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Delivering Hydrologic Data On Your Desktop From A Robotic Water Monitoring Platform

Congress: 2015
Author(s): Nuno Charneca, Jos Rocha, Joo Rogeiro, Anabela Oliveira
National Laboratory for Civil Engineering1, AmbiSIG2

Keyword(s): Sub-theme 10: Management of water resources,

The knowledge about the physical, chemical and biological mechanisms controlling water quantity and quality is usually limited by the availability of observations and measurements with adequate spatial density and temporal frequency. Since the fixed monitoring sites can only offer a restricted sampling of the water body conditions, we have developed an innovative autonomous robotic vessel capable of observe and measure water quality and hydromorphological elements on rivers, estuaries and reservoirs. This platform was conceived to be used in narrow (a few meters) to large systems and in a variety of depths, having the ability to monitor obstacles and handles sharp bathymetric, geometric and hydrodynamic variations.
The development of the AquaGIS robotic platform is being done in the scope of a research and development project to create and demonstrate an autonomous catamaran vessel for surface water monitoring, configurable enough to deal specifically with the Water Framework Directive (WFD) monitoring requirements. The main objective of the project is to offer a flexible solution to comply with WFD monitoring programmes (European Commission, 2003) established in the European River Basin Management Plans (RBMP).
Considering the RBMP of Vouga, Mondego and Lis in Portugal, the fixed monitoring sites comprehend: 49% of rivers and 66% of lakes. The RBMP refers that the actual monitoring network is not representative for rivers and only partially representative for lakes (Vouga, Mondego and Lis RBMP, 2012). All over Europe several RBMP refer significant gaps on monitoring networks and data about the quality elements used to classify water body status (biological, physico-chemical and hydromorphological).
Herein we describe the design and architecture of the information system and the functional requirements of the platform that supports the collection, organisation, storage, analysis and publication of continuously hydrologic observations based on a SOAP and REST web-services architecture. These data services, and the corresponding metadata information published in the Internet, allow users to discover and consume water observations and measurements into the most popular analysis platforms, like MS Excel®, R, Matlab® or ArcGIS®. This methodology reduces considerable the use of valuable personal time and resources to discover and access hydrologic data for research and water management.


The platform hardware architecture is based on the following components: 1) AquaLab (set of water quality sensors, sampler, weather station, acoustic doppler and video); 2) navigation sensors; 3) actuators and motors (set of equipment to steer and control the vessel); 4) communications (infrastructure to transmit control signals and hydrologic data); 5) command computer (to plan monitoring missions and monitor platform behaviour); 6) onboard central computer (to control steering processes, autonomous navigation, and receive digital and analogical signals from AquaLab). The onboard software architecture is based on the MOOS (Mission Orientated Operating Suite) library components, used to control the navigation and water monitoring sensors according to programmed monitoring missions (Newman, 2013).

The AquaGIS information technology infrastructure is based on the CUAHSI Hydrologic Information System (CUAHSI, 2008) for the platform data management. However, the underlying Observations Database Model -- ODM (Horsburgh, 2008) was designed to store fixed-location measurements, not appropriate for the AquaGIS robotic platform measurements acquisition methods (based on non-fixed location measurements). To accommodate our needs without disrupting the ODM, additional behaviour was introduced in the way data are stored. The chosen approach addresses limitations concerning the management of non-fixed measurements, bathymetric surveys, remote sensing data, and weather and climate grids (e.g. NetCDF). We have preserved ODM philosophy and maintenance of capacity to deliver data according to standards such as WaterML (OGC, 2012). We have developed and tested a new version of the database to deal with collections of time series of many variables measured simultaneously at several locations belonging to the same monitoring campaign.

Results and Discussion

The AquaGIS platform was conceived to be generic and adaptable for simpler or more complex and complete monitoring requirements. The prototype built and under testing is equipped with a sampler that maintains water recipients at 3ºC in ambient temperature from 0ºC to 40ºC and can hold 24 samples of 1 litre each. The platform can get samples until 10m deep and sample volumes varying from 10ml with acquisition frequencies from 1 minute to 100 hours. The Acoustic Doppler Current Profiler (ADCP) onboard allows for bottom tracking from 0.4m to 120m deep with a resolution of 0.01 cm/sec and a cell size of 2 cm (minimum). The water quality multi-sensors probe can measure the parameters presented in Table 1.

Table 1 -- Water quality parameters that could be measured

The information infrastructure that supports data management has been proven to be a flexible, robust and innovative solution that allows its users to get their data in near real time in standard formats over the internet. The hydrological data collected is documented by centralised metadata registries that permit discovery through geographic location or keywords.


Collect, transmit, register and publish high frequency hydrologic data present challenges for the community of researchers working toward the establishment of water observation robotic platforms. We have presented the general architecture and functional requirements of a new robotic water monitoring. This platform is made up of hardware and software components which demonstrate a specific implementation of a vessel to comply with surface water bodies monitoring programmes under WFD specifications. The unique set of tools that make up AquaGIS information system is supporting the storage and management (including data quality control) of all our test bed data and the open distribution of data via Internet-based tools, ensuring its availability in simple to use formats that are easily accessible, discoverable and interoperable. EU Water Framework Directive (2000/60/EC). Official Journal (OJ L 327) on 22 December 2000.

European Commission (2003). Common Implementation Strategy for the Water Framework Directive (2000/60/EC) – Guidance Document N.º 7 – Monitoring under the Water Framework Directive – Working Group 2.7.

Horsburgh, J.; Tarboton, D. (2008). CUAHSI Community Observations Data Model (ODM). Version 1.1.1 Design Specifications. Available from: (accessed 17.09.2014)

Maidment, D. (2008). CUAHSI Hydrologic Information System: Overview of version 1.1. Center for Research in Water Resources. The University of Texas at Austin.

Newman, P. (2013). A MOOS-v10 Tutorial. University of Oxford.

OGC – Open Geospatial Consortium (2012). WaterML 2.0: Part 1- Timeseries. OGC project document: OGC 10-126r3.

Vouga, Mondego and Lis River Basin Management Plan – RBMP (2012). Synthesis report. ARH do Centro I.P..

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