Part2 Yesuf


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Part2 Yesuf

  1. 1. Costs of Land Degradation
  2. 2. 1. Loss of agricultural production due to removal of top soil by soil erosion
  3. 3. 2. Loss of nutrients : The invisible threat (Biological and chemical) • All soils in the country (except pastoralist areas) suffer from soil nutrient mining: Open nutrient cycle! – Use of cow dung and crop residue as a source of energy in the country is equivalent to 500,000 tons of grain/year – Deteriorates chemical and physical properties of the soil • OM content • Soil moisture holding capacity • Infiltration capacity • Soil structure
  4. 4. 3. Siltation of lakes, rivers, and reservoirs
  5. 5. 4. Gravel Redeposition to down stream productive crop lands
  6. 6. 5. Other Offsite Costs • Hydrologic drought: in many places of the country springs, water wells and even permanent rivers are dried. Some wetlands shrinked, some totally dried up (Adele, Alemaya, etc) – Recharging of ground water and aquifers is affected by • Reduction of infiltration cased by land degradation (soil & vegetation) • Deterioration of soil hydrologic properties • High flooding: extreme floods and land slides are getting common in many parts of the country – Destroy many structures and farm lands • Water pollution: surface water bodies of various size are being seriously polluted by sediment and chemicals (fertilizers, pesticides, factory effluents, solid wastes, etc)
  7. 7. Economic approaches – Replacement cost approach (RCA) – Change of productivity Approach (CPA) – (Others: CVM, Hedonic Pricing)
  8. 8. Economic approaches (con’t) • RCA: The cost that would be incurred to replace a damaged asset (soil). – Eg: cost of fertilizer application to compensate for the loss of soil nutrient (N and P) • CPA: The cost of LD damage equals the value of the lost crop production valued at market price. – Relies on projected yield with and without soil erosion
  9. 9. Economic approaches (con’t) • Major weaknesses of RCA: – Original good and replaced good may not be perfect substitutes – Assumes lost nutrients were readily available for plant growth – Soil nutrients may not be the limiting factor in crop production – Fertilizer may not be the most cost effective way of replacing nutrients; in some deep soil, they may not even feel yield reduction due to soil erosion, hence not willing to apply fert.
  10. 10. Economic approaches (con’t) • Weaknesses of CPA: – Yield decline is not always ascribable to land degradation, especially in rain feed agri. Thus need to control other factors or apply it on an assumed average situation. – Fertilizer or other input uses could mask long term impacts hence RCA underestimates cost of LD. – Yield declines are compared with hypothetical benchmarks of undegraded soils. The question of what production would be in the “without land degradation” case is not obvious in most studies. – Ignores rediposition
  11. 11. Applications of CPA • On-site cost of sheet erosion: – The value of the lost crop production valued at market prices (with future losses discounted by market interest rates) – As a physical measurement, it relies on projected yields with and without soil erosion or with or without soil conservation measures. Differences in crop or other yields are then multiplied by their unit price to get the value of lost production due to soil erosion damage
  12. 12. Applications of CPA (con’t) • Off-site costs: – the income forgone from reduced capacity to generate electricity – the income forgone from reduced capacity to irrigate crop lands – reduced fish harvest due to eutrophication of lakes – Income lost due to increased cost of production of electricity or irrigation water through increased operation and maintenance costs of irrigation or power supply schemes, and the higher operating costs for removing sediments through dredging) or increased cost of fishing
  13. 13. Applications of RCA • On-site cost of nutrient depletion: – Annual costs of fertilizer applications to compensate for the loss of soil nutrients due to breaching of nutrient cycles • Off-site costs: – The cost of replacing the live storage lost annually or the costs of constructing dead storage to anticipate the accumulation of sediments (defensive expenditure) in the case of siltation of water storages – In terms of eutrophication of lakes, the replacement cost would become the costs of removing water hyacinth in the lake.
  14. 14. CBF for ETH • Use SCRPs’ station gauged data set, woody biomass data sets, river basin datasets and other available data sets from different sources. • Extrapolate their results to homogenous land units (map units) represented by each station (discussed in the Biophysical section in detail) • Use the LD info in the biophysical analysis and convert them into economic units and generate economic coefficients for each mapping unit. • Two major on-site costs (production loss due to soil erosion) and nutrient losses due to removal of dung and crop residues. • Two major off-site impacts (siltation of dams and resorviors and gravel deposition to down stream productive crop lands) • Applications only to cultivated lands but could easily be extended to other land uses.
