changing responses of land dynamics and vulnerability to ... · (levees) • siltation •...
TRANSCRIPT
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Changing Responses of Land Dynamics and Vulnerability to Flooding
Under Policy and Environmental Change near Poyang Lake, China
Dan Brown, Kathleen Bergen, Shuming Bao
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Research Team• PI/co-PIs:
– Dan Brown, Shuming Bao, Kathleen Bergen (University of Michigan)
• Post-Docs (support from China Scholars Council):– Shuhua Qi (JXNU), Luguang Jiang (CAS)
• Research Assistants:– Tingting Zhao and Qing Tian (UM)
• In-Country Collaborators (support from NSFC):– Lin Zheng (JXNU), Ying Liu (JXNU) Heqing Huang
(CAS)
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Land-Change Science
• Involves– Documenting and monitoring land-cover
changes– Explaining coupled human-environment
dynamics giving rise to these changes– Developing spatially explicit land-change
models that are compatible with other Earth system models
Rindfuss et al. (2004) Proc of the National Acad. Of Sci. (U.S.)
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LCS and Vulnerability
Understanding vulnerability requires that we account for:
• The coupled human-environment system• Linkages to broader human and biophysical
conditions• Perturbations and stresses that arise from these
broader conditions
Turner et al. (2003) Proc of the National Acad. Of Sci. (U.S.)
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LCS and Vulnerability to Flooding
Flood dynamics
Land-use & land-cover
dynamics
Land-tenure policy
Development policies
Economic environmentMajor basin
floodworks (e.g., Three Gorges)
El Niño and interannualvariability
Long-term Climate change
Ecological Effects
Human Vulnerability
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Poyang Lake Region• Poyang Lake is largest
freshwater lake in China.• Jiangxi Province• Connected to Chang Jiang• Average water level
fluctuates seasonal from ~7 m to ~19 m a.m.s.l.
• Population of the Poyang Lake Region increased from 7.7 million to 8.7 million from 1990 to 1999.
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Flooding at Poyang Lake
• reduced surface area (levees)
• siltation• fluctuations in
Changjiang levels• Deviations from trend
show correlation with ENSO
Shankman and Liang 2003
Maximum Annual Water Levels at Hukou
0
5
10
15
20
25
1950 1960 1970 1980 1990 2000
Year
mAM
SL
• Highest water level ever recorded in 1998 (22.6 m)– 4 million households damaged– 97 levees broken
Causes of rising flood levels:
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Broader Policy Context• Economic liberalization has presented increasing
opportunities for Chinese citizens.• Changes in land-use and their effects on vulnerability are
driven by these changes.- Major Yangtze Floods (Wang et al. 2003)
Household Responsibility System
Liberalization of Agriculture Markets
Liberalization of Urban Housing/Job Markets
Governor’s & Mayor’s Grain-Bag Responsibility Systems
20.0 21.2*
Return Land to the Lake
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
22.6
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Our Proposal• Research questions
– How have LCLUC patterns and dynamics changed as a consequence of flood dynamics and changes in land and economic policies?
– How have changes in LCLUC patterns and dynamics affected vulnerability of people and economy to flooding?
– What are the implications of changes for amount of wetland habitat?
– How might future changes in lake levels affect vulnerability of humans and wetland habitats?
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Overall Framework
Lake Stagemodel
Land-use agent-based model
Landsat Lake Surface Area
Lake Stage Records
DEM
Levees
Household Survey
Census Data and Models
Policy Scenarios
LandsatLandcover
Assessments of Human Vulnerability
Avian Habitat Model
Observations of Avian Population
Assessments of Habitat Vulnerability
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Activities
1. Land-cover characterization2. Digital elevation/flood modeling3. Social survey and data analysis 4. Agent-based modeling 5. Ecological/habitat data modeling
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1: Land-CoverOverall:
Goal is to observe, understand, and model changesYear 1 Goals• Acquire Landsat images.• Analysis of alternative land-cover characterization
approaches and development of protocolYear 2 Goals• Implement protocol for processing Landsat images.• Spatial modeling of land-cover dynamics in
comparison with (a) variations in flood dynamics and (b) trends in the demographic and economic context based on spatial statistical models.
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Important land-use changes• Factors: flooding, policy, changes in agricultural market
structure (Vegetables are 5-6 times profitable of rice), land-use tradition
• Early period (before 1980s) – rice, build aquaculture ponds• ~mid-1990s – farmland abandonment begins, less profit
• Mostly rice (e.g., go from 2 plantings to 1)• Increase in area of market crops (e.g., tea, vegetables)• Forest area (planted monoculture) increase: source of energy,
out migration, switch to coal/gas• Agricultural response to flooding: short-term effect, but
increased risk, may combine with market changes to encourage 1 season instead of 2.
