Water, sustainability and climate for south Florida 5 million, 5 yr project beginning in 2013 Almost every major University in Florida represented as well as other institutions Multi-disciplinary (ecology, biogeochemistry, economics, engineering, climatology, behavioral science) Expect to train ~ 4 undergrad, 11 grad, and 4 post-docs Our overall goal is to initiate a new process for managing water resources in south Florida utilizing hydro-economic optimization modeling that enables explicit representations of these trade-offs along socio-economic and ecological dimensions. Presented at the LTER All Scientists Meeting, Miami, March 11, 2013 1

Objectives Develop a hydro-economic optimization model for south Florida Link value of ES to EF and incorporate results into optimization model Investigate socio-ecological trade-offs of management schemes needed to increase the resilience of water resources under different scenarios of climate, SLR, LULC, and population change Utilize stakeholder participation to improve understanding of cognitive and perceptual biases in risk assessment and decision-making Develop recommendations for adaptive water management plans which foster sustained public support in south Florida From the proposal

General Approach Regional economic valuation of urban, agricultural, ecosystem, and industrial water use Economic valuation of ecosystem services (expanded from WSC Category 1) Surveys of stakeholder risk perception and preferences Integrating stakeholder preferences into scenario-driven, regional hydro-economic optimization Decision-modeling of group interactions in experimental tradeoff negotiations

General Approach

Similar efforts at this scale CALVIN is a regional hydro-economic model developed for the central valley probably about 10 years ago They are addressing the types of questions we ultimately seek to address in the Florida model What’s similar? Water sources are temporally offset from demands. Most of CA water comes from snow and rain in northern winter while most of their demand comes during the dry summer in the south Florida and California both sort of have more water than we can handle at certain times of the year and not enough at other times. What’s different about the WSC project? Unlike the central valley, we have to deal with salt water intrusion into our drinking water. During our rainy season we have to deal with flooding issues We also have a big battle with water quality and a larger proportion of our land is wetlands As a result of these factors and the other factors that are unique to south Florida we can expect our hydro-economic optimization schemes will be very different from the central valley There are several other unique things about our project that differentiate us from the CALVIN project One is that we intend to include the value of ecological services in our optimization from the beginning We are including flood control constraints in our optimization schemes And we are devoting a lot of effort to behavioral decision analyses and applying this to our conflict resolution efforts

Hydro-economic modeling Linked-node optimization model Optimization according to ecol & econ benefit/cost functions and decision criteria, such as “expected value” or “expected regret” Initial focus on regional level trade-offs under different optimization schemes and current infrastructure Long term robustness of optimization schemes to be tested under different scenarios using a decision-tree approach We are not building a "planning" model for agency use, but instead are interested more in developing a process by which water resources are modeled and managed with stakeholder input in south Florida. This process is cognizant of the need to address competing interests in a sustainable way (i.e. hydro-economic trade-offs), a changing climate, and the value of ecosystem services. This process will also uniquely utilize, in a structured and deliberate way, both stakeholder perceptions of risk as well as their preferred means of risk aversion in the optimization modeling. The unregulated flows represented by the dashed lines represent “within” basin components of the hydrologic cycle that impact the overall water balance and which in turn influence the systems ability to meet particular water demands. These flows are typically parameterized with something like “rainfall-runoff” relationships or derived from simulation modeling. In the proposal we stated that we would use the model to investigate tradeoffs, and the tradeoffs that we decide to address may determine to a large degree the detail that we choose to build into the model. Some examples of these tradeoffs are things like allowing high water in lake okeechobee and essentially using it more like a reservoir versus maintaining lower water levels for the benefit of the lake littoral zone and the bass fishery. Another tradeoff might be the choice between delivering water of good quality to the Everglades versus more water of lower quality, a third might be the choice between delivering water to the natural areas versus to the urban area, and a fourth might be the tradeoff between maintaining freshwater in the coastal canals to fight salt water intrusion versus the increased flood risk to low lying properties around the canals. We have proposed to structure the modeling and our stakeholder interactions around a few major tradeoffs facing the region just like these. But how easy it will be to represent these tradeoffs in a hydro-economic optimization scheme while preserving an acceptable level of realism is another matter. It may make sense to start with coarse model for first round of analyses and work in more detail as needed and as the ecological and economic analyses mature to the point where we can realistically look into more detail. w/o changing infrastructure what make us most robust wrt climate, SLR, pos, land use change? Sustainable requires multiple potential futures; need to be able to adapt.

Hydro-economic modeling Linked-node optimization model Nodes will represent macro-scale properties of the SoFl system For each node: flow-response function(s)-- costs or penalty for missing certain that include a target water allocation target Cost functions: both ecological and economic parameters (e.g. ecological costs associated with low flows; economic costs associated with exceeding flood risks) Value of ecosystem services to be included in optimization targets

Penalty Function: Everglades Watkins, D., Kirby, K., and Punnett, R. (2004). ”Water for the Everglades: Application of the South Florida Systems Analysis Model.” J. Water Resour. Plann. Manage., 130(5), 359–366. doi: 10.1061/(ASCE)0733-9496(2004)130:5(359) Water supply to the Everglades “Penalties” are in arbitrary units here but can be directly related to some aspect of ecosystem functions (e.g. peat accretion), $ value of ecosystem services, or other metric Function for Everglades in this earlier representation shows steep “penalties” for not meeting flow target of ~ 200 KAF/Mo, but exceeding this optimum is less damaging. We’ll need to something similar for the built areas but in that case, the cost functions will be formulated in economic terms. In other words, what are the economic costs of not meeting agricultural water demands? And what are the costs associated with optimizing the system to maintain a certain level of flood protection in the urban areas?

