Climate Change Impact Assessment for Surface Transportation in the Pacific Northwest and Alaska

WA-RD 772.

Multiple scenario analyses forecasting the impacts of sea level rise in Cape Town, South Africa

Sea level rise is highly interdisciplinary and its study entails not only oceanography, but other fields such as geomatics, climatology and geology. In this study we relied on the tools from geomatics to produce sea level rise maps in order to assess the vulnerability of the coastline of Cape Town, South Africa. After generating a DEM of a spatial resolution of 2 m from LiDAR point cloud data, we made use of GIS to design 4 sea level rise scenarios based on the RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 scenarios from the IPCC. Among the findings, it was found that 2.16 – 3.09 km² of land would be potentially inundated by 2100. The main receptors which were identified were sandy beaches, rocky shores and built-up land. Permanent inundation would possibly change the appeal and the nature of the beaches and affect the tourism industry. Hence the coastline requires immediate attention as it is one of the most valuable assets in the tourism industry. Tidal effect and storm surge effect were also identified as additional factors which brought temporary changes to the sea level in Cape Town. These impacts were further investigated in 8 coastal suburbs (Tableview, Woodbridge Island, Paarden Eiland, Foreshore, Sea Point, Glencairn, Fish Hoek and Strand.) Suitable adaptation strategies including hard protection measures (e.g groynes, sea walls, barriers) and soft protection measures (e.g beach nourishment) were also proposed for these 8 suburbs

