In co-operation with BUILDING BLOCKS OF AN INTEGRATED ... · 2nd APWS Building blocks of a...

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In co-operation with BUILDING BLOCKS OF AN INTEGRATED FRAMEWORK FOR EFFECTIVE WATER RESOURCES MANAGEMENT Hans Korving Witteveen+Bos

Transcript of In co-operation with BUILDING BLOCKS OF AN INTEGRATED ... · 2nd APWS Building blocks of a...

Page 1: In co-operation with BUILDING BLOCKS OF AN INTEGRATED ... · 2nd APWS Building blocks of a framework for effective water resources management May 16, 2013 Outline Framework for water

Building blocks of a framework for effective water resources management2nd APWS May 16, 2013

In co-operation with

BUILDING BLOCKS OF ANINTEGRATED FRAMEWORK

FOR EFFECTIVE WATER RESOURCES MANAGEMENT

Hans KorvingWitteveen+Bos

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My background

Hans Korving Ccivil engineer, PhD in mathematics 15 years experience in data science for water and

delta technology Witteveen+Bos Consultancy and engineering firm Areas of expertise: water, infrastructure,

environment and construction Business unit Coasts, rivers and land reclamation

TU Delft Delft Institute of Applied Mathematics Focus area: data assimilation

May 16, 2013

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Building blocks of a framework for effective water resources management2nd APWS May 16, 2013

Outline

Framework for water resources management Use case 1: Amsterdam water quality management integrating data from different sources

Use case 2: Utrecht sewer system management real time model calibration integrating data and models

Future perspective integrated data and modelling framework research project in Delft city centre

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Building blocks of a framework for effective water resources management2nd APWS

Integrated water resource modeling

This means: Water quantity and water quality Water needs (droughts) and water safety (flood) Planning (mid/long term) and early warning (fast) Forecasting, decision support and crisis

management

This all needs: Good/validated monitoring data Supported by simulation tools (1d/2d-models, DSS)

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Good/validated monitoring data

Select need for monitoring data (is historic data not available or not enough for prediction)

What kind of data is needed: weather forecasting, rainfall runoff, flow, water quality, waterlevel, flooding, sewer, etc.?

Select type of monitoring data: sensor, satellite, social media, etc.

Install, monitor, calibrate, etc. sensors (real time) Data validation/assimilation of online

data Regular evaluation of monitoring program and

sensoring2 examples/caes of monitoring optimization

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Modeling tools

Weather forecasting: need for: expected precipitation/evaporation in coming 14 days and 3 months: based on satellite data, in combination with monitored rainfall/evaporation/irradiation and regional or global weather forecasting models

Rainfall Runoff: need for estimated flow at end of a watershed: based on precipitation/evaporation, area size, soil type, land use, groundwater, and rainfall runoff simulation (black box, statistical or more fysical approach)

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Modeling tools

River transport: need for forecasted waterlevels and flow at crucial locations: Based on online monitoring of waterlevel and flow in combination with 1D/2D combined modeling. Newest simulation models can automatically swith from 1D to 2D in situations of over land flooding

Flood management: Disaster management demands for estimations of flooding (where, when, how long, how deep, economic and social costs) to decide on controlled flooding elsewhere, temporary dike improvement, etc.

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Modeling tools

Water quallity: need for estimation of changes in salinity, oxygen problems due to (organic) pollution, accidental pollutions; based on monitoring of pollution in combination with water quality simulaton model, predicting the progression of the pollution and the effect of certain measures (flushing, re-routing, etc.)

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Building blocks of a framework for effective water resources management2nd APWS

Rainfall RunoffIN

Q plus concentration

OU

T

Water quality calculation based on mixing and processes

Industry and domesticsupply

Sea conditions

River 1D sectionsRiver 1D structures

River 1D model

Q plus concentration Q plus concentration

mod

el

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Integrated Modeling approach

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Building blocks of a framework for effective water resources management2nd APWS May 16, 2013

Use case 1: Amsterdam

photo: Albert Jan Perrier

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Flushing the canal system

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Building blocks of a framework for effective water resources management2nd APWS May 16, 2013

Our questions

Can the flushing regime be optimised? What is the impact of flushing on oxygen balance? What is the impact of flushing on light climate? What is the origin of water at a specific location?

Can the system behaviour be described using a limited number of stations and additional monitoring vessels?

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Monitoring system

monitoring location

Hortus bridge

Berlage bridge

Pumping station Zeeburg

Lijnbaansgracht

system boundary

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Sensors

Multi probe oxygen temperature conductivity turbidity

Redox sonde

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Building blocks of a framework for effective water resources management2nd APWS May 16, 2013

Monitoring vessel

pump

multi probe

data logger

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Data validation

Automatic algorithms (both real time and offline) missing data outliers (linear) trends signal variance spatial correlations mobile and nearby stationary sensors

Also accounting for cleaning and recalibration actions pollution and bio-fouling using manual checks

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Real time validation

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Data integration - conductivity

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Building blocks of a framework for effective water resources management2nd APWS May 16, 2013Nov 10-14. 2011: DRY

Conductivity

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Impact of sluices in IJmuiden

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Building blocks of a framework for effective water resources management2nd APWS May 16, 2013Nov 10-14. 2011: DRY

Oxygen

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Building blocks of a framework for effective water resources management2nd APWS May 16, 2013Aug 1, 2011: WET

Oxygen

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Conclusions use case 1

Monitoring of proxies provides enough understanding of the water flows in the Amsterdam canals

The canal system behaves like a (inter)tidal zone

The water quality in the canal system can be described with a limited number of stations and a boat

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Use case 2: Utrecht

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Catchment Prof Fuchslaan

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In-sewer defects

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Building blocks of a framework for effective water resources management2nd APWS

In-sewer defects

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Monitoring network

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Monitoring data

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Building blocks of a framework for effective water resources management2nd APWS

Model calibration

1st: Genetic algorithm2nd: Levenberg Marquart

May 16, 2013

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Building blocks of a framework for effective water resources management2nd APWS

Calibration result

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Building blocks of a framework for effective water resources management2nd APWS

Conclusions use case 2

Real time model calibration is an effective tool to identify in-sewer defects schedule maintenance

The impact of in-sewer defects varies in time

Time-varying fouling affects calibrations results

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Future perspective

@ TRANSLATE + ADD ASSIMILATION

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Building blocks of a framework for effective water resources management2nd APWS

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Data-assimilation

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Example: storm surge forecasting

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Building blocks of a framework for effective water resources management2nd APWS

Open interface standard for data assimilation Quick implementation of data assimilation for

arbitrary numerical models

Implementation in research project Delft Management of pluvial flooding in city centre Co-operation of management authorities, TU Delft

and Witteveen+Bos

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Data assimilation: possibilities

Real time modeling Forecasting Early warning Real time control

Re-analysis Optimisation of control Planning of management

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Building blocks of a framework for effective water resources management2nd APWS May 16, [email protected]

Questions?