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From Se Research To Modeling Impacts Of Interventions (Part 4 5)

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  • 1. From Soil Erosion Research to Modeling Impacts of Interventions: The Case of Ethiopia By Gete Zeleke GMP UN expert group meeting on “Sustainable land management and agricultural practices in Africa: Bridging the gap between research and farmers” April 16 – 17, 2009, University of Gothenburg, Sweden.
  • 2. Part IV: Mechanisms of capturing process to influence agricultural development positively
  • 3. What is need to make informed decisions on Agri. deve? – Need to have resource database (at least soil, water, climate and genetic resources…) – Need to know rate and magnitude of soil erosion/runoff under different AEZ, soil types, land use systems, etc – Need to know what technology works, where, and under what condition – Need to know negative impacts of Soil erosion (land degradation) and positive impacts of applying improved land management practices
  • 4. What are Possible approaches? Approach 1: • Measuring soil erosion in all watersheds • Measuring effects of all land management practices in different parts (too expensive) Approach 2: • Measure selective and representative watersheds • Measure selective and right combinations of LM practices (Achievable) Approach 3: • Extrapolate the result to ungauged areas using a combination of GIS, biophysical and economic models (Achievable)
  • 5. Framework for Assessing Major LD Processes & Impacts (Approach 2) Processes captured Impacts quantified Types of Impacts • Soil loss due to Sheet & On- rill erosion by water • Production loss site • Loss of soil nutrients through DB, CRB & GR • water supply LD • irrigation water supply • Power Siltation/sedimentation generation Off- • Reservoirs/dams • Biodiversity site • Lakes • On farm lands • Destruction of productive lands
  • 6. What do we have on this? Processes captured Impacts quantified Types of Impacts We know – SCRP & others • Soil loss due to Sheet & On- • Production rill erosion by water loss site • Loss of soil nutrients through DB, CRB & GR • water supply LD • irrigation water Very little supply • Power Siltation/sedimentation generation Off- • Reservoirs/dams • Biodiversity site • Lakes • On farm lands • Destruction of productive lands
  • 7. Afdeyu
  • 8. Two key processes to be captured: • Watershed status (hill slope Processes • Stream gauging
  • 9. Database from SCRP 1. Watershed level With and without • Catchment runoff - hydrographs } scenario • Sediment yield • Climate • Land use • Harvest • Soil depth • Socio-economic data 2. Plot level – Soil loss – Runoff – Yield – SWC measures impact/land use/design/type
  • 10. Framework for Assessing Impacts of LM Practices (Approach 2 cont..) Processes captured Impacts quantified Types of Impacts • Effectiveness in reducing On- soil loss • Production gains site • Effect in improving soil fertility and depth • Effect on moisture • water supply conservation and soil water LM • irrigation water holding capacity supply • Power Effect in reducing generation Siltation/sedimentation Off- • Reservoirs/dams • Biodiversity site • Lakes • Protection of • On farm lands productive lands
  • 11. What do we have? Processes captured Impacts quantified Types of Impacts • Effectiveness in reducing On- soil loss • Production gains site • Effect in improving soil We have some data and depth fertility (SCRP/HLI/EIAR but need • Effect on moisture • water supply to be organized) conservation and soil water LM • irrigation water holding capacity supply • Power Effect in reducing generation Siltation/sedimentation Off- • Reservoirs/dams • Biodiversity site • Lakes • Protection of No measured • On farm lands productive lands data