  15. 15. CBF for ETH: On-site costs Loss of Agricultural production On-farm Reduced costs Benefits Loss of Nutrients
  16. 16. CBF for ETH: Off-site costs Loss of dam or lake yield Reduced Increased Benefits production cost Off-farm costs Loss of dam or lake capacity Increased defensive Extra dam expenditure capacity to store silt
  17. 17. CBF for ETH: Practical steps • A production function will be estimated for each treatment in each recommendation domain using SCRP data. Using price & cost data, farm profit out of adoption of a given treatment would then be computed • A production function for the baseline scenario (no treatment) would be estimated in each recommendation domain using SCRP data. Using price & cost data, the corresponding farm profit would be computed. • Differences in farm profit for the treated and untreated land would give us the on-site costs due to soil erosion or the private costs or benefits of conservation. • Adding costs due off-site costs to the private net benefits would give us the social net benefit. • These estimated coefficients (for each treatment, each domain and each major crop) will then be the basis for the simulations of impacts of treatments in the various mapping units i. • For each unit, the generated explanatory variables from the GIS layers will be used (such as slope, soil, rainfall etc). • These will be combined with the coefficients estimated based on the SCRP data in order to predict crop yield change due to a particular treatment.
  18. 18. CBF for ETH (con’t) 1. On-site impacts: Loss of agricultural production due to soil erosion and nutrient depletion: – The difference between farm profit with and without SLM practices (off-site costs excluded)  n  Pit f t ( x , q , A , S , C )    eit x it  M C t   c c c c c c c t t t t t t  i 1  n   Pit f t ( x , q , A , S , C )   eit x it 0 0 0 0 0 0 0 t t t t t t i 1   1  r  T t t  p 0 c NPV t t0
  19. 19. CBF for ETH (con’t) 2. Offsite impacts and social net costs/benefits of SLM:      1  r  T t   s 0 c NPV t t t t0
  20. 20. CBF in ETH: Cost/Benefit Categories • Immediate income gains or losses (NAIG) – the immediate costs of soil erosion or benefits of         N conservation measures. c 0 it it it i 1 • Future income gains or losses (NDIG) – the loss in potential income over a number of years due to effects of one year of erosion (which are future benefits of conservation measures)  N NAIG it i 1 1  r t • Cumulative income gains or losses (NDCIG) – It reflects the present value of the cumulative costs N T of erosion over a defined period of time.   NAIG it i 1 t 1   – t 1 r .
  21. 21. Economic Criteria • NPV and IRR • Earlier strategies were based on physical criteria that classified the whole country as “high” and “low potential”, which we believe is a partial criteria and could misguide resource allocation • In our framework, we will use the following combination of both biophysical and economic criteria to target interventions on SLM. – The rate of soil erosion (EROSION) – Net Annual Income Gain (NAIG) from intervention – Net Discounted Cumulative Income Gain (NDCIG) from intervention
  22. 22. Decision Matrix Low returns from soil Unlikely cases High returns from soil conservation conservation Case 1: Case 4: Case 7: Erosion: High Erosion: Low Erosion: Low NAIG: High NAIG: Low NAIG: High NDCIG: High NDCIG: Low NDCIG: High Case 2: Case 5: Case 8: Erosion: High Erosion: Low Erosion: Low NAIG: Low NAIG: High NAIG: Low NDCIG: High NDCIG: Low NDCIG: High Case 3: Case 6: Erosion: High Erosion: High NAIG: High NAIG: Low NDCIG: Low NDCIG: Low
  23. 23. Targeting priorities • Top priorities (case1): – Areas with high soil erosion rates and high NAIG and NDCIG • Second priorities (case 2): – high risk of soil erosion, low short term returns from SLM intervention but high long term returns from intervention • Third priorities (case 3): – high soil erosion risk, with high short term returns but small long term gains. • Cases 4 and 5 are not at risk of soil erosion and hence returns from SLM intervention are smaller . • Case 6, no conservation (except area closure) is recommended on economic grounds. Alternative livelihood strategy should be sought.
  24. 24. Policy implications on private adoption of technologies • In areas where available technologies are highly profitable with high NAIG and NDCIG (such as case 1 in the decision matrix table 2), the focus should be on identifying the most binding constraints limiting their adoption, and the strategies that can most effectively relax these constraints (such as low cost credit provision). • In areas where available technologies are far from profitability with low NAIG and low NDCIG, despite high risk of soil erosion (such as case 6 in table 2), the strategy should focus more on opportunities for alternative livelihood strategies that are less dependent on intensive land use. In these areas, since the technology is far from profitable, other constraints to adoption are irrelevant.
  25. 25. Thank You!