Austin Becker NRS 509 Nov. 30, GIS and Coastal Planning for Sea-Level Rise Overview and Annotated Bibliography

Transcription

1 Austin Becker NRS 509 Nov. 30, 2005 GIS and Coastal Planning for Sea-Level Rise Overview and Annotated Bibliography All over the US, the demand for coastal land is increasing. The coastal areas of the US are growing in population faster than any other part of the country, stressing the natural resources of these areas with new development and additional use. Average increases of 3,600 people per day are forecast for coastal counties around the country (USCOP, 2004; Beach, 2002). History has shown that building along the coast is often a recipe for disaster. Numerous hurricanes, Katrina being the most recent, have devastated coastal communities only to have Federal programs spend billions of dollars to rebuild in the same vulnerable locations. Coastal storms have always threatened the world s coastlines, but now a new threat has emerged. Global warming (or climate change ) is contributing to an accelerated sea-level rise (SLR) and even, perhaps, fueling the number and intensity of coastal storms. Sea-level rise is caused by two major forces, both resulting from an increase in mean global temperature: melting of polar ice caps and thermal expansion. In addition, land subsidence further accelerates the process of gradual inundation. Although the reasons for the rise in temperature are not completely understood, it is widely believed by scientists that anthropogenic contributions in the form of CO2 emissions are significant. Estimates of global sea-level rise range from.5 meters/century to 6m/century (Nicholls et al., 2004), though most are in the neighborhood of.5 to 1 meter for the next 50 to 75 years. In an attempt to quantify the potential effects of sea-level rise, researchers have begun using Geographical Information Systems (GIS) models to look at various aspects of sea-level rise. Based on a survey of the research currently available, it seems that researchers have exposed only the tip of the iceberg when it comes to the potentials of GIS analysis and sea-level rise. Over the past decade, they have pursued two tracks simultaneously. First, they have attempted to model sea-level rise itself and how it could physically affect the land, based primarily on elevation and coastal processes models. Second, using this information, they have attempted to assess the impacts of SLR. Impacts may be broadly categorized as environmental, economic, and human-welfare related. None of these, of course, is mutually exclusive and each has a significant effect on the other two. Because of the ever-growing availability of data and the capabilities of GIS, modeling sea-level rise together with each of these three broad categories has become possible. For a simple example, by overlaying expected sea-level rise predictions onto an elevation dataset and a wetlands dataset, one can calculate the amount of potential wetland loss in a given area. Or, instead of wetland loss, one might calculate coastal land values that might be lost due to sea-level rise in order to forecast potential costs associated with property inundation. Similarly, a population density layer from the US Census Bureau might be used to calculate the direct impacts of SLR or a coastal storm on people living in coastal areas. Accurate analysis, of course, is quite a bit more complicated than these simple examples. As evidenced in the annotated bibliography provided at the end of this paper, researchers are using GIS to do extremely complex analysis in each of the three impacts categories. Recently, three studies have been conducted that assess the impact of SLR on Boston, New Jersey, and the New York Metro Region. The results are startling. The Boston study, undertaken by the EPA, forecasts a potential $94billion in damages from Austin Becker, NRS 509 Page 1 11/30/2005

2 coastal storms and SLR during the next century (Kirshen et al., 2004). In extreme cases, flood waters and storm surge could reach Harvard Square and portions of Back Bay! The New Jersey study (Oppenheimer et al., 2005) used Digital Elevation Models to assess the threat of sea level rise to New Jersey. It found New Jersey may shrink by as much as 3% by The New York study, conducted by Columbia University, found that areas at risk of severe flooding could embrace significant segments of lower Manhattan (MECA, 2000). Other studies have shown that sea level rise may inundate as much as 58,000 square kilometers of land along the Atlantic and Gulf coasts alone (Titus and Richman, 2000). Here in Rhode Island, coastal planners at the Coastal Resources Management Council are working to create a new model for the flood plain in the northern end of the Narragansett Bay. They have found that old 1939 flyover data, collected before much of the filling of Providence Harbor took place, may be driving incorrect analysis of Sea, Lake and Overland Hurricane (SLOSH) models and Federal Emergency Management Agency (FEMA) flood maps. To rectify this, they hope to have LIDAR flyovers of the area that will accurately depict elevation features so that proper surge and sea-level models can be created using GIS. These new models will be used to drive policy around building placement and construction requirements in the project area. New and greater building restrictions based on the paradigm of pre-disaster mitigation can be a hard nut to swallow for builders and developers wishing to carry out projects in the coastal zone. In addition, this information often indicates the need to invest significantly in better infrastructure. However, GIS makes it easier to communicate the real dangers of building in a flood plain or failing to properly plan. It gives a quick visual representation of possible inundation that even the lay-person can easily understand. By modeling economic, environmental, and human-welfare impacts of sealevel rise using GIS, the costs of neglecting pre-emptive action can be better quantified in any cost benefit analysis. The powerful visual representations that GIS allows may also go a long way toward convincing decision makers of the wisdom in investing now to save billions later. In the future, GIS may continue to make improvements in this arena. For example, individual property owners presented with a graphical display of their own property being inundated by a coastal storm or rising sea level might think twice about skimping on construction costs or not properly elevating their home. Although such graphics do already exist (see the Boston study below for example), they are still lacking in quality and take some imagination to interpret. It would make for interesting research to explore the true effects of GIS produced models on decisions of planners and individual property owners. We will, indeed, stay tuned as researchers explore the rest of the GIS and sea-level rise iceberg as they continue to melt away the tip! Sources cited, not included in annotated bibliography: Avril, Tom Princeton study puts up to 3% of N.J. under water by Philadelphia Inquirer, Nov. 16, Beach, D Coastal sprawl: The effects of urban design on aquatic ecosystems in the United States. Pew Ocean Commission, Arlington, VA. Darwin, Roy and R.S.J. Tol Estimates of the Economic Effects of Sea Level Rise. Environmental and Resource Ecnomics.19: Kirshen, Paul, R. Matthias, W. Anderson, T.R. Lakschmanan Infrastucture Systems, Services and Climate Change: Integrated Impacts and Response Strategies Austin Becker, NRS 509 Page 2 11/30/2005