  • 12. What is missing or less addressed? • Offsite processes and impacts of LD • Info on impacts of LM practices (only few) • Info on impacts of integrated land management practices • Socio-economic aspects of SLM and LD (need more work)
  • 13. Approach 3: Methods of extrapolation 1. Selection of appropriate models and tools – Modeling • Model – Choice of appropriate model » USLE – On-site processes (soil loss) » SWAT- Off-site process (siltation) • Gauged values to calibrate and validate model » SCRP watersheds – GIS • To identify recommendation domains
  • 14. Methods of extrapolation cont… 2. Steps to be followed • Characterize each station – Biophysical parameters – Socio-economic parameters • Reclassify country coverages of bio-physical and SE parameters • Identify recommendation domains • Test model on station • Calibrate and validate model using gauged station data • Apply model on recommendation domains
  • 15. Processes of Identifying Recommendation Domains using GIS Environment (soil loss, Nutrient loss & SLM) Develop Reclassify country Overlay Ranges of coverage and develop (model) parameters layers for each parameter - Altitude - Rainfall - LGP - Slope Recommend. GIS - Soil Domains Modelling -Farming system -Land Use …etc
  • 16. Examples of National coverage for key parameters ann.precip. (mm) m.a.s.l. < 400 High : 4378 401 - 800 801 - 1,200 Low : -152 1,201 - 1,600 > 1,600 slope growing days < 2% 0 - 60 2% - 5% 61 - 120 5% - 8% 121 - 180 8% - 12% 181 - 240 > 12% 241 - 365
  • 17. Farming system: Ethiopia farming system dominant cereal Anjeni station Barley Maize Millet Sorghum Teff Wheat Pastoral
  • 18. extrapolation of station data based on similarity of environmental conditions
  • 19. Farming system – Similar to Anjeni farming system Farming system: teff, wheat, maize & pulses
  • 20. Soils – Similar to Anjeni soils
  • 21. Altitudinal belts – Similar to Anjeni altitude m.a.s.l. Anjeni station -152 - 1,700 1,701 - 2,600 2,601 - 4,378
  • 22. Annual rainfall – Similar to Anjeni rainfall annual rainfall (mm) Anjeni station 95 - 1,400 1,401 - 1,800 1,801 - 2,231
  • 23. LGP – Similar to Anjeni LGP (days) Anjeni station 0 - 180 181 - 250 251 - 365
  • 24. Slope – Similar to Anjeni slope slope Anjeni station 0% - 2% 3% - 8% 9% - 62%
  • 25. Annual Meant Temp – Similar to Anjeni temperature Annual Mean Temperature Anjeni station degrees Celsius < 15 15 - 22 > 22
  • 26. GIS Modelling and Overlays: Areas that can be represented by Anjeni similarity of environmental conditions Anjeni station most similar least similar
  • 27. Areas that can be represented by Anjeni- by woreda (best fit areas only) Anjeni station representative areas
  • 28. Part V: Extrapolation A: Model application (Eg. USLE) to extrapolate on-site processes and impacts
  • 29. Processes captured Impacts quantified Types of Impacts • Soil loss due to Sheet & • Production rill erosion by water LD loss • Loss of soil nutrients through DB, CRB & GR On- site • Effectiveness in reducing • Production soil loss SLM gains • Effect in improving soil fertility and depth • Effect on moisture conservation and soil water holding capacity
  • 30. Phase I: Model validation at station level 1. Quantifying Soil Loss: • Parameter generation – R, K, S, L, C, P • Model calibration • Parameter adjustment including methods of generation • Validate model • Recommend options for: – Model response and interpretation requirements – procedures parameter generation – Options including tables, equations
  • 31. Parameter generation options • Eg. K factor 1 . 14 00021 12 OM 3 . 25 2 2 .5 3 S S M 1. str per K 100 2. f f f f K csand cl si org hisand 2 log 1 . 659 D 3. K g 7 . 594 0 . 0034 0 . 0405 exp 0 .5 0 . 7101 4. Or use table developed based on Ethiopian experience
