Difference between revisions of "FedCloudIFCAWaterQuality"

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FCUC_StartDate = 25/09/2014|  
 
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FCUC_EGIName  = Diego Scardaci / diego.scardaci@egi.eu|  
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FCUC_EXTName  = Fernando Aguilar / aguilarf@ifca.unican.es|  
  
 
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The framework of this development is the collaboration of our center within the European LIFE+ project ROEM+ where a Spanish SME, Ecohydros, is addressing the problem of modeling Water Quality in a water reservoir (Cuerda del Pozo in Soria) that is supplying drinking water to an small city in Spain.
 
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Understanding the Water Quality model requires a complete simulation of the processes that affect the water, and then validating this simulation with real data.
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IFCA has worked together with Ecohydros for the last five years, first to implement a near real time data acquisition system that provides this data directly to an offline data management system, and more recently, using a well-known software suite, Delft3D, to model the physical, chemical and biological conditions of the water.
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The key process to be modeled is Eutrophication, a process caused by the excess of nutrients in the water reservoirs leading to an increase in vegetation and other organisms and microorganisms, in particular algae, deriving in algae bloom when combined with certain conditions of solar radiation and water temperature.  The following depletion of oxygen in the water leads to the death of many microorganisms and in general to a large reduction of life in it, and their impact is important in water reservoirs used for urban supply. The final aim of the project is to develop an early warning system for this reservoir that allows policy makers and authorities to know when an algae bloom is going to happen, in order to take actions.|
 
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Delft3D is an Open Source software suite that works over a mesh made from a map of the modeled water body, in our case Cuerda del Pozo reservoir in Soria (Spain). The program runs with 2D and 3D meshes with a number of layers that can be edited by the user. Hence mesh resolution is an important factor for program performance. With a low or medium resolution mesh (cells larger than 250x250 meters with few vertical layers) execution can be successfully accomplished with standard PCs. However, when a detailed simulation is required, as it is the case to model the complex conditions’ leading to eutrophication, the resolution has to be increased (e.g. 100x100 meter cells with more than 30 vertical layers) and more powerful computers are needed. Given the project requirements in CPU (>=2.5Ghz, few cores), memory (>12Gb) and disk (up to a few Terabytes), the community needs a Cloud services provider like EGI FedCloud which allow them to manage the entire workflow of data processing and analysis. Also, given the needs for the output, the community needs a service able to support the storage of few terabytes and let them to transfer it using an easy and fast way.|
 
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[http://indico.egi.eu/indico/contributionDisplay.py?sessionId=0&contribId=5&confId=2160 Slides presented at the EGI Conference on Challenges and Solutions for Big Data processing on Cloud (24-26 September 2014)}}
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Revision as of 18:05, 23 December 2014

General Information

  • Status: Test & Integration
  • Start Date: 25/09/2014
  • End Date: -
  • EGI.eu contact: Diego Scardaci / diego.scardaci@egi.eu
  • External contact: Fernando Aguilar / aguilarf@ifca.unican.es

Short Description

The framework of this development is the collaboration of our center within the European LIFE+ project ROEM+ where a Spanish SME, Ecohydros, is addressing the problem of modeling Water Quality in a water reservoir (Cuerda del Pozo in Soria) that is supplying drinking water to an small city in Spain. Understanding the Water Quality model requires a complete simulation of the processes that affect the water, and then validating this simulation with real data. IFCA has worked together with Ecohydros for the last five years, first to implement a near real time data acquisition system that provides this data directly to an offline data management system, and more recently, using a well-known software suite, Delft3D, to model the physical, chemical and biological conditions of the water. The key process to be modeled is Eutrophication, a process caused by the excess of nutrients in the water reservoirs leading to an increase in vegetation and other organisms and microorganisms, in particular algae, deriving in algae bloom when combined with certain conditions of solar radiation and water temperature. The following depletion of oxygen in the water leads to the death of many microorganisms and in general to a large reduction of life in it, and their impact is important in water reservoirs used for urban supply. The final aim of the project is to develop an early warning system for this reservoir that allows policy makers and authorities to know when an algae bloom is going to happen, in order to take actions.

Use Case

Delft3D is an Open Source software suite that works over a mesh made from a map of the modeled water body, in our case Cuerda del Pozo reservoir in Soria (Spain). The program runs with 2D and 3D meshes with a number of layers that can be edited by the user. Hence mesh resolution is an important factor for program performance. With a low or medium resolution mesh (cells larger than 250x250 meters with few vertical layers) execution can be successfully accomplished with standard PCs. However, when a detailed simulation is required, as it is the case to model the complex conditions’ leading to eutrophication, the resolution has to be increased (e.g. 100x100 meter cells with more than 30 vertical layers) and more powerful computers are needed. Given the project requirements in CPU (>=2.5Ghz, few cores), memory (>12Gb) and disk (up to a few Terabytes), the community needs a Cloud services provider like EGI FedCloud which allow them to manage the entire workflow of data processing and analysis. Also, given the needs for the output, the community needs a service able to support the storage of few terabytes and let them to transfer it using an easy and fast way.

Additional Files

[http://indico.egi.eu/indico/contributionDisplay.py?sessionId=0&contribId=5&confId=2160 Slides presented at the EGI Conference on Challenges and Solutions for Big Data processing on Cloud (24-26 September 2014)