Multi-scale water management and modeling for Jordan David

Multi-scale water management and modeling for Jordan David E. Rosenberg Utah State University david. rosenberg@usu. edu CEE Seminar at Stanford University May 19, 2008

Acknowledgements In Jordan • Samer Talozi, Jordan Univ. of Science and Technology • Hani Abu Qdais, German-Jordan University • Rania Abdul-Khaleq, MWI • Suzan Taha, MWI • Khair Khadidi, MWI • Chris Decker, LEMA • Roger Griffin, LEMA • 14 water managers • Tarek Tarawneh, Id. RC • Hazim El-Nasser, OSD • Ya’koob Al-Qaisia, Sanitary Ware & Pipes • • • 36 families 40 water tradesmen Mona Grieser, AED Anwar El-Halah, RSCN Dawoud Al-Said, ARD In the U. S. • U. S. National Science Foundation • Frank Fisher, MIT • Annette Huber-Lee, IFPRI • Jay Lund, U. C. Davis • Richard Howitt, U. C. Davis • Mimi Jenkins, U. C. Davis 2

Outline • Systems modeling • Jordan’s water problems • Modeling with uncertainty – Households – Water utility (Amman) – National (Jordan) • Contributions Top: Tanker truck refilling rooftop tank Middle: New diversion works near the Dead Sea Bottom: Drying mudflat at Burqa, eastern Jordan 3

Systems Modeling Themes • Infrastructure at multiple scales • Integrating diverse options • Long- vs. short-term actions • Multiple water qualities • Uncertainties • Mix engineering, economics, and operations research Background: Bathroom with bathtub, floor drain, squat toilet, squeegee, faucet, and bucket for flushing 4

Integrated Modeling Approach Household Water Utility (City) Region (Nation) At each scale: 1. Identify available options 2. Characterize each option 3. Describe interdependencies 4. 5. Quantify shortage events Optimize – 6. Stochastic programming with recourse Reapply at larger scales 5

Jordan Water Overview 100 mm/yr 0 500 900 50 100 km Irbid Zarka Amman • 5+ mill. people Israel / Palestine • 1, 000 Mm 3/yr consumption Jordan • 850 Mm 3/yr supplies Ma’an IRAN PAL. Aqaba EGYPT SAUDI ARABIA Red Sea • Severe groundwater overdraft 6

Key problems • Insufficient supplies • Leaky distribution systems • Water safety concerns • Little water conservation experience • Rapid population growth Top: “Biader Water” sells RO filtered water in 20 -liter jugs Left: Leaky irrigation system pipe 7

Modeling & Management for Households 8

Identified 39 potential actions 9

Characterize action costs and effectiveness Above: Drip irrigation store 10

Stochastic optimization with recourse • Objective: Minimize expected annual costs • 1 st stage decisions: Long-term actions (Li) • Stochastic events: Public water availability (e) • 2 nd stage decisions: Short-term actions (Sje) • Subject to: – Mass balance; Storage capacity; Block pricing – Upper limits on actions – Interdependencies – Meet water requirements in each event • Monte-Carlo samples: parameter variability among households 1 st Event 2 nd Stage = Decision = State where stochastic information acquired 11

Calibrate to household piped water use • 500 Monte-Carlo simulated households • Adjust occupancy parameter (vacant residences) 12

Distributions of water savings for conservation actions in Amman (error bars represent 10 th and 90 th percentiles) 13

Demand response before and after household conservation 14

Willingness-to-pay to avoid network rationing 15

Household-level contributions 1. Modeling integrates source, availability, quality, storage, costs, conservation, and user behaviors. 2. Empirically estimates water use in Amman, Jordan. 3. Simultaneous output of: § Conservation technology adoption § Water use response § Household willingness-to-pay 4. Target conservation to select customers. Above: Store selling rooftop water tanks 16

Modeling and Management for Amman, Jordan

Amman water system • • 2. 2+ million residents 360, 000+ connections 133 Mcm/yr supply 2, 700 km 2 service area 5, 100 km of mains 1, 700+ employees Government owned Contract operator Right: Component analysis for 2005 18

