1. VYŠKOV - HYDRAULIC ANALYSIS OF WATER SUPPLY NETWORK
HYDROINFORM a.s. + AQUA PROCON s.r.o.
Czech republic

2. INTRODUCTION Vyškov is a district city with app. 20,000 inhabitants
100 km of pipeline, DN 50 - DN 500
Cast and PVC, 1936
Four main water sources supplying the whole area together
High pressure (up to 7.5bar), redundant high leakage

3. MODEL AREA
CZECH REPUBLIC
PRAGUE
VYŠKOV
BRNO

4. MODEL AREA

5. MODEL AREA

6. MODEL AREA 20,000 Inhabitants 100 km of pipelines DN 50 - DN 500
4 Water sources
High pressure
Big water losses

7. OBJECTIVES
Development, calibration and verification of a mathematical model
Steady state and extended period simulation
Dividing the existing network into several pressure zones:
optimum pressure distribution
leakage decrease
savings (electricity consumption, water production)

8. ODULA MODELLING PACKAGE
Analyses an entire water distribution system under steady-state and extended period simulations with water quality analysis.
Operates within Microsoft Windows 95 and Windows NT.
Integrates robust SQL Client - Server Database.

9. ITEA‘97
ODULA package was awarded by the European Innovation Technology Price ITEA‘97 in Brussels.

10. ODULA OVERVIEW Interactive model development.
Data exchange with MapInfo, ArcInfo, ArcView and MicroStation Outlook GIS.
Import ASCII files.
Import database files.
Display of vector and raster images.
Fast and accurate modelling.
High quality graphical capabilities.

11. ODULA MODELLING PACKAGE
ODULA DATA IMPORT
GRAPHICS
DATABASE
GIS DATA
MODELS
AutoCAD DXF
Raster Files
ASCII
InterBase
DBASE
PARADOX
ODBC
- Oracle
- Informix
- others
MAPINFO
ArcVIEW
LIDS
EPANET
WATERCAD
H2ONET
CYBERNET
KYPIPE
HYPRESS
ODULA MODELLING PACKAGE

12. ODULA MODELLING PACKAGE
ODULA DATA EXPORT
ODULA MODELLING PACKAGE
GRAPHICS
DATABASE
GIS DATA
MODELS
ASCII
InterBase
DBASE
PARADOX
ODBC
- Oracle
- Informix
- others
AutoCAD DXF
Raster Files
Microsoft AVI
MAPINFO
ArcVIEW
EPANET
HYPRESS

13. ODULA ANALYSIS ENGINE Industry standard EPANET (EPA) algorithm.
Powerful rigorous Hybrid method.
Hydraulic and water quality modelling.
Fast and accurate modelling.

14. ODULA ANALYSIS ENGINE Storage node equations:
¶ys /¶t = Qs / Sv (1)
Qs = Si Qis - Sj Qsj (2)
hs = Es + ys (3)
Link and junction node equations:
hi - hj = f(Qij) (4)
Si Qik - Sj Qkj - Qk = 0 (5)

15. ODULA ANALYSIS ENGINE Substance mass conservation:
¶ cij / ¶ t = -(Qij / Sij) (¶ cij / ¶ xij) + q(cij) (6)
First order kinetics reaction rate:
q(c) = -kbc - (kf / RH) (c - cw) (7)

16. ODULA ANALYSIS ENGINE Hydraulic model Dynamic water quality model
Gradient algorithm, Todini,E, Pilati, S, 1987
Efficient sparse matrix solution, George-Liu, 1981
Dynamic water quality model
Discrete volume element method, Rossmann, 1983

17. ODULA APPLICATIONS Master plans of water distribution networks.
Fire-flow analysis.
Pressure zones optimisation.
Water quality analysis.
Water age analysis.
Source tracing.
Industry pipe networks.
IF-THEN control rules modelling.

18. ODULA PROJECT EXAMPLES
MASTER PLAN OF PRAGUE
DATA IMPORTED
FROM LIDS GIS

19. ODULA PROJECT EXAMPLES
OKLAHOMA CITY
24-HRS SIMULATION

20. ODULA USERS More than 60 users within: Czech Republic (Czech version)
Poland (Polish version)
Russia (Russian version)
Italy (English version)
Austria (English version)
USA (US version)
Denmark (English version)
Sweden (English version)

21. COMPUTATIONAL SCHEME
WATER INFLOW
WATER TRANSFER

22. INPUT DATA PROCESSING ORIGINAL NETWORK DATA WAS DIGITIZED IN MAPA2
PIPE DATA
- MATERIAL
- RESIDENTIAL TYPE
- DIAMETER
NODE DATA
- X,Y,Z

23. INPUT DATA PROCESSING ORIGINAL NETWORK DATA WAS IMPORTED INTO ODULA
PIPE SCHEMATIZATION
HYDRAULIC STRUCTURES
- Tanks, reservoirs
- Pumps, valves
DEMAND DISTRIBUTION
- Reduced pipe lengths

24. INPUT DATA PROCESSING
PIPE SCHEMATIZATION

25. CALIBRATION DATA
RADOM DATA
H - POINTS
Q - POINTS

26. CALIBRATION DATA LARGE WATER CONSUMERS DATALOGGERS 14 DAYS PERIOD
DEMAND
DATALOGGERS

27. MODEL CALIBRATION Macro-level calibration Micro-level calibration
pipe roughness coefficients
nodal demands
Steady state calibration
Extended period calibration

28. MODEL CALIBRATION Steady state calibration PUMPING STATIONS
Accuracy about 3% of the total flow
within selected time level
TANKS
Accuracy from 0-22% of the total flow within
some of the time levels.
The differences are probably caused by undefined water consumers.

