Use of Data Driven Techniques for Short Lead Time Streamflow Forecasting in Mahanadi basin

Streamflow forecasts at daily time scale are necessary for effective management of water resources systems. Typical applications include flood control, water quality management, water supply to multiple stakeholders, hydropower and irrigation systems. Conventionally physically based conceptual models and data-driven models are used for forecasting streamflows. Conceptual models require detailed understanding of physical processes governing the system being modeled. Major constraints in developing effective conceptual models are sparse hydrometric gauge network and short historical records that limit our understanding of physical processes. On the other hand, data-driven models rely solely on previous hydrological and meteorological data without directly taking into account the underlying physical processes. Among various data driven models Auto Regressive Integrated Moving Average (ARIMA), Artificial Neural Networks (ANNs) are most widely used techniques. The present study assesses performance of ARIMA and ANNs methods in arriving at one-to seven-day ahead forecast of daily streamflows at Basantpur streamgauge site that is situated at upstream of Hirakud Dam in Mahanadi river basin, India. The ANNs considered include Feed-Forward back propagation Neural Network (FFNN) and Radial Basis Neural Network (RBNN). Daily streamflow forecasts at Basantpur site find use in management of water from Hirakud reservoir. (C) 2015 The Authors. Published by Elsevier B.V.

Probabilistic Models for Forecasting Earthquakes in the Northeast Region of India

Northeast India and its adjoining areas are characterized by very high seismic activity. According to the Indian seismic code, the region falls under seismic zone V, which represents the highest seismic-hazard level in the country. This region has experienced a number of great earthquakes, such as the Assam (1950) and Shillong (1897) earthquakes, that caused huge devastation in the entire northeast and adjacent areas by flooding, landslides, liquefaction, and damage to roads and buildings. In this study, an attempt has been made to find the probability of occurrence of a major earthquake (M-w > 6) in this region using an updated earthquake catalog collected from different sources. Thereafter, dividing the catalog into six different seismic regions based on different tectonic features and seismogenic factors, the probability of occurrences was estimated using three models: the lognormal, Weibull, and gamma distributions. We calculated the logarithmic probability of the likelihood function (ln L) for all six regions and the entire northeast for all three stochastic models. A higher value of ln L suggests a better model, and a lower value shows a worse model. The results show different model suits for different seismic zones, but the majority follows lognormal, which is better for forecasting magnitude size. According to the results, Weibull shows the highest conditional probabilities among the three models for small as well as large elapsed time T and time intervals t, whereas the lognormal model shows the lowest and the gamma model shows intermediate probabilities. Only for elapsed time T = 0, the lognormal model shows the highest conditional probabilities among the three models at a smaller time interval (t = 3-15 yrs). The opposite result is observed at larger time intervals (t = 15-25 yrs), which show the highest probabilities for the Weibull model. However, based on this study, the IndoBurma Range and Eastern Himalaya show a high probability of occurrence in the 5 yr period 2012-2017 with >90% probability.

Testing the Forecasting Performance of Ibex 35 Option-implied Risk-neutral Densities

Published also as: Documento de Trabajo Banco de España 0504/2005.

A review of travel time estimation and forecasting for advanced traveler information systems

Providing on line travel time information to commuters has become an important issue for Advanced Traveler Information Systems and Route Guidance Systems in the past years, due to the increasing traffic volume and congestion in the road networks. Travel time is one of the most useful traffic variables because it is more intuitive than other traffic variables such as flow, occupancy or density, and is useful for travelers in decision making. The aim of this paper is to present a global view of the literature on the modeling of travel time, introducing crucial concepts and giving a thorough classification of the existing tech- niques. Most of the attention will focus on travel time estimation and travel time prediction, which are generally not presented together. The main goals of these models, the study areas and methodologies used to carry out these tasks will be further explored and categorized.

Forecasting Climate Impacts on Future Production of Commercially Exploited Fish and Shellfish

