Decision Support Systems for Designing & Managing

Productive, Resilient Landscapes (Work in Progress)

Erick Fernandes1 & Jeffrey Richey2

1. The World Bank, Washington, DC (USA)

2. The University of Washington, Seattle, WA (USA)

Himalayas

Bhutan

India

Guiding Principles

• “If we knew what it was we were doing, it would not be called research, would it?

• Logic will get you from A to B. Imagination will take you everywhere.

• Not everything that can be counted counts and not everything that counts can be counted.

• If the facts don't fit the theory, change the facts.”

Albert Einstein

GHG Emissions by Region & Country

1880-89

2000-09

…and the preponderance of evidence says it’s humans—thermometer readings all around the world have risen steadily since the beginning of the Industrial Revolution

The world is getting warmer

30 year Baseline (1951-1980) = Normal Temp

In the last decade (2000-2009), land temperature changes are

• 2x greater in the United States than ocean temperature changes;

• 2-3x greater in Eurasia; and

• 3-4x greater in the Arctic and the Antarctic Peninsula.

NASA, 2013

World Bank – Turn Down the Heat Series

https://openknowledge.worldbank.org/handle/10986/20595

Projected Economic Losses from Coral Reef Ecosystems in the Caribbean

• Coral reef fisheries - Estimated loss of net revenues between US$95-140 million per year by 2015-2020.

• Dive Tourism - Estimated loss of net revenues between US$100-300 million per year by 2015-2020.

• 20% Caribbean coastline protected by coral reefs – Estimated loss of coastal protection service US$140-420 million per year by 2050.

Caribbean coral reefs provide goods and services with an annual net economic value in 2000 estimated at between US$3.1 - 4.6 billion from fisheries, dive tourism, and shoreline protection services – WRI “Reefs at Risk 2010”

From 2000-2011 there were 154 Hurricanes (H1-H5) recorded in the Atlantic and Pacific

Central America & the Caribbean are increasingly vulnerable if the projected increase in Hurricane Intensity (more H4&5s) happens over the next 3-5 decades

Source: NOAA Hurricane Tracker

Increasing Number & Intensity of Atlantic Storms & Hurricanes in LCR Likely

(2000-2011) 38 Hurricanes were H4 or H5

Source: NOAA

Climate Change resulting in a new type of El Niño ?

El Niño “Modoki” could result in: 1. Significantly drier Central America and Caribbean during El Niño events 2. Increase in frequency of AND a greater potential of Hurricanes making landfall

along the Gulf coast and the coast of Central America.

-40 -30 -20 -10 0

BRA

ARG

MEX

CAC

URY

PER

CHL

ECU

COL

XSM

Corn

2050

2020

-40 -30 -20 -10 0 10 20

BRA

COL

CAC

ECU

XSM

ARG

MEX

CHL

PER

URY

Soybean

2050

2020

0 5 10 15 20

CHL

MEX

ARG

CAC

XSM

BRA

URY

PER

ECU

COL

Rice

2050

2020

-60 -40 -20 0 20

COL

ARG

XSM

ECU

CHL

BRA

CAC

MEX

URY

PER

Wheat

2050

2020

Impact of CC on Cereals in LCR

Source: World Bank, 2012

Agroecological Domains & Landscapes Key for Decision Making in the Face of Climate Change

554 million ha of native vegetation

• 107 million ha of Conservation Units

• 103,5 million ha of Indigenous Land

• 274 million ha of native vegetation in private

properties (PPAs riparian and hills + Legal

Reserves)

• 69,5 m ha native remaining vegetation in PPAs

60 million ha of productive land (crops fruits, and planted forest)

38 million ha of urbanization and other uses

198 million ha of pastureland

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six regions

Study Results (2014)

http://www.profor.info/sites/profor.info/files/docs/web%20brasil_2030_portugues.pdf

Data, Data Layers, Coupled Models, Spatial & Time Referenced Outcome Scenarios for Policy Making

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1. Seven climate models - four Global Climate Models

(GCMs) and three Regional models (RCMs) were used to

simulate the temperature and precipitation to 2020 and

2030 with 2010 as the baseline.

2. Temperature and precipitation simulations were

calibrated against hydrometerological data from a

range of Brazilian agencies (ANA, CPETEC, EMBRAPA,

INMET, UNICAMP). The AGRIPEMPO hydromet

system has a network of 1,200 meteorological stations

and 4,000 rain gauges nationally with at least 25 years

of data records that have been quality checked to 2007.

3. Crop productivity simulations were based on Brazil’s

Agro Climatic Risk and Vulnerability Zoning Model

(Assad and Pinto, 2008) developed by EMBRAPA and

UNICAMP that currently underpins all Ag & rural credit

in Brazil and was upgraded by this study.

4. Brazilian Land Use Model (BLUM) is a one-country,

multi-regional, multi-market, dynamic, partial equilibrium

economic model for the Brazilian agricultural sector

5. Legal Framework Context for Land Cover Land Use

Change policy and program for implementation

Projected Productivity for Pastures, Maize, and Soybean (2010 2030)

High Value Crops: Will Coffee be viable in Central America?