On the use of logistic functions for coastal flood assessment

Coastal flooding results as the combination of wave conditions, mean water level and terrain characteristics. The associated damage can be expressed as a function of the flooding water column and it will rarely remain stationary in a sea level scenario. The objective of the study is to determine the importance of the dynamic (waves) and hydrostatic (sea level) component as a function of a damage level and to determine what combinations of hydrodynamic drivers may lead to unacceptable damage levels. The analysis has been performed through the use of logistic functions in the beach of Sant Pere Pescador (Girona province), covering an extension of 6,3 kilometres with an average width of 90m. The approach of the research consists of the creation of two multinomial regression models to be analyzed for 6 hydrodynamic scenarios derived from a coupled hydromorphodynamic model, one made in a node-by-node basis and the other one through polygons. The results show that a node-by-node model has nearly 10% of information loss due to the small variability and the small number of measurements. However, both models successfully predict similar expected prediction and probability to reach a flood categories for the proposed scenarios. Results from the multinomial regression clearly reveals sea level rise as the main contribution to flood increase, with the wave return period being less significant. The model also suggests that a drastic increase in the flooding water column, approximately between 0,6 and 1 m will occur for sea level rise bigger than 0,25m. According the IPCC predictions for the sea level rise in the Mediterranean Coast, this is expected to occur between a time range of 2040-2070 (for the RCP 8.5, the most dramatic climate scenario) or starting in 2045 (for RCP 2.6 and RCP 4.5, less severe scenarios). For what concerns the spatial extension of the flooding, the expected categories of flooding shows that the northern region of the Sant Pere Pescador beach is likely to suffer more severe flooding than the central and southern regions, both in intensity and spatial extent, reaching water depths larger than 0,6 - 1m for scenarios with sea level rise larger than 0,25m.Las inundaciones de costas son fenómenos causados por la combinación del oleaje, el nivel medio del mar y las características del terreno. El daño asociado puede ser expresado en función de la columna de agua de inundación, tomando diferentes valores para distintas situaciones de subida del nivel del mar. El objetivo del presente estudio es determinar la importancia de la componente dinámica (olas) e hidrostática (nivel del mar) como componentes de predicción del nivel de daño para poder determinar qué combinaciones de parámetros hidrodinámicos lleva a niveles de daño inaceptables. El análisis se ha llevado a cabo a través del uso de modelos logísticos en la zona de playa de Sant Pere Pescador (Provincia de Girona), cubriendo una extensión de 6,3 Km de largo con un ancho medio de 90m. Para su desarrollo, se han elaborados dos modelos multinomiales de regresión analizando 6 escenarios hidrodinámicos. Uno de los modelos se ha centrado en el estudio nodo a nodo y el otro mediante el análisis de polígonos. Los resultados muestran que, para el modelo nodo a nodo, hay una pérdida de cerca del 10% de la información inicial debido a la escasa variabilidad en la muestra y debido al reducido número de datos disponibles. No obstante, ambos modelos consiguen predecir de manera similar la probabilidad y la predicción de llegar a ciertas categorías de inundación para los distintos escenarios. Los resultados del modelo de regresión logística muestran la subida del nivel del mar como principal contribuyente al incremento de la cota de inundación, mientras que el período de retorno de la ola es menos significativo. El modelo también indica que para niveles de incremento del nivel del mar mayores que 0,25m, gran parte de la costa se va a ver seriamente afectada con inundaciones entre 0,6 y 1 metro de agua. Según las predicciones del IPCC, para incrementos del nivel del mar en la costa del Mediterráneo, se espera que una subida del nivel del mar alcance los 0,25m entre el 2040 y el 2070 (para el RCP 8.5, el escenario climático más severo) o 2045 (para escenarios climáticos menos graves como el RCP 2.6 y RCP 4.5). En cuanto a la extensión de la inundación, se prevé que en la zona norte de la Playa de Sant Pere Pescador se obtengan mayores categorías de inundación, en comparación con la zona centro y sur, debido a la elevación y la configuración de las dunas. Concretamente, se esperan valores de inundación entre 0,6m y 1m en la zona norte para escenarios de subida del nivel del mar mayor que 0,25m.Les inundacions de costes son fenòmens causats per la combinació de l’onatge, el nivell mig del mar i les característiques del terreny. Els danys associats poden ser expressats en funció de la columna d’aigua d’inundació, prenent valors variables en funció dels diferents escenaris d’augment del nivell. del mar. L’objectiu d’aquest treball és determinar la importància de la component dinàmica (onades) i hidrostàtica (nivell del mar) en la predicció del nivell de dany per tal de determinar quines combinacions dels paràmetres hidrodinàmics duen a nivells de dany inacceptables. L’anàlisi s’ha dut a terme a través de l’ús de models logístics en la zona de platja de Sant Pere Pescador (Província de Girona), cobrint una extensió de 6,3 Km de llarg i un ample mitjà de 90m. S’han analitzat 6 escenaris hidrodinàmics mitjançant l’elaboració de dos models multinomials, un centrat en l’estudi node a node i l’altre mitjançant polígons. Els resultats mostren que, per el model node a node, hi ha una pèrdua aproximada d’un 10% de la informació inicial, degut a l’escassa variabilitat en la mostra i al reduït nombre de dades mesurades. No obstant, ambdós models aconsegueixen predir de manera molt similar la probabilitat i les prediccions d’arribar a certes categories d’inundació per a diferents escenaris. Els resultats del model de regressió logístic mostra la pujada del nivell del mar com a principal contribuïdor a l’increment del nivell d’inundació, mentre que el període de retorn resulta menys significatiu. El model també indica que, per a nivells d’increment del mar majors de 0,25m, gran part de la costa es veurà greument afectada amb inundacions d’entre 0,6 i 1m d’aigua. Segons les prediccions del IPCC, s’espera que en la costa Mediterrània el nivell del mar pugi fins els 0,25m entre el 2040 i el 2070 (per el RCP 8.5, que és l’escenari climàtic més advers) o al 2045 (per a prediccions climàtiques menys greus, com el RCP 2.6 i 4.5) Pel que fa l’extensió de la inundació, es preveu que a la zona nord de la Platja de Sant Pere Pescador s’hi obtinguin majors cotes d’inundació que en les zones centre i sud, degut a l’elevació i la configuració de les dunes. Concretament, s’esperen valors d’inundació entre 0,6 i 1m per a escenaris on la pujada del nivell del mar sobrepassi els 0,25m

Analysis of Rob Flood Risk on The Coast of East Luwu District Using GIS

Rob floods caused by rising sea levels are a natural disaster that can potentially threaten coastal areas, especially in Indonesia. Tidal floods seriously threaten coastal areas, especially East Luwu Regency. Environmental factors and rapid growth on the coast of East Luwu Regency influence the vulnerability and complexity of the environment. This research aims to identify the spatial distribution of tidal flood risk levels and predict tidal flood inundation in 2050 at the highest tide on the coast of Luwu Timur District. This effort is part of a disaster mitigation strategy due to rising sea levels. The modeling approach involves Geographic Information Systems (GIS) overlaying data and integrating DEM, HHWL, and SLR data for 28 years (1992-2020). The research results show that the coastal areas studied have a high risk related to tidal flooding, with locations closest to the coastline being at the highest risk. In contrast, the risk decreases as you move away from the coastline. Apart from that, the modeling results also estimate that in 2050, inundation will reach a height of 1,570 meters. The area affected by tidal flood inundation has increased in each sub-district. The inundation will spread evenly along the coastline and extend inland due to seawater intrusion. Coastal areas dominated by production land, such as ponds and agricultural areas, are predicted to experience the most extensive impact of inundation compared to other land uses. Emphasizes the need for mitigation efforts to minimize the impacts that may be caused by tidal floods in the future

