10 - CSIRO - WRM technologies and tools-Sep-16

1. Multiple tools and techniques for water
resources management
Modern Tools and Techniques for Water Resources Assessment and Management
Geoff Podger
16 September 2014
LAND AND WATER FLAGSHIP

2. Overview
CSIRO: Who we are
IWRM
Nexus webs
Modelling framework
Model choice
Water resource management technology
Best practice modelling
Geoff Podger | Page 2

3. We provide scientific responses
and solutions to major national
and global challenges
Top 1% of global research
institutions in 14 of 22 research
fields
Top 0.1% in 4 research fields
Darwin
Alice Springs
Geraldton
2 sites
Atherton
Townsville
2 sites
Rockhampton
Toowoomba
Gatton
Myall Vale
Narrabri
Mopra
Parkes
Griffith
Belmont
Geelong
Hobart
Sandy Bay
Wodonga
Newcastle
Armidale
2 sites
Perth
3 sites
Adelaide
2 sites Sydney 5 sites
Canberra 7 sites
Murchison
Cairns
Irymple
Melbourne 5 sites
CSIRO: Who we are
Werribee 2 sites
Brisbane
6 sites
Bribie
Island
People
Locations
Flagships
Budget
6000
58
9
$1B+
Geoff Podger | Page 3

4. CSIRO: What it brings to Water Resource
Management
•Significant depth and breadth of skills/expertise
•An understanding of complex multi-disciplinary systems
•Framework for integrating science
•A focus on impact in the science that we do
Geoff Podger | Page 4

5. CSIRO supporting water resource management
in South Asia
Brahmani – Baitarni: development of a
planning model to support water resource
management across three states.
Koshi Basin: development of a water
balance model to support hydro-power,
flood and sediment management.
Indus Basin: development of a planning
model to support management of
transboundary flows and within country
water resource sharing.
Bangladesh: supporting development of
groundwater resource plans
Geoff Podger | Page 5

6. Integrated Water Resource Management
“Integrated Water Resources Management (IWRM) is a process which promotes the coordinated
development and management of water, land and related resources, in order to maximise the resultant
economic and social welfare in an equitable manner without compromising the sustainability of vital
ecosystems.” GWP-TAC, 2000[i]
[i] GWP–TAC (2000). Integrated water resources management. Stockholm, Sweden, Global Water Partnership, Technical Advisory Committee Paper No. 4.

7. • Water System
o Water balance (domestic, irrigation, storage, end-of-system flows) ~Σ1
o Dynamics (hydropower flows, low flows, medium flows, flood flows)
o Additional (groundwater, desalinisation)
• Assets
o Infrastructure (water supply, irrigation, hydropower, dams)
o Natural assets (estuary, wetlands, floodplains)
• Services
o Products from infrastructure (food, energy, mitigation)
o Ecosystem system services (food, nutrient cycling, recreation)
• Wellbeing
o Economic (water/food/energy security, economic security)
o Social (social security, social cohesion, health)
o Environmental (environmental security/sustainability)
Water-Assets-Services-Wellbeing
Sharing a finite and changing resource for people
Geoff Podger | Page 7

8. ASSETS
WELLBEING
SERVICES
WATER SYSTEM
Bio-physical Modelling
Socio-economic Modelling
Social Decision Modelling
NEXUS WEBS
Geoff Podger | Page 8

9. Conceptual Model Design
• Climate
• Rainfall/Snow/Ice
• Surface/groundwater
• Water quality
• River systems modelling
• Biophysical modelling
• Ecosystems
• Socio-economic modelling
• Potable water
• Hydropower
• Agriculture
• Ecosystem services
• Social benefits
Geoff Podger | Page 9

10. Integrating Conceptual Framework
Hydrological systems and assets
Services
Wellbeing
Bio-physical Modelling
Threats
Levers for trade-off scenarios
Risk management
Socio- economic Modelling
Social Decision Modelling