3 for Boston Metropolitan Area or Climate s Long-term Impacts on Metro Boston (CLIMB). EPA Grant# R Metropolitan East Coast Assessment (MECA) Climate Change and a Global City: An Assessment of the Metropolitan East Coast Region. U.S. Global Change Research Program. Online at Accessed United States Commission on Ocean Policy (USCOP) Managing coasts and their watersheds. Ân Ocean Blueprint for the 21 st Century Final Report. Washington, DC. Online at Austin Becker, NRS 509 Page 3 11/30/2005

4 Annotated Bibliography Fish, Marianne R., I. M. Cote, J. A. Gill, A. P. Jones, S. Renshoff, and A. R. Watkinson Predicting the Impact of Sea-Level Rise on Caribbean Sea Turtle Nesting Habitat. Conservation Biology Vol. 19, No. 2. This study used GIS to model the impact of sea level rise on nesting habitats on the beaches of Bonaire, Netherlands Antilles. The consequences of a loss of beach habitat were deemed to be both economic, in the case of tourism and loss of buildings, and environmental, in that the beaches provide direct habitat to endangered species as well as serve as protection for adjacent lagoons and wetlands. Fish et al. used three different sea-level rise scenarios (0.2m, 0.5m, and 0.9m) and using ArcView v2.3 modeled each over the elevation data collected with a handheld GPS unit and manual surveying. They found that 14-53% of the beach area to be under threat of loss. Their study identified long term change, but perhaps more importantly offers baseline data that can be used to monitor change over time. Hennecke, Werner and P. Cowell GIS Modeling of Imapct of an Accelerated Rate of Sea-Level Rise on Coastal Inlets and Deeply Embayed Shorelines. Environmental Geosciences. Vol.7 No. 3. This study attempts to model Sea-Level Rise (SLR) as it might impact bays and inlets. They discuss the merits and shortcomings of the Bruun-GIS Model, Aggradation Model, and Flood-Tide Delta Model and how each model handles shoreline response, landside and bathymetric terrain, and shape of inlets. They were chosen due to their particular emphasis on sediment transport and its effect on shoreline change. Each seemed to be better for general analysis, rather than the analysis of single properties. This study emphasized the importance of modeling shoreline processes, as well as elevation, in order to get an accurate model of potential impacts. Hennecke, Werner, C. Greve, P. Cowell, and B. Thom GIS-Based Coastal Behavior Modeling and Simulation of Potential Land and Property Loss: Implications of Sea-Level Rise at Collaroy/Narrabeen Beach, Sydney (Australia). Coastal Management. 32: In this 2004 study, Hennecke et al. used GIS to consider sea-level rise, impacts of 50- year storms, and shoreline recession. They studied the economic effects these events might have on Cooaroy/Narrabeen Beach in Australia. This particular beach is highlycapitalized and built-up. Using GIS, they input hazard data (shoreline dune height, sealevel rise scenarios, etc) together with vulnerability (land values, consumer price index, etc.) in order to develop a risk assessment data overlay. They found that GIS was a quick and cost-effective means of developing these risk assessments. The results of their study on this particular beach show risk is higher in the case of short-term coastal storm events than for long-term sea level rise. Austin Becker, NRS 509 Page 4 11/30/2005

