Why relatively fewer people died? The case of Bangladesh’s Cyclone Sidr

Cyclone Sidr, a Category IV storm, struck the southwestern coast of Bangladesh on November 15, 2007 killing 3,406 people. Despite a similar magnitude, Sidr claimed far fewer lives than Cyclone Gorky, also a Category IV storm, which struck Bangladesh in 1991 causing an estimated 140,000 fatalities. The relatively low number of deaths experienced with Sidr is widely considered the result of Bangladesh government’s efforts to provide timely cyclone forecasting and early warnings, and successful evacuation of coastal residents from the projected path of Cyclone Sidr. Using information collected from both primary and secondary sources, this study identified several other reasons for the unexpectedly lower mortality associated with Cyclone Sidr relative to Cyclone Gorky. Fewer casualties may be attributed to a number of physical characteristics of Cyclone Sidr, such as duration of the storm and storm surge, landfall time and site, varied coastal ecology, and coastal embankment. This article recommends improvements to the cyclone warning systems, establishment of more public cyclone shelters, and implementation of an education campaign in coastal areas to increase the utilization of public shelters for future cyclone events.     

Impact assessment using DEA of coastal hazards on social-economy in Southeast Asia

Southeast Asian countries suffer from severe coastal hazards each year. A large number of these countries are incurring consequential costs that impact their national economies. It is crucial, therefore, to analyze the impact of such hazards on their economic development and provide a solid basis for future development strategies. The purpose of this paper is to assess the relationship between the economic development and the losses from coastal disasters, and to identify both the impact of hazards on the development, as well as the function of such development on the resilience to hazards. The data envelopment analysis (DEA) method is employed to build the assessment models. Data from 1995 to 2005 from eight Southeast countries are analyzed using the DEA models. A set of “resilience index” of these countries are concluded from the results. It is found that the economic development does not contribute to the strengthening of national resilience to coastal hazards. Inappropriate development could even impair the resilience. Additionally, the resilience to coastal hazards is impacted by various factors such as the allocation of resources and external assistance. From the analysis, a clear image is gained of the interaction between economic development and coastal hazards, which provides a basis for future development strategies.

Estimation of wave period statistics using numerical coastal wave model

We used field and model wave data to investigate that zero crossing and average wave period distribution follow Gamma distribution. Since Gamma CDF is an infinite power series, further mathematical treatment is difficult. Hence its shape parameter is approximated to the nearest integer to arrive at Erlang distribution. An expression is derived from Erlang distribution to estimate various mean wave periods and significant wave period and validated by relative root mean square (RRMS) error criteria. It is shown by mathematical logic that the significant wave period distribution follows Erlang (or Gamma) distribution and is validated. The average of one-third and one-tenth highest wave periods (T _s ) estimated from Erlang distribution are in accordance with the values computed from recorded buoy and numerical coastal wave model wave period data. The predicted T _s values from coastal wave model wave period data underestimates the values from buoy wave period data.     

Delineation of saltwater intrusion into the freshwater aquifer of Lekki Peninsula,Lagos, Nigeria

Recently, the deterioration of water quality in the coastal zones of Lekki Peninsula area of Lagos due to saltwater infiltration into the freshwater aquifer has become a major concern. With the aim of providing valuable information on the hydrogeologic system of the aquifers, the subsurface lithology and delineating the groundwater salinity, vertical electrical resistivity (VES) sounding survey was carried out utilizing surface Schlumberger electrode arrays, and electrode spacing varying between 1 and 150 m. The DC resistivity surveys revealed significant variations in subsurface resistivity. Also, the VES resistivity curves showed a dominant trend of decreasing resistivity with depth (thus increasing salinity). In general, the presence of four distinct resistivity zones were delineated viz.: the unconsolidated dry sand (A) having resistivity values ranging between 125 and 1,028 Ωm represent the first layer; the fresh water-saturated soil (zone B) having resistivity values which correspond to 32–256 Ωm is the second layer; the third layer (zone C) is interpreted as the mixing (transition) zone of fresh with brackish groundwater. The resistivity of this layer ranges from 4 to 32 Ωm; while layer four (zone D) is characterized with resistivities values generally below 4 Ωm reflecting an aquifer possibly containing brine. The rock matrix, salinity and water saturation are the major factors controlling the resistivity of the formation. Moreover, this investigation shows that saline water intrusion into the aquifers can be accurately mapped using surface DC resistivity method.     

