Session 6.5 modelling the effects of adopting agroforestry on basin scale runoff, philippines


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  • Thank you for the introduction. It’s an honour to be sharing a stage with such distinguished scientists and be presenting this research on behalf of my co-author and I at such a prestigious event. Indeed, as my first conference presentation it represents somewhat of a baptism of fire. Please be gentle!As the title suggests this study involves the simulation of key hydrologic and watershed functions at basin scale in the Philippines. <next slide>
  • I’d like to quickly provide you with an overview of the study site. As part of the Carood basin situated in the east of the Island province of Bohol, in the central island group of the Philippines It’s over 5,000ha with a relief of 790m and a mean slope of 17.1%. It receives an average of 1677mm of rainfall each year (based on a 30yr time series) with a pronounced dry season between February and April and the heaviest rainfall occurring between October and December. The dominant soil type is Ubay series clay loam which is slightly acidic<next slide>
  • Current land use is highly varies throughout the watershed and is characterised by (moving clockwise): A mosaic land scape including pasture, maize and some forest fragmentsTerraced rice which is mainly irrigated from surface water sourcesAnnual agriculture (mainly, maize, cassava and some vegetables) with some perennials (coconut, mango and increasingly coffee and cacao) Grassland are degraded and seasonally burned to promote growth for grazing livestockThe area is home to mainly smallholder farmers whose principal livelihood activities of subsistence agriculture - particularly rice and maize production - are closely bound to the ecosystem services provided by the watershed. Reported environmental problems such as alternate flooding and drought episodes, reduction in water quality,an accelerated level of soil erosion as well as downstream sedimentation of irrigation networks have impacted the agricultural activities of local communities and been linked to land management practices and the degraded nature of the watershed.However, reported problems remain largely anecdotal with little available biophysical or hydrological data. Our hypothesis is that these problems are associated with a disruption of watershed scale ecosystem services and that these could be partially restored or some of the negative affects avoided through applying a combination of conservation agriculture and agroforestry systems in strategic locations. <next slide>
  • Based on this hypothesis, our objective was to quantify the effects of land use on specific ecosystem services identified by local stakeholders as being under threat. <Describe table>In order to do this we used USDA Soil and Water Assessment Tool (SWAT) to simulate the effects on watershed hydrology of different land use practices under two scenarios: current land-use practices and conservation agriculture with agroforestry in strategic locations.<next slide>
  • In order to simulate these scenarios, Arc SWAT 2012 was selected which interfaces with Arc GIS.For those of you unfamiliar with this model, it was developed by the USDA and is a quasi-distributed, continuous model used to simulate and quantify the impact of land management practices on water balance and sediment transport at watershed scaleThe basic inputs include topography, land cover, soils and climate data – time series data where possibleThe volume of surface runoff is predicted from daily rainfall by using the Soil Conservation Service (SCS) curve number methodA modified universal soil loss equation (MUSLE) was designed for the model and vegetative cover (c), soil erodibility (k) and crop management (p) values parametised using secondary literature for the Philippines. Parameter SourceRunoffCurve Number (CN)Yu (1990)C Values David (1988)P Values David (1988)K Values FAO (1998)Manual Calibration and constraints:NSE R2 Result0.2-0.43 0.45 – 0.61 Acceptable<next slide>
  • This is the result of a land classification exercise using a 30m resolution landsat 5 image from June 1990As we can see there is extensive forest cover and large areas of secondary, open canopy forest and coconut. There is minimal agriculture and grassland and no discernible urban centresNow, skip forward 20 years and we see that a marked differenceThe upland areas retain forest cover although there has been further fragmentationIn lower areas of the watershed however, we see extensive conversion to agriculture and grassland We also notice areas of low density urban centres which includes roads and settlementsThis has resulted in a: 44% reduction in closed canopy forest 62% increase in mixed annual agriculture26 % increase in open canopy and mixed coconutThe appearance of settlements and idlelands – barren patches
  • Based on the land cover change analysis we wanted to develop a scenario which simulated changes to existing land cover by making adjusting the configuration and type of vegetative cover and management practices including tillage and management practices.This was based on the matching biophysically and locally familiar or acceptable species in agroforestry systems and combining this with conservation agriculture practices which have been deployed in other areas of the Philippines and designed to restore watershed functions, especially to reduce sediment yield and transfer to stream channels. After preparing the land cover data and re-parametising the model, it was run based on all 3 land cover scenarios some of the results of which are highlighted in the next few slides. <Next slide>
  • Here we can see the key components of the water balance at the watershed level in absolute and percentage termsOverall the proportions are roughly similar with ET dominating at 60% or over in each scenario.However, there has been a notable increase in surface runoff between S0 and S1 of around 20% and we will see later how this may have affected sediment yield and transfer. We also see an increase in ET which we might expect from a land cover scenario with increased tree cover through greater interception and ‘green water’ demand from introduced perennial species. We actually found a consistently lower level of total stream discharge under S2 results of which were not included here for brevity.
