928 resultados para Flood forecasting.


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In this paper, we explore the firm-level impacts of flooding in Thailand in 2011, specifically those on the procurement patterns at Japanese affiliates in Thailand. Our findings are as follow. First, the damaged small firms are more likely to lower their local procurement share, particularly the share of procurement from other Japanese-owned firms in Thailand. Second, damaged young firms and damaged old firms are more likely to raise the shares of imports from Japan and China, respectively. Third, there are no impacts on imports from ASEAN and other countries. These findings are useful for uncovering how multinational firms adjust their production networks before and after natural disasters.

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Forecasting tourism demand is crucial for management decisions in the tourism sector. Estimating a vector autoregressive (VAR) model for monthly visitor arrivals disaggregated by three entry points in Cambodia for the years 2006–2015, I forecast the number of arrivals for years 2016 and 2017. The results show that the VAR model fits well with the data on visitor arrivals for each entry point. Ex post forecasting shows that the forecasts closely match the observed data for visitor arrivals, thereby supporting the forecasting accuracy of the VAR model. Visitor arrivals to Siem Reap and Phnom Penh airports are forecast to increase steadily in future periods, with varying fluctuations across months and origin countries of foreign tourists.

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Processes of founding and expanding cities in coastal areas have undergone great changes over time driven by environmental conditions. Coastal settlements looked for places above flood levels and away from swamps and other wetlands whenever possible. As populations grew, cities were extending trying to avoid low and wet lands. No city has been able to limit its growth. The risk of flooding can never be eliminated, but only reduced to the extent possible. Flooding of coastal areas is today dramatically attributed to eustasic sea level rise caused by global climate change. This can be inaccurate. Current climate change is generating an average sea level upward trend, but other regional and local factors result in this trend being accentuated in some places or attenuated, and even reversed, in others. Then, the intensity and frequency of coastal flooding around the planet, although not so much as a unique result of this general eustasic elevation, but rather of the superposition of marine and crustal dynamic elements, the former also climate-related, which give rise to a temporary raising in average sea level in the short term. Since the Little Ice Age the planet has been suffering a global warming change leading to sea level rise. The idea of being too obeying to anthropogenic factors may be attributed to Arrhenius (1896), though it is of much later highlight after the sixties of the last century. Never before, the human factor had been able of such an influence on climate. However, other types of changes in sea levels became apparent, resulting from vertical movements of the crust, modifications of sea basins due to continents fracturing, drifting and coming together, or to different types of climate patterns. Coastal zones are then doubly susceptible to floods. Precipitation immediately triggers pluvial flooding. If it continues upland or when snow and glaciers melt eventually fluvial flooding can occur. The urban development presence represents modifying factors. Additional interference is caused by river and waste water drainage systems. Climate also influences sea levels in coastal areas, where tides as well as the structure and dynamic of the geoid and its crust come into play. From the sea, waters can flood and break or push back berms and other coastline borders. The sea level, controlling the mouth of the main channel of the basin's drainage system, is ultimately what governs flood levels. A temporary rise in sea level acts as a dam at the mouth. Even in absence of that global change, so, floods are likely going to increase in many urban coastal areas. Some kind of innovative methodologies and practices should be needed to get more flood resilience cities

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In this work, we propose the Seasonal Dynamic Factor Analysis (SeaDFA), an extension of Nonstationary Dynamic Factor Analysis, through which one can deal with dimensionality reduction in vectors of time series in such a way that both common and specific components are extracted. Furthermore, common factors are able to capture not only regular dynamics (stationary or not) but also seasonal ones, by means of the common factors following a multiplicative seasonal VARIMA(p, d, q) × (P, D, Q)s model. Additionally, a bootstrap procedure that does not need a backward representation of the model is proposed to be able to make inference for all the parameters in the model. A bootstrap scheme developed for forecasting includes uncertainty due to parameter estimation, allowing enhanced coverage of forecasting intervals. A challenging application is provided. The new proposed model and a bootstrap scheme are applied to an innovative subject in electricity markets: the computation of long-term point forecasts and prediction intervals of electricity prices. Several appendices with technical details, an illustrative example, and an additional table are available online as Supplementary Materials.