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CrowdWater | SPOTTERON

CrowdWater is a SNF-funded project at the University of Zurich, Department of Geography, Unit Hydrology & Climate

CrowdWater is a SNF-funded project at the University of Zurich, Department of Geography, Unit Hydrology & Climate

CrowdWater | SPOTTERON

by SPOTTERON Gmbh
CrowdWater | SPOTTERON
CrowdWater | SPOTTERON
CrowdWater | SPOTTERON

What is it about?

CrowdWater is a SNF-funded project at the University of Zurich, Department of Geography, Unit Hydrology & Climate.

CrowdWater | SPOTTERON

App Details

Version
4.0.6
Rating
NA
Size
94Mb
Genre
Education Travel
Last updated
September 24, 2024
Release date
March 10, 2017
More info

App Screenshots

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CrowdWater | SPOTTERON screenshot-1
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App Store Description

CrowdWater is a SNF-funded project at the University of Zurich, Department of Geography, Unit Hydrology & Climate.

This PhD project aims to examine the potential of “crowdsourcing”, meaning observations of voluntary participants. As the name suggests, the project looks at the potential of crowdsourcing in the field of hydrology. We will collect water level, streamflow and soil moisture data. The project will not only look at the possibilities of collecting data but also at the value of this data for hydrological forecasts. The long-term aim of the project is to collect a large amount of data and to improve the forecast of hydrological events, such as droughts or floods.

There are two basic parts of the CrowdWater project. On the one hand, we will assess public involvement in hydrological observations. For this we use a “geocaching” type approach with the help of smartphones. By using an app that will be developed over the coming months, users can install a virtual measuring station. Anyone can then add their observations to this station and all observations will be collected and published anonymously on the CrowdWater homepage. Another goal of the CrowdWater project is to analyse the potential of using the collected data for hydrological models. This question will be addressed by using hydrological computer models to predict streamflow. These models will assess the benefit of the crowd-sourced data.

At the moment the app is under development, so for now we are collecting data with the help of information boards and paper forms at various locations in the greater Zurich area. This data will help us to improve our methodology and enables us to make a first assessment of the data quality. As soon as new stations are installed, we will post the location here and on facebook.

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