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Pricing water to respond to climate change in Amman, Jordan

Pricing water to respond to climate change in Amman, Jordan. David E. Rosenberg david.rosenberg@usu.edu http://www.engr.usu.edu/cee/faculty/derosenberg/ AWRA Specialty Conference Anchorage, Alaska May 4 – 6, 2009. Outline. Jordan’s water Climate change impacts Deductive model

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Pricing water to respond to climate change in Amman, Jordan

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  1. Pricing water to respond to climate change in Amman, Jordan David E. Rosenberg david.rosenberg@usu.edu http://www.engr.usu.edu/cee/faculty/derosenberg/ AWRA Specialty Conference Anchorage, Alaska May 4 – 6, 2009

  2. Outline • Jordan’s water • Climate change impacts • Deductive model • Rates and prices simulated • Results & limitations • Conclusions Top: Tanker truck refilling rooftop tank Middle: New diversion works near the Dead Sea Bottom: Leaky distribution pipe

  3. 100 mm/yr 500 900 0 50 100 km Irbid Zarka Amman Israel / Palestine Jordan Ma’an IRAN PAL. Aqaba EGYPT SAUDI ARABIA Red Sea Jordan Water Overview • 5+ mill. people • 1,000 Mm3/yr consumption • 850 Mm3/yr supplies • Severe groundwater overdraft

  4. Amman, Jordan

  5. Amman water system • 2.2+ million residents • 360,000+ connections • 133 Mcm/yr supply • 2,700 km2 service area • 5,100 km of mains • 1,700+ employees • Significant leakage • Rationing • Rapid population growth Right: Component analysis for 2005

  6. Climate Change Impacts • Increased temperatures (0 to 4 oC) • Reduced precipitation (0 to 20%) • Reduced runoff (12 to 70%) • Unknown impacts on groundwater • Jordan just starting to address Right: Drying mudflat at Burqa, eastern Jordan

  7. Deductive Modeling Approach • Identify available options • Characterize each option • Describe interdependencies • Quantify shortage events • Optimize • Stochastic programming with recourse • Monte Carlo simulations • Simulate different rate structures & price schedules

  8. Identified 39 potential actions

  9. Characterize action costs and effectiveness Above: Drip irrigation store

  10. = Decision = State where stochastic information acquired 1st Stage 2nd Stage Event Stochastic optimization with recourse • Objective: Minimize expected annual costs • 1st stage decisions: Long-term actions (Li) • Stochastic events:Public water availability (e) • 2nd stage decisions: Short-term actions (Sje) • Subject to: • Mass balance; Storage capacity; Rate structure • Upper limits on actions • Interdependencies • Meet water requirements in each event • Monte-Carlo samples: parameter variability among households

  11. Calibrate to household piped water use • 500 Monte-Carlo simulated households • Adjust occupancy parameter (vacant residences) • K-S test significant at 98%

  12. Demand response before and after household conservation Note: η = -0.187 ± 0.053 [α = 1%; 10,564 HH; Salman et. al (2008)]

  13. Willingness-to-pay to avoid network rationing

  14. Rate Structures Simulated • Uniform • Increasing block rates • IRB-shrinking block width • Declining block rates • Flat / Uniform • Linear (quadratic charge) • Historical (mixed flat, IBR, quadratic) • 59 price schedules

  15. Demand response under alternative rate structures and price schedules 60% SW reduction Existing availability 40% SW reduction

  16. Distributions of use among customers

  17. Distributions of use among customers

  18. Cost Recovery among Rate Structures

  19. Limitations • Initial estimates set upper bounds on water use • Risk neutral decision criteria • Perfect price information • Rising temperatures and reduced precipitation do not otherwise influence residential demand • Commensurate reductions in use by other classes Above: “Biader Water” sells RO filtered water in 20-liter jugs

  20. Conclusions • At low prices, neither prices nor rate structure type significantly influence use • IBRs and linear price structures most promising at higher prices Still must double or triple prices! Fairness and equity associated with rate structure choice Need pricing and leak reduction, conservation, plus other actions Above: Store selling rooftop water tanks

  21. Further Information • Rosenberg et al (2007) Water Resources Research. “Modeling integrated water user decisions in intermittent supply systems.” • Rosenberg (2007) ASCE-JWRPM. “Probabilistic estimation of water conservation effectiveness.” • Rosenberg et al (2008) Water International. “Intermittent water supplies: challenges and opportunities for residential water users in Jordan.” • Rosenberg (submitted) ASCE-JWRPM. Residential water demand under alternative rate structures: a simulation approach

  22. ?? Questions ?? David E. Rosenberg david.rosenberg@usu.edu http://www.engr.usu.edu/cee/faculty/derosenberg/ Left: Wadi Musa wastewater treatment plant (near Petra)

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