Technical Note: Low cost stage-camera system for continuous water
level monitoring in ephemeral streams

Noto, Simone; Tauro, Flavia; Petroselli, Andrea; Apollonio, Ciro; Botter, Gianluca; Grimaldi, Salvatore

doi:10.5194/hess-2021-36

Cited by 5 publications

(3 citation statements)

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“…Being flood monitoring a continuous task, we believe that solutions should take night-operation into consideration as we did. Generally, this system is going to be installed into unconstrained and not-standardised contexts, hence, it can't rely on strong chromatic assumptions, like the solutions proposed by [16], which requires the gauge to be brighter than its background, by [17], whose processing steps rely on color and morphology of the gauge, by [21] that exploits color for extracting gauge's ROI. Our solution is not based on chromatic assumptions.…”

Section: Discussionmentioning

confidence: 99%

“…By looking at some sample frames, we noticed that during extreme weather the quality of captured images might become very low, thus making OCR not a viable nor reliable solution. Noto et al [16] proposed a solution tested in a non-simulated scenario with some critical conditions of lighting and landscape. Their solution is capable of working 24 h a day but adopted a pole instead of a gauge.…”

Section: Introductionmentioning

confidence: 99%

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A Computer Vision System for Staff Gauge in River Flood Monitoring

et al. 2021

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Rivers close to populated or strategically important areas can cause damages and safety risks to people in the event of a flood. Traditional river flood monitoring systems like radar and ultrasonic sensors may not be completely reliable and require frequent on-site human interventions for calibration. This time-consuming and resource-intensive activity has attracted the attention of many researchers looking for highly reliable camera-based solutions. In this article we propose an automatic Computer Vision solution for river’s water-level monitoring, based on the processing of staff gauge images acquired by a V-IoT device. The solution is based on two modules. The first is implemented on the edge in order to avoid power consumption due to the transmission of poor quality frames, and another is implemented on the Cloud server, where the frames acquired and sent by the V-IoT device are processed for water level extraction. The proposed system was tested on sample images relating to more than a year of acquisitions at a river site. The first module of the proposed solution achieved excellent performances in discerning bad quality frames from good quality ones. The second module achieved very good results too, especially for what it concerns night frames.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Computer Vision System for Staff Gauge in River Flood Monitoring

et al. 2021

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“…CC BY 4.0 License. riancic et al, 2018;Jensen et al, 2018;Lovill et al, 2018;Ward et al, 2018;Barefoot et al, 2019;Garbin et al, 2019;Jaeger et al, 2019;Jensen et al, 2019;Botter and Durighetto, 2020;Durighetto et al, 2020). Seasonal and event-based variability of the climatic forcing in these uppermost areas often originate intermittent and ephemeral streams, whereby discontinuous flow or sporadic flow in response to rainfall events posit severe challenges to a thorough characterization of network patterns (Borg Galea et al, 2019; van Meerveld et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Comment on hess-2021-36

2021

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Monitoring ephemeral and intermittent streams is a major challenge in hydrology. While direct field observations are best to detect spatial patterns of flow persistence, on site inspections are time and labor intensive and may be impractical in difficult-to-access environments. Motivated by latest advancements of digital cameras and computer vision techniques, in this work, we describe the development and application of a stage-camera system to monitor the water level in ungauged headwater streams. The system encompasses a consumer grade wildlife camera with near infrared (NIR) night vision capabilities and a white pole that serves as reference object in the collected images. Time-lapse imagery is processed through a computationally inexpensive algorithm featuring image quantization and binarization, and water level time series are filtered through a simple statistical scheme. The feasibility of the approach is demonstrated through a set of benchmark experiments performed in controlled and natural settings, characterized by an increased level of complexity. Maximum mean absolute errors between stage-camera and reference data are approximately equal to 2 cm in the worst scenario that corresponds to severe hydrometeorological conditions. Our preliminary results are encouraging and support the scalability of the stage-camera in future implementations in a wide range of natural settings.

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ArduHydro: A Low-Cost Device for Water Level Measurement and Monitoring

Galli

Peruzzi

Gangi

et al. 2022

Preprint

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ArduHydro is a low-cost device for water level measurement and monitoring designed for a short and long-term employment in controlled and outdoor environments. It measures water level through an ultrasonic sensor and elaborates the signals through an Arduino micro controller. The small size of this device, the low energy required for its operation, its robustness and accuracy make ArduHydro properly versatile for different applications in the field for water control and management. This article describes the design, the components, the costs, and the performance of ArduHydro. Performance was assessed with a laboratory test inside a hydraulic circuit constituted by an open channel flume and comparing ArduHydro measurements with those obtained with a traditional ultrasonic sensor. An example of ArduHydro application for detecting the wavefront evolution during a surface irrigation is presented as well. The results revealed that ArduHydro measurements were on average very consistent with those obtained by the traditional ultrasonic sensor in all different flow conditions (i.e. different flowrate and water depth) demonstrating its reliability and accuracy in the measuring water level. The application of ArduHydro during a surface watering of an agricultural field allowed to obtain important spatio-temporal information about the water depth along the longitudinal direction of the field, paying the way for a real comprehension of the dynamics of wavefront evolution in a real-world case study.

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Technical Note: Low cost stage-camera system for continuous water level monitoring in ephemeral streams

Cited by 5 publications

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A Computer Vision System for Staff Gauge in River Flood Monitoring

A Computer Vision System for Staff Gauge in River Flood Monitoring

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ArduHydro: A Low-Cost Device for Water Level Measurement and Monitoring

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