Does Deforestation
affect River Flows across the Mekong Basin?
What Controls Water Flows across the
Mekong Basin: (Geology), Climate,
Landcover (Change), Engineering,
Jeffrey Richey & Colleague
University of Washington
SEA-BASINS
We have 2 OBJECTIVES:
Mine: Evaluate the “Issue” of
Mekong Flows
-
Measured “truth”
Modeling as analytical tool
Details of discharge regime: 1979-2001
Climate influences
Engineering
Landcover change
My friend’s sub-plot: To remind us
that the integrated approach used is
“more” than “just” hydrology modeling, is
imminently transportable to other regions,
the sheer act of building such an analysis
promotes interdisciplinary cooperation,
and there are very useful
stakeholder/policy applications..
Mae Chaem Basin, NW Thailand
(as proxy for feeder to Mekong)
550
500
% croplands
Observed discharge, m3/s
0
18.0
450
19.9
Pearson r = 0.70
19.1
Simulated
discharge, m3/s
400
350
300
250
200
150
100
50
0
5/94
10/94
5/95
11/95
5/96
11/96
5/97
11/97
5/98
11/98
5/99
11/99
5/00
11/00
>4601 m
4001-4600
3001-4000
1501-3000
1001-1500
751-1000
301-750
101-300
<300 m
Yunnan
MN
CS
Chiang Saen
LP
BHH
Luang Prabang
NP
Vt
Vientiane
Mukdahan
MM
BC
Pakse
Mk
BKD
Ys
RS Ub Pk
ST
Stung Treng
Phnom Penh
Tonle Sap
PP
*How does land use intensification affect watershed functions
in large-scale drainage basins (high flow, low flow)? Would
switching landcover back to forest change flow regimes?
*How does total water yield depend on the distribution of
rainfall and portioning between hydrologic processes, under
historical and current conditions?
*How are the temporal dynamics of high and low flows of rivers
influenced by spatial scale?
*How are “Far field effects” on people living downstream linked
to changes in total and seasonal water yield?
LONG-TERM DISCHARGE: “THE TRUTH”
30000
Mekong Mainstem
Chiang Saen
20000
10000
0
30000
Luang Prabang
20000
10000
0
30000
Vientiane
20000
10000
0
40000
30000
Mukdahan
20000
10000
0
80000
Stung Treng
60000
40000
20000
0
1910
20
30
40
50
60
70
80
90
2000
LONG-TERM DISCHARGE: “THE TRUTH”
Mun-Chi (NE Thailand)
8000
Ubon
6000
4000
2000
0
10
2000
20
30
40
50
60
70
80
90
00
30
40
50
60
70
80
90
00
Yasothon
1500
1000
500
0
4000
Rasai Salai
3000
2000
1000
0
2000
Ban Chot
1500
1000
500
0
10
20
To “deconvolve” the signal, we need suitable tools…..
MEKONG
VIC (Variable Infiltration
Capacity)
These geospatially-explicit
process-based
models are an
Meso/Macroscale Landscape/Hydrologic Model
exciting new tool, as+ Reservors
representation
of space and dynamics,
+ Irrigation
from tectonics to a local(Daily,
rainstorm.
1-10 km)This allows exploration, but
the “answer” is grounded in the assumptions…..
Should be thought of as “intelligent interpolators of diffuse
data”
Today is “Version 3,” advanced as (solid) basis for discussion of details
…. not a priori the definitive answer
“Virtual Scaled Basin”
The Mekong (and elsewhere) @ 10km (or 10 m) ….
Digital Elevation Model & River Network
Tonle Sap
1-km GTOPO30 DEM
10-km resolution, using
“upscaling”
SOILS
From USDA texture classes to soil parameters saturated hydraulic conductivity (Ks),
porosity (qs), field capacity (qc), wilting point (qw), and parameter n in the Brooks-Corey
equation for unsaturated conductivity
Top layer (0-10 cm)
Deeper layer (10-100 cm)
VEGETATION – GETTING IT RIGHT
MODIS/ OGE Rice
OGE
GLC/SE Asia
UMD
GLC/Asia
MSU
MODIS/ OGE Rice
VEGETATION “CLASSES”
….of interest to many, for multiple purposes…
Minimum stomatal resistance, RGL, and solar radiation attenuation
Vegetation height, displacement height, roughness length, and architectural resistance
Leaf Area Index, albedo
Maximum rooting depth, and distribution of root mass with depth
Wind height and wind attenuation
Surface Climatology
Wind speed data: interpolated from the NCEP-NCAR Reanalysis data set; Minimum and maximum daily temperature and wind speed value,
Surface Summary of Day Data (SoD) records from the National Climate Data Center (NCDC); interpolated
