Landscape-level shifts in plant species distribution and abundance can fundamentally change the ecology of an ecosystem. Such shifts are occurring within mangrove-marsh ecotones, where over the last ...few decades, relatively mild winters have led to mangrove expansion into areas previously occupied by salt marsh plants. On the Texas (USA) coast of the western Gulf of Mexico, most cases of mangrove expansion have been documented within specific bays or watersheds. Based on this body of relatively small-scale work and broader global patterns of mangrove expansion, we hypothesized that there has been a recent regional-level displacement of salt marshes by mangroves. We classified Landsat-5 Thematic Mapper images using artificial neural networks to quantify black mangrove (Avicennia germinans) expansion and salt marsh (Spartina alterniflora and other grass and forb species) loss over 20 years across the entire Texas coast. Between 1990 and 2010, mangrove area grew by 16.1 km(2), a 74% increase. Concurrently, salt marsh area decreased by 77.8 km(2), a 24% net loss. Only 6% of that loss was attributable to mangrove expansion; most salt marsh was lost due to conversion to tidal flats or water, likely a result of relative sea level rise. Our research confirmed that mangroves are expanding and, in some instances, displacing salt marshes at certain locations. However, this shift is not widespread when analyzed at a larger, regional level. Rather, local, relative sea level rise was indirectly implicated as another important driver causing regional-level salt marsh loss. Climate change is expected to accelerate both sea level rise and mangrove expansion; these mechanisms are likely to interact synergistically and contribute to salt marsh loss.
AbstractThe 100-year floodplain is the traditional indicator of flood risk and the area in which specific flood mitigation requirements are required to occur in the United States. However, recent ...studies have indicated that there is a growing disconnect between the 100-year floodplain and the location of actual losses. As a result, there is a strong need to understand what is undermining the efficacy of the 100-year floodplain and to generate a more accurate depiction of flood risk. However, there have been few studies that examine the characteristics of insured flood claims occurring outside the 100-year floodplain and how more advanced hydrologic models may improve flood risk delineation. This study addresses this issue by cross-validating a fairly new distributed hydrologic flood inundation model and the Federal Emergency Management Association’s 100-year floodplain with historical, parcel-level insured flood losses in two subbasins near Houston, Texas. Results illustrate that spatially distributed hydrologic models greatly improve floodplain delineation, provide important insights on the drivers of flood damage outside of the floodplain, and offer alternative ways to more effectively communicate flood risk.
► Communities are increasingly using protected open space as a land-use tool to reduce adverse impacts from floods. ► Protecting areas within the floodplain significantly reduces property damage ...caused by flooding events. ► Communities protecting open space under the CRS saved, on average $200,000 per year in property damage caused by floods.
Open space protection is increasingly being used for flood mitigation at the local level. However, little if any empirical research has been conducted on the effectiveness of this land use policy in terms of reducing actual damage caused by floods. Our study addresses this issue by statistically examining the performance of open space dedicated for flood mitigation purposes across a nationally representative sample of local jurisdictions. We measure the amount of open space protection designated under FEMA's Community Rating System (CRS) program for 450 local communities, and then test the degree to which this strategy reduces insured flood damages over an eleven-year period from 1999 to 2009. Results indicate that, even when controlling for environmental, socioeconomic, and policy-related variables, open space protection is an important land use planning tool for mitigating the adverse impacts of flood events in the U.S. Our findings provide insights for local planners and decision makers interested in pursuing an avoidance strategy of flood mitigation, where people and structures are essentially removed from the most vulnerable locations.
Climate change is conventionally recognised as a large-scale issue resolved through regional or national policy initiatives. However, little research has been done to directly evaluate local climate ...change action plans. This study examines 40 recently adopted local climate change action plans in the US and analyses how well they recognise the concepts of climate change and prepare for climate change mitigation and adaptation. The results indicate that local climate change action plans have a high level of 'awareness', moderate 'analysis capabilities' for climate change, and relatively limited 'action approaches' for climate change mitigation. The study also identifies specific factors influencing the quality of these local jurisdictional plans. Finally, it provides policy recommendations to improve planning for climate change at the local level.
Although there is a growing body of research examining public perceptions of global climate change, little work has focused on the role of place and proximity in shaping these perceptions. This study ...extends previous conceptual models explaining risk perception associated with global climate change by adding a spatial dimension. Specifically, Geographic Information Systems and spatial analytical techniques are used to map and measure survey respondents' physical risk associated with expected climate change. Using existing spatial data, multiple measures of climate change vulnerability are analyzed along with demographic, attitudinal, and social contextual variables derived from a representative national survey to predict variation in risk perception. Bivariate correlation and multivariate regression analyses are used to identify and explain the most important indicators shaping individual risk perception. Analysis of the data suggests that the relationship between actual and perceived risk is driven by specific types of physical conditions and experiences.