Foreword [pdf, < 0.1 MB] Acknowledgements PHASE 1 [pdf, 0.2 MB] Summary of the PICES/NPRB Workshop on Forecasting Climate Impacts on Future Production of Commercially Exploited Fish and Shellfish (July 19–20, 2007, Seattle, U.S.A.) Background Links to Other Programs Workshop Format Session I. Status of climate change scenarios in the PICES region Session II. What are the expected impacts of climate change on regional oceanography and what are some scenarios for these drivers for the next 10 years? Session III. Recruitment forecasting Session IV. What models are out there? How is climate linked to the model? Session V. Assumptions regarding future fishing scenarios and enhancement activities Session VI Where do we go from here? References Appendix 1.1 List of Participants PHASE 2 [pdf, 0.7 MB] Summary of the PICES/NPRB Workshop on Forecasting Climate Impacts on Future Production of Commercially Exploited Fish and Shellfish (October 30, 2007, Victoria, Canada) Background Workshop Agenda Forecast Feasibility Format of Information Modeling Approaches Coupled bio-physical models Stock assessment projection models Comparative approaches Similarities in Data Requests Opportunities for Coordination with Other PICES Groups and International Efforts BACKGROUND REPORTS PREPARED FOR THE PHASE 2 WORKSHOP Northern California Current (U.S.) groundfish production by Melissa Haltuch Changes in sablefish (Anoplopoma fimbria) recruitment in relation to oceanographic conditions by Michael J. Schirripa Northern California Current (British Columbia) Pacific cod (Gadus macrocephalus) production by Caihong Fu and Richard Beamish Northern California Current (British Columbia) sablefish (Anoplopoma fimbria) production by Richard Beamish Northern California Current (British Columbia) pink (Oncorhynchus gorbuscha) and chum (O. keta) salmon production by Richard Beamish Northern California Current (British Columbia) ocean shrimp (Pandalus jordani) production by Caihong Fu Alaska salmon production by Anne Hollowed U.S. walleye pollock (Theragra chalcogramma) production in the eastern Bering Sea and Gulf of Alaska by Kevin Bailey and Anne Hollowed U.S. groundfish production in the eastern Bering Sea by Tom Wilderbuer U.S. crab production in the eastern Bering Sea by Gordon H. Kruse Forecasting Japanese commercially exploited species by Shin-ichi Ito, Kazuaki Tadokoro and Yasuhiro Yamanka Russian fish production in the Japan/East Sea by Yury Zuenko, Vladimir Nuzhdin and Natalia Dolganova Chum salmon (Oncorhynchus keta) production in Korea by Sukyung Kang, Suam Kim and Hyunju Seo Jack mackerel (Trachurus japonicus) production in Korea by Jae Bong Lee and Chang-Ik Zhang Chub mackerel (Scomber japonicus) production in Korea by Jae Bong Lee, Sukyung Kang, Suam Kim, Chang-Ik Zhang and Jin Yeong Kim References Appendix 2.1 List of Participants PHASE 3 [pdf, < 0.1 MB] Summary of the PICES Workshop on Linking Global Climate Model Output to (a) Trends in Commercial Species Productivity and (b) Changes in Broader Biological Communities in the World’s Oceans (May 18, 2008, Gijón, Spain) Appendix 3.1 List of Participants Appendix 3.2 Workshop Agenda (Document contains 101 pages)

Extreme events and ecological forecasting

Almost all extreme events lasting less than several weeks that significantly impact ecosystems are weather related. This review examines the response of estuarine systems to intense short-term perturbations caused by major weather events such as hurricanes. Current knowledge concerning these effects is limited to relatively few studies where hurricanes and storms impacted estuaries with established environmental monitoring programs. Freshwater inputs associated with these storms were found to initially result in increased primary productivity. When hydrographic conditions are favorable, bacterial consumption of organic matter produced by the phytoplankton blooms and deposited during the initial runoff event can contribute to significant oxygen deficits during subsequent warmer periods. Salinity stress and habitat destruction associated with freshwater inputs, as well as anoxia, adversely affect benthic populations and fish. In contrast, mobile invertebrate species such as shrimp, which have a short life cycle and the ability to migrate during the runoff event, initially benefit from the increased primary productivity and decreased abundance of fish predators. Events studied so far indicate that estuaries rebound in one to three years following major short-term perturbations. However, repeated storm events without sufficient recovery time may cause a fundamental shift in ecosystem structure (Scavia et al. 2002). This is a scenario consistent with the predicted increase in hurricanes for the east coast of the United States. More work on the response of individual species to these stresses is needed so management of commercial resources can be adjusted to allow sufficient recovery time for affected populations.

Ecological forecasting: new tools for coastal and marine ecosystem management

Policy makers, natural resource managers, regulators, and the public often call on scientists to estimate the potential ecological changes caused by both natural and human-induced stresses, and to determine how those changes will impact people and the environment. To develop accurate forecasts of ecological changes we need to: 1) increase understanding of ecosystem composition, structure, and functioning, 2) expand ecosystem monitoring and apply advanced scientific information to make these complex data widely available, and 3) develop and improve forecast and interpretative tools that use a scientific basis to assess the results of management and science policy actions. (PDF contains 120 pages)

Wind-driven desertification: process modeling, remote monitoring, and forecasting

Arid and semiarid landscapes comprise nearly a third of the Earth's total land surface. These areas are coming under increasing land use pressures. Despite their low productivity these lands are not barren. Rather, they consist of fragile ecosystems vulnerable to anthropogenic disturbance.