11. Integrating Conceptual Framework
Cyrosphere / Snow melt models
River Flows
Groundwater
Sediment
Nutrients
Rainfall / Runoff models
Assets
Hydropower
Food production
Ecosystem Services
Hazard/Risk
Services
Energy production
Water Security
Economic Security
Food Security
Wellbeing
Energy Security
Sense of Security / Place
Bio-physical Modelling
Climate
•Change
•Variability
Population Growth
Land use
•Forest cover
•Landslides
•Bushfires
Threats
Environmental Security
Storages
Floodplains
Water Quantity
Water Quality
Irrigation
Environment
Levers for trade-off scenarios
Policy/Management, Build Infrastructure, Treatment, Targets/Standards, Education
Risk management
Socio- economic Modelling
Over-allocation
•Surface water
•Groundwater
Pollution
•Point
•Non point
Transport and fate
Treatment
Organics
Pathogen
Heavy metals
Urban water
Industrial
Recreational
Navigation
Social Decision Modelling
Potable WaterEnergy Security

12. Model choice
There are lots of different models available (too many acronyms to
remember) and in many cases the underlying algorithms are similar
There is no one model that can do everything
Model choice is a trade-off
Parsimony: Choose the simplest model that best answers the
question
Take into consideration uncertainty. Is the model telling us
something useful or is it noise?
Model
Choice
Problem Space
Data Complexity
Geoff Podger | Page 12

13. Model choice Questions
Problem Space (What are the issues to be considered?)
Planning (scale, sectors, sharing rules, WQ)
Operations (dams, structures, hydro, irrigation, environment, culture, WQ)
Forecasts (scale, lead time, extent, floods, allocations)
Data (What is needed and available?)
Global/Local, Observed/Inferred, Historic/Realtime
What is the uncertainty in the data?
Complexity (What is justified given data and problem space?)
Spatial and temporal scale
Process description
Run times
Number or parameters
Geoff Podger | Page 13

14. Water Resource Management Technology
Remote sensing (LIDAR, DEM, ET and
Land use)
Climate surfaces, GCMs and
downscaling
Water Resource Information Systems
Flood forecasting systems
Flexible hydrological modelling
frameworks
Workflow tools (integrating hydrological,
environmental and economic models)
Modelling uncertainty and risk
Technology in the cloud and web
Geoff Podger | Page 14

15. The spectrum of DEM products
9 second SRTM 3 second DEM-H 1 second Lidar 5 m
Geoff Podger | Page 15

16. Catchment delineation
Error in
delineated
watershed
area
5%
0.5%
1” : 30 m 3 arcsec: 90 m
DEM Cell Size
1990’s
2000’s
From: Maidment (2011)
Geoff Podger | Page 16

17. Climate data for South Asia
Data sources
• Local climate stations and local data products
• Aphrodite Asian precipitation data base
– 0.25o gridded daily rainfall data for Monsoon Asia
– 1951–2007
– http://www.chikyu.ac.jp/precip/products/index.html
• IMD Indian precipitation data base
– 0.25o gridded daily rainfall data for India
– 1901–2010
– http://www.imd.gov.in/doc/nccraindata.pdf
• Princeton global reanalyses climate data base
– 0.5o gridded daily climate data
– 1948–2008
– http://hydrology.princeton.edu/data.pgf.php
Climate variables
• Precipitation (rainfall, snow)
• Temperature
• Potential evaporation
• Humidity
• Solar radiation
• Wind speed/run
Geoff Podger | Page 17

18. Comparison of annual precipitation series
500
600
700
800
900
1000
1100
1200
1300
1400
1500
1901
1903
1905
1907
1909
1911
1913
1915
1917
1919
1921
1923
1925
1927
1929
1931
1933
1935
1937
1939
1941
1943
1945
1947
1949
1951
1953
1955
1957
1959
1961
1963
1965
1967
1969
1971
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
2011
2013
Rainfall (mm)
Year
Aphrodite (SA)
Princeton (SA)
IMD
Aphrodite (India)
Princeton (India)
Geoff Podger | Page 18

20. Precipitation, APET and runoff across South Asia
Mean annual
PRECIPITATION
Mean annual
RUNOFF
Mean annual
AREAL POTENTIAL
EVAPORATRANSPIRATION
From Aphrodite database Estimated from Princeton
climate data using
Morton’s Ew formulation
Estimated using
Budyko relationship
Geoff Podger | Page 20

21. 2046–2065 Dec–Feb temperature relative to 1986–2005 [RCP4.5]
2046–2065 Jun–Aug temperature relative to 1986–2005 [RCP4.5]
IPCC AR5 future temperature projections for South Asia
MEDIAN
MEDIAN
From IPCC AR5 “Atlas of global and regional climate projections”,
http://www.climatechange2013.org/report/full-report/
CMIP5 data portal, http://cmip-pcmdi.llnl.gov/cmip5/data_portal.html
Geoff Podger | Page 21