Abstract Timely, accurate, and reliable information is essential for decision-makers, emergency managers, and infrastructure operators during flood events. This study demonstrates that a proposed ...machine learning model, MaxFloodCast , trained on physics-based hydrodynamic simulations in Harris County, offers efficient and interpretable flood inundation depth predictions. Achieving an average $$R^2$$ R 2 of 0.949 and a Root Mean Square Error of 0.61 ft (0.19 m) on unseen data, it proves reliable in forecasting peak flood inundation depths. Validated against Hurricane Harvey and Tropical Storm Imelda, MaxFloodCast shows the potential in supporting near-time floodplain management and emergency operations. The model’s interpretability aids decision-makers in offering critical information to inform flood mitigation strategies, to prioritize areas with critical facilities and to examine how rainfall in other watersheds influences flood exposure in one area. The MaxFloodCast model enables accurate and interpretable inundation depth predictions while significantly reducing computational time, thereby supporting emergency response efforts and flood risk management more effectively.
Ecosystem planning in Florida Brody, Samuel David
c2008., 2008, 20160429, 2008-06-01, 2016-04-29, 2016-05-06
eBook, Book
While ecosystem management requires looking beyond specific jurisdiction and focusing on broad spatial scales, most planning decisions particularly in the USA, are made at local level. By looking at ...land-use planning in Florida, this volume recognizes the need for planners and resource managers to address ecosystem problems at local and community levels. The factors causing ecosystem decline, such as rapid urban development and habitat fragmentation occur at the local level and are generated by local land use policies. This book argues that understanding how local jurisdictions can capture and implement the principles of managing natural systems will lead to more sustainable levels of environmental planning in the future.
Building a community that is resilient to disasters has become one of the main goals of disaster management. Communities that are more disaster resilient often experience less impact from the ...disaster and reduced recovery periods afterwards. This study develops a methodology for constructing a set of indicators measuring Community Disaster Resilience Index (CDRI) in terms of human, social, economic, environmental, and institutional factors. In this study, the degree of community resilience to natural disasters was measured for 229 local municipalities in Korea, followed by an examination of the relationship between the aggregated CDRI and disaster losses, using an ordinary least squares (OLS) regression method and a geographically weighted regression (GWR) method. Identifying the extent of community resilience to natural disasters would provide emergency managers and decision-makers with strategic directions for improving local communities' resilience to natural disasters while reducing the negative impacts of disasters.
Climate Change Vulnerability and Policy Support Zahran, Sammy; Brody, Samuel D.; Grover, Himanshu ...
Society & natural resources,
10/1/2006, 2006-10-00, 20061001, Volume:
19, Issue:
9
Journal Article
Peer reviewed
Climate scientists note that the effects of climate change vary regionally. Citizen willingness to absorb the costs of adaptation and mitigation policies may correspond with these place-specific ...effects. Geographic information systems (GIS) analytic techniques are used to map and measure survey respondents' climate change risk at various levels of spatial resolution and precision. Spatial data are used to analyze multiple measures of climate change vulnerability along with demographic, attitudinal, and perception-based variables derived from a representative national survey of U.S. residents to predict variation in support for interventionist climate change policies. Ordinary Least Squares (OLS) regression results show that objective risk measures explain a modest amount of variation in our dependent variable. The effect of risk perception on climate policy support is far more robust. Of all variables examined, the extent to which citizens regard climate change as threatening to their material well-being drives support for costly climate change policies.
Pre-disaster planning and mitigation necessitate detailed spatial information about flood hazards and their associated risks. In the US, the Federal Emergency Management Agency (FEMA) Special Flood ...Hazard Area (SFHA) provides important information about areas subject to flooding during the 1 % riverine or coastal event. The binary nature of flood hazard maps obscures the distribution of property risk inside of the SFHA and the residual risk outside of the SFHA, which can undermine mitigation efforts. Machine learning techniques provide an alternative approach to estimating flood hazards across large spatial scales at low computational expense. This study presents a pilot study for the Texas Gulf Coast region using random forest classification to predict flood probability across a 30 523 km2 area. Using a record of National Flood Insurance Program (NFIP) claims dating back to 1976 and high-resolution geospatial data, we generate a continuous flood hazard map for 12 US Geological Survey (USGS) eight-digit hydrologic unit code (HUC) watersheds. Results indicate that the random forest model predicts flooding with a high sensitivity (area under the curve, AUC: 0.895), especially compared to the existing FEMA regulatory floodplain. Our model identifies 649 000 structures with at least a 1 % annual chance of flooding, roughly 3 times more than are currently identified by FEMA as flood-prone.
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