- Background
Ensemble Streamflow Forecasting becomes a well-established technique in operational (flood) forecasting centers to assess forecast uncertainty. Currently, these forecasts are communicated to decision makers; however, taking decisions is still up to the subjective experience of the specific stakeholder. Due to the large amount of information in ensemble forecasts, this task is a major challenge in particular when time is limited during ongoing flood events.
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RTC-Tools 2 software framework
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Release overview:
- RTC-Tools 2.2.0 beta1 released on May 28, 2018
- RTC-Tools 2.2.0 beta2 released on June 18, 2018 (using Pymoca 0.2.7)
- RTC-Tools 2.2.0 beta3 released on Aug 24, 2018 (using Pymoca 0.2.8)
- RTC-Tools 2.2.0 beta4 released on Sep 27, 2018 (using Pymoca 0.3/0.4)
- RTC-Tools 2.2.0 rc1 (release candidate 1) expected mid November, 2018 (using Pymoca 0.3/0.4)
- RTC-Tools 2.2.0 (final release) expected December, 2018 (using Pymoca 0.3/0.4)
Associated URLs:
- License condition: GNU Lesser General Public License V3 (Lesser GPL)
- Website: https://www.deltares.nl/en/software/rtc-tools/
- RTC-Tools 2.2 python pip installation package: https://pypi.python.org/pypi/rtc-tools
- ChannelFlow Modelica library pip installation package: https://pypi.python.org/pypi/rtc-tools-channel-flow
- Python code repository: https://gitlab.com/deltares/rtc-tools
- ChannelFlow Modelica library repository: https://gitlab.com/deltares/rtc-tools-channel-flow
- Documentation: http://rtc-tools.readthedocs.io/
- Optimization API: http://rtc-tools.readthedocs.io/en/latest/optimization.html
- Simulation API (BMI): http://rtc-tools.readthedocs.io/en/latest/simulation.html
- Tutorial: http://rtc-tools.readthedocs.io/en/latest/examples.html
Dependencies Code dependencies are all managed within the installation package. RTC-Tools 2.2 has a strong co-development relation with pymoca.
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