b1. quantifying the role of af in modifying watershed functions
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B1. Quantifying the role of AF in modifying watershed functions . Starting from current practice in 'integrated watershed management' with participatory methods Biophysical Gains of Participatory Agroforestry: Evidence from Integrated Watershed Development Project, Hills II, India - PowerPoint PPT PresentationTRANSCRIPT
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B1. Quantifying the role of AF in modifying watershed functions
Starting from current practice in 'integrated watershed management' with participatory methods
• Biophysical Gains of Participatory Agroforestry: Evidence from Integrated Watershed Development Project, Hills II, India
• Collective action in integrated soil and water conservation: the case of Gununo Watershed, Southern Ethiopia
Delving deeper into the biophysical processes• CONVERSION OF FOREST TO COFFEE-BASED AGROFORESTRY IN
INDONESIA: Litter layer, residence time, population density of earthworm and
• Modelling water dynamics in coffee systems - Parameterization of a mechanistic model over two production cycles in Costa Rica.
• Impacts of shade trees on hydrological services and erosion in a coffee AFS of Costa Rica: Scaling from plot to watershed
• Tree roots anchoring soil and reducing landslide risk during high rainfall episodes as basis for adaptation and mitigation to climate change
Scaling back up to the landscape• Buffering water flows through agroforestry management: quantifying the
influence of landscape mosaic composition and pattern
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Buffering water flows through agroforestry management: quantifying
the influence of landscape mosaic composition and pattern
Meine van Noordwijk, Betha Lusiana, Bruno Verbist
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Sustainable land use
Agroforestry
Hydrological Functions
Watershed management
‘Protec-tive
garden’
Trees, Soil,
Drainage
Stakehol-der nego-
tiation
Criteria & Indicators
Buffering water flows through agroforestry management: quanti-fying the influence of landscape mosaic composition and pattern
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rainfall
lateral
outflow
percolation
surfaceevaporation
transpiration
canopy waterevaporation
uptake
quick-flow
baseflow
{
surface run-on
sub-surfacelateral
inflow
surface run-off
Stream:
stem-flow
through-fall
cloudinterception
rechargeinfiltration
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Diagnostic Actions to remedy Spatial prioritization for program efficiency
Other benefits (Public) Fund
allocation
Improved watershed services?
% Forest cover Tree planting Qmax/ Qmin Buffered flow expec-tation, no floods
Diagnostic Actions to remedy Spatial prioritization for program efficiency
Other benefits (Public) Fund
allocation
Improved watershed services?
% Forest cover Tree planting Qmax/ Qmin Buffered flow expec-tation, no floods
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Is Qmax/Qmin a suitable indicator?
• Maximum flow (Qmax) reflects the biggest rainfall event (minus infiltration)
• Minimum flow (Qmin) reflects the longest dry period (as long as groundwater was fully recharged at end of rains)
• The ratio of these two reflects climate variability – with potentially some impacts of landscape quality
We need real indicator of watershed condition, independent of weather
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Basic Watershed Components
Base Flow
Groundwater
Sediment Loss
Rainfall
Overland Flow
River
Transpiration
Sub-surfaceflow
Water Input
Lateral Flows, Filters, Channels, & Storage
“pump”“pump”
“sponge”
“sponge”
Water Outputs
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Buffering of flows at multiple scales
Contributing factors• Interception + canopy drip => half hour shift• Surface flow vs infiltration => 1-2 day shift• Flow conditions in river bed => few hours• Impoundments, wetland overflow areas => days• Spatial variability of rainfall => weeks• Lakes and man-made reservoirs => months,
rarely years
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Precipitation = P
Evapotranspiration = ERiver flow = Q
Qquick Qslow Eveg Esoil EintercEirr
infiltration
interception
Esoil + Eveg
Einterc
Qslow
Qquick
Energy-limited Epotential
Signal modification along river
precipitation
1. Transmit water
2. Buffer peak rain events
3. Release gradually
4. Maintain quality
5. Reduce mass wasting
• Q/P=1-(E/P) QabAvg/PabAvg
• Qslow/P = (Pinf – ES+V)/P
• Qualout/Qualin
risk
Scaledependent
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Point of inflection when landscape sponge reaches saturation
A. Cumulative rainfall, mm
Small effects of land use change relative to
interannual variability
Cumulative dry season flow = drying
out the sponge
Source: Xing Ma, Jianchu Xu & Meine van Noordwijk : Sensitivity of streamflow from
a Himalayan catchment to plausible changes in land-cover and climate
(submitted)
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0
5
10
15
20
25
30
0 20 40 60 80 100 120 140Rainfall, mm day-1
Riv
er
flo
w, m
m d
ay
-1
1975-19811982-19881990-19981st quarter2nd quarter3rd quarter4th quarter
Way Besai
Mae Chaem
Wettest month in Mae Chaem is
approaching Way Besai
1 – slope of line = buffering indicator
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Source: Xing Ma, Jianchu Xu & Meine van Noordwijk : Sensitivity of streamflow from a Himalayan catchment to plausible changes in land-cover and climate (submitted)
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0
20
40
60
80
100
120
0 20 40 60 80 100 120
River today
Riv
er y
este
rday
19751985
1995
Flow persistence 0.75
Way Besay, Sumberjaya
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Interpreting flow persistence on basis of flow pathways:
• Flow persistence of overland flow ~ 0.0
• ,, interflow (soil quick flow) ~ 0.5
• ,, groundwater flow ~ 0.95
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ConclusionsThree quantitative indicators are now available for
further testing:1) Flow persistence – day-to-day predictability of
riverflow; 1 = perfectly bufferred, 0 = no buffering at all; index can be decomposed into flow path contributions
2) Buffer indicator as above-average discharge per unit above-average rainfall: seasonal or yearly indicator
3) CumRain versus CumRiverflow transition points for sponge saturation effects and timing of buffer saturation