hydrological forecasting and data assimilation the hydrocast...

Hydrological Forecasting and Data Assimilation – The HydroCast Project Henrik Madsen

Head of Innovation, DHI

With contributions from the HydroCast team Danish Water Research and Innovation Platform, Annual Meeting, January 31, 2013

Project overview

• Research grant from the the Danish Council for Strategic Research

• Project period: 1 Jan 2012 – 31 Dec 2015

• Partners:

o DHI (Co-ordinator)

o Geological Survey of Denmark and Greenland (GEUS)

o Department of Geography and Geology, University of Copenhagen

o Department of Civil Engineering, Aalborg University

o Danish Meteorological Institute

o European Centre for Medium-Range Weather Forecasts (ECMWF)

o Institute of Applied Mathematics, Delft University of Technology

o Danish Road Directorate

o Knowledge Centre for Agriculture

o Danish Nature Agency

© DHI #2

Project objective To establish and test a general framework for hydrological forecasting and data

assimilation that integrates different data sources with meteorological and hydrological

modelling systems

© DHI #3

Time of

forecast

Hydrological ensemble forecast Hydrological data assimilation

Weather

radar nowcast

Short-range, limited

area NWP forecast

Medium-range, large

scale NWP forecast

Seasonal, large

scale forecast

Project activities - overview

© DHI #4

Work packages

• WP1: Combining weather radar and numerical weather prediction for short-range

forecasting

• WP2: Probabilistic hydrological forecasting

• WP3: Hydrological data assimilation

Test studies

• Test study 1: Forecasting of floods for rural infrastructure

• Test study 2: Seasonal forecasting of irrigation potentials

• Test study 3: Integration of modelling in environmental monitoring

WP1: Combining weather radar and numerical weather

prediction for short-range forecasting

• Forecasting system that combines weather

radar and high-resolution short-range NWP

modelling

• Weather radar forecast model based on a

combination of a storm cell and a radar

reflectivity tracking model

• Data assimilation of weather radar in NWP

model

• Quality control algorithms for state-of-the-art

dual polarisation weather radars

© DHI #5

First results of combined NWP-weather radar forecast system

Extreme rainfall event in Copenhagen 2 July 2011

© DHI #6

Maximum 30-min intensity



© DHI #7

Radar, 18 UTC Forecast 18 UTC, 3 hour lead time

WP2: Probabilistic hydrological forecasting

• Use of ensemble precipitation forecast products to

produce ensemble hydrological forecasts

Nowcast (few hours): weather radar ensemble

prediction

Short-range (< 48 hours): DMI ensemble prediction

system

Medium-range (2-10 days): ECMWF ensemble

prediction system

Seasonal: ECMWF seasonal ensemble prediction

system

• Framework for quantification and propagation of

different uncertainty sources in the hydrological

forecast system

© DHI #10

DMI’s limited-area, short-range ensemble prediction system

• Based on the HIRLAM model

• 0.05º horizontal resolution

• 25 ensemble members

Initial and lateral boundary condition

perturbations

Model physics perturbations

• 54h forecasts, four times per day

© DHI #11

DMI’s limited-area, short-range ensemble prediction system

© DHI #12

WP3: Hydrological data assimilation

• Multi-variate hydrological data assimilation based

on the MIKE SHE hydrological modelling system

• Generic data assimilation framework that uses

the open modelling interface (OpenMI) standard

and links to the OpenDA data assimilation

toolbox

• Assimilation of in-situ data (runoff, groundwater

levels, soil moisture profiles) and remote sensing

data (soil moisture, land surface temperature)

© DHI #13

Hydrological data assimilation - Example

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Simulated heads with DA Prediction uncertainty

Optimising the monitoring effort

© DHI #15

Environmental state

uncertainty

Costs

Optimal design of monitoring

effort (modelling + monitoring

network)

Test study 1: Forecasting of floods for rural infrastructure

• Test the data assimilation and forecasting techniques developed with respect to short-

range forecasting of flooding at a motorway infrastructure at Silkeborg

• Flooding is caused by a combination of rising groundwater levels and overland flow

generated by heavy rainfall

© DHI #16

Test study 2: Seasonal forecasting of irrigation potentials

• Test the probabilistic hydrological forecasting

tools for seasonal forecasting of river flows to

determine the potential amount of irrigation

water to be abstracted for maintaining a given

minimum flow

• Two forecast horizons considered

Forecast mid-February to be used for

planning of agricultural crops

Forecast mid-April to be used for issuing

irrigation permissions

© DHI #18

Test study 3: Integration of modelling in environmental

monitoring

• Test the developed multi-variate data

assimilation system for monitoring of the

hydrological state at catchment scale

• Application to the Skjern catchment

using data collected as part of the HOBE

center (www.hobecenter.dk)

© DHI #19

http://www.hobecenter.dk/

Main project results

• A methodology for combining weather radar and NWP modelling for short-range

forecasting.

• A seamless probabilistic hydrological forecasting system, considering short-range,

medium-range and seasonal forecasting.

• A multi-variate hydrological data assimilation system.

• Test of the developed hydrological forecasting and data assimilation methodologies in

three studies.

• Recommendations for local and central authorities on use of hydrological forecasting

and data assimilation.

• Three graduated PhD students and two completed Post Doc studies.

© DHI #20

Thank you for your attention Henrik Madsen

[email protected] This work was carried out with the support of the Danish Council for Strategic Research as part of the project “HydroCast – Hydrological Forecasting and Data Assimilation”, Contract No. 11-116880 http://hydrocast.dhigroup.com/ © DHI #21

hydrological forecasting and data assimilation the hydrocast...

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