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Economic Risks Associated with Low Flows in the Elbe River Basin (Germany): an Integrated Economic-Hydrologic Approach to Assess Vulnerability to Climate Change

Economic Risks Associated with Low Flows in the Elbe River Basin (Germany): an Integrated Economic-Hydrologic Approach to Assess Vulnerability to Climate Change

IWRM Conference in 12-13 October 2011

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Dresden

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Economic risks associated with low flows in the River Basin (): an integrated economic-hydrologic approach to assess vulnerability to climate change.

Malte Grossmann TU

IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Hamburg Overview

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1 / General background Dresden 2/ Approach of the GLOWA Elbe Project Ústí n. L. 3/ Results – assessment of climate risk 4/ Results - cost benefit analysis of adaptation options 5/ Conclusions

IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Hamburg

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Ústí n. L. 1 / General background

IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Why develop integrated hydrologic-economic waterHamburg

resources models? Magdeburg

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Ústí n. L. Management challenges:

(a) to develop strategies to minimise economic impact of drought and periodic water shortages (b) to assess basin wide efficiency of water use and to assess instruments to improve efficiency for example by inter-sectoral reallocations in water scarce basins (c) to assess infrastructure investments in terms of benefits and costs in the context of long term water systems planning

=> to assess the impacts of climate change on the long term performance of water resource system

IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Hamburg Two principal modelling approaches

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Optimisation Dresden => ability to identify economically efficient water allocations and to analyse Ústí n. L. different institutional mechanisms of water allocation. Simulation ⇒ allow a more detailed analysis of the hydrological processes. ⇒ assessment of the feasibility of management options with regard to infrastructure operations and to identify systems components that have a high risk of failure under extreme conditions.

IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Hamburg Aims of the GLOWA Elbe Project

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IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Hamburg

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Ústí n. L. 2 / GLOWA Elbe Approach

IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Hamburg WBALMO - Water Resources Simulation Framework

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- node - link network with catchments, reservoirs, water users, etc - stochastic simulation with 100 climate realisations over 50 years - statistical analysis of results based on 500 draws per five year period

IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Hamburg A definition: basic risk concept

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Risk = hazard (location, intensity and frequency) * Ústí n. L. vulnerability of the elements at risk (exposition to hazard and the sensitivity or susceptibility to hazard).

Sensitivity or susceptibility = relationship between the intensity of hazard and the degree of damage caused.

Sensitivity or susceptibility relationship is also referred to as a damage or loss function.

IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Hamburg A second definition: economic loss functions

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Ústí n. L. 1. maximum water demand is defined as the amount current users would require if water were priced at its current level and had unrestricted availability.

2. In any period in which water availability is less than the maximum demanded, economic losses represent the economic value or benefits that users would gain from additional water if availability were increased to the maximum quantity demanded.

3. Losses therefore reflect the value of the forgone water use or the scarcity costs of water. Conceptually are equal to the willingness to pay to have water supply increased to the demanded level.

IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Hamburg Risk concept – formal representation

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Ústí n. L.

LE ,dst )( ∑[]⋅= WLP ,, dstrr )( r n ∑ Pr = 1 r=1

P = occurance probability of water availability W E = expectation value of economic loss L

IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Hamburg Different water uses included in the model

Magdeburg Water user type Demand Public / Main short term effect of Method for sites in private reduced water availability parameterisation of loss

model good function Dresden

Off‐stream, consumptive uses Ústí n. L. Thermal power plants 17 private Reduced electricity Change in net rents generation Municipal water supply utilities 57 private Substitution Change in net rents Industry 47 private Reduction of production Change in net rents capacity Pond fisheries 62 private Reduced pond area and Change in net rents yield Irrigation for agriculture 91 private Reduced crop yield Change in net rents Sub irrigation of wetland sites: 35 - agricultural production private Reduced crop yield Change in net rents - habitat conservation public Reduction of area with high stated preferences / water levels benefit transfer - greenhouse gas emissions public Increase in GHG emission Shadow price of carbon from peat oxidation In‐stream, non consumptive uses Hydropower 53 private Reduced electricity Change in net rents generation Recreational boating of minor 36 public Reduced locking frequency stated preferences / waterways with increased waiting time choice model

Transportation by ship on 12 private Reduced effective carrying Change in transport inland waterways (transport capacity of ships costs relations) IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Hamburg Some data requirement for parametrisation

Magdeburg Water use Variable Unit Market price of base load electricity. €kWh‐1 Dresden

Renewable energy price for base load Ústí n. L. Thermal power plants, Hydropower €kWh‐1 electricity

