Diagnóstico ambiental do rio corumbataí em trecho urbano do município de rio claro, SP

The environmental analysis is an important tool used in forecasting and mitigation of environmental problems. Focusing on the occupation of marginal areas of the Corumbataí River in an urban stretch in the city of Rio Claro (SP), this study aimed to gather information on situations of risk, both to the environment and the population, verified in that area. Through field observation and in specific studies, the geological and geotechnical aspects, the characteristics of surface waters and aspects of urbanization were analyzed. The results show that the environmental problems diagnosed are related to lack of planning in the occupation of the area. Moreover, the natural characteristics of the physical environment expose people to risks such as floods and soil slides.

Flash floods and their effects on the development in El-Qaá plain area in South Sinai, Egypt

The arid regions are dominated to a much larger degree than humid regions by major catastrophic events. Although most of Egypt lies within the great hot desert belt; it experiences especially in the north some torrential rainfall, which causes flash floods all over Sinai Peninsula. Flash floods in hot deserts are characterized by high velocity and low duration with a sharp discharge peak. Large sediment loads may be carried by floods threatening fields and settlements in the wadis and even people who are living there. The extreme spottiness of rare heavy rainfall, well known to desert people everywhere, precludes any efficient forecasting. Thus, although the limitation of data still reflects pre-satellite methods, chances of developing a warning system for floods in the desert seem remote. The relatively short flood-to-peak interval, a characteristic of desert floods, presents an additional impediment to the efficient use of warning systems. The present thesis contains introduction and five chapters, chapter one points out the physical settings of the study area. There are the geological settings such as outcrop lithology of the study area and the deposits. The alluvial deposits of Wadi Moreikh had been analyzed using OSL dating to know deposits and palaeoclimatic conditions. The chapter points out as well the stratigraphy and the structure geology containing main faults and folds. In addition, it manifests the pesent climate conditions such as temperature, humidity, wind and evaporation. Besides, it presents type of soils and natural vegetation cover of the study area using unsupervised classification for ETM+ images. Chapter two points out the morphometric analysis of the main basins and their drainage network in the study area. It is divided into three parts: The first part manifests the morphometric analysis of the drainage networks which had been extracted from two main sources, topographic maps and DEM images. Basins and drainage networks are considered as major influencing factors on the flash floods; Most of elements were studied which affect the network such as stream order, bifurcation ratio, stream lengths, stream frequency, drainage density, and drainage patterns. The second part of this chapter shows the morphometric analysis of basins such as area, dimensions, shape and surface. Whereas, the third part points the morphometric analysis of alluvial fans which form most of El-Qaá plain. Chapter three manifests the surface runoff through rainfall and losses analysis. The main subject in this chapter is rainfall which has been studied in detail; it is the main reason for runoff. Therefore, all rainfall characteristics are regarded here such as rainfall types, distribution, rainfall intensity, duration, frequency, and the relationship between rainfall and runoff. While the second part of this chapter concerns with water losses estimation by evaporation and infiltration which are together the main losses with direct effect on the high of runoff. Finally, chapter three points out the factors influencing desert runoff and runoff generation mechanism. Chapter four is concerned with assessment of flood hazard, it is important to estimate runoff and tocreate a map of affected areas. Therefore, the chapter consists of four main parts; first part manifests the runoff estimation, the different methods to estimate runoff and its variables such as runoff coefficient lag time, time of concentration, runoff volume, and frequency analysis of flash flood. While the second part points out the extreme event analysis. The third part shows the map of affected areas for every basin and the flash floods degrees. In this point, it has been depending on the DEM to extract the drainage networks and to determine the main streams which are normally more dangerous than others. Finally, part four presets the risk zone map of total study area which is of high inerest for planning activities. Chapter five as the last chapter concerns with flash flood Hazard mitigation. It consists of three main parts. First flood prediction and the method which can be used to predict and forecast the flood. The second part aims to determine the best methods which can be helpful to mitigate flood hazard in the arid zone and especially the study area. Whereas, the third part points out the development perspective for the study area indicating the suitable places in El-Qaá plain for using in economic activities.

