Decision Support for Urban Environmental Planning
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Transcript of Decision Support for Urban Environmental Planning
Decision Support for Urban Environmental Planning
Vishal K. Mehta, Ph.D.Stockholm Environment Institute
[email protected] www.sei-international.orgwww.sei-us.org
Dec 29, 20116th International Public Policy and Management ConferenceIIM-Bangalore, India
Acknowledgements: M.Sekhar, D.Malghan, Arghyam
OUTLINE
I. Decision Support in PlanningNeed for Decision Support
Examples
II. Barriers to effective decision SupportKnowledge Gaps
III. Ongoing Research
Transport
Energy
Water
Infrastructure
Landuse
Security
1. Need for Decision Support in Urban Planning
Comprehensive and Integrated Urban Planning
THE CHALLENGE
Decisions made across multiple sectors In multiple dimensionsby multiple actors/agencies
1. Need for Decision Support in Urban Planning
LARGE UNCERTAINTIES
Uncertainty
Impact
Drivers
Critical uncertainties
1. Need for Decision Support in Urban Planning
RAPID URBANIZATION -> CHANGING CITY Bangalore, India:
YearPopulation (m)
Density (per sq km)
Built-up area % urban footprint
1971 1.65 9,465 20%
1981 2.92 7,990 26%
1991 4.13 9,997 39%
2001 5.1 11,545 69%
2011 ~9 na na
Sources: Census; Iyer et al (2007)
• In 60 yrs, India’s urban population growth rate twice that of overall population
• Urban poor ~2 5% of urban population
• 20 m/100m lack safe water/sanitation
I. Role of Scenario-based Risk assessment
Scenario-Based Risk Assessment considers:
System performance over all plausible conditions, moves away from traditional “design event” approach
Explicitly recognizes that uncertainty (lack of quantified probabilities) exists in the process and must be addressed through scenario analysis
Relies upon two way communication with stakeholders to select the level of risk they can tolerate with consideration of tradeoffs of multidimensional costs vs safety
Results in Robust Decisions – adaptation strategies that are least likely to fail
I Examples of DST: Urban Air pollution (Meerfert, Denmark)
Jensen et al., 2001. A Danish decision-support GIS tool for management of urban air quality and human exposures. Transportation Research Part D: Transport and Environment 6, 229-241.
Motivation: Larsen et al (1997) found that mortality from traffic-related air pollution as high as that from accidents
I Examples of DST: Urban Air pollution (Meerfert, Denmark)
Elements of Air Pollution
DSS
Air Quality Monitoring
Emissions inventory
Air Quality &Exposure mapping
Assessment of abatement
measures
Information to the public
Forecasts
Linking Environmental Quality to Public Health is key to public awareness &behavioral change, and should be an urban governance mandate
I Examples of DST: Broad St Cholera Outbreak, London 1854
Linking Environmental Quality to Public Health :
the beginnings of epidemiologyDr. John Snow mappedCholera outbreak to a single contaminated pump
I Examples of DST: Low-carbon development
https://www.eureapa.net/ EUREAPAConsumption-based footprint of 45 countries, 57 sectors
I. Examples of DST: Water Supply/Water Resources Management
• Focus on increasing extraction and supply -> No comparative cost-benefit analysis of various options (scenarios)-> Examples:
BangaloreChennai
Delhi
UTILITY PERFORMANCE• No city has 24/7 water supply• Poor often pay more for water• High leakage rates (20-60%)
• Big cities: surface water supply from afar• Small towns: groundwater
• Electricity is >30% of costs• Inability to recover costs
Projects Year
Installed
Capacity (MLD)
Present Supply (MLD)
Arkavathy (TG Halli) 1933 149 60
Cauvery Stage I 1974 135 135
Cauvery Stage II 1983 135 135
Cauvery Stage III 1993 270 300
Cauvery Stage IV, Phase – I 2002 270 270
Total Supply 959 900
Will agriculturecompete for shared water supplies or become a potential source?Agricultural production models with water rights database
Will the hydrology change?Hydrology models with land use projections
Will groundwater remain viable?Groundwater flow and transport models
Will retail customers practice conservation?Demand side models
How much will new residential construction increase demand?Regional economic models
Will this fish be listed for protection?Habitat and species lifecycle models with Ecosystem databases
Can we tap into a new supply?River hydraulic and contaminant transport models with water treatment models
Will industrial discharges change?Regulatory and emerging technology analysis with industry forecast models
Will hydropower management change in response to shifts in the market?Energy policy analysis with energy sector forecast models
Will recreation remain compatible with future operations?Recreational use surveys with future projections
Note: Image adapted with permission from the City of Portland, Oregon Water Bureau
How will climate change?Climate models
324643
I Examples of DST: Integrated Water Resources Management
Water Evaluation and Planning (WEAP) System ( www.weap21.org ) A generalized water resources software that provides flexible user-friendly interface to build custom applications
A Decision Support Tool for Integrated, Comprehensive, Cross- Scale Water Management Planning
Integrated : Hydrology with Priority-based Demand Allocation
Comprehensive: Can include Equity, Environmental constraints, Financial Aspects, Water quality, Groundwater
Cross-Scale: From a single house to a city to a riverbasinIdeal for ”What-if” scenario investigations for PLANNING and POLICY Analysis
Management scenariosClimate change impacts
I. Example: Water Supply - Lake Victoria townsLake Victoria region
Masaka Bukoba Kisii
Population 70,000 69,000 200,000
Streamflow(106 m3)
6.9 - -
Water produced (106 m3)
2.35 0.9
Demand coverage 80% 60% <50%
Operating Costs 496,000 USD 465,000 USD 726,000 USD
Revenues 768,000 USD 470,000 USD 383,000 USD
Key issues Waterworks capacity, population growth
Unaccounted Water (UAW)~50%, high electricity costs
Revenue<<CostsVery low coverage UAW~50%, high electriciity costs
Scenarios Investigated
Infrastructure Increased capacity Increased capacity, reduced EAW
Increased capacity, reduced EAW
Demand 2% population growth and climate-related demand model
4% population growth
4% population growth
Climate CCSM,Reduced rainfall
None None
(1) To examine how climate, demography and infrastructure impacts water utility performance in 3 east African towns
(2) To develop water resources management tools that integrate above aspects in a single platform
Results from Masaka, Uganda
I. Example: Water Supply - Lake Victoria towns
“…Hydrologic integration is necessary to evaluate the water availability and impacts side of the water supply problem. Collection of the hydroclimatic data needed in order to do the same, should be a priority for utilities and agencies in the LV region…”
II Barriers to Effective Decision Support
Knowledge Gaps
Institutional
Financial
Technical
Inclusion
Communication
Barriers
II Barriers to Effective Decision SupportCrucial Knowledge Gaps
• Hydrology is rarely understood -> biophysical limits to water availability
What is the natural water balance ?