Penalty Function: Water Supply Watkins, D., Kirby, K., and Punnett, R. (2004). ”Water for the Everglades: Application of the South Florida Systems Analysis Model.” J. Water Resour. Plann. Manage., 130(5), 359–366. doi: 10.1061/(ASCE)0733-9496(2004)130:5(359) Example of urban cost or penalty function Water supply to coastal canals “Penalties” are in arbitrary units here but can be related to $ or other metric No penalties with meeting target of 10 KAF/Mo Piece-wise linear increase in penalties with more or less water relative to target due to salt water intrustion (not enough water) or increased flood risks (too much water)

Scenario generation Resilience of regional water supply optimization schemes will be tested under different scenarios of climate, land use change, population growth (water demands), SLR, and economic setting Initial effort will be based on integrating existing scenario information (e.g. MIT LULC scenarios, SFWMD, Weisskoff 2011) Later work will utilize new IPCC climate forecasts and stakeholder-driven preferences for adaptive responses to climate-related stressors We want to test the robustness of our decision criteria for meeting targets around the system given a certain level of climate variability and, ultimately under different scenarios of sea level rise, climate change, population growth etc. How does the trade-off space change under these different scenario? What criteria for optimizing water deliveries throughout the system are sustainable under these scenarios? What we have to work with includes the these types of land cover land use change scenarios that Mike Flaxman (GeoDesign) has put together. These GIS based maps represent potential land use and land cover under differing assumptions along 4 primary dimensions of Population growth, Climate change, planning assumptions, and financial resources. These types of scenarios will be used to help calculate water demands and overall hydrologic conditions needed for the optimization modeling. We also have climate model scenarios that we’ll be applying in the modeling. We will likely start with some climate scenario products for SoFL that are already available. Later, we’ll utilize downscaling of the new IPCC simulations using a technique developed by Mike Mann. We need to find a way to make these climate change scenarios consistent with our scenarios of sea level rise. This will be something that develops probably over the course of a year or two. We’re also going to include scenarios of population growth and water demand, and we’ll rely on Rich Weisskoff to generate these as a follow up and re-analysis of some of the modeling that formed the basis of some of his previous publications. Rich has also looked into projections of economic growth in south Florida, so we’ll want to utlize that information as much as possible. Ultimately, once we decide on a set of scenarios we’ll want to use these to test the implications and robustness of various water management optimization schemes whose criteria are derived from what comes out of the stake-holder driven behavioral decision analyses (later slide). We may at some point decide we want to use output from the optimization modeling in order to generate new scenarios. These new scenarios would be based on what we learn about stakeholder preferences for the future and based on what is possible under certain optimization schemes. Importantly, the shape of the flow response functions may vary with these scenarios if the factors other than flow that affect the flow response also change. Geodesign Inc.

Behavioral decision analyses Hypothesis: Information type and format influences risk perception and preferences for future management options and adaptive responses to climate change Complex geo-visualization of scenario outcomes will be used in stakeholder risk assessment So a little more detail here on the types of questions and activities this group will be engaging in In the proposal we suggest that we use complex geovisualizations like this one generated by Mike Flaxman’s group that represent some of the possible scenarios for SoFlo in terms of things like the expected changes in certain aspects of the built and natural system caused by sea level rise or perhaps some other aspect of water management and use these visualizations to get a better idea of the general public’s and more involved stakeholders perceptions of risk, and their preferences for risk aversion As part of this we’re going to add information about the economic dimensions associated with each scenario and compare stakeholder preferences when faced with different types of impact metrics. Some of this information can be used to formulate targets in a way that is most appealing to stakeholders. How do economic dimensions of trade-offs influence stakeholder preferences?

Ecosystem Valuation Work for the Project Based on Flow-Responses Rates Assess values of changes in ES, such as fish and carbon Work closely with fish and carbon groups Provide ES valuation parameters to modeling group

Ecosystem Valuation Group of the Project Will draw from previous valuation studies: our own, MARES, Everglades Foundation-support ed studies See next slides on carbon and fishery valuation studies

Selection of Carbon Prices based on Valuation Methodologies Meenakshi Jerath, Mahadev Bhat, Victor Rivera-Monroy, Edward Castañeda,-Moya, Marc Simard, and Robert Twilley., 2013. An Economic Valuation of Carbon Sequestration in the Mangroves Forests of the Florida Everglades.” Ecological Economics (under preparation)

Economic Value of Carbon in the ENP Mangroves ($/ha) Valuation Methodology Source Cost of Carbon ($/tC) U.S. 2010 dollars Value of ENP Mangroves ($/ha) Market Price RGGI, 2010 7 50,008 Social Cost of Carbon U.S. Government Interagency Report, 2010 86 614,384

Example study: the value of recreational benefits of Improved coral reef protection Contingent Behavior Modeling Florida Keys study (Bhat, 2003) T1

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