A Web GIS Decision Support System For Coastal Risk Assessment and Mitigation Planning

Coastal flooding poses serious threats to coastal areas around the world, billions of dollars in damage to property and infrastructure, and threatens the lives of millions of people. Therefore, disaster management and risk assessment aims at detecting vulnerability and capacities in order to reduce coastal flood disaster risk. In particular, non-specialized researchers, emergency management personnel, and land use planners require an accurate, inexpensive method to determine and map risk associated with storm surge events and long-term sea level rise associated with climate change. This study contributes to the spatially evaluation and mapping of social-economic-environmental vulnerability and risk at sub-national scale through the development of appropriate tools and methods successfully embedded in a Web-GIS Decision Support System. A new set of raster-based models were studied and developed in order to be easily implemented in the Web-GIS framework with the purpose to quickly assess and map flood hazards characteristics, damage and vulnerability in a Multi-criteria approach. The Web-GIS DSS is developed recurring to open source software and programming language and its main peculiarity is to be available and usable by coastal managers and land use planners without requiring high scientific background in hydraulic engineering. The effectiveness of the system in the coastal risk assessment is evaluated trough its application to a real case study.

Price risk management in the copper market using commodity derivatives and options strategies

Metals price risk management is a key issue related to financial risk in metal markets because of uncertainty of commodity price fluctuation, exchange rate, interest rate changes and huge price risk either to metals’ producers or consumers. Thus, it has been taken into account by all participants in metal markets including metals’ producers, consumers, merchants, banks, investment funds, speculators, traders and so on. Managing price risk provides stable income for both metals’ producers and consumers, so it increases the chance that a firm will invest in attractive projects. The purpose of this research is to evaluate risk management strategies in the copper market. The main tools and strategies of price risk management are hedging and other derivatives such as futures contracts, swaps and options contracts. Hedging is a transaction designed to reduce or eliminate price risk. Derivatives are financial instruments, whose returns are derived from other financial instruments and they are commonly used for managing financial risks. Although derivatives have been around in some form for centuries, their growth has accelerated rapidly during the last 20 years. Nowadays, they are widely used by financial institutions, corporations, professional investors, and individuals. This project is focused on the over-the-counter (OTC) market and its products such as exotic options, particularly Asian options. The first part of the project is a description of basic derivatives and risk management strategies. In addition, this part discusses basic concepts of spot and futures (forward) markets, benefits and costs of risk management and risks and rewards of positions in the derivative markets. The second part considers valuations of commodity derivatives. In this part, the options pricing model DerivaGem is applied to Asian call and put options on London Metal Exchange (LME) copper because it is important to understand how Asian options are valued and to compare theoretical values of the options with their market observed values. Predicting future trends of copper prices is important and would be essential to manage market price risk successfully. Therefore, the third part is a discussion about econometric commodity models. Based on this literature review, the fourth part of the project reports the construction and testing of an econometric model designed to forecast the monthly average price of copper on the LME. More specifically, this part aims at showing how LME copper prices can be explained by means of a simultaneous equation structural model (two-stage least squares regression) connecting supply and demand variables. A simultaneous econometric model for the copper industry is built: {█(Q_t^D=e^((-5.0485))∙P_((t-1))^((-0.1868) )∙〖GDP〗_t^((1.7151) )∙e^((0.0158)∙〖IP〗_t ) @Q_t^S=e^((-3.0785))∙P_((t-1))^((0.5960))∙T_t^((0.1408))∙P_(OIL(t))^((-0.1559))∙〖USDI〗_t^((1.2432))∙〖LIBOR〗_((t-6))^((-0.0561))@Q_t^D=Q_t^S )┤ P_((t-1))^CU=e^((-2.5165))∙〖GDP〗_t^((2.1910))∙e^((0.0202)∙〖IP〗_t )∙T_t^((-0.1799))∙P_(OIL(t))^((0.1991))∙〖USDI〗_t^((-1.5881))∙〖LIBOR〗_((t-6))^((0.0717) Where, Q_t^D and Q_t^Sare world demand for and supply of copper at time t respectively. P(t-1) is the lagged price of copper, which is the focus of the analysis in this part. GDPt is world gross domestic product at time t, which represents aggregate economic activity. In addition, industrial production should be considered here, so the global industrial production growth that is noted as IPt is included in the model. Tt is the time variable, which is a useful proxy for technological change. A proxy variable for the cost of energy in producing copper is the price of oil at time t, which is noted as POIL(t ) . USDIt is the U.S. dollar index variable at time t, which is an important variable for explaining the copper supply and copper prices. At last, LIBOR(t-6) is the 6-month lagged 1-year London Inter bank offering rate of interest. Although, the model can be applicable for different base metals' industries, the omitted exogenous variables such as the price of substitute or a combined variable related to the price of substitutes have not been considered in this study. Based on this econometric model and using a Monte-Carlo simulation analysis, the probabilities that the monthly average copper prices in 2006 and 2007 will be greater than specific strike price of an option are defined. The final part evaluates risk management strategies including options strategies, metal swaps and simple options in relation to the simulation results. The basic options strategies such as bull spreads, bear spreads and butterfly spreads, which are created by using both call and put options in 2006 and 2007 are evaluated. Consequently, each risk management strategy in 2006 and 2007 is analyzed based on the day of data and the price prediction model. As a result, applications stemming from this project include valuing Asian options, developing a copper price prediction model, forecasting and planning, and decision making for price risk management in the copper market.