5 Nicholls, Robert, R. Tol, and N. Vafeidis Global Estimates of the Impact of a Collapse of the West Antarctic Ice Sheet. Work supported by the project Atlantic Sea Level Rise: Adaptation to Imaginable Worst Case Climate Change, supported by the European Union. This paper assesses the impact of a high impact, low probability event, such as the collapse of the West Antarctic Ice Sheet (WAIS), on coastal areas of Europe. Other authors have already assessed the impact of this type of event on sea level rise and place it in the 5 to 6 meter range due to displacement alone, not accounting for melting. Nicholls et al. Bring this work to the next step but modeling the global impact of a 5 meter sea level rise. They acknowledge that the likelihood of such an event is quite low, but approach the analysis more as an exercise in thinking through an extreme scenario. The authors collected a variety of datasets including: Gridded Population of the World, LandScan global population, SRTM Enhanced Global Map, Land-Ocean interactions in the Coastal Zone (LOICZ), Digital Chart of the World (DCW), and IMAGE datasets. These helped them model population, elevation, tidal range, boundaries, and land use. They then modeled using the Climate Framework for Uncertainty, Negotiation and Distrubtion (FUND) model. Not surprisingly, the results show that such a sea level rise would have profound effects on the world s coasts. Abandonment would be the only answer for large sections of coastline, though some 50% might be able to be protected at significant cost. Nicholls, Robert J Coastal flooding and wetland loss in the 21 st century: changes under the SRES climate and socio-economic scenarios. Global Environmental Change. 14: Nicholls 2003 study looks at the impact of coastal wetland loss and coastal flooding based on the four models of sea-level rise and global population developed by the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES). He set out to answer the basic question, are the global-mean sealevel rise scenarios a problem if we ignore them? In particular, he considers the impact of flooding (a human system impact) and the loss of coastal wetlands (an ecosystem impact). The study uses the four scenarios developed by the IPCC to assess the extent of flooding and wetland loss for each. The four scenarios present different global outcomes based on human behaviors. They consider the priority placed on the environment, the relative level of consumerism, and the development of clean and efficient technologies. Nicholls analyzed each scenario and assessed the risk and impacts of sea level rise on each of the four scenarios in order to demonstrate how human behavior may impact sea-level rise in the future. Simas, T., J.P. Nunes, J.G. Ferreira Effects of Global Climate Change on Coastal Salt Marshes. Ecological Modeling 139:1-15. This study offered a touch of good news to a fairly dismal general forecast of the effects of SLR. Simas et al. modeled SLR on salt marsh areas in the Tagus estuary (Portugal). Austin Becker, NRS 509 Page 5 11/30/2005

6 They found that salt marshes of mesotidal estuaries such as these are only susceptible to worst-case scenario SLR because small increases in sea level cause greater mineral deposition, which compensates for the newly inundated salt marsh. The authors used a combination of a model that described the ecological processes, remote sensing, and finally GIS to model and give spatial dimension to various sea-level rise scenarios. Though good news, in the sense that this particular estuary would not be highly vulnerable, other salt marshes that are bordered by more hardened edges or development may not be able to produce the upland sediment and deposition to make up for inundation. Titus, James and C. Richman Maps of Lands Vulnerable to Sea Level Rise: Modeled Elevations along the U.S. Atlantic and Gulf Coasts. Climate Research. 18:3. This article is the result of the author s attempts to develop more accurate maps for coastal areas subject to inundation. They discuss the shortcomings of the various studies done before theirs. Most of these simply lacked higher resolution data. But, other problems were encountered with inconsistent benchmarks, which made determining a base elevation difficult. This problem is resolved with maps that use the North American Vertical Datum of 1988 (NAVD). Titus and Richman s study relied on one degree Digital Elevation Models and data developed for the National Wetland Inventory. They also are working on another set of maps that use the 7.5 minute DEM s for a set of maps with even greater resolution. Unlike some of the other studies included here, this one is focused on modeling sea-level rise itself, rather than the impacts it will have on the environment, the economy, or human welfare. However, using a study like this one as a base, other research that does attempt to quantify these impacts can be presumed more accurate in its results. Zeng, Thomas Q., Q. Zhou, P. Cowell, and H. Huang Coastal GIS: Functionality Versus Application. Journal of Geospatial Engineering. 3:2. This paper identifies three reasons that the development of GIS is relatively slow: 1) the complexity of coastal/marine systems in the 3D environment; 2) lack of data; and 3) lack of communication between coastal experts and GIS professionals. Coastal GIS applications are quantified as coastal mapping, environment monitoring, coastal processes modeling, navigation and port facilities management, coastal environment/hazard assessment, coastal management/strategic planning, and coastal ecological modeling. To this list, I would add disaster management and preparation, as we have seen in a number of cases that GIS is an important tool. Zen et al. offer a survey of current (2001) coastal GIS applications and offers some suggestions to developers of new GIS systems. At the time, all applications could perform data management and had mapping tools, but many were weak in terms of use as decisionsupporting tools that required more complex modeling and simulation. It would be interesting to follow up on their work to see how GIS systems have changed to answer some of the problems the authors describe. Austin Becker, NRS 509 Page 6 11/30/2005