29. MODEL CALIBRATION Extended period calibration
RADOM and DATALOGGERS readings within the time step of 15 minutes.
The total simulation time was 24-hours

30. MODEL CALIBRATION TANK LHOTA TANK DRNOVICE TANK LHOTA TANK DEDICE
[%]
[ HOURS ]
TANK
LHOTA
TANK
DEDICE
PUMPING
STATION
KASPAROV
PUMPING
STATION
DRNOVICE
TANK
DRNOVICE
PUMPING
STATION
KRECKOVICE

31. HYDRAULIC SIMULATION Steady state analysis Extended period analysis
Multiple operational scenarios
Dividing the network into separate pressure zones

32. HYDRAULIC SIMULATION Dividing the network into separate pressure zones
Three main pressure zones
The estimate of the designed total demand was based on:
RADOM readings within the period of
Reduced pipe length method and the ratio of the invoiced water
Future development coefficient correction (increase of industry, population, specific demands)

33. HYDRAULIC SIMULATION ODULA allows you to model these pressure zones
all together
III. I.
IV.
II.

34. I. PRESSURE ZONE PUMPING STATION DEDICE
AT-Station with frequency regulation
TANK BRNANY
RECONSTRUCTED TANK

35. I. PRESSURE ZONE II. PRESSURE ZONE TANK DEDICE
Pumping station with the
frequency regulation
0.5
TANK BRNANY
I.PRESSURE ZONE
3.2
CONTROL RULES
were defined in the ODULA package
for both fast and slow filling including
water transfer from the II.PRESSURE ZONE
and the automatic frequency regulation
of the AT-Station
FAST FILLING
2.3
SLOW FILLING
2.0

36. I. PRESSURE ZONE II. PRESSURE ZONE TANK DEDICE
Pumping station with the
frequency regulation
II. PRESSURE ZONE
0.5
80l/s
TANK BRNANY
Minimum frequency
Maximum frequency
3.2
FAST FILLING
IF h(DEDICE)<0.5m THEN Q=80l/s
from II.PRESSURE ZONE.
Minimum frequency for h=3.2m in BRNANY
Maximum frequency for h=2.3m in BRNANY
FAST FILLING
2.3

37. I. PRESSURE ZONE II. PRESSURE ZONE TANK DEDICE
Pumping station with the
frequency regulation
II. PRESSURE ZONE
0.5
10l/s
TANK BRNANY
Maximum frequency
SLOW FILLING
IF h(BRNANY)<2.0m THEN Q=10l/s
from II.PRESSURE ZONE.
Maximum frequency for h=2.3m in BRNANY
2.3
SLOW FILLING
2.0

38. I. PRESSURE ZONE - SAMPLE RESULTS
TANK BRNANY
TANK BRNANY
FILLING
EMPTYING
BACKWARD TRACING
FORWARD TRACING
FLOW TRACING
220 HOURS
1700 HOURS

39. I. PRESSURE ZONE - SAMPLE RESULTS
SOURCE TRACING
OF DEDICE
24-Hours simulation

40. II. PRESSURE ZONE TANK LHOTA TANK DEDICE CONTROL VALVE TANK DRNOVICE
PUMPING STATION
KASPAROV
PUMPING STATION KRECKOVICE

41. II. PRESSURE ZONE III. PRESSURE ZONE I. PRESSURE ZONE TANK LHOTA
TANK DEDICE
TANK DRNOVICE
4.90
Control valve
2.45
PUMPING
STATION KASPAROV
I. PRESSURE ZONE
CONTROL VALVE SETTINGS
IF h(DRNOVICE)=4.9m THEN OPEN %
IF h(DRNOVICE)=2.45m THEN CLOSED 0%
FROM 2.45 TO 4.90 smooth opening %
PUMPING
STATION
KRECKOVICE

42. SAMPLE RESULTS
ORIGINAL STATE
PROPOSED STATE
PRESSURE ABOVE 60m
COMPARISON OF PRESSURE DISTRIBUTION BETWEEN THE ORIGINAL AND PROPOSED NETWORK STATE DURING MINIMUM FLOW.

43. PROPOSED NETWORK STATE
CONCLUSION
PROPOSED NETWORK STATE
FOUR PRESSURE ZONES
III.
AUTOMATIC THROTTLE VALVE BOA-COMPACT
PUMPING STATION WITH FREQUENCY REGULATION
LOWARA
RECONSTRUCTED
TANK I.
IV.
II.

44. SIGNIFICANT ENERGY SAVINGS
CONCLUSION
SIGNIFICANT ENERGY SAVINGS
Total energy consumption was calculated from the simulation results for both existing and proposed state for designed demands
app. 500 kW/day - Proposed state
app. 770 kW/day - Existing state
35% of energy savings

45. PRESSURE OPTIMIZATION
CONCLUSION
PRESSURE OPTIMIZATION
“Average pressure HĆ” is defined as statistical average of all junction nodes pressure values
HĆ = 38.7m - Proposed state
HĆ = 51.4m - Existing state
33% of the average pressure decrease

46. WATER QUALITY IMPROVEMENT
CONCLUSION
WATER QUALITY IMPROVEMENT
Groundwater sources are preferred
Surface water sources are less used

47. CONCLUSION LEAKAGE DECREASE NETWORK SEGMENTATION
Redundant leakage decrease corresponding to the average pressure decrease
Systematic leakage control is suggested for the future network maintenance
NETWORK SEGMENTATION
Easier network operational control