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Climate change and environmental drivers (CPWF-GD workshop, Sept 2011)
Climate change and environmental drivers (CPWF-GD workshop, Sept 2011)
Climate change and environmental drivers (CPWF-GD workshop, Sept 2011)
Climate change and environmental drivers (CPWF-GD workshop, Sept 2011)
Climate change and environmental drivers (CPWF-GD workshop, Sept 2011)
Climate change and environmental drivers (CPWF-GD workshop, Sept 2011)
Climate change and environmental drivers (CPWF-GD workshop, Sept 2011)
Climate change and environmental drivers (CPWF-GD workshop, Sept 2011)
Climate change and environmental drivers (CPWF-GD workshop, Sept 2011)
Climate change and environmental drivers (CPWF-GD workshop, Sept 2011)
Climate change and environmental drivers (CPWF-GD workshop, Sept 2011)
Climate change and environmental drivers (CPWF-GD workshop, Sept 2011)
Climate change and environmental drivers (CPWF-GD workshop, Sept 2011)
Climate change and environmental drivers (CPWF-GD workshop, Sept 2011)
Climate change and environmental drivers (CPWF-GD workshop, Sept 2011)
Climate change and environmental drivers (CPWF-GD workshop, Sept 2011)
Climate change and environmental drivers (CPWF-GD workshop, Sept 2011)
Climate change and environmental drivers (CPWF-GD workshop, Sept 2011)
Climate change and environmental drivers (CPWF-GD workshop, Sept 2011)
Climate change and environmental drivers (CPWF-GD workshop, Sept 2011)
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Climate change and environmental drivers (CPWF-GD workshop, Sept 2011)

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By Mark Mulligan. As part of a CPWF September 2011 workshop in Thailand regarding global drivers. We have divided driver types into five categories: …

By Mark Mulligan. As part of a CPWF September 2011 workshop in Thailand regarding global drivers. We have divided driver types into five categories:
1. Demographic/Social,
2. Economic,
3. Political/Institutional/Legal,
4. Environmental/Climate change,
5. Technological/ Innovations

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  • 1. CLIMATE CHANGE AND ENVIRONMENTAL DRIVERS Mark Mulligan, King’s College London
  • 2.
    • KEY POINTS:
    • Environmental drivers (ED’s) are fundamental , don’t forget them
    • Some cannot be managed by us (e.g. rainfall inputs) so we are at their mercy
    • We do not know it all – still a lot to understand about ED’s
    • We cannot even measure the most fundamental ones at policy relevant scales ( e.g. rainfall inputs)
    • ED’s are spatially variable within as well as between basins – need for careful spatial targeting of interventions rather than ‘broad-brush’
    • ED’s are highly dynamic in time
    • Capacity of natural systems to buffer ED changes diminishing as ecosystems are degraded – impact on ecosystem service delivery
    • Climate change will be an increasingly important ED
      • must be seen within the context of current climate variability
      • rainfall change (not temperature) is the key for most of the basins but is highly localised - rainfall may increase or decrease locally (global average is increase)
      • catchments may wet up for 2040s then dry or vice versa thus continuous adaptation required
  • 3. Ganges Volta Limpopo
    • RS productivity and rainfall compared for 1000 points in and around each basin
    • Rainfall is not the only driver of plant productivity
    • There are other environmental (and socio-economic) drivers
    • Relationships with rainfall much stronger at low rainfall (e.g. Limpopo)
    • Form of relationship varies between and within basins
  • 4. There is already significant inter-annual climate variability in some of the basins and this needs to be incorporated in any intervention or planning These are entire basin averages, parts of the basins may have different responses
  • 5. Recent historic climate trends are not significant in the basins Most 20 th C warming occurs post 1950, so not seen here
  • 6. Climate change is basins to 2050 Temperature change within and between CPWF phase I basins (mean of 17 GCM ensemble) All warming Significant differences within as well as between basins. Change much more uniform in some basins than others. South American basins Asian basins African basins
  • 7. Precipitation change within and between CPWF phase I basins (mean of 17 GCM ensemble) African basins South American basins Asian basins Some wetting, some drying Significant differences within as well as between basins. Parts of a basin may dry while other parts wet Change much more uniform in some basins than others.
  • 8. Impacts of climate change on water availability for Andes basin. (mean of 17 GCM ensemble) Combines effect of precipitation, temperature and thus evapo-transpiration changes
  • 9. But environmental drivers are just one of many. Need to consider them within context of other drivers such as: Population, economics and others in an integrated way
  • 10. A spatial example for the Ganges
  • 11. ar4-a2-ci-mean-2041-2060 Ganges basin water balance Mean of 17 GCMs 2050 sees possible increases in rainfall over most of lowlands. Some decreases in rainfall in Himalaya % change Some sharp increases in water balance because of additional snowmelt inputs Very high % changes relative to current baseline in some areas
  • 12. ar4-a2-ci-mean- 2081-2100 40 years later spatial pattern changes a little Still dominantly wetting in most of lowlands but now drying in the western high plateau Stronger wetting in Himalaya % change
  • 13. % change ar4-a2-ci-mean- 2041-2060 Seen by administrative region , it is clear that some regions will have to deal with less water (eg Uttar Pradesh) and some with more water (Tibet). National adaptation plans of action (NAPAs) then not so relevant as regional ones (possibly even local ones).
  • 14. % change ar4-a2-ci-mean- 2081-2100 40 years later admin areas that had dried relative to baseline are now wetter than baseline (e.g. UP) Some undergo further wetting (e.g. Tibet) Interventions would need to be highly adaptable to cope with such water resource flip-flops even with the buffering of groundwater
  • 15. ar4-a2-ci-mean- 2041-2060 Water supply to urban populations The implications for water supply to urban areas indicates mostly increases (because of increased rainfall) and snowmelt. % change Increases in % terms especially high in foothills where extra snowmelt also contributes and in areas with lower baseline flows to start with
  • 16. % change ar4-a2-ci-mean- 2081-2100 Water supply to urban populations Impacts on runoff through urban areas change in magnitude and pattern over the subsequent 40 years. Again adaptive capacity is important.
  • 17. There is no flatlining in nature (most EDs vary over time) – water and food systems therefore need to be responsive and adaptable to environmental drivers (as they often used to be) Concluding
  • 18.
    • Win-wins and adaptation
    • Water is a common pool resource (CPR, use degrades the resource available to others) : so there may be no win-win solutions to managing change in ED’s. Someone’s gain is someone else’s loss. Role for BSM here.
    • Responding to changing Eds (esp. CV/CC) requires adaptive capacity perhaps focused as:
    • Less focus on?: More focus on?:
    • International capacity Local capacity
    • Hard(er) interventions Soft(er) interventions
    • Centralization Decentralization
    • Resource exploitation Efficiency of use
    • Livelihood homogenization .. Diversification
    • Built capital Social capital
  • 19.
    • Can we define the best intervention(s) to make under current environmental driver states?
        • System understanding (do we understand the system?)
        • Data quality (do we have the data?)
        • Politics (are the technical solutions politically feasible?)
        • Funding (is there investment potential?)
    • How will this intervention also work through the full cycle of climate variability?
    • How will the intervention work for 2040-4060 hydro-climatic conditions in the area?
    • How will it also work for 2080-2100 hydro-climatic conditions in the area?
    Discussion: relevance of ED’s to CPWF related interventions
  • 20. Thank you Questions?

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