P49

New approach based on image processing techniques for water level measurements in the field
and laboratory applications〇Dina ELLEITHY, Sameh A. KANTOUSH, Tetsuya SUMI

1. Introduction and objectives:
Water level is crucial for observation andmanagement of water resources and account as anessential part in any hydraulic study1,2. There aremany conventional techniques used to measure thewater level which require manual inspection for datacollection where water level is directly measured1.
Nowadays, New techniques emerged compatible withdifferent situations which are based on remotemeasuring

developedperformancethroughtoimprove

enhancing1.

durability, and/or simplicity, etc

thethegeneralaccuracy,However, there issome structural or financial disadvantages exist. For
example, pressure and ultrasonic sensors are very
accurate but they are often very costly to purchase andregularly

toberenewed2.

Image

Processing

Techniques (IPT) are very promising measuring

Fig.1 Arase dam before, during and after removal (Right); and Locationof Arase Dam inside Kuma River Basin (Left)

For the laboratory application, continuous images
are collected from fixed camera recording the change
in piezometer water level during the run of a physicalmodel, fig.2. These images will be used for thecalculating the water pressure inside the piezometertubes.

techniques. Not so many applications have beenstudied to test the resulted accuracy and applicabilityof IPT for research purpose1–5.
In this paper, two different applications for
employing IPT in measuring water level using manualand automatic water level detection scheme will be
studied, an in-situ and a laboratory application, tohighlight their capabilities and limitations.
For the in-situ application, A series of scatteredFig.2 Piezometer tubes before and after IPT (Right); and Location ofchosen piezometer tubes on the physical model (Left)

images were taken during estimated high flow periods
at Arase dam removal site6,7, fig.1, are collected
before, during and after the weir removal with a totalof 229 image. they were recorded using a fixedcamera for the structure surveillance purposes. These
images will be tested for the reliability to represent theactual water level and calculate the dischargehydrographs.

The study objectives are: 1) evaluate the use of IPT
for water level measuring in these two applications, 2)
assess the capability to automatically track water
surface, and 3) identifying the accuracy of the resulted
water level data.
This paper utilizes water level measurement basedon IPT using the ImageJ® open source software.

2. Methods and techniques:riverbed and the low resolution of the surveillance

To achieve these objectives, data collection andimage, which reflects the good accuracy andarchiving is done by dividing all collected images andreliability of the outputs. However, separating thevideos in two groups chronologically, one group forwater surface automatically was very difficult andeach application (Field & Lab.). For each group, One

automatic tracking for the water level wasn’t

Image is chosen randomly and scaled according to theapplicable.

original as built drawings and the scale is calibrated
and verified at different times.

On the other hand, regarding the laboratory
application, after applying the surface markers,

For the in-situ, the right abutment of the structuresurface detection was doable, and automatic tracing

was chosen to be the benchmark during the waterwith time was possible. Resulted water pressure heads

level measuring process. Water level is measured atfrom automatic tracking, fig.4, was precise and thethe benchmark location through all images. Water

resulted accuracy was ±0.005mm compared todepth is deduced from the water level with respect toaccuracy of ±0.1mm for traditional measuring

the original bed level. All the 229 collected images

techniques.

were combined in the form of an Audio Video
Interleave (AVI) movie using the ImageJ® to facilitate
the scaling and the data collection.

Fig.4 Change in Pressure Head During applying Clear and turbid water
for both the Top and Bottom of the soil column.

References:Fig.3 Detected water depth and Observed discharge at Arase dam in2013, before dam removal(1)

For the laboratory application, the video wasconverted from MP4 to AVI using Blender® open
source software to be ready to be processed by(2)ImageJ®.
Video converted to 8-bit color bands was adjusted(3)and FFT filter was applied. The color thresholdadjusted to separate the surface markers from the restof the background as shown in fig. 2. Furthermore,

(4)
(5)

automatic tracking was performed to detect thesurface markers location at each frame. Water level isdeduced with respect to the piezometer datum.

(6)

3. Results and discussion:
For the In-situ application, the resulted water depths
showed same trends compared to the observed
discharges measured at the dam location, fig.3.
Additionally, rating curves resulted from plotting thewater depth vs the observed discharge showing good
trends, although the difference in the conditions of the(7)Chetpattananondh,K.;
Tapoanoi,T.;
Phukpattaranont,P.;
Jindapetch,N.
A
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DETECTION BY IMAGE PROCESSING. 9.
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https://doi.org/10.13140/2.1.3089.2320.
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Zhang, Z.; Zhou, Y.; Liu, H.; Gao, H. In-Situ
Water Level Measurement Using NIR-Imaging
Video Camera. Flow Measurement andInstrumentation
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95–106.
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4.
郁次郎若井. 消えゆく球磨川・荒瀬ダム: 川の流れ再生の予兆. 水資源・環境研究 2014, 27(2), 51–56.
Fukuoka, S.; Sumi, T.; Horiuchi, S. SedimentManagement on the Arase Dam Removal Project.
Advances in River Sediment Research 2013, 9.

The work carried out through this paper is part of the PhD thesis
research which aims: 1) to minimize the impacts of the physicalclogging occurrence; due to the existence of suspended sediments in
the harvested floodwater and 2) to hinder the change of thecharacteristics of the recharge basin.