• Of both far-off source waters, of local water sources
Ex: The resolution of groundwater monitoring (1 per 40-50 km2) is not enough for highly variable urban landscapes
II Barriers to Effective Decision Support
Crucial Knowledge Gaps
• Changed hydrology of urban environments -> (biophysical impacts)
What is the impacted water balance?
• E.g. Elevated, and contaminated water tables (Seoul, Mulbagal, Bangalore)
Sekhar, M. and Kumar, M.S.M. 2009. “Geo-hydrological studies along the Metro Rail Alignment in Bangalore
BWSSB supplies 900 MLD into the city from surface water that is not local to Bangalore
II Barriers to Effective Decision Support
Crucial Knowledge Gaps
• Extraction and Demand from each source remains unknown
• Demand drivers for above across the social-economic spectrum
• E.g. tankers, pvt borewells, local water bodies
• How many wells? How much being pumped out? How much returning and where?
• E.g. Chennai: 22-66% of water demand met by private wells
II Barriers to Effective Decision Support
Streamflow~ 10%
Surface watershed
Rain 100%
AET ~ 80%
Groundwater Aquifer
Percolation (Rainfall Recharge)~ 10%
Net Groundwater discharge~ 10%
Aim: Impacts of population growth on GW depths; RWH, WWT, investment decisions
What can we do the in the meantime?
Example: Mulbagal
With Arghyam, IISc
II Barriers to Effective Decision SupportWhat else can we do in the meantime?Room for innovation?• Public participation in data collection (e.g. OpenStreetMaps)• Crowdsourcing (e.g. Thailand flood)• Sensor Networks
http://de21.digitalasia.chubu.ac.jp/floodmap/
III. Current Research Activity in Bangalore
Key research questions:
1. What is the city-wide pattern of (water) resource availability?
2. What is the geographic distribution of (water) consumption?
3. What are the drivers that explain the pattern of water consumption observed?
4. What projections can we make for water demand and supply, as well as feedbacks to sources into the future?
5. What are the links and feedbacks to the biophysical system
III. Current Research Activity in BangaloreResearch Activities and Methods ..
1. Household Water consumption surveyMental model for drivers of Quantity, source-mix
III. Current Research Activity in Bangalore
Groundwater –surface water models, mass balances
Research Activities and Methods…
2. Understanding the biophysical resource: groundwater models, mass balances
3. Optimal monitoring density in urban environments Adaptive sampling, Bayesian data fusion
III. Current Research Activity in Bangalore
Geospatial web tools
Research Activities and Methods …
4. Formal participatory planning exercises5. Urban Metabolic MappingGeospatial web-based planning platform
An open-source application for
- Information Communication- Web-based scenario-planning
http://www.seimapping.org/bump/index.phphttp://seilinux.tccs.tufts.edu/~douglas/bump/index.php
Summary
1. Decision Support Tools can be very valuable for comprehensive urban and
regional planning
2. These tools already exist; or can be built with scientific input
3. Knowledge gaps limit the full potential of DST to be achieved – but progress
can be made in parallel
4. Intensive data-driven approaches will be necessary to fill knowledge gaps
5. Urgent need for• Intensive environmental quality monitoring• Linkage between environmental quality and public health• Effective public participation and communication• Formal scenario-based planning for the future
THANK YOU !
I. Some WEAP examples
Water Systems PlanningSmall Reservoirs Project, Ghana/BrazilCalifornia Water Plan, California, USAGuadiana River, SpainTransboundary Water PolicyOkavango River, Angola/Namibia/BotswanaLower Rio Grande, USA/MexicoMekong River, Thailand/Cambodia/Vietnam/LaosJordan River, Syria/Israel/JordanClimate Change StudiesSacramento and San Joaquin River Basins, California, USAMassachusetts Water Resources Authority, Massachusetts, USAYemen Second National CommunicationMali Second National CommunicationEcological FlowsConnecticut Department of Environmental ProtectionTown of Scituate, Massachusetts, USAWater Utility DSS ApplicationPortland, Oregon; Austin, Texas; Philadelphia, PennsylvaniaTowns in East Africa; Mulbagal, India.
Intuitive GIS-based graphical interface
GIS Tool
Model Building
Graphs &
Maps
Scenario
Building
WEAP Network Schematic
Urban Water examples > Austin, Texas
Aim: Cost-effectiveness of conservation and reuse strategies vs increasing water treatment capacity