Uncertain future for global sea turtle populations in face of sea level rise

Sea level rise has accelerated during recent decades, exceeding rates recorded during the previous two millennia, and as a result many coastal habitats and species around the globe are being impacted. This situation is expected to worsen due to anthropogenically induced climate change. However, the magnitude and relevance of expected increase in sea level rise (SLR) is uncertain for marine and terrestrial species that are reliant on coastal habitat for foraging, resting or breeding. To address this, we showcase the use of a low-cost approach to assess the impacts of SLR on sea turtles under various Intergovernmental Panel on Climate Change (IPCC) SLR scenarios on different sea turtle nesting rookeries worldwide. The study considers seven sea turtle rookeries with five nesting species, categorized from vulnerable to critically endangered including leatherback turtles (Dermochelys coriacea), loggerhead turtles (Caretta caretta), hawksbill turtles (Eretmochelys imbricata), olive ridley turtles (Lepidochelys olivacea) and green turtles (Chelonia mydas). Our approach combines freely available digital elevation models for continental and remote island beaches across different ocean basins with projections of field data and SLR. Our case study focuses on five of the seven living sea turtle species. Under moderate climate change scenarios, by 2050 it is predicted that at some sea turtle nesting habitats 100% will be flooded, and under an extreme scenario many sea turtle rookeries could vanish. Overall, nesting beaches with low slope and those species nesting at open beaches such as leatherback and loggerheads sea turtles might be the most vulnerable by future SLR scenarios

Uncertain future for global sea turtle populations in face of sea level rise

Sea level rise has accelerated during recent decades, exceeding rates recorded during the previous two millennia, and as a result many coastal habitats and species around the globe are being impacted. This situation is expected to worsen due to anthropogenically induced climate change. However, the magnitude and relevance of expected increase in sea level rise (SLR) is uncertain for marine and terrestrial species that are reliant on coastal habitat for foraging, resting or breeding. To address this, we showcase the use of a low-cost approach to assess the impacts of SLR on sea turtles under various Intergovernmental Panel on Climate Change (IPCC) SLR scenarios on different sea turtle nesting rookeries worldwide. The study considers seven sea turtle rookeries with five nesting species, categorized from vulnerable to critically endangered including leatherback turtles (Dermochelys coriacea), loggerhead turtles (Caretta caretta), hawksbill turtles (Eretmochelys imbricata), olive ridley turtles (Lepidochelys olivacea) and green turtles (Chelonia mydas). Our approach combines freely available digital elevation models for continental and remote island beaches across different ocean basins with projections of field data and SLR. Our case study focuses on five of the seven living sea turtle species. Under moderate climate change scenarios, by 2050 it is predicted that at some sea turtle nesting habitats 100% will be flooded, and under an extreme scenario many sea turtle rookeries could vanish. Overall, nesting beaches with low slope and those species nesting at open beaches such as leatherback and loggerheads sea turtles might be the most vulnerable by future SLR scenarios

Vulnerability of the agricultural sector to climate change: The development of a pantropical Climate Risk Vulnerability Assessment to inform sub-national decision making

As climate change continues to exert increasing pressure upon the livelihoods and agricultural sector of many developing and developed nations, a need exists to understand and prioritise at the sub national scale which areas and communities are most vulnerable. The purpose of this study is to develop a robust, rigorous and replicable methodology that is flexible to data limitations and spatially prioritizes the vulnerability of agriculture and rural livelihoods to climate change. We have applied the methodology in Vietnam, Uganda and Nicaragua, three contrasting developing countries that are particularly threatened by climate change. We conceptualize vulnerability to climate change following the widely adopted combination of sensitivity, exposure and adaptive capacity. We used Ecocrop and Maxent ecological models under a high emission climate scenario to assess the sensitivity of the main food security and cash crops to climate change. Using a participatory approach, we identified exposure to natural hazards and the main indicators of adaptive capacity, which were modelled and analysed using geographic information systems. We finally combined the components of vulnerability using equal-weighting to produce a crop specific vulnerability index and a final accumulative score. We have mapped the hotspots of climate change vulnerability and identified the underlying driving indicators. For example, in Vietnam we found the Mekong delta to be one of the vulnerable regions due to a decline in the climatic suitability of rice and maize, combined with high exposure to flooding, sea level rise and drought. However, the region is marked by a relatively high adaptive capacity due to developed infrastructure and comparatively high levels of education. The approach and information derived from the study informs public climate change policies and actions, as vulnerability assessments are the bases of any National Adaptation Plans (NAP), National Determined Contributions (NDC) and for accessing climate finance

