Merging and calibration of radar rain products for quantification of input uncertainty in urban drainage modelling for the Haute-Sûre catchment in Luxembourg
Environmental Informatics 2017
By Jairo Arturo Torres-Matallana in Talks
September 15, 2017
Abstract
We present and illustrate a proposed work flow to build and calibrate a space-time geostatistical model of rain, using radar imagery as a covariate in regression-kriging based simulation. Then, a work flow for run-off and sewer system modelling is presented as well. These work flows are repeated as many times as the Monte Carlo simulation design requires to obtain an ensemble of rainfall input maps and time series of quantity variables and quality variables are produced to analyze how input uncertainty propagates to output uncertainty.
Date
September 15, 2017
Time
2:00 PM
Location
Luxembourg, Luxembourg
Event
Environmental Informatics 2017
From Science to Society: The Bridge Provided by Environmental Informatics
The 31st International Conference on Environmental Informatics, EnviroInfo, is held in Luxembourg, hosted by the Luxembourg Institute of Science and Technology (LIST). The conference focus: From Science to Society. The themes:
- Applications of Geographical Information Systems and Disaster Management.
- Environmental Modelling and Simulation.
- Energy Informatics and Environmental Informatics.
- Software Tools and Environmental Databases.
- Energy Aware Software-Engineering and Development.
- Sustainable Mobility.
A proposed workflow for rainfall ensemble in uncertainty propagation
In this talk, I present how the proposed workflow represents a more realistic simulated time series of rainfall originating run-off that enters the sewer system, and therefore we can do the Monte Carlo input uncertainty propagation and compare with results obtained in previous studies we did. In the future, we expect that validation will show a better job done not only in terms of mean error and root mean squared error of tank volume and overflow, but also in quantifying the uncertainty in the sewer system model outputs.