Distribution of coastal cliffs in Kerala,India: their mechanisms of failure and related human engineering response

The 560-km-long Kerala coast is characterised by long barriers with narrow beaches and steep cliffs. Distribution of cliffs from nine sections measuring a cumulative length of 63.5 km is evaluated in ArcGIS Software using topomaps and field survey data. The cliff sections in the southern coast comprise both permeable and impermeable rocks, whereas those along northern coast are comprised of either Precambrian crystalline and/or Tertiary formations. Notches, caves and even small arches are developed in Cannanore, Dharmadam and Kadalundi cliffs, where only primary laterites are exposed to wave attack. Stacks composed of laterite and Precambrian crystallines found in nearshore of cliffed coast indicate recession of shoreline. Mass wasting, mudslide and mudflow type of cliff failures are common in permeable to semi-permeable rocks, whereas rotational sliding, rockfall and toppling failure are found in hard rock cliffs. Retreat of cliff sections are induced by natural or anthropogenic activities or both. Rate of recession vary from a few centimetres to one metre/year depending upon the nature of lithology, structures and recession agents acting upon the cliffs. Various methods of cliff protection for e.g. hard structures—revetments, groins, seawalls, breakwater and jetties—and soft measures—artificial reefs/marsh creation, floating breakwaters, beach nourishment, beach scraping and vegetation planting—are suggested.     

胶州湾高分辨率三维风暴潮漫滩数值模拟

基于海表气压项改进的FVCOM(Finite-Volume Coastal Ocean Model)海洋模式,研发胶州湾高分辨率三维风暴潮漫滩数值模式(JS-FVCOM).利用 JS-FVCOM 模式通过对天文潮、台风强度和径流3要素的不同组合,共设计了5个试验,分别进行风暴潮漫滩模拟实验.分析各试验结果得到如下结论:(1)随着台风最大风速的增加,风暴潮增水迅速增加,当综合水位超过防潮堤高程后增水速度明显减慢.海水淹没范围和淹没深度受综合水位超防潮堤高程时间影响明显.(2)在入海河流的河口区,当洪水位与高潮位相遇时,由于高潮位的顶托作用,洪水下泄不畅,造成综合水位上升明显,极易发生海水漫溢现象.JS-FVCOM 的模拟结果清楚地再现了海水漫堤的淹没过程,可为紧急情况下的人员疏散提供科学的基础数据.     

Sea Levels and Coastal Inundation Due to Tropical Cyclones in Indian Coastal Regions of Andhra and Orissa

Coastal inundation associated with extreme sea levels is the main factor which leads to the loss of life and property whenever a severe tropical cyclonic storm hits the Indian coasts. The Andhra and Orissa coasts are most vulnerable for coastal inundation due to extreme rise in sea levels associated with tropical cyclones. Loss of life may be minimized if extreme sea levels and associated coastal flooding is predicted well in advance. Keeping this in view, location specific coastal inundation models are developed and applied for the Andhra and Orissa coasts of India. Several numerical experiments are carried out using the data of past severe cyclones that struck these regions. The simulated inland inundation distances are found to be in general agreement with the reported flooding.     

Sea Level Variations Associated with Upwelling/ Downwelling Along the West Coast of India

A three-dimensional numerical model is developed and used to study the coastal upwelling processes and corresponding seasonal changes in the sea level along the west coast of India. The upwelling and associated sea level variations are seen as a response of coastal ocean to pure wind stress forcing. The model is designed to represent coastal ocean physics by resolving surface and bottom Ekman layers as realistically as possible. The prognostic variables are the three components of the velocity field, temperature, salinity and turbulent energy. The governing equations together with their boundary conditions are solved by finite-difference techniques. Experiments are performed to investigate sea level fluctuations associated with the thermal response and alongshore currents of the coastal waters. The model is forced with mean monthly wind stress forcing of January, May, July and September representing northeast monsoon and different phases of the southwest monsoon. It is known from the observational study that the upwelling process reaches to the surface waters by May along the coastal waters of the extreme southwest peninsular region. The process is more intense in July compared to May and September and its strength decreases from south to north. However, during the northeast monsoon season, which is represented by January wind stress forcing in the model, downwelling is simulated along the coast. The model simulations of the coastal response are compared with the observations and are found to be in good agreement. The maximum computed vertical velocity of about 2.0 2 10 -3 cm s -1 is predicted in July in the southern region off the coast.     