  • 32. 2. Quantifying Nutrient Loss • We choose only three important ways of nutrient loss from the soil – Burning of dung – Burning of crop residue – Removal of grain • We consider three possibilities of nutrient addition to the soil – Fixation – Weathering – Artificial fertilizer or manuring • We only address two nutrients –N –P Remark: the method can be used to include others
  • 33. Procedures • Determine nutrient content of dung, crop residue and major crops • Set conversion coefficient - % of energy consumption covered by dung and crop residue per person, per year • Convert this to dung and CR used • Convert this to N & P loss from dung and CR
  • 34. Procedures cont… • Estimate production of major crops for each zone and • Convert this into N & P loss • Calculate Nutrient addition by different means • Calculate net nutrient loss: gr db cb A N N N N N gr P db P cb PA P P
  • 35. 3. Quantifying impacts of SLM practices 1. Scenario 1. Only Physical SWC measures – Use SCRP values – Adjust P factor 2. Scenario 2. Physical SWC with SF/SMM – Extrapolate from existing values or measure – Adjust P factor and may be C factor 3. Scenario 3. All best LMP – Extrapolate of measure – Adjust P factor and C factor 4. Area closure and forestry – – Extrapolate or measure – adjust P factor and C factor
  • 36. Phase II: Procedures of extrapolation to Recommendation Domains (Eg) Overlay Ai R aez K i C i P i SL i Soil Map K- Map DEM LS - Map Soil Loss Land Use (Map and Data) C/P - Map Map Climate R – Map n g A Ai i 1 n A S f n g * 0.01 D S A A B
  • 37. B: Model application (Eg. SWAT) to extrapolate off-site processes and impacts
  • 38. Impacts quantified Types of Impacts Processes captured • water supply • irrigation water supply Siltation/sedimentation • Power generation • Reservoirs/dams LD • Biodiversity loss • Lakes • Destruction of • On farm lands productive lands Off- Improved: site • water supply • irrigation water supply Effect in reducing • Power generation Siltation/sedimentation SLM • Reservoirs/dams • Biodiversity • Lakes • Protection of • On farm lands productive lands
  • 39. 1. Quantifying siltation using SWAT • SWAT is a dynamic watershed/basin model • Developed by USDA-ARS • It simulates: – Crop growth – Hydrology – Soil erosion – Climate – Updates model parameters on a daily basis – It takes point sources as input – Impacts of land management practices – Point and non point pollutant • Output: – Sediment yield – Runoff – Nutrient and pollutant balance – Etc……
  • 40. 1. Quantifying siltation using SWAT cont…. • SWAT simulates at three levels – HRU • Homogenous units in terms of soil and land use – Sub-basin (smaller watershed) • Holds a number of HRU – Basin (bigger watershed) • Holds a number of sub-basins • Has GIS interface and the model can run through GIS • Has weather generator
  • 41. HRUs !! ( ( (( !! (( !! Sub- Basin/Big basin/sub- drainage outlets ( ! ( ! watershed drainage lines watershed microbasins ( !! ( (( !! ( ! ( ! ( ! (( !! (( !! ( !! ( ( ! ( ! ( ! !! ( ( ( !! ( ( ! ( ! ( ! !! ( ( !! ( ( ( ! watersheds ( ! (( !! & drainage ( !! ( ( ( !! ( ! ( !! ( ( ! ( !! ( drainage lines ( !! ( ( ! ( ! ( ! drainage outlets ( ! ( !! ( ( !! ( ( !! ( ( !! ( ( ! ( !! ( ( !! ( (( !! ( ! ( ! ( ! !! ( ( ( !! ( ( ! !! ( ( ( ! ( ! ( ! !! ( !! ( ( ( ( ! ( !
  • 42. Procedures of using SAWT 1. Validate model using SCRP station data • Generate parameter • Conduct sensitivity analysis • Calibrate model • Adjust model parameters • Validate model 2. Apply model on selected basins • Prepare soil map and data • Prepare and use map and data • Prepare DEM • Map climate variables • Indicate point sources • Produce parameter – built model database • Run the model
  • 43. Conclusion a. Build required resource database b. Develop information on SLM scenarios • Develop generic values based on some observation • If absolutely needed establish learning sites c. Build capacity • On modelling • Parameterization d. Develop packages of recommendation e. Develop feedback system among research, extension and policy makers