Relative Energy Balance, CKD, and Risk of Cardiovascular and All-Cause Mortality.

BACKGROUND Mortality risk for people with chronic kidney disease is substantially greater than that for the general population, increasing to a 7-fold greater risk for those on dialysis therapy. Higher body mass index, generally due to higher energy intake, appears protective for people on dialysis therapy, but the relationship between energy intake and survival in those with reduced kidney function is unknown. STUDY DESIGN Prospective cohort study with a median follow-up of 14.5 (IQR, 11.2-15.2) years. SETTING & PARTICIPANTS Blue Mountains Area, west of Sydney, Australia. Participants in the general community enrolled in the Blue Mountains Eye Study (n=2,664) who underwent a detailed interview, food frequency questionnaire, and physical examination including body weight, height, blood pressure, and laboratory tests. PREDICTORS Relative energy intake, food components (carbohydrates, total sugars, fat, protein, and water), and estimated glomerular filtration rate (eGFR). Relative energy intake was dichotomized at 100%, and eGFR, at 60mL/min/1.73m(2). OUTCOMES All-cause and cardiovascular mortality. MEASUREMENTS All-cause and cardiovascular mortality using unadjusted and adjusted Cox proportional regression models. RESULTS 949 people died during follow-up, 318 of cardiovascular events. In people with eGFR<60mL/min/1.73m(2) (n=852), there was an increased risk of all-cause mortality (HR, 1.48; P=0.03), but no increased risk of cardiovascular mortality (HR, 1.59; P=0.1) among those with higher relative energy intake compared with those with lower relative energy intake. Increasing intake of carbohydrates (HR per 100g/d, 1.50; P=0.04) and total sugars (HR per 100g/d, 1.62; P=0.03) was associated significantly with increased risk of cardiovascular mortality. LIMITATIONS Under-reporting of energy intake, baseline laboratory and food intake values only, white population. CONCLUSIONS Increasing relative energy intake was associated with increased all-cause mortality in patients with eGFR<60mL/min/1.73m(2). This effect may be mediated by increasing total sugars intake on subsequent cardiovascular events.

Lake sediments as archives of recurrence rates and intensities of past flood events