The purpose of this thesis is threefold: (I) to develop and test a process model of wind-driven desertification, (II) to evaluate next-generation process-relevant remote monitoring strategies for use in arid and semiarid regions, and (III) to identify elements for effective management of the world's drylands.

In developing the process model of wind-driven desertification in arid and semiarid lands, field, remote sensing, and modeling observations from a degraded Mojave Desert shrubland are used. This model focuses on aeolian removal and transport of dust, sand, and litter as the primary mechanisms of degradation: killing plants by burial and abrasion, interrupting natural processes of nutrient accumulation, and allowing the loss of soil resources by abiotic transport. This model is tested in field sampling experiments at two sites and is extended by Fourier Transform and geostatistical analysis of high-resolution imagery from one site.

Next, the use of hyperspectral remote sensing data is evaluated as a substantive input to dryland remote monitoring strategies. In particular, the efficacy of spectral mixture analysis (SMA) in discriminating vegetation and soil types and detennining vegetation cover is investigated. The results indicate that hyperspectral data may be less useful than often thought in determining vegetation parameters. Its usefulness in determining soil parameters, however, may be leveraged by developing simple multispectral classification tools that can be used to monitor desertification.

Finally, the elements required for effective monitoring and management of arid and semiarid lands are discussed. Several large-scale multi-site field experiments are proposed to clarify the role of wind as a landscape and degradation process in dry lands. The role of remote sensing in monitoring the world's drylands is discussed in terms of optimal remote sensing platform characteristics and surface phenomena which may be monitored in order to identify areas at risk of desertification. A desertification indicator is proposed that unifies consideration of environmental and human variables.

The Voting Rights Act, Shelby County, and Redistricting: Improving Estimates of Racially Polarized Voting in a Multiple-Election Context

The Supreme Court’s decision in Shelby County has severely limited the power of the Voting Rights Act. I argue that Congressional attempts to pass a new coverage formula are unlikely to gain the necessary Republican support. Instead, I propose a new strategy that takes a “carrot and stick” approach. As the stick, I suggest amending Section 3 to eliminate the need to prove that discrimination was intentional. For the carrot, I envision a competitive grant program similar to the highly successful Race to the Top education grants. I argue that this plan could pass the currently divided Congress.

Without Congressional action, Section 2 is more important than ever before. A successful Section 2 suit requires evidence that voting in the jurisdiction is racially polarized. Accurately and objectively assessing the level of polarization has been and continues to be a challenge for experts. Existing ecological inference methods require estimating polarization levels in individual elections. This is a problem because the Courts want to see a history of polarization across elections.

I propose a new 2-step method to estimate racially polarized voting in a multi-election context. The procedure builds upon the Rosen, Jiang, King, and Tanner (2001) multinomial-Dirichlet model. After obtaining election-specific estimates, I suggest regressing those results on election-specific variables, namely candidate quality, incumbency, and ethnicity of the minority candidate of choice. This allows researchers to estimate the baseline level of support for candidates of choice and test whether the ethnicity of the candidates affected how voters cast their ballots.

O direito ao entretenimento na função social da cidade

O art. 6 da Constituição Federal estabelece que o lazer é um direito social. A referida proteção constitucional conquistada com a Carta Cidadã de 1988, somada a previsão internacional da Declaração Universal dos Direitos Humanos por si só ensejam a elaboração de estudo detalhado do tema. Além disso, a ascensão de uma nova classe média com maior poder de consumo, a efervescência da terceira revolução industrial e a eleição do Brasil, e especificamente da cidade do Rio de Janeiro, como sede de diversos eventos de entretenimento internacional, são os argumentos que introduzem o estudo a cidade e a satisfação do direito ao (do) entretenimento. Assim, a partir da conceituação de entretenimento à luz da comparação com as outras ciências humanas e o direito alienígena, enseja-se a propositura de um conceito próprio para o ordenamento jurídico pátrio, que delimita os deveres do Estado na satisfação deste direito, e na regulação e fomento da atividade econômica que circundam o lazer, denominada indústria do entretenimento. O estudo aborda ainda a compreensão de que a cidade pode ser concebida como oikos do entretenimento, permitindo uma análise das formas como as cidades devem comportar conteúdo mínimo que viabilize a satisfação do lazer. Ao final, tendo por paradigma a cidade do Rio de Janeiro, se analisa como determinadas cidade podem possuir características geográficas, históricas e culturais próprias que permitem que sua vocação econômica seja a satisfação do entretenimento em nível internacional.