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Multi-Season Image Pairs
Summer Flood Season
Winter Low Water Season
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Landsat Images• Dates of acquired data.
1995/1998 Floods
1987/89 1993 1999/2000 20041983/84Dates of Image Pairs
1983/11/281984/8/2
1987/12/171989/7/15*
1993/1/311993/7/10
1999/12/10*2000/7/5
2004/3/10 2004/7/24
WinterSummer
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Upland CropsLake/River ShoreLevee
Village
Rice Paddy Seasonally Flooded
Forests
Land Covers – Jan/June 2006
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2: DEM/flooding
Overall: Goal is to characterize spatial-temporal dynamics in flood levels based on DEM.
Year 1 Goals• Edited and validated DEM.• Calibrated level-area relationship for Poyang Lake,
based on the best available DEM data, historical lake levels and Landsat images.
• Identification and digitization of archival GIS and other data.
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Shuttle Radar Topographic Mapping (STRM)
• Digital terrain data collected Jan-Feb 2001 – Lake at low level
• Resolution: 90 m• We are supplementing
with data on levees.• Relation between lake
volume and water levels used to characterize flood dynamics.
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Levee Information
Levee Elevation
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Lake Levels
• Statistical summaries of lake levels from last 50 years (including trends) provide basic probabilistic model.
• Estimated distributions can be modified to evaluate flooding scenarios based on basin LU change, hydrologic and climate changes.
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Flood Frequency from DEM
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Comparison of DEM and TM
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3: Social Data Analysis & Survey
OverallWe want to characterize and understand the factors affecting decision making related to out migration and land-use.
Year 1 Goals• Development of spatial statistical models of economic
and demographic context of Jiangxi Province and the Poyang Lake Region.
Year 2 Goals• Survey of with village leaders and sampled
landowners and farmers.
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Household Survey
• Sample of villages (n=4-8) stratified by flood risk.
• Sample of households within villages (~50)• Questions structured to identify economic
inputs and outputs at the household level, as well as perceptions of flood risk.
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Village Structure
Administrative Village
Natural Village (~10 per A. Vill.)
Households (10-200 per N. Vill.)
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Flood Risk Mapping
• Used to stratify village sample.
• Combination of ground elevation (DEM), levee height, and levee quality.
• Purples and blues are low
• Orange and red are high.
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4: Agent-Based Modeling
OverallThe goal is to represent dynamics of decision making
that affects land use in the context of economic conditions and policies as well as flood risk.
Outputs are land-use maps and vulnerability measures.Year 1 Goals• Development of conceptual framework for agent-
based model with Chinese colleagues.• Programming and analysis of skeletal agent-based
models, presentation to and discussion with Chinese collaborators.
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Skeletal model created using RePast and ArcObjects.
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Legendlevee
wetland
aquaculture
residential area
lowland
highland
Legenddem25mValue
126
126 - 129
129 - 135
135 - 140
140 - 150
150 - 326
Data Sets: DEM, levee map, land capability zones
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At the beginning
Scenario1: levee is removed
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Flooded in summer
Scenario1: levee is removed
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5: Ecological Modeling
OverallGoal is to develop an empirical habitat model that we can use to relate changes in water levels and land-cover to ecological impacts on water birds
Year 1 Goals• Collection of field-based land-cover and bird-
observation data.
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Data• In-country collaborators working with
conservation agencies to acquire existing observational data.
• World Wildlife Fund International Crane Foundation collected observations of white crane since 1994 (other birds since 2000) at 40 points in lake.
• Poyang Lake Nature Reserve Office also has observational data
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ScenariosIntegration of components to evaluate economic,
human, and ecological impacts of changing policy and flood levels
Flooding component– Recent trends continue– Recent trends continue, but more levees are removed– Flooding trends altered by Three Gorges Dam
Policy component– No change– Further liberalization of land and migration policies– More rapid development of Poyang Lake Region
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Next Steps
• Develop five dates of land-cover classification (Q2 2007)
• Implement spatial statistical model of migration (Q1 2007)
• Conduct survey (Q1 2007)• Continue ABM model development (on-
going)• Further definition of scenarios
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Jiangxi Poyang Lake Nat’l Nature Reserve (talk with Ji Wei Tao, Director)
1. ICF – four sites within preserve area counted every week, four times per month, count only big birds. 1994-2005
2. WWF – 49 points over lake, 2004-2005.• Talk to WWF, office in Beijing, www.wwfchina.org,
010-652271003. Jiangxi Natural Preserve Office –
a) mark locations of birds within the preserve area on the 3’s and 8’s of the month.
b) observe from fix locations (3)a) Chapter in Poyang Lake research book.