Saved variable costs * €kWh‐1 €employee‐ Gross revenue * Industry 1 Share of variable costs of gross revenue* [‐] Additional variable costs for substituting Water utilities €m‐³ surface water

Produce price fish €kg‐1 Pond fishery Saved variable costs €ha‐1 Produce price irrigated crop (potatoes) €dt‐1 Irrigation Saved variable costs harvest €dt‐1 Saved variable costs irrigation €m‐³ Produce price for substitute: biomass energy €dt FM‐1 maize ‐1 Wetlands Saved variable costs harvest €dt DM Shadow price of carbon €tCO2‐1 Willingness to pay for habitat conservation €ha‐1 a‐1 ‐1 Shipping Variable vessel operating costs* €h Recreational boating Willingness to pay to avoid waiting time €boat‐1 h‐1

IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Hamburg Two applications of the risk indicator

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Ústí n. L.

1. Assessment of climate change impacts: => change in risk over time as an economic indicator

2. Cost-benefit analysis of adapation options: => reduction of risk = benefit of adaptation option

IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Hamburg

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Ústí n. L. 3 / Results – climate change risk assessment for two baseline scenarios

IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Hamburg Aggregate change in water demand 2010 - 2050

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IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Hamburg Example: fen wetlands – multifunctional water uses

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IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Hamburg Risk across individual users and time

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IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Hamburg Spatial distribution of water demand and risk

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IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Hamburg Change in risk 2010 - 2050

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Ústí n. L. 4 / Results – Cost-benefit analysis of adaptation options

IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Water management in a regulated river and wetlandHamburg

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Elbe Main River

Grossmann & Dietrich 2010

IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Hamburg Cost benefit analysis

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Dresden L Ústí n. L.

IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Hamburg

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Ústí n. L. 5 / Conclusions

IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann 4 / Conclusions: implications for water resources mgmt.Hamburg

Magdeburg a. long-term planning can no longer be based on static assumptions regarding climatic conditions and resultant water availability. Dresden Ústí n. L. b. findings reflect the water allocation rules and minimum flow requirements that constitute the water resources management baseline. The results therefore indicate localities where these kind of restraints need to be investigated in more detail in order to identify measures to climate proof the long term water resource allocation plans. c. Water scarcity related risks are highest for those water uses that are either affected by an increasing water demand induced by increased evapo-transpiration demands (irrigation, wetland landscapes) or that are directly susceptible to variations in in-stream flows (hydropower, shipping). d. Climate risks for industrial, thermal power generation and municipal uses are mitigated by reduction in demand associated with the projected population, economic and technological developments. e. Substantial economic value is associated with public good benefits from recreation or wetland ecosystem services that should not be left out of the assessment of water management options.

IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann 4 / Conclusions: methods Hamburg

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a. Novel approach now available for water resources planning in a centralDresden Ústí n. L. European context b. Analysing water scarcity in terms of economic risk has the advantage that a single, monetary criterion can be used to compare losses and benefits effects across a wide range of water uses. c. Models are unlikely to be able to represent the full range of coping options and so might be pessimistic in many regards. d. The methodology presented here has primarily been designed for the comparative assessment of water management options in a cost benefit analytical framework e. The challenge is to adequately capture the whole range of possible adaptation options such as improvements in infrastructure operation, demand management or changes in water allocation mechanisms

IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Hamburg Paper

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Economic risks associated with low flows in the Ústí n. L. Elbe River Basin (Germany): an integrated economic-hydrologic approach to assess vulnerability to climate change

Malte Grossmann1, Koch2, Nele Lienhoop3, Stefan Vögele4, Konar Mutafoglu1, Jacob Möhring1, Ottfried Dietrich5, Michael Kaltofen6

1 Technische Universität Berlin, Institut für Landschafts‐ und Umweltplanung, EB 4‐2, Straße des 17 Juni 145, D‐10623 Berlin. 2 Brandenburgische Technische Universität (BTU). 3 Helmholtz Zentrum für Umweltforschung (UFZ), Department für Ökonomie, 4 Forschungszentrum Jülich, Institut für Energieforschung ‐ Systemforschung und Technologische Entwicklung (IEF‐STE), Jülich 5 Leibniz‐Zentrum für Agrarlandschaftsforschung, Institut für Landschaftswasserhaushalt, Müncheberg. 6 DHI‐WASY GmbH, Berlin

IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann Hamburg

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Thank you for your attention!

IWRM Conference 12.-13. Oct. 2011 Dresden Grossmann