Managing coupled naturalhuman. changing climate

Transcription

1 Managing coupled naturalhuman systems under a changing climate Y. C. Ethan Yang, Ph.D., GISP March 8, Joint Global Change Research Institute/ Pacific Northwest National Laboratory

2 Background Dynamics of Coupled Natural and Human Systems ~The Dynamics of Coupled Natural and Human Systems (CNH) Program promotes interdisciplinary analyses of relevant human and natural system processes and complex interactions among human and natural systems at diverse scales~ watershed nature water human 2/46

3 Outline Systematized watershed modeling watershed water nature human Groundwater economics modeling Stream temperature modeling 3/46

4 Systematized Watershed Modeling Systematized watershed modeling watershed water nature human Groundwater economics modeling Stream temperature modeling 4/46

5 Systematized Watershed Modeling Water allocation studies Climate change studies Top-down Bottom-up Centralized GCM-origin optimization approach Decentralized Decision scaling optimization approach This talk will focus more on the Bottom-up approach because we want to inform decision making 5/46

6 Systematized Watershed Modeling Bottom-up Water allocation studies Format the management question into Agentbased modeling (ABM) structure Solve the ABM formatted question with decentralized optimization method 6/46

7 Systematized Watershed Modeling The theory of ABM has emerged from computer science: distributed artificial intelligence (Sycara, 1998) An agent is an object that Driven by their own utility function interacts with others and the environment the interactions are characterized by behavioral rules 7/46

8 Systematized Watershed Modeling Agent-Based Modeling Question Information exchange Top-Down Everyone knows everything Bottom-up Everyone only knows things that matter Agent interactions Not easy to trace Traced naturally Policy implementation Computation Everyone will follow orders curse of dimensionality Everyone act based on their interests Usually easier to solve 8/46

9 Systematized Watershed Modeling Typical mathematical format for the optimization problem of i th agent: max x i f i subject ( x i to ) g i ( x i x j i ) g Transfer the problem into Penalty-based format gi g l i ( x ( x i i x ) j i ) 0 0 local constraint interconnecting constraint x ) max{f ( x, } x i i i i j i max{ x i i f i ( x i ) e i k 1 max(0, g i ( x i x j i ) } Local interest factor 9/46

10 Systematized Watershed Modeling 10/46

11 Systematized Watershed Modeling Yellow River case study Background Multiple stakeholders and multiple purposes Water use conflicts between human and ecosystem; between upstream and downstream Existing institution Yellow River Conservancy Commission (YRCC) Unified Water Flow Regulation (UWFR) 11/46

12 Systematized Watershed Modeling water use agents 5 reservoir agents 3 ecosystem agents R R 1 12 R R R E E 2 52 E 3 37 A i A i R i Water use agents Water use agents with source flow Reservoir agents Mainstream inflow source Tributary inflow source Mainstream E i Ecosystem agents Tributary 12/46

13 Systematized Watershed Modeling Market based scenario Based on the free market concept, water use agents pursue maximal marginal benefit Change β i to local water price p i (p i =1/ β i ) A water trading mechanism is used to deal with the violation, i.e., agents are allowed to buy or sell water 13/46

14 Systematized Watershed Modeling Local water price in low flow and high flow season Higher average water price Lower average water price 14/46

15 Water Con. GDP. Systematized Watershed Modeling System water consumption and GDP Bottom-up Top-down Price UWFR Price Bottom-up Top-down UWFR Month Top-down billion m 3 Bottom-up billion m Month Top-down billion RMB Bottom-up billion RMB 15/46

16 Systematized Watershed Modeling Bottom-up Climate change studies US Climate Change Science Program (2009):..there are limits to the applicability and usefulness of classic decision analysis to climate-related problems. Bottom-up assessment focusing on the decision information needs Using GCM climate projections at the end of the process Making decisions with the understanding of uncertainty 16/46

17 Systematized Watershed Modeling Climate change impact assessment GCM level Modeling level Stakeholder level Top-Down Downscaling from multiple model projections Compute system responses based on multiple GCM projection Be informed by boxed range of possibility Bottom-up Estimate likelihood of climate states; incorporate GCMbased projections Generate wider range of plausible climate; simulate system performance Identify stakeholder concerns; be informed by wider climate range with uncertainty 17/46

18 Systematized Watershed Modeling Climate Risks on Water and Agriculture in the Indus Basin of Pakistan Winston Yu, Yi-Chen E. Yang, Andre Savitsky, Donald Alford, Casey Brown, James Wescoat, Dario Debowicz and Sherman Robinson The World Bank, South Asia Region 18/46

19 Systematized Watershed Modeling Indus River Irrigation System Contribute 90% of Pakistan s Ag-GDP - 3 major reservoirs - 19 barrages - 12 inter-river link canals - 43 major irrigation canal commands - Over 120,000 watercourses - Total length of the canals is about 60,000 km 19/46

20 Systematized Watershed Modeling Coupled modeling structure *Endowment *Productivity *Prices *Other data *Agronomic data *Economic data *Hydro-climatic inputs *Other data Hydroagronomic model Cropped area and Crop production at provincial level Economic model GDP, Ag-GDP and Household income *Net benefit *Power *Water uses *Other results *Production *Relative prices *Imports and exports 20/46

21 Changing temperature Systematized Watershed Modeling Climate stress test Adaptations e. g. GDP % change = -1% More efficient irrigation More storage Changing inflow (Precipitation & Temperature) New crops 21/46

