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

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1 In co-operation with BUILDING BLOCKS OF AN INTEGRATED FRAMEWORK FOR EFFECTIVE WATER RESOURCES MANAGEMENT Hans Korving Witteveen+Bos May 16, 2013

2 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

3 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 May 16, 2013

4 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)

5 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 sensoring 2 examples/caes of monitoring optimization

6 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)

7 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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9 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.)

10 Rainfall Runoff Sea conditions IN Q plus concentration Q plus concentration Q plus concentration River 1D model model Industry and domestic supply Water quality calculation based on mixing and processes River 1D structures River 1D sections OUT

11 Integrated Modeling approach

12 Use case 1: Amsterdam photo: Albert Jan Perrier May 16, 2013

13 Flushing the canal system May 16, 2013

14 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? May 16, 2013

15 Monitoring system Lijnbaansgracht Hortus bridge Pumping station Zeeburg Berlage bridge monitoring location system boundary May 16, 2013

16 Sensors Multi probe oxygen temperature conductivity turbidity Redox sonde May 16, 2013

17 Monitoring vessel multi probe pump data logger May 16, 2013

18 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 May 16, 2013

19 Real time validation May 16, 2013

20 Data integration - conductivity May 16, 2013

21 Conductivity Nov : DRY May 16, 2013

22 Impact of sluices in IJmuiden May 16, 2013

23 Oxygen Nov : DRY May 16, 2013

24 Oxygen Aug 1, 2011: WET May 16, 2013

25 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 May 16, 2013

26 Use case 2: Utrecht May 16, 2013

27 Catchment Prof Fuchslaan May 16, 2013

28 In-sewer defects May 16, 2013

29 In-sewer defects May 16, 2013

30 Monitoring network May 16, 2013

31 Monitoring data May 16, 2013

32 Model calibration 1 st : Genetic algorithm 2 nd : Levenberg Marquart May 16, 2013

33 Calibration result May 16, 2013

34 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 May 16, 2013

35 Future TRANSLATE + ADD ASSIMILATION May 16, 2013

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37 Data-assimilation May 16, 2013

38 Example: storm surge forecasting May 16, 2013

39 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 May 16, 2013

40 Data assimilation: possibilities Real time modeling Forecasting Early warning Real time control Re-analysis Optimisation of control Planning of management May 16, 2013

41 Questions? May 16, 2013