Palaeoflood hydrology is an expanding field as the damage potential of flood and flood-related processes are increasing with the population density and the value of the infrastructure. Assessing the risk of these hazards in mountainous terrain requires knowledge about the frequency and severness of such events in the past. A wide range of methods is employed using diverse biologic, geomorphic or geologic evidences to track past flood events. Impact of floods are studied and dated on alluvial fans and cones using for example the growth disturbance of trees (Stoffel and Bollschweiler 2008; Schneuwly-Bollschweiler and Stoffel 2012: this volume) or stratigraphic layers deposited by debris flows, allowing to reconstruct past flood frequencies (Bardou et~al. 2003). Further downstream, the classical approach of palaeoflood hydrology (Kochel and Baker 1982) utilizes geomorphic indicators such as overbank sediments, silt lines and erosion features of floods along a river (e.g. Benito and Thorndycraft 2005). Fine-grained sediment settles out of the river suspension in eddies or backwater areas, where the flow velocity of the river is reduced. Records of these deposits at different elevations across a river’s profile can be used to assess the discharge of the past floods. This approach of palaeoflood hydrology studies was successfully applied in several river catchments (e.g. Ely et al. 1993; Macklin and Lewin 2003; O’Connor et al. 1994; Sheffer et al. 2003; Thorndycraft et al. 2005; Thorndycraft and Benito 2006). All these different reconstruction methods have their own advantages and disadvantages, but often these studies have a limited time coverage and the records are potentially incomplete due to lateral limits of depositional areas and due to the erosional power of fluvial processes that remove previously deposited flood witnesses. Here, we present a method that follows the sediment particle transported by a flood event to its final sink: the lacustrine basin.

Flood triggering in Switzerland: the role of daily to monthly preceding precipitation

Determining the role of different precipitation periods for peak discharge generation is crucial for both projecting future changes in flood probability and for short- and medium-range flood forecasting. In this study, catchment-averaged daily precipitation time series are analyzed prior to annual peak discharge events (floods) in Switzerland. The high number of floods considered – more than 4000 events from 101 catchments have been analyzed – allows to derive significant information about the role of antecedent precipitation for peak discharge generation. Based on the analysis of precipitation times series, a new separation of flood-related precipitation periods is proposed: (i) the period 0 to 1 day before flood days, when the maximum flood-triggering precipitation rates are generally observed, (ii) the period 2 to 3 days before flood days, when longer-lasting synoptic situations generate "significantly higher than normal" precipitation amounts, and (iii) the period from 4 days to 1 month before flood days when previous wet episodes may have already preconditioned the catchment. The novelty of this study lies in the separation of antecedent precipitation into the precursor antecedent precipitation (4 days before floods or earlier, called PRE-AP) and the short range precipitation (0 to 3 days before floods, a period when precipitation is often driven by one persistent weather situation like e.g., a stationary low-pressure system). A precise separation of "antecedent" and "peak-triggering" precipitation is not attempted. Instead, the strict definition of antecedent precipitation periods permits a direct comparison of all catchments. The precipitation accumulating 0 to 3 days before an event is the most relevant for floods in Switzerland. PRE-AP precipitation has only a weak and region-specific influence on flood probability. Floods were significantly more frequent after wet PRE-AP periods only in the Jura Mountains, in the western and eastern Swiss plateau, and at the outlet of large lakes. As a general rule, wet PRE-AP periods enhance the flood probability in catchments with gentle topography, high infiltration rates, and large storage capacity (karstic cavities, deep soils, large reservoirs). In contrast, floods were significantly less frequent after wet PRE-AP periods in glacial catchments because of reduced melt. For the majority of catchments however, no significant correlation between precipitation amounts and flood occurrences is found when the last 3 days before floods are omitted in the precipitation amounts. Moreover, the PRE-AP was not higher for extreme floods than for annual floods with a high frequency and was very close to climatology for all floods. The fact that floods are not significantly more frequent nor more intense after wet PRE-AP is a clear indicator of a short discharge memory of Pre-Alpine, Alpine and South Alpine Swiss catchments. Our study poses the question whether the impact of long-term precursory precipitation for floods in such catchments is not overestimated in the general perception. The results suggest that the consideration of a 3–4 days precipitation period should be sufficient to represent (understand, reconstruct, model, project) Swiss Alpine floods.

Forecasting cost based on a stochastic utilization plan and a fixed cost function

The application of Markov processes is very useful to health-care problems. The objective of this study is to provide a structured methodology of forecasting cost based upon combining a stochastic model of utilization (Markov Chain) and deterministic cost function. The perspective of the cost in this study is the reimbursement for the services rendered. The data to be used is the OneCare database of claim records of their enrollees over a two-year period of January 1, 1996–December 31, 1997. The model combines a Markov Chain that describes the utilization pattern and its variability where the use of resources by risk groups (age, gender, and diagnosis) will be considered in the process and a cost function determined from a fixed schedule based on real costs or charges for those in the OneCare claims database. The cost function is a secondary application to the model. Goodness-of-fit will be used checked for the model against the traditional method of cost forecasting. ^

Predicting the Past and Forecasting the Future

A commentary on Santos' article, "Explaining Scholarship Addressing Hispanic Children’s Issues."