22 % change Temperature increase Systematized Watershed Modeling 54 climate scenarios by changing temperature from 0 to 4.5 degree C and Inflow from 10% to 90% excee. Prob. GDP GDP % change No Investment CANEFF NEWDAM CYIELD 90% 80% 70% 60% 50% 40% 30% 20% Flow exceedance probability +0 10% Hotter Drier 22/46

23 Systematized Watershed Modeling GDP 23/46

24 Groundwater Economics Modeling Systematized watershed modeling watershed water nature human Groundwater economics modeling Stream temperature modeling 24/46

25 Groundwater Economics Modeling For some areas, the water resources management issue is focus on groundwater instead of surface water. Excessive groundwater pumping might results in cone of depression for the surrounding area exacerbates the critical pressure on streamflow depletion It is easier for the computational purpose and for the general public to understand if the damage can be presented in economic values. 25/46

26 Groundwater Economics Modeling Based on the economic concept, two different ways can be used to evaluate this question: from demand side and from supply side Water price Demand curve Benefit Production function D actual D max Water demand S actual S optimal Water supply 26/46

27 Groundwater Economics Modeling Case study for demand side - Top-down approach 27/46

28 Groundwater Economics Modeling Consider a drought condition that forces the countywide water demand can only be satisfied at 80% 28/46

29 Groundwater Economics Modeling Consider the trade-off between welfare loss and streamflow depletion for each municipality 29/46

30 Groundwater Economics Modeling Case study for supply side Top-down/Bottom-up approach Frenchman sub-watershed 30/46

31 Groundwater Economics Modeling Objective Function Bottom-up Decentralized Applied to Each farmer for Each Year Top-Down Centralized Applied to All farmers for All Time Maximize Individual farmer Profit Sum of farmers Profits Climate Conditions Average ( ) Average ( ) Planning Horizon 1 Year (repeated for 50 years) 50 Years Management Period 1 Year 10 Years Simulation Software MODFLOW-2005 MODFLOW-2005 Optimization Software MATLAB GWM-2005 V 1.3 Decision Variables 2 (2 per agent, 1 year, 1 agent per objective function) 500 (2 per agent, 5 decades, 50 agents per objective function) Constraint 1 Pumping Upper Bound (Q a,s ) Pumping Upper Bound (Q a,s ) Constraint 2 Water Use Cap Streamflow Lower Bound 31/46

32 Groundwater Economics Modeling OCM means the Topdown approach ABM means Bottomup approach with different regulation settings: cap or tax Different ways to view tax Farmer s cost or system s revenue 32/46

33 Groundwater Economics Modeling Results of different tax rate Tax collected Farmer s profit 33/46

34 Stream Temperature Modeling Systematized watershed modeling watershed water nature human Groundwater economics modeling Stream temperature modeling 34/46

35 Stream Temperature Modeling How will climate change impact the ecosystem in Taiwan? Formosa landlocked salmon (Oncorhynchus masou formosanus) is the salmonidae species that can be found in the lowest latitude It is a cold water species and can only survive in streams with water temperature below 17 degree C. The water temperature needs to be lower than 12 degree C during the spawning season 35/46

36 Stream Temperature Modeling 36/46

37 Stream Temperature Modeling A physically-based model was built to evaluate the water temperature of the existing and potential habitats for Formosa landlocked salmon under current and future climate conditions. Applying the principle of conservation of thermal energy to a one-dimensional vertically well-mixed open channel or stream, the conservative form of the transport equation is 37/46

38 Stream Temperature Modeling T 為河川斷面之平均水溫 is stream water temperature( ) w 為河道頂部寬度 is channel width(m) (m) u is stream velocity(m/s) HB is heat flex at river bed(j.m2/s) 為水流平均流速 (m/s) HB 為河床傳導熱 (J.m2/s) q is lateral flow(m2/s) p is wet perimeter(m) 為側向流補注流量 (m2/s) 為河道潤周長 (m) TL is water temp from q( ) A is cross section area(m2) TL D is 為側向流的水溫 dispersion ( ) 為河道斷面積 (m2) coeff.(m2/s) Cw is the specific heat of water(j/kg ) D HT 為沿水流方向之傳遞係數 is heat flex at water surface(j. (m2/s) Cw ρw 為水的比熱 is water density(kg/m3) (J/kg ) m2/s) HT 為水表之熱通量 (J.m2/s) ρw 為水的密度 (kg/m3) 38/46

39 H T H B ( I direct L d L u L T H E H H H fc ) H B 39/46

40 Stream Temperature Modeling 1996/01/ /08/04 40/46

41 Stream Temperature Modeling 41/46

42 Elevation(meter) Stream Temperature Modeling The change of suitable habitats: Temperature in July HADCM HADCM HADCM current below 17 above Distance from the junction(meter) 42/46

43 Managing coupled natural-human systems under a changing climate Surface water quantity watershed water nature human Groundwater quantity Surface water quality 43/46

44 Other research interests Ecohydrology Quantitatively connecting the aquatic ecosystem with hydrological statistics Uncertainty quantification Bayesian nonparametric approach GIScience Application bridge the gap between scientific result and general public 44/46

45 Acknowledgement Yellow River project Ximing Cai, Claudia Ringler, Jianshi Zhao Indus River project Casey Brown, Winston Yu, Dario Debowicz McHerny County project Yu-Feng Lin, Jun Wan Republican River project - Kevin Mulligan, David Ahlfeld Formosa landlocked Salmon project Ching-pin Tung, Tsung-Yu, Lee 45/46

46 Thank you for having me here! Y. C. Ethan Yang, Ph.D. GISP