Observed vs Predicted River Flow
Issues of calibration, validation
* Approximate from DEM
MEKONG DISCHARGE 1979 -2000 (m3/s; monthly)
OBSERVED (
VIC-COMPUTED (
)
12000
Chiang Saen
9000
60000
16000
Phnom Penh
6000
12000
45000
3000
30000
0
8000
4000
15000
0
0
60000
Luang Prabang
20000
Stung Treng
45000
15000
30000
10000
15000
5000
0
0
40000
30000
20000
10000
0
Pakse
28000
28000
21000
14000
7000
0
Mukdahan
21000
14000
7000
0
Vientiane
Nakhon Phanom
)
MEKONG TRIBS DISCHARGE 1979 -2000 (m3/s; monthly)
OBSERVED (
800
)
VIC-COMPUTED(
)
2800
Muong Ngoy
Ban Chot
2100
600
1400
400
700
200
2800
0
Rasi Salai
2100
0
1600
1400
Ban Hin Heup
1200
700
800
0
400
8000
0
Ubon
6000
12000
4000
9000
2400
1800
Yasothon
2000
6000
0
3000
1200
0
600
0
Inputs Tonle Sap
“Diagnostic” Landscape/Hydrology Processes
Average annual simulated runoff ratio
Average monthly soil moisture saturation
in 1979-2000 in the calibrated simulation
(farmers, flood prediction)
Functional Relations; e.g. Vientiane
40000
Precipitation
30000
20000
10000
0
400
350
Soil Moisture)
300
250
200
16000
12000
8000
4000
0
Discharge
Soil Moisture Antecedent: the 2000 Flood
Chiang Saen
Ubon
DISCHARGE “ANOMALIES” (mo)
Vientiane
Stueng Treng
Ubon
20
30
40
50
60
70
80
90
00
REGIONAL CLIMATE PROXIES
Indian Ocean Sea Surface
Temperature
Pacific Decadal Oscillation
Southern Oscillation Index
20
30
40
50
60
70
80
90
00
Composite SLP anomaly maps for 12 highest &
lowest Stueng annual flow years
Jan-June (yr)
Highest
Lowest
Contour/shading interval = 0.5mb
Jul-Dec (yr)
EFFECT OF DAMS ON FLOW
Input
Output
Nam Ngum(Σ=-15%)
Ubol Ratana % (Σ=-14%)
500
160
400
120
300
80
200
40
100
0
0
1200%
400%
800%
200%
400%
0%
0%
-200%
-100%
1
2
3
4
5
6
7
8
9 10 11 12
1
2
3
4
5
6
7
8
9 10 11 12
Irrigation
(esp NE Thailand)
120%
100%
Rasi Salai
80%
60%
40%
20%
Ubon
Yasothon
0%
J
F
M
A
M
J
Near Udonthani
J
A
S
O
N
D
Land Cover Scenarios
Permanent v Swidden Agriculture (of different fallow periods)
Scenario
Ω
f
(yr)
Permanent agriculture scenarios:
Sc.1 10% deforestation
Sc.2 100% deforestation
Sc.3 10% afforestation
Sc.4 100% afforestation
Swidden agriculture scenarios:
Sc.5 Increased Ω
5 Ω0
=131,245
km2
Sc.6
Sc.7
5 Ω0
Increased Ω but long
=131,245
fallow period
km2
No swidden
agriculture
0
5
30
?
Percentage of current forest (and classes 21 and 22)
replaced by these land cover classes
23
9A
9
9B
Total
(agricul(1-5
(6-15 years (16-30
ture)
years in in fallow) years in
fallow)
fallow)
10%
100%
-
-
5/6 Ω0
25/6 Ω0
=21,874 =109,37
km2
1 km2
=11.5% =57.4%
5/31 Ω0 25/31 Ω0
=4,234 =21,169
km2
km2
=2.2% =11.1%
-
-
-
-
-
10%
100%
-
Percentage of current
permanent agriculture
(class 23) replaced by
forest
(forest class 5; except for
China, where forest class
28 is introduced)
10%
100%
-
68.9%
50/31 Ω0 75/31 Ω0
=42,337 =63,506
km2
km2
=22.2% =33.3%
-
68.9%
-
100%
Land Cover Scenarios (Tributaries)
15% Ban Hin Heup
10%
5%
0%
-5%
-10%
-15%
10% def.
100% def.
10% aff.
100% aff.
Fallow=5 yr
Fallow=30 yr
No swidd. ag.
-20%
10%
Muong Ngoy
5%
0%
-5%
-10%
-15%
J
F
M
A
M
J
J
A
S
O
N
D
Land Cover “100%”: MEKONG BASIN
20%
20% 100% Deforestation
100% Deforestation
15%
15%
10%
10%
5%
5%
0%
0%
J F M A M
J
J A S O N D
0%
J
J A S O N D
0%
-20%
-5%
-40%
-10%
-60%
-15%
-80%
-100%
J F M A M
100% Afforestation
Ban Hin Heup
Muong Ngoy `
Ban Chot
-20%
Rasi Salai
Yasothon
Ubon
100% Afforest
Chiang Saen
Luang Prabang
Vientiane
Nakhon Phanom
Mukdahan
Pakse
Stung Treng
Obj. 1. Are upstream changes detectable as “farfield” affects on
water yield even in a very “big” basin?
Depends –quantitatively!- on relative magnitude, in a dynamic (in)balance:
Transition forest to agriculture
Irrigation
Dams
Climate
Obj. 2. Applications of “VSB” Construct as a Tool
•Scenario & Dynamics Analyses: Past, Present, Future
•“Now-casting” – Drought and flood forecasting (especially if coupled to
climate model)
•Elsewhere – very much!
Mekong River Commission Secretariat, Vientiane