Firm-level impacts of natural disasters on production networks : evidence from a flood in Thailand

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.

Coastal Urban Flood Resislience versus Climate Change

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

A bivariate return period based on copulas for hydrologic dam design: accounting for reservoir routing in risk estimation

A multivariate analysis on flood variables is needed to design some hydraulic structures like dams, as the complexity of the routing process in a reservoir requires a representation of the full hydrograph. In this work, a bivariate copula model was used to obtain the bivariate joint distribution of flood peak and volume, in order to know the probability of occurrence of a given inflow hydrograph. However, the risk of dam overtopping is given by the maximum water elevation reached during the routing process, which depends on the hydrograph variables, the reservoir volume and the spillway crest length. Consequently, an additional bivariate return period, the so-called routed return period, was defined in terms of risk of dam overtopping based on this maximum water elevation obtained after routing the inflow hydrographs. The theoretical return periods, which give the probability of occurrence of a hydrograph prior to accounting for the reservoir routing, were compared with the routed return period, as in both cases hydrographs with the same probability will draw a curve in the peak-volume space. The procedure was applied to the case study of the Santillana reservoir in Spain. Different reservoir volumes and spillway lengths were considered to investigate the influence of the dam and reservoir characteristics on the results. The methodology improves the estimation of the Design Flood Hydrograph and can be applied to assess the risk of dam overtopping

Modelling and forecasting fossil fuels, CO2 and electricity prices and their volatilities

In the current uncertain context that affects both the world economy and the energy sector, with the rapid increase in the prices of oil and gas and the very unstable political situation that affects some of the largest raw materials’ producers, there is a need for developing efficient and powerful quantitative tools that allow to model and forecast fossil fuel prices, CO2 emission allowances prices as well as electricity prices. This will improve decision making for all the agents involved in energy issues. Although there are papers focused on modelling fossil fuel prices, CO2 prices and electricity prices, the literature is scarce on attempts to consider all of them together. This paper focuses on both building a multivariate model for the aforementioned prices and comparing its results with those of univariate ones, in terms of prediction accuracy (univariate and multivariate models are compared for a large span of days, all in the first 4 months in 2011) as well as extracting common features in the volatilities of the prices of all these relevant magnitudes. The common features in volatility are extracted by means of a conditionally heteroskedastic dynamic factor model which allows to solve the curse of dimensionality problem that commonly arises when estimating multivariate GARCH models. Additionally, the common volatility factors obtained are useful for improving the forecasting intervals and have a nice economical interpretation. Besides, the results obtained and methodology proposed can be useful as a starting point for risk management or portfolio optimization under uncertainty in the current context of energy markets.

Dynamic D-Vine copula model with applications to Value-at-Risk (VaR)

Regular vine copulas are multivariate dependence models constructed from pair-copulas (bivariate copulas). In this paper, we allow the dependence parameters of the pair-copulas in a D-vine decomposition to be potentially time-varying, following a nonlinear restricted ARMA(1,m) process, in order to obtain a very flexible dependence model for applications to multivariate financial return data. We investigate the dependence among the broad stock market indexes from Germany (DAX), France (CAC 40), Britain (FTSE 100), the United States (S&P 500) and Brazil (IBOVESPA) both in a crisis and in a non-crisis period. We find evidence of stronger dependence among the indexes in bear markets. Surprisingly, though, the dynamic D-vine copula indicates the occurrence of a sharp decrease in dependence between the indexes FTSE and CAC in the beginning of 2011, and also between CAC and DAX during mid-2011 and in the beginning of 2008, suggesting the absence of contagion in these cases. We also evaluate the dynamic D-vine copula with respect to Value-at-Risk (VaR) forecasting accuracy in crisis periods. The dynamic D-vine outperforms the static D-vine in terms of predictive accuracy for our real data sets.

Automotive manufacturers' cost/revenue, financial and risk analysis: projected impact of automobile manufacturing on the plastics industry. Final report.

National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.