INTOGENER Feasibility Study - on water flow monitoring and prediction services

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Objectives of the service

The main objective of the INTOGENER project is to enable the implementation of a water flow monitoring and prediction service supported by satellite-based technologies. INTOGENER is an ambitious initiative that uses space assets in different ways (observation, signal source of opportunity and data link). The activity starts with a feasibility phase that includes the identification of user needs, an analysis of the state of the art technologies, and from the output of these two tasks the definition of the service specifications and architecture. This feasibility study will also include the development of a prototype set-up as a proof-of-concept using a reduced set of EO data, in-situ instruments and a simplified model. This feasibility study shall demonstrate that the rationale of INTOGENER i.e. using an integrated system based on space assets, will bring added value in comparison to other solutions for water flow prediction for hydro power production and water management. This feasibility study will also asses the economic and non-economic viability of such a service in the long term and prepare a roadmap for the implementation of a larger scale demonstration project.

Users and their needs

ENDESA, the major power generation company in Spain and one of the most important in Latin America, will be INTOGENER's main user and stakeholder.

The project gathers EO service providers (image processing and distribution), satellite-based communication providers (data transfer from remote based sensors), scientific private and academic structures (hydrological modelling, EO image processing, in-situ sensors), navigation system actors (GNSS-R in-situ technologies) ,as well as the energy industry segment as final users.

Different actors in the field of hydropower and water Management were involved with their contribution to user needs, including utilities and water management agencies.

A first analysis of User Need has been performed, leading to a set of statements concerning the current status of flow prediction:


  • The indicators and methodology used to assess the hydrological uncertainty, i.e. flow prediction, through models are key to obtain valuable results to monitor the plants energy production.
  • Current operation models used in water management require hydrological information of water resource availability, particularly during drought events. To monitor these events is also very important for risk management.
  • The current hydrological model inputs are based on in situ measurements and statistical analysis based on past events. In situ data might sometimes be of difficult retrieval due to the extremely difficult access to the area to be monitored.
  • There is a clear need to include EO NRT data in the prediction methodology (assimilation by the model).
  • Flow prediction tasks are often subcontracted. Statistical Tools are the most common prediction tool in certain areas.
  • Flow prediction models used by majors companies can have between 40% and 80% of accuracy


The first INTOGENER target implementation will be Chile, where the Interconnected Central System (SIC) provides energy to more then 93% of the 15 million inhabitants, being 50.1 % of the generated energy derived from hydropower.

Due to the actual volume of the hydropower and associated water management activities in the area of study, a pre-operational service  improving the current flow prediction in the area will represent a significant milestone.

INTOGENER expects to improve the following points with respect the current system:

  • Prediction performance
  • Data availability
  • Continuity of predictions

Product Features

In the frame of this activity the feasibility of the technical architecture of the integrated service will be investigated, based on current existing technologies. The initially suggested architecture suggested is illustrated in the following figure.

Click to enlarge

The different elements of the system supporting the service are gathered in the following table:




Actions during Intogener



Water flow models using in-situ data and EO data

Use of the implemented  distributed model and algorithms

These include reliable parameters such as snow coverage as part of the control system

In-situ data

Deployment of an upgraded version of the Oceanpal instrument (GNSS-R instrument), complying with user requirements.

Reliable, cost effective,  easy installation and maintenance. Easily accessible data from remote mountain areas.

EO Data

Generation of Snow Cover Area maps (SCA) using
SAR images from Envisat WS-ASAR (150m resolution,  cloud free)

Better resolution and temporal continuity.

 GNSS-R data

If elements of the GALILEO IOV are available, the instrument will be upgraded to be able to exploit those additional satellites.

Continuous, real time measurements.


Key Issues

The INTOGENER project will analyse the feasibility to combine and integrate different service assets:

  • Satellite-based EO data
  • In situ information retrieved from GNSS reflections
  • Satellite communications
  • Assimilation of these data into a discharge model

The aim of INTOGENER is to:

  • Perform a feasibility study with the final goal of implementing a water flow prediction service aimed at hydro power production and water management companies.
  • Overcome current constrains and difficulties to count on reliable water flow predictions.

Current Status

INTOGENER study  finished on July 2011. Due to the promising results, a follow-on demonstration project is under preparation, targeting two Chilean basins and involving ENDESA Chile as the user.

The following tasks have been successfully conducted:

  • Identification and consolidation of user requirements.
  • Analysis on the current state-of-the-art technologies and services for water flow monitoring.
  • INTOGENER service definition.
  • Feasibility of the service concept.
  • Viability analysis.
  • Service roadmap, including a detailed plan for the follow-on demonstration project.

Status Date

Updated: 08 November 2011 - Created: 15 February 2014