Non-Parametric Bayesian Networks for Hydrological Studies

2020 ◽  
Author(s):  
Elisa Ragno ◽  
Markus Hrachowitz ◽  
Oswaldo Morales-Nápoles
Keyword(s):  
United States ◽  
Risk Assessment ◽  
Bayesian Networks ◽  
River Discharge ◽  
The United States ◽  
Catchment Scale ◽  
New Information ◽  
Discharge Estimation ◽  
Hydrological Applications ◽  
Non Parametric

<p>Non-Parametric Bayesian Networks (NPBNs) are graphical tools for statistical inference when new information become available. They have been widely used for reliability analysis and risk assessment. However, few hydrological applications can be found in the literature. Consequently, we explore the potential of NPBNs for maximum river discharge estimation by investigating a number of catchments with contrasting climate across the United States. Different networks schematizing river discharge generation processes at the catchment scale are built and analysed. Hydro-meteorological forcings and catchment's attributes are retrieved from Catchment Attributes for Large-Sample Studies (CAMELS). We highlight the benefits but also the challenges encountered in the application of NPBNs for river discharge estimation. Finally, we provide insights on how to overcome some of the difficulties met.</p>

scholarly journals Applying Non-Parametric Bayesian Network to estimate monthly maximum river discharge: potential and challenges

2021 ◽  
Author(s):  
Elisa Ragno ◽  
Markus Hrachowitz ◽  
Oswaldo Morales-Nápoles
Keyword(s):  
River Discharge ◽  
The United States ◽  
Gaussian Copula ◽  
Statistical Characteristics ◽  
Single Element ◽  
Ungauged Basins ◽  
Catchment Scale ◽  
Positive Dependence ◽  
Predictions In Ungauged Basins ◽  
Non Parametric

Abstract. Non-Parametric Bayesian Networks (NPBNs) are graphical tools for statistical inference widely used for reliability analysis and risk assessment. However, few hydrological applications can be found in the literature. We therefore explore here the potential of NPBNs to reproduce catchment-scale hydrological dynamics by investigating 240 catchments with contrasting climate across the United States from the CAMELS dataset. First, two networks, one unsaturated (UN-1) and one saturated network (SN-1) based on hydro-meteorological variables are used to generate monthly maximum river discharge considering the catchment as a single element. Then, the saturated network SN-C, based on SN-1 but additionally including physical catchments attributes, is used to model a group of catchments and infer monthly maximum river discharge in ungauged basins based on the attributes similarity. The results indicate that the UN-1 model is suitable for catchments with a positive dependence between precipitation and river discharge, while the SN-1 model can reproduce discharge also in catchments with negative dependence. Furthermore, in ~40 % of the catchments analysed the SN-1 model can reproduce statistical characteristics of discharge, tested via the Kolmogorov-Smirnov (KS) statistic, and Nash-Sutcliffe Efficiencies (NSE) ≥ 0.5. Such catchments receive precipitation mainly in winter and are located in energy-limited regions at low to moderate elevation. Further, the SN-C model, in which the inference process benefits from catchment similarity, can reproduce river discharge statistics in ~10 % of the catchments analysed. However, in these catchments a common dominant physical attribute was not identified. In this study, we show that, once a NPBNs is defined, it is straightforward to infer discharge, when the remaining variables are known. We also show that it is possible to extend the network itself with additional variables, i.e. going from SN-1 to SN-C. Despite these advantages, the results also suggest that there are considerable challenges in defining a suitable NPBN, in particular for predictions in ungauged basins. These are mainly due to the discrepancies in the time scale of the different physical processes generating discharge, the presence of a “memory” in the system, and the Gaussian-copula assumption used by NPBNs for modelling multivariate dependence.

RAILROAD INVESTING AND THE IMPORTANCE OF FINANCIAL ACCOUNTING INFORMATION IN 1880s AMERICA

2013 ◽  
Vol 40 (2) ◽  
pp. 55-89 ◽  
Author(s):  
Joel E. Thompson
Keyword(s):  
United States ◽  
Information Sources ◽  
Accounting Information ◽  
The United States ◽  
Financial Accounting ◽  
Wall Street ◽  
New Information ◽  
Other Information ◽  