Using SRTM and GDEM2 data for assessing vulnerability to coastal flooding due to sea level rise in Lagos: a comparative study

Climate change and its associated sea level rise is one of the recent challenging global issues especially in coastal areas, where a large percentage of the world population resides. Sealevel rise (SLR) is expected to increase coastal inundation and erosion. This may disrupt the physical and human processes including economic systems and social structures in coastal regions, which are densely populated. Digital Elevation Model (DEM) especially Shuttle Radar Topography Mission (SRTM) is a common source of elevation data for assessing the risk of flooding due to sea level rise. Recently, a new Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER) Global DEM Version 2 (GDEM2) has been released to the public. This paper compares the flood risk estimations of SRTM and GDEM2. It examines different scenarios of sea level rise and its consequences on flooding in Mainland Lagos. It uses high resolution remote sensing data within Geographic Information System (GIS) environment to visualize the scenarios. The result shows that Lagos Mainland is vulnerable to sea level rise and SRTM (RMSE = 1.98) gives better flood risk estimations than GDEM2 (RMSE = 10.09).Keywords: geospatial techniques; sea level rise, coastal flooding, SRTM, ASTER GDEM2 and flood risk estimation

The Impacts of the 2015/2016 El Niño on California’s Sandy Beaches

AbstractThe Impacts of the 2015/2016 El Niño on California’s Sandy BeachesBy Schuyler SmithThe El Niño Southern Oscillation is the most dominant mode of interannual climate variability in the Pacific. The 2015/2016 El Niño event was one of the strongest of the last 145 years, resulting in anomalously high wave energy across the U.S. West Coast, and record coastal erosion for many California beaches (Barnard et al., 2017). Currently, 26 million people live in California’s coastal counties (2010 U.S. Census), and over 600,000 people in California will likely be at risk of coastal flooding by the end of this century due to projected sea level rise and storms (Barnard et al., 2019). To better manage our coastal resources, it is critical that we understand the impacts of both short-term climate variability and long-term climate impacts across the varied coastal settings of California. This study is the first to quantify the effects of one of the strongest El Niño events in the historical record across the entire coast of California, represented by 8000, 50-m spaced shore-normal transects across sandy beaches along the length of the state’s shoreline. The response of sandy shorelines to the extreme El Niño winter of 2015/2016 is quantified in the context of net shoreline movement, using the mean high water (MHW) line as a shoreline proxy. MHW contours were extracted from Light Detection and Ranging (LiDAR) digital elevation models (DEMS) from the Oregon border to Mexico using ArcGIS, to represent the 1998/2002, 2015 and 2016 shorelines. Both net shoreline movement values (from fall of 2015 to spring of 2016) and long-term end-point rates of change (1998/2002-2016) were calculated. Satellite-derived long-term (1984-2019) rates of shoreline change acquired from Luijendijk et al. (2018) are summarized for comparison. To determine the influence of wave energy on the coastal response observed here, wave energy flux values for the El Niño winter were calculated at the 20 m depth contour every 100 m along the entire California coastline using hindcast data generated by O'Reilly et al. (2016).We find that central and northern California experienced the most sandy beach erosion during the El Niño winter, with 96% of analyzed beaches in Central California eroding (mean = 45.7 m of erosion), compared to 89% in northern California (mean = 25.5 m of erosion), and 79% in southern California (mean = 9.7 m of erosion). Although local beach response was highly variable, much of the erosion was observed at river mouths, and on the southern side of structures impeding littoral drift, with accretion observed on the northern or upcoast side of these structures. Within west-facing embayments, more extreme erosion was observed in the north than in the south. These erosional patterns contrast to those of typical El Niño events, when the direction of alongshore transport has been observed as south to north, and accretion occurs in the northern end of embayments. In the long-term (1998/2002-2016), southern California and central California beaches are moderately accreting, while northern California is eroding on average at 79 cm per year. A significant correlation was found between cumulative wave energy flux and shoreline change during the El Niño winter across the state of California (R2 = -0.45, P<0.001). The correlation is lower (-0.25, P<0.001) for the 2015/2016 winter cumulative wave energy flux anomaly and shoreline change in southern California. After assessing the impact of the 2015/2016 El Niño event, spatial patterns indicate that an unusual, more northerly wave direction, extreme wave energy, and coastline orientation were key factors in the observed shoreline response. This response was markedly different from the classic El Niños of 1982-83 and 1997-98, where more southerly storm tracks and southerly wave directions were key factors controlling shoreline behavior