  • As an indicator of the evenness of flow or seasonal we compared the lowest monthly discharge (Q min or low flow) relative to the mean monthly rainfall for every simulated hydrologic year and for each of the two scenarios - (S1) shown in chart (a) and (S2) shown in chart (b) – over the simulated period.What this basically demonstrates is that there is an increasing amount of low flow relative to mean monthly rainfall over the simulated period under S2. Essentially low flows are lower under a degraded scenariosThere are other indicators of evenness of flow and seasonal availability not included here but in the paper.
  • Turning our attention now to simulated sediment yield, the outputs from the three scenarios are presented here spatially for each of the 14 topographically delineated sub-basins. Darker colours represent higher levels of mean sediment yield in t/ha/year and lighter colours lower amountsWe can clearly see that under the degraded scenario there appears to be an accelerated level of sediment yield when compared to the baseline 1990 map although the upper reaches which maintained their forest cover appear less affected. We can pick out critical watersheds – those with the highest levels of sediment yield – as 1,2,6 and 8We can also see that under the CA and AFS scenario there appears to be sizeable reduction even when compared to the baseline scenario. This is supported when we look at the mean figures for the entire watershed which suggest that there has been a 20% decrease when compared to the baseline in contrast to a 155% increase under the degraded scenario.
  • Having identified critical sub-basins riparian buffers were introduced in order to reduce the risk of sediment transfer and to act as river bank stabilisersWe can see from the chart presented here that simulations appear to show they would be effective. In all of the critical sub-basins we see that sediment concentration is reduced to below that of even the baseline 1990 scenario and in all cases to below 500 mg/lUnder the current degraded scenario, the simulation shows that there is an increased risk of high sediment concentration which would corroborate some of the reported water quality issues identified by community members including the sedimentation of
  • To summarise….Results of simulations using SWAT showed a 20% increase in surface run off under S1 with only a slight increase under S2There appears to be more water available to the system in the leanest rain months under CA and AFS over the simulated periodBoth sediment yield and sediment concentration – that which reaches the channel – are reduced under CA and AFSKey messages are…..ApplicationsDecision support toolBaseline and monitoringTesting appropriate interventions Focus limited resources
  • Session 6.5 modelling the effects of adopting agroforestry on basin scale runoff, philippines

    1. 1. Modelling the effects of adopting agroforestry on basin scale surface runoff and sediment yield in the Gabayan watershed, Bohol, Philippines. David M Wilson1, 2 & Rodel D Lasco1, 1World Agroforestry Centre (ICRAF) Philippines 2SESAM, University of the Philippines Los Baños Presented to the World Congress on Agroforestry, New Delhi, India February 12th 2014 Breakout session: 6.5 Agroforestry, water quality and nutrient export 1
    2. 2. Study Site Gabayan watershed, Carood basin - Bohol Characteristic Weather Station Description Watershed Area 52.05km2 (5205 ha) Sub basins 14 Elevation Range 7m – 797m (790m) (Relief) Mean slope 17.1% Drainage Pattern Mean Annual Rainfall Dendritic 1677mm Soil (dominant) Ubay Clay loam (31%clay/59%Silt/40 %Sand) pH 5.9 2