23 potential city-level actions

Data collection • Meetings with 20 managers – – – Ministry of Water and Irrigation (MWI) Water Authority of Jordan (WAJ) Jordan Valley Authority (JVA) Amman contract operator (LEMA) U. S. Agency for International Development (USAID) Private consultants • Notes, e-files, paper and web reports • Prior household results Top: MWI offices in Amman Right: WAJ report on wastewater treatment operations in 2004 Left: Water-meter manifold for an apartment building 20

Including city-level uncertainties • Stochastic water shortages – Future demands (5 experts) – Surface water availability (65 years of runoff) Expected shortage events in 2020 – Groundwater (fixed) • Uncertain parameters – Average parameter values – Parameter value scenarios (“Robust”) – Best and worst cases (“B/W”) – Interacting best and worst cases (“Grey-number”) 21

Implementation levels and costs for 2020

Shortterm actions B = Buy agricultural water C = Cloud seeding RT = Rent tanker trucks D = Disconnect illegal connections RL = Reduce leak fix time RO = Restrict outdoor water use R 1 = Normal rationing R 2 = Severe rationing 23

City-scale study contributions Methodological • Modeling integrates multiple supply and conservation options with explicit uncertainties. • Consistent results with different approaches to handle parameter uncertainties. Project-specific • Conservation plays growing role over time. • Delayed need for mega-supply projects like pumping the Disi Aquifer. Red-Dead Canal not needed. 24

Modeling and Management for all of Jordan Background: Agricultural production near the Dead Sea

Potential national actions • Supplies – – Wastewater reuse – Source use – Inter-district transfers – Sector reallocations – • Seawater desalination Infrastructure expansions Conservation – Limit import of waterwasting appliances – Middle: King Abdullah Canal Leak reduction – Top: Alternatives to bananas? Targeted retrofits with water -efficient appliances Bottom: Zara-Ma’een pipes near the Dead Sea 26

National-level model • Middle East Water Project (MIT Water Allocation System) – Urban, Industrial, and Agricultural demands in 12 governorates – Single-year, deterministic optimization – Maximize net benefits Price – Mass balance, environmental, pricing, wastewater reuse, and social policy constraints Demand Curve Net benefit Quantity Cost Curve (Adapted from Fisher et al. , 2005) 27

National-level model extensions Water use efficiency (non-price demand shift) • Variable water availability • Infrastructure expansions and conservation program developments Price • p*st p*lt Original Shifted Demand Curve Cost Savings q*lt q*st Quantity 28

New national level decision support system Inputs Outputs • Regional layout • Net benefits • Demands • Prices paid • Supplies • Quantities used • Shared Resources • Shadow value of constrained infrastructure • Benefits of cooperation • Infrastructure • Policies User Interface (Visual Basic) Database Optimization Graphical (MS Engine Results Access) (GAMS) Display 29

Shadow values in districts Water conservation No conservation 30

Overall net benefits for 2020 31

Nationwide contributions Methodological • Include conservation decisions in hydro-economic model • Infrastructure expansions with variable water availability Project-specific • Conservation generates regional economic benefits • Infrastructure expansions, leak reduction, and conservation forestall desalination • Disi carrier should include branch to Karak 32

Overall Conclusions • Modeling can integrate source, reliability, conservation, quality, costs, and explicit uncertainties. • Empirically estimate water use in Amman, Jordan. • Multiple scales to improve water availability and management. • Urban water conservation is very promising. • Target conservation to customers who will save the most water and money. • Improving availability will require significant investments. 33

Publications • Rosenberg, Howitt, and Lund (in press) Water Resources Research. Water management with water conservation, infrastructure expansions, and source variability in Jordan. ” • Rosenberg (in press) Water Policy. “Integrated water resources management and modeling at multiple spatial scales in Jordan. ” • Rosenberg and Lund (in press) Water Resources Management. Modeling integrated decisions for a municipal water system with recourse and uncertainties. ” • Rosenberg et al (in press) Water International. “Intermittent water supplies: challenges and opportunities for residential water users in Jordan. ” • 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. ” 34

Questions? ? • David E. Rosenberg • david. rosenberg@usu. edu 35

Complementary scales for action 36