Sea Level Variations and Geomorphological Changes in the Coastal Belt of Pakistan

The UNEP in its regional seas program in 1989 has included Pakistan in a group of countries which are vulnerable to the impact of rising sea level. If the present trend of sea level rise (SLR) at Karachi continues, in the next 50 years the sea level rise along the Pakistan Coast will be 50 mm (5 cm). Since the rising rates of sea level at Karachi are within the global range of 1-2 mm/year, the trends may be treated as eustatic SLR. Historical air temperature and sea surface temperature (SST) data of Karachi also show an increasing pattern and an increasing trend of about 0.67°C has been registered in the air temperature over the last 35 years, whereas the mean SST in the coastal waters of Karachi has also registered an increasing trend of about 0.3°C in a decade. Sindh coastal zone is more vulnerable to sea level rise than Baluchistan coast, as uplifting of the coast by about 1-2 mm/year due to subduction of Indian Ocean plate is a characteristic of Baluchistan coast. Within the Indus deltaic creek system, the area nearby Karachi is more vulnerable to coastal erosion and accretion than the other deltaic region, mainly due to human activities together with natural phenomena such as wave action, strong tidal currents, and rise in sea level. Therefore, The present article deals mainly with the study of dynamical processes such as erosion and accretion associated with sea level variations along the Karachi coast and surrounding Indus deltaic coastline. The probable beach erosion in a decade along the sandy beaches of Karachi has been estimated. The estimates show that 1.1 mm/year rise in sea level causes a horizontal beach loss of 110 mm per year. Therefore, coast eroded with rise in sea level at Karachi and surrounding sandy beaches would be 1.1 m during a period of next 10 years. The northwestern part of Indus delta, especially the Gizri and Phitti creeks and surrounding islands, are most unstable. Historical satellite images are used to analyze the complex pattern of sediment movements, the change in shape of coastline, and associated erosion and accretion patterns in Bundal and Buddo Islands. The significant changes in land erosion and accretion areas at Bundal and Buddo Islands are evident and appear prominently in the images. A very high rate of accretion of sediments in the northwestern part of Buddo Island has been noticed. In the southwest monsoon season the wave breaking direction in both these islands is such that the movement of littoral drift is towards west. Erosion is also taking place in the northeastern and southern part of Bundal Island. The erosion in the south is probably due to strong wave activities and in the northeast is due to strong tidal currents and seawater intrusion. Accretion takes place at the northwest and western parts of Bundal Island. By using the slope of Indus delta, sea encroachment and the land area inundation with rising sea level of 1 m and 2 m have also been estimated.     

Integrating Uncertainty Theories with GIS for Modeling Coastal Hazards of Climate Change

Prediction of coastal hazards due to climate change is fraught with uncertainty that stems from complexity of coastal systems, estimation of sea level rise, and limitation of available data. In-depth research on coastal modeling is hampered by lack of techniques for handling uncertainty, and the available commercial geographical information systems (GIS) packages have only limited capability of handling uncertain information. Therefore, integrating uncertainty theory with GIS is of practical and theoretical significance. This article presents a GIS-based model that integrates an existing predictive model using a differential approach, random simulation, and fuzzy set theory for predicting geomorphic hazards subject to uncertainty. Coastal hazard is modeled as the combined effects of sea-level induced recession and storm erosion, using grid modeling techniques. The method is described with a case study of Fingal Bay Beach, SE Australia, for which predicted responses to an IPCC standard sea-level rise of 0.86 m and superimposed storm erosion averaged 12 m and 90 m, respectively, with analysis of uncertainty yielding maximum of 52 m and 120 m, respectively. Paradoxically, output uncertainty reduces slightly with simulated increase in random error in the digital elevation model (DEM). This trend implies that the magnitude of modeled uncertainty is not necessarily increased with the uncertainties in the input parameters. Built as a generic tool, the model can be used not only to predict different scenarios of coastal hazard under uncertainties for coastal management, but is also applicable to other fields that involve predictive modeling under uncertainty.