    3. 3. Current land use 3
    4. 4. Objectives To quantify the effects of land use on ecosystem services: Domain Ecosystem Service Indicator Provision Water supply Water balance Gradual release Q min: mthly mean P Soil stabilisation Sediment yield (t ha-1 yr-1) Water quality Sediment concentration (mg l-1) Regulating …..under two land use scenarios vs baseline (S0): 1. S1 - degraded 2. S2 - Conservation Agriculture with Agroforestry (CA + AFS) 4
    5. 5. Methods: Soil and Water Assessment Tool (SWAT) 1. Model input preparation i. Time series climatic data (25yrs): rh, wind, s.rad, P&T ii. Land cover iii. Soils - FAO iv. 30m DEM 3. Parametisation, calibration & validation 4. Scenario development 5. 3 runs – SO, S1, S2 ArcSWAT 2012 Model inputs Topography Land Cover Soils Climate Water Balance Components + Sed. Yld & concentration S1 (Degraded) S2(CA + AFS) 5
    6. 6. Methods: Land Cover Change analysis 1990 Land Cover (S0) 2010 Land Cover (S1) 6
    7. 7. Methods: CA + AFS scenario (S2) S1: degraded S2: CA + AFS Reduced Tillage Mixed annual agriculture (maize, cassava, cash crops) Degraded grasslands AFS: Jackfruit (Artocarpus sp.) + mango (Mangifera indica) Cowpea (Vigna unguiculata) Contour planting and naturally vegetated strips Rubber – Cacao – Coffee Ipil Ipil (Leucaena leucocephala) Riparian planting (15m wide buffers in critical sub-basins) Shrubs & grasses 7
    8. 8. Results: supply indicator Water balance 100% 90% 196.14 (12%) 155.19 (10%) 1007.32 (60%) 1108.66 (67%) 427.31 (26%) 271.91 (16%) 368.95 (22%) 80% 70% 60% 50% 1017.39 (61%) 40% 30% 20% 10% 338 (22%) 0% S0 Surface Runoff ET S1 Lateral Flow Baseflow S2 8
    9. 9. Results: Gradual release indicator 1 1 (a) 0.8 0.8 0.6 0.6 0.4 0.4 0.2 (b) 0.2 0 0 0 5 10 15 Simulated year 20 25 0 5 10 15 20 25 Simulated Year Lowest monthly discharge relative to mean monthly rainfall* in each hydro. year (a) – S1: degraded (b) S2: CA & AFS See van Noordwijk et al. 2006 & 2011 for more indicators 9
    10. 10. Results: Soil stabilisation Sediment yield S0: 1990 S1: degraded Total Watershed Mean sed. yld. (t ha-1 yr-1) % change vs. baseline S2: CA + AFS Baseline (S0) Degraded (S1) CA + AFS (S2) 17.8 45.5 14.19 n/a 155 -20 10
    11. 11. Results: water quality Sediment concentration Sed. Conc (mg/l) 2500 2000 1500 1000 500 0 1 2 6 8 Sub Basin S0 S1 S2 Mean monthly in-stream sediment concentration  Riparian Buffer: 15m either side of streams in critical sub-basins (1,2, 6, & 8)  Fast growing Ipil Ipil (Leucaena leucocephala) – fuelwood, charcoal and mulch  Bank stabilisation and sediment trap 11
    12. 12. Summary Indicator S1: Degraded S2: CA + AFS + 19.80% + 3.43% Gradual release Shallow ∆ in monthly low flow Steeper ∆ in monthly low flow Sediment Yield + 155% -20% Sediment conc. in critical sub-basins + 165% -35% Surface runoff Key messages: 1. SWAT provides a reasonable estimation of hydrologic function at basin scale 2. Ecosystem services are under threat based on current land use 3. Combining Conservation Agriculture with strategically located agroforestry systems could improve water quality and reduce sediment yield 12
    13. 13. Acknowledgements This research was conducted as part of an Environmental Science MSc at University of the Philippines, Los Banos and is generously supported by ICRAF, Philippines via an Associate Graduate Fellowship. Special thanks to the members of the Carood Watershed Model Forest Management Council and local communities for their help, warmth and guidance. David Wilson. Associate Graduate Fellow, ICRAF Philippines 13