22. 2046–2065 Oct–Mar precipitation relative to 1986–2005 [RCP4.5]
2046–2065 Apr–Sep precipitation relative to 1986–2005 [RCP4.5]
IPCC AR5 future precipitation projections for South Asia
MEDIAN
MEDIAN
From IPCC AR5 “Atlas of global and regional climate projections”,
http://www.climatechange2013.org/report/full-report/
CMIP5 data portal, http://cmip-pcmdi.llnl.gov/cmip5/data_portal.html
Geoff Podger | Page 22

23. Change in mean annual runoff for 2oC warming
2080 flood frequency for 20th century 100-year flood
• Changed water availability
• Enhanced variability and reduced
water security:
- longer droughts
- more precipitation falling as rain
rather than snow
- retreat of glaciers
- increased seasonality of flow
• Enhanced flood risk
Climate change impact on water
Geoff Podger | Page 23

24. Water Resource Information Systems: Geofabric

25. • 3 month probabilistic outlook of
unregulated total streamflow volumes
• Ensemble forecasts at 74 sites in 32
river basins
• Uses CSIRO developed statistical
model (BJP)
• Further testing on sites in all states
and territories
• Extend to 200 sites by the mid 2015
• www.bom.gov.au/water/ssf
Seasonal streamflow forecasting

26. Flood & short-term forecasting
Ensemble forecast of a flood event in the Stanley River
Geoff Podger | Page 26

27. Short term streamflow forecasting
• Flow forecasts up to 10 days
ahead
• Unregulated inflows to regulated
systems
• Includes rainfall forecasts
• R&D conducted through CSIRO
• Ovens River pilot for registered
users

28. CLIMATE
LAND USE
ECOLOGICAL
ASSETS
DAMS &
WEIRS
IRRIGATION
CITIES
Flexible hydrological modelling
frameworks
Geoff Podger | Page 28

29. Tamor daily rainfall runoff model
• Area: 4058 km2
• Elevation: 422 – 8505 m
• Glacier area: 13%
Rainfall runoff model
• GR4J+snow+glacier
• 7 parameters
• 44 HRUs
• Bias 2% NSE 0.87

30. Brahmani-Baitarani river model

31. Dam break modelling
• CSIRO 2 and 3d hydrodynamic models
• Geheyan Dam in China
• Different dam break scenarios
Scenario 1 Scenario 2 Scenario 3
Scenario 4 Scenario 5 Scenario 6
Geoff Podger | Page 31

32. Urban water management
Geoff Podger | Page 32

33. Irrigation modelling
Farm scale bio-physical models (e.g. APSIM) consider:
 Physical properties of different crops over growing period
 Soil type
 Water and heat stress
 Irrigation efficiency
 Fertiliser application
 Yield and production
Regional scale crop models (e.g. Source) consider:
 Supply storages both regional and local
 Water access rules
 Multiple water sources (surface and groundwater)
 Distribution and return systems (irrigation districts)
 FAO 56 crop factors to drive current use and future demands
 Losses (channel, escapes, deep percolation)
 Crude yield and production estimates
Geoff Podger | Page 33

34. Floodplain modelling
hydrologic vs 2d hydrodynamic
a) Simulated inundation by LiDAR based approach b) Simulated inundation by 2D HD model
22 month event
10 minute run time
55 day event
10 day run time
Geoff Podger | Page 34

35. Revised annualised Ungauged Losses and Adjusted Losses (ML): Willara to Wanaaring.
(Positive values are losses, negative values are gains)
-200000
-100000
0
100000
200000
300000
1975 1980 1985 1990 1995 2000 2005 2010
Ungauged Loss Function
Adjusted Loss Function
0
20000
40000
60000
80000
1/01/2000 1/04/2000 2/07/2000 1/10/2000 1/01/2001
-10000
-5000
0
5000
10000
Raw Flow (Fit + UGL)
Groundwater Loss
Ungauged Loss Function
Adjusted ULF (ULF - GWL)
Revised daily flow components for the year 2000 (ML/d), Willara to Wanaaring.
River flow and GW loss are on left-axis, loss/gain functions on the right-axis.
• Establishing relationships in losing and
gaining streams
• Validating the relationships
• Integrating with the river system model
Preliminary results from Paroo
SW-GW connectivity map (MDBSY)
SW-GW interaction
Geoff Podger | Page 35

