Driss SCARCE-InVEST Dec2010 · ecosystem services – Apply tools in important places – Support...
Transcript of Driss SCARCE-InVEST Dec2010 · ecosystem services – Apply tools in important places – Support...
How Valuing Water Related Ecosystem Services Could Improve
Hydrologic Sustainability?
Driss Ennaanay, Ph.D. Natural Capital Project,
Stanford University
SCARCE – December 2010
Outline
• Natural Capital Project
• InVEST Water Models
• Applications
Nature to Society…Global or Local? 60% of global ES in decline (Millennium Assessment)
$33 Trillion/y (Costanza et al. 1997 Nature)
2 forest patches: $60K/year (Ricketts et al. 2004. PNAS)
22 others (just for pollination!)
Most Policy WindowsMedium spatial scale
Short timelineStandard approach
Most Policy WindowsMedium spatial scale
Short timelineStandard approach
Global or Local?
Needs…?
• Relevant to many kinds of decisions• Scenario based• Applicable anywhere on the globe• With minimal data• Flexible scale• Biophysical and economic• Biodiversity and multi-services
Make conservation economically attractive– Develop science and policy tools to address
ecosystem services
– Apply tools in important places
– Support policies to maintain / pay for services
– Change the way ecosystems are viewed
InVEST
Bridging Global & Local…
The Natural Capital Project
Stakeh
olde
r En
gagemen
t Identify ObjectivesIdentify Objectives
Develop ScenariosDevelop Scenarios
Compile DataCompile Data
Post‐AnalysesPost‐Analyses
Biophysical ModelsBiophysical Models
Economic ModelsEconomic ModelsInVE
ST
Natural Capital Project Approach
History…
20072007 20082008 20092009 20102010
Project Launch: Terrestrial and FW modeling
First public release of InVESTPNAS Special Issue
Frontiers Special IssueHainan Island App
China, CA, HI, OR, Tanzania
Global, MN published
Marine Initiative
CAMEO: 3 new US sites
WCVI AppBelize App
Colombia, Ecuador, Uganda, Sumatra Apps
Amazon Application
OUP Book in press
First public release?
InVESThttp://invest.ecoinformatics.org
Ecosystem Services?
Map, quantify and value multiple ecosystem services
• Biodiversity, • Water yield for hydropower production• Avoided reservoir sedimentation• Water purification: nutrient retention• Carbon sequestration & storage• Managed timber production• Crop pollination
“…. Remember that all models are wrong; the practical question is how wrong do they have to be to not be useful…”
Box and Draper, Empirical Model‐Building,
Modelers: …. What’s our addition to make them more useful? …
Simplicity vs. Complexity…
Tier 1 Tier 2
Simple Complex
Models
Data
Tier 3
Annual
Data Hungry
Hourly
Data Poor
Water Purification
Storm Peak Mitigation,
Irrigation, Baseflow, , Groundwater recharge
Hydropower
Water yield
Sediment
Valuation
Land use land cover
Soil
Digital Elevation Model
Climate: PPT, PET
Water yield
Sediment
Nutrient
Energy
Others
Ret.$
Pur. $
E. $
Root dep
th
Leaf type
Seasonality
Water Availability
Precipitation
Yield
EvaporationRain
Snow
Fog
Groundwater Recharge
Inflow
Plant type
Water Yield Model
Transpiration
xjxjx
xjx
x
xj
RR
RP
AET11
1
++
+=
ω
ω
x
xx P
AWCZhang=ωx
xxj P
ETokcR ⋅=
⎟⎟⎠
⎞⎜⎜⎝
⎛−=
x
xjxjx P
AETPY 1.
kc = vegetation coefficientETo = potential evapotranspirationP = precipitation
Zhang = seasonality factorAWC = available water contentP = precipitation
Water Yield ModelAt Pixel Level
• Variables – Land use/land cover– Precipitation (rain and snow, not fog)– PET– AWC– Vegetation coefficient– Root depth– Soil depth
Water Yield Model
Testing …
Irrigation
Urban Consumption
Irrigation
Hydropower Model
Water Transfer
Catchment /Basin Water Balance
Subtracts water used by others
Estimates amount of power generated by water available for hydropower
Calculates yield at the pixel scale as difference between precipitation and evapotranspiration
Calculates net present value
• Variables (7 required, 10 optional)– Land use/land cover– Precipitation (rain and snow, not fog)– PET– AWC– Vegetation coefficient– Root depth– Soil depth– Consumptive use by LULC– Points of interest– Calibration coefficient– Turbine efficiency– Reservoir management fraction– Head– Production costs– Energy price– Timeframe– Discount rate
Water Yield & Hydropower Production Models
Maths…
⎟⎟⎠
⎞⎜⎜⎝
⎛−=
x
xjxjx P
AETPY 1.
