Mobile Crowd Sensing of Water Level to Improve Flood Forecasting in Small Drainage Areas

Abstract

Flood forecasting is particularly difficult and uncertain for small drainage basins. One reason for this is due to inadequate temporal and spatial hydrological input variables for model-based flood predictions. Incorporating additional information collected by volunteers with the help of their smartphones can improve flood forecasting systems. Data collected in this way is often referred to VGI data (Volunteered Geographic Information data). This paper discusses how this information can be incorporated into a flood forecasting system to support flood management in small drainage basins on the basis of mobile VGI data. It therefore outlines the main functional components involved in such a VGI-based flood forecasting platform while presenting the component for mobile data acquisition (mobile sensing) in more detail. In this context, relevant measurement variables are first introduced and then suitable methods for recording these data with mobile devices are described. The focus of the paper lies on discussing various methods for measuring the water level using inbuilt smartphone sensors. For this purpose, three different image-based methods for measuring the water level at the banks of small rivers using a mobile device and the inbuilt orientation and camera sensors are explained in detail. It is shown that performing the measurements with the user's help via appropriate user interaction and utilising known structures at the measuring points results in a rather robust image-based measurement of the water level. A preliminary evaluation of the methods under ideal conditions found that the developed measurement techniques can achieve both an accuracy and precision of less than 1cm.

Use of Mobile Crowdsensing in Disaster Management: A Systematic Review, Challenges, and Open Issues

“…Zabota and Kobal [ 41 ] discuss a new methodology for collecting data on past rockfall events through mobile application to enhance the quality of rockfall risk assessment. Burkard et al [ 42 ] present image-based methods for measuring the water level at small drainage areas with a mobile phone and inbuilt sensors.…”

“…Information exchange between citizens is overlooked in this study. Burkard et al [ 42 ] present image-based measurement methods to feed into a conceptual flood prediction system that can be used in rivers. The methods are based on three variants of inclination, reference points, and correspondence points, which are measured using the camera and orientation sensors (accelerometer and gyroscope) of a smartphone.…”

Toward Integrated Large-Scale Environmental Monitoring Using WSN/UAV/Crowdsensing: A Review of Applications, Signal Processing, and Future Perspectives

“…Due to the severe climate changes experienced in the last few years, flood occurrences increased considerably, and containing their effects requires up-to-date and accurate knowledge of some critical environmental state variables [269]. Some studies have demonstrated that smartphones can estimate important parameters such as water levels, with an accuracy that can even achieve the cm level when the images captured by cameras are fused with the builtin orientation sensors [269,270]. The main drawback resides in the still too-involved operations that are demanded of the volunteers in order to carry out meaningful measurements.…”