36. Physically based groundwater models
Geoff Podger | Page 36

37. Ecological Systems: Environmental Flow Modelling
Understanding Ecosystem
Complexity
• Species, habitats and refugia
Predicting Ecological Outcomes
• Ecological Response Models
• Driver-Pressure-Stressor-Impact-Response
Integration: Models & Assessment
• Scenario-based tools
• Optimisation-based tools
Time Since Last Wet (Low_Floodplain)
current
up to 05y
btn 05 to 1
btn 1 to 2
btn 2 to 5
btn 5 to 10
greater 10
0
0
0
100
0
0
0
Suitabiliy_TSLW1
Extreme Dry
Dry
Optimal
0
0
100
Redgum_Forest
Extreme Dry
Dry
Optimal
Wet
0
0
100
0
Suitabiliy_Duration1
Extreme Dry
Dry
Optimal
Wet
0
0
100
0
Duration1
irrelevant
up to 1mo
up to 2mo
up to 4mo
up to 6mo
up to 12mo
100
0
0
0
0
0
Suitabiliy_FF1
Extreme Dry
Dry
Optimal
Wet
0
0
100
0
FF_last_ten_yrs (Low Floodplain)
one in one
one in two
one in five
one in ten
less one in ten
0
100
0
0
0
Geoff Podger | Page 37

38. Impacts of….? Vulnerability of ecosystems to….?
• River Regulation?
• Climate Change?
• Hydropower?
• Land cover change?
What to consider in Basin planning?
• Ecosystem Services
• Water Quality
• Ecosystem function
• Fish for food
• Tourism / Recreation
• Habitat
• Cultural values
• Conservation
• System assets
• Biodiversity
• Threatened species, Ramsar sites
Environmental Flows: Why? What?
Geoff Podger | Page 38

39. Predicting Ecological Outcomes:
Models that are ‘Fit for Purpose’
No Data, High uncertainty
Some Data, Some
Knowledge
Lots of Data, Good
Knowledge
Data complete, System
well defined
Conceptual, Hydrologic
Alteration
Expert system, Habitat
models, Uncertainty analysis
Population dynamics,
Function dynamics
Dynamic ecosystem models
Participation
Geoff Podger | Page 39

40. Ecological Context | Danial Stratford
Prioritisation of Effort: A Data Poor Basin
• Defining Ecosystem Classes:
Which classes are predicted to
change hydrologically (dam
development, climate
change?)
What are the essential
services, functions and assets
by class?
Classes for extrapolation
Assessment: Uniqueness,
Vulnerability to change

41. Economic modelling
Local scale (farm, hydro station)
Regional scale (irrigation districts, countercyclical trade)
National scale (computable general equilibrium)
Trans-boundary scale (trade between countries)
Price, $
Quantity, GL
Supply
Demand
Qe
Pe
Pareto surface
Geoff Podger | Page 41

42. Many different workflow tools are available
Allow different models, data sources and outputs to be connected together in a
windows based interface.
Can connect different scale models
Can link hydrologic, environmental and economic models.
Can use HPC to run things many times on lots of computers.
Provides provenance so that you can reproduce results
Workflows to integrate and run models
Geoff Podger | Page 42

43. 419053 Manilla R @ Black Springs
Quantifying rating uncertainty Quantifying river model uncertainty
Quantifying groundwater model uncertainty
BATEA Uncertainty analysis
Uncertainty and risk assessment
Quantifying rainfall uncertainty

44. Decision Support
Geoff Podger | Page 44

45. Emerging Technologies
The cloud
– Running models as a service
– Running workflows as a service
Semantic web, linked open data
– Common data formats (e.g. WaterML2.0)
– Linking models to data and parameters via the
web
– Making results publicly available in a standard
form
Geoff Podger | Page 45

46. Best practice modelling framework
Geoff Podger | Page 46

47. Thank you
CSIRO Land and Water
Geoff Podger
Project Director South Asia SDIP
t +61 2 6246 5851
m +61 418 454 283
E geoff.podger@csiro.au
w www.csiro.au
LAND AND WATER FLAGSHIP