracking devices used were well capable of measuring the water flow, and even seemed capable of showing the influence of the pseudo-tide on the water flow direction. At least, they can if they do not get stuck be-hind houseboats or reed. For future studies it would be interesting to investigate the effect of heavy rain showers on the water flow.