Abstract

Abstract. In the last decades, an increase in the number of extreme precipitation events has been observed, which leads to increasing risks for flash floods and landslides. Thereby, conventional gauging stations are indispensable for monitoring and prediction. However, they are expensive in construction, management, and maintenance. Thus, density of observation networks is rather low, leading to insufficient spatio-temporal resolution to capture hydrological extreme events that occur with short response times especially in small-scale catchments. Smaller creeks and rivers require permanent observation, as well, to allow for a better understanding of the underlying processes and to enhance forecasting reliability. Today’s smartphones with inbuilt cameras, positioning sensors and powerful processing units may serve as wide-spread measurement devices for event-based water gauging during floods. With the aid of volunteered geographic information (VGI), the hydrological network of water gauges can be highly densified in its spatial and temporal domain even for currently unobserved catchments. Furthermore, stationary low-cost solutions based on Raspberry Pi imaging systems are versatile for permanent monitoring of hydrological parameters. Both complementary systems, i.e. smartphone and Raspberry Pi camera, share the same methodology to extract water levels automatically, which is explained in the paper in detail. The annotation of 3D reference data by 2D image measurements is addressed depending on camera setup and river section to be monitored. Accuracies for water stage measurements are in range of several millimetres up to few centimetres.

Highlights

  • It is impossible to imagine today’s weekly news without hearing the term of ”climate change”

  • Terrestrial Laser Scanning (TLS) was applied at the Triebenbach and Wesenitz to check the quality of the Structure from Motion (SfM)-based point clouds

  • Thereby, multi-seeded region growing is applied within a user-defined region of interest (RoI) using either the spatio-temporal texture or the average image depending on the distinctiveness between water and land in both data sources

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Summary

INTRODUCTION

It is impossible to imagine today’s weekly news without hearing the term of ”climate change”. Hydrological networks may have an insufficient coverage for threatened areas in case of need Improvements in this sense can be achieved using photogrammetry for contactless monitoring of environmental parameters For the development of a versatile mobile and stationary low-cost system for hydrological measurements, the image data of a monitored river section, captured by smartphone or Raspberry Pi camera, is analysed for its prevalent water line. Due to the intersection of image and object data, the water line can be interpreted as series of water levels. Three study regions situated close to conventional water gauges, one for mobile and two for stationary water level observation, are chosen to enable evaluation of the results (section 3).

Related work
LOW-COST MEASUREMENT HARDWARE
Smartphone
Raspberry Pi
STUDY AREAS
Digital surface models
Camera requirements
APPLICATION DEVELOPMENT
Time lapse image sequences for water line determination
Surface annotation
EVALUATION
OUTLOOK
Full Text
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