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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 

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b1 quantifying the role of af in modifying watershed functions
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 
slide2

Buffering water flows through agroforestry management: quantifying the influence of landscape mosaic composition and patternMeine van Noordwijk, Betha Lusiana, Bruno Verbist 

slide3

Buffering water flows through agroforestry management: quanti-fying the influence of landscape mosaic composition and pattern

‘Protec-tive garden’

Sustainable land use

Stakehol-der nego-tiation

Watershed management

Agroforestry

Trees, Soil, Drainage

Hydrological Functions

Criteria & Indicators

slide4

cloud

interception

surface run-on

Stream:

surface run-off

sub-surfacelateral

inflow

rainfall

canopy water

evaporation

Forest

transpiration

surface

evaporation

through-fall

stem-flow

{

infiltration

quick-

flow

recharge

lateral

outflow

uptake

base

flow

percolation

slide5

Watershed rehabilitation as business:

Better diagnostic and performance criteria:

realistic, conditional & voluntary

is q max q min a suitable indicator
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

basic watershed components

Water Input

Rainfall

Transpiration

“pump”

“pump”

“sponge”

“sponge”

Water Outputs

Basic Watershed Components

Overland Flow

Lateral Flows, Filters, Channels, & Storage

Sediment Loss

Sub-surface

flow

Ground

water

Base Flow

River

buffering of flows at multiple scales
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
slide9

Precipitation = P

River flow = Q

Evapotranspiration = E

Eveg

Esoil

Eirr

Einterc

Qquick

Qslow

precipitation

Signal modification along river

Einterc

Energy-limited Epotential

interception

Qquick

Esoil + Eveg

infiltration

Qslow

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

Scale

dependent

slide10

Cumulative dry season flow = drying out the sponge

Small effects of land use

change relative to

interannual variability

A. Cumulative rainfall, mm

Source:Xing Ma, Jianchu Xu & Meine van Noordwijk : Sensitivity of streamflow from a Himalayan catchment to plausible changes in land-cover and climate (submitted)

Point of inflection when landscape sponge reaches saturation

slide11

1 – slope of line = buffering indicator

Wettest month in Mae Chaem is approaching Way Besai

slide12

Source:Xing Ma, Jianchu Xu & Meine van Noordwijk : Sensitivity of streamflow from a Himalayan catchment to plausible changes in land-cover and climate (submitted)

slide13

120

Way Besay, Sumberjaya

100

Flow persistence 0.75

80

60

River yesterday

40

1975

20

1985

1995

0

0

20

40

60

80

100

120

River today

interpreting flow persistence on basis of flow pathways
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

Direct link with water balance

Easy to understand and interpret

Some challenges in quantification

conclusions
Conclusions

Three quantitative indicators are now available for further testing:

  • Flow persistence – day-to-day predictability of riverflow; 1 = perfectly bufferred, 0 = no buffering at all; index can be decomposed into flow path contributions
  • Buffer indicator as above-average discharge per unit above-average rainfall: seasonal or yearly indicator
  • CumRain versus CumRiverflow transition points for sponge saturation effects and timing of buffer saturation