Source: Jarvis, CIAT (2012)

Example of suitable area projections due to temperature & precipitation changes

Land Insecurity, Uneven Tenure, Land Rights, Indigenous Communities, Competition

Increase food production

Build resilience/ Reduce poverty / Share Prosperity

Increase Carbon Sequestration (& Reduce Carbon Emissions)

Forests & Agroforests: Wood + Fuel & Carbon + Water + Biodiversity

Ecosystem Services for Resilient Landscapes

People in Landscapes Ag, Biodiversity, forests, land, water…

WATERSHEDS TO

BASINS Nested scales

• Topography/DEM

• River networks & riparian

• Soils (depth, texture,

fertility)

• Landuse/cover,

• Biodiversity gradients

• Infrastructure

DECISION

SUPPORT

SYSTEMS

Integrated

• Policy

• Planning

• Budgeting

CONCEPTUAL FRAMEWORK FOR LANDSCAPE SCALE PLANNING

Observations, Measurements, Models

CLIMATE FORCING Rainfall, Temp, Radiation,

Wind

• Local met records

• Satellite data

• Reanalysis

• Regional Climate Models

• IPCC Scenarios

A

S

S

E

T

V

A

L

U

E

S

WATER MOVEMENT Field to landscape to basins

• Soil moisture, infiltration,

ET, runoff

• Stream/river flow

• Dams, reservoirs

• Irrigation

• Environmental flows

• Recreational flows

PRODUCTION Field to Landscape

• Annual crops,

• Pastures, trees, incl

biofuels

• Agricultural Models

• Industrial

Sediments/Pollutants Fields to Rivers to Coastal

• Sediment erosion &

transport

• Dissolved chemicals

DIF Cyber Infrastructure

Sensors &

Instruments

Earth

System

Models

Data

Archive

Metadata

Registry

GIS

Mapping

&

Translation

Scientific

Visualization

Media

Archive

Simulation

Resource

Planning

Biodiversity

Energy/ Hydropower

Water Resources Irrigation,

Environmental Flows

Climate &

IPCC Scenarios

Land cover &

Landuse

Soils Topography

Land Cadastral

Boundaries

2000

2020

2060

2080

Dynamic

Information

Framework Urban

to Rural Infrastructure

The Framework: “Earth System Models”

Moving from Data & Apps to Decision Support!!

Climate

Landcover,

Biodiversity

Soils

Boundaries

Topography

Infrastructure

GHG Emissions

Agriculture

Productivity

Floods &

Droughts

Evapotranspiration

Soil Moisture

E

y 0 1 2

Rs

RL

S L

Es

E1

Q

Q

tG

R

B

Movement of water, energy, and carbon (e.g. VIC, CLM…)

Figure 2 VIC model schematicFigure 2 VIC model schematic

Computation-Engines

• Based on “first principles”

mechanics, and not

statistics. They can be

used more reliably for

changing conditions, in a

non-stationary world.

• Developed in public

academic forum, has been

applied to many

watersheds globally

• Software open source !! Download the code here

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http://www.hydro.washington.edu/Lettenmaier/Models/VIC/

Nested Geo-spatial Structure facilitates scale up-scale down

Geo-Located Land Cover Land Use Mapping and Analysis

Decision Support Systems for Policy Makers Municipality to National Scales

• Multi-sector data layers assembled

• Distributed hydrological models calibrated

• Dynamic Information Framework for quantitative projections

• Visualization Tool for Decision and Policy Makers – what, where, when to invest????

Cyber Infrastructure (Data, DIF, Models)

Planning Tool for Infrastructure (Dams, Drains, Embankments)

BIG Data

Big Data Analytics [Terrabytes to Exabytes]

Principles for Climate Smart Landscapes 1. Protect the soil, reduce surface flows of water & enhance infiltration, 2. Stabilize slopes via contour plantings & terraces, 3. Integrate perennial species, forests, and agroforestry in the landscape 4. Protect all stream and river banks (riparian zones) with native

vegetation/forests 5. Rehabilitate all degraded lands 6. Combine best available science with adapted local best practices

Terracing Terracing + Perennials Agroforestry & Forestry for Productive and Env. services

Vegetated Riparian Zones

Locally Adapted Best Practices

Dynamic Landscape Restoration - Amazon

Optimize Production and Service Synergies and Tradeoffs at Landscape Scales

Manage Synergies & Tradeoffs across plots to the Landscape scale

Clark et al. 10.1073/pnas.0900231108

Take Home Lessons 1. Landscape Scale Planning and Decision Support Frameworks are

practical and necessary tools for governments and policy makers

2. Cross sector (inter Ministry) data integration and linkages are essential for effective local to national to regional/global analyses, synthesis, scenarios and decision-making

3. Climate Change and Population Growth require that countries undertake appropriate simulations of likely impacts on critical sectors for economic development at relevant spatial and time scales

4. Many WBG partners in Latin America, Central Asia, South Asia, and Africa are implementing Dynamic Data and Information Frameworks for Landscape Scale Resource Management and Planning

5. The World Bank is providing technical assistance and project financing to assist client countries to develop their own Dynamic Information Frameworks for Landscape Scale Management of Natural Resources and to conduct impact simulations for prioritizing investments for Enhanced Resilience to Climate Change.

6. Scale up action NOW!!