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WWF report
• ISBN 7-5038-3857-4• Waterbird Survey of the Middle and Lower
Yangtze River Floodplain in Late January and Early February 2004
• by Mark Barter, Chen Liwei, Cao Lei, and Lei Gang
• China Forestry Publishing House• 49 wetlands observed
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Historical Landsat Images
Low-water image:
10 Dec 1999
High-water image:
15 Jul 1989
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History
• 1960s lots of levee construction for farmers• 1978 – last levee built (1970s levees built for
flood protection)• 1980s – reforms started, households start to have
more of influence on land use (now gov’t and hh)• 1998 – levee destruction begins• 2004 – food security plan - gov’t eliminate
agriculture tax, provide subsidy and penalize abandonment
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Seasonal Changes
• Rice– Planted in two seasons:
• Apr-Jul• Aug-Oct
• Natural Wetlands– Jan-Feb: low water– June: grass productivity peaks– July: wet, water peaks
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DEMs• 1:50,000 DEM – UM cost sharing ($500)
– 1977• 1:25,000 topos – in process (AutoCAD)
– 1952, December– Includes levees, contours, land cover, roads– 1 meter interval– Yangtze River Hydrological Commission
• 1:25,000 topos – MRL has coverage– 1983– Jiangxi Survey Agency updated 1952 maps– 3 sources: Army, previous maps, additional surveys
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Survey Suggestions
• When asking about land-use types, use same categories as government statisticsn
• Change question about party membership to “position in government”
• Drop question about army.
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Issues
• MRL has 1:50,000 township boundaries• County level most have 50 years of social data
• Estimate net migration. • Develop models and select variables to describe
push/pull factors that affect migration.• Develop and pre-test questionnaire – draft
available.
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Polder Conditions
• Not impoldered – uplands• Not impoldered – lowlands• Impoldered – farm fields and residents
– different heights = different risks• Partially restored polders – farm fields only
(but residents still there)• Restored polders – no farms or residents
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Issues
• Who are the primary actors?• What are their key decisions with respect to
land-use?• What attributes of the actors or of their
context (environment, policy, social/economic context) affect those decisions?
• How are the decisions made?
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Actors and decisions• Households
– To move • Temporary migration but maintain house – abandon crops• Forced movement for flood protection, improved infrastructure• Farmers can buy house in city or move from area
– How to earn a living• What crops? – affected by technical support from gov’t
– decisions affected by neighbors• Raising ducks/chickens• To abandon crops? – crops unprofitable• Off-farm income? – primary income w/ farming
• Government (central) – decide policy, actions affected by economic situation– establishes wildlife protection laws
• Government (agency local offices)– infrastructure investment– upland areas managed by forest dept., underwater by Agriculture
• Market
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Frequency of Water from Images
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After harvest
Scenario1: levee is removed
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some years later
Scenario1: levee is removed
![Page 52: Changing Responses of Land Dynamics and Vulnerability to ... · (levees) • siltation • fluctuations in Changjiang levels • Deviations from trend show correlation with ENSO Shankman](https://reader036.vdocuments.net/reader036/viewer/2022071217/604b64ef85899667fc747819/html5/thumbnails/52.jpg)
At the beginning
Scenario1: levee is present
![Page 53: Changing Responses of Land Dynamics and Vulnerability to ... · (levees) • siltation • fluctuations in Changjiang levels • Deviations from trend show correlation with ENSO Shankman](https://reader036.vdocuments.net/reader036/viewer/2022071217/604b64ef85899667fc747819/html5/thumbnails/53.jpg)
Flooded in summer
Scenario1: levee is present
![Page 54: Changing Responses of Land Dynamics and Vulnerability to ... · (levees) • siltation • fluctuations in Changjiang levels • Deviations from trend show correlation with ENSO Shankman](https://reader036.vdocuments.net/reader036/viewer/2022071217/604b64ef85899667fc747819/html5/thumbnails/54.jpg)
After harvest
Scenario1: levee is present
![Page 55: Changing Responses of Land Dynamics and Vulnerability to ... · (levees) • siltation • fluctuations in Changjiang levels • Deviations from trend show correlation with ENSO Shankman](https://reader036.vdocuments.net/reader036/viewer/2022071217/604b64ef85899667fc747819/html5/thumbnails/55.jpg)
The same years later
Scenario1: levee is present