Vin = Y - ud
εd = Vin βγhd2.72e-3
NPVHd = (peεd -TCd) x∑ 1(1+r)t
t = 0
T - 1
corn
forest
wheat
forest
Stream
Cumulative Sediment Yield
PCLSKRUSLE ....=
Subtracts ‘allowed’ sediment
Calculates sediment export and retention at each pixel based on USLE and routing
Calculates present value
• Variables (8 required, 5 optional)– Land use/land cover– Rainfall erosivity– Soil erodability– Crop factor– Management factor– DEM– Sediment retention efficiency– Slope threshold– Reservoir dead volume– Points of interest– Sediment removal cost– Timeframe– Discount rate
Avoided Reservoir Sedimentation Models
Valuation
SEDxD = Rx ⋅ Kx ⋅ SLx ⋅ 1− Cx ⋅ Px( )( )+ SEx USLEy (1− SEz )z=y+1
x −1
∏y =1
x −1
∑⎛
⎝ ⎜ ⎜
⎞
⎠ ⎟ ⎟
SEDRETxD = SEDxD − Sa
PVSRxD = (SEDRETx × MCD ) ×1
1+ r( )tt =0
T∑
Longtang: 2003, 2006, 2007 Santan: 2003, 2006, 2007Jiabao: 2003, 2006, 2007 Baoqiao: 2003, 2006, 2007
Sedimentation retention model
y = 1.23xR² = 0.74p < 0.01
0
50
100
150
200
250
300
350
400
450
0 50 100 150 200 250
Sim
ulat
ed so
il lo
ss (1
03t)
Observed soil loss (103 t)
ARS Testing
Water Purification: Nutrient Retention
Slope
Water Yield -
Downslope Retention
corn
forest
wheat
forest
Stream
Cumulative Nutrient Loading
Water Purification: Nutrient Retention
Valuation
)_1(**)(_CNL
LoadAnnretainedpCostValuewp xx −=
Longtang: 2001, 2008 Songtao: 2001, 2008Longjiang: 2008 Baoqiao: 2001, 2008
Water purification model – TP
y = 0.81xR² = 0.94p < 0.01
0
100
200
300
400
500
600
0 100 200 300 400 500 600 700
Sim
ulat
ed to
tal p
hosp
horu
s (t)
Observed total phosphorus (t)
WP:NR Testing
Longtang: 2003, 2008 Songtao: 2003, 2008Longjiang: 2008 Baoqiao: 2001, 2008
Water purification model – TN
y = 1.11xR² = 0.92p < 0.01
0
1000
2000
3000
4000
5000
6000
7000
0 1000 2000 3000 4000 5000 6000
Sim
ulat
ed to
tal n
itrog
en (
t)
Observed total nitrogen (t)
WP:NR Testing
Applications: How InVEST is helping Enhance Hydrologic Sustainability?
Water Fund: Water for Life
Service providers: Local communities managing / owning watersheds
Buyers: water utilities, hydropower, sugarcane plantations etc.
Services: water flow regulation, water purification, erosion control
Motivations: Avoid costs of water treatment, ensure regular supply
PROVIDERS USERS
Methodology
• Prioritization index for 4 BMPs.
• Ranking Landscape for each BMP
• InVEST application of Sediment and Water Yield models for each Investment Portfolio
Sediment Reduction for each Portfolio
Both Services …
Sumatra Master Plan
• Significant Palm expansion
• New Environmental Law
• WWF‐ Vision
• Governmental Development Plan
• Sustainability?
Fig w.1. Distribution of water yield for Vision scenario
Fig w.2. Difference between water yield per pixel in the Sumatra vision and the government plan
Sumatra-Water Yield
Fig w.3. Spatial Distribution of exported sediment to stream for Vision scenario
Fig w.4. Difference between sediment exported per pixel in the Sumatra vision and the government plan
Sumatra Sediment Yield
Fig w.5. Spatial Distribution of exported phosphorus to stream for Current scenario
Sumatra Nutrients
Fig w.6. Spatial Distribution of exported nitrogen to stream for Current scenario
Conclusions
InVEST water models are Distributed GIS-based models
They are based on widely used hydrologic laws, using minimal data
Provide biophysical and valuation functions
Testing and verification show satisfactory results for different models.
Next Steps…
• More Tier 1 models: Storm Peak Mitigation, Baseflow and Groundwater recharge
• In‐stream Processes in these Sediment Retention and Water Purification models.
• Tier 2 Platform (daily time step and bundled services)
THANKS
Natural Capital Project:
www.naturalcapitalproject.org
InVEST: invest.ecoinformatics.org