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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 

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B1. Quantifying the role of AF in modifying watershed functions 

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  1. 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 

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

  3. 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

  4. 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

  5. Watershed rehabilitation as business: Better diagnostic and performance criteria: realistic, conditional & voluntary

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 1 – slope of line = buffering indicator Wettest month in Mae Chaem is approaching Way Besai

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

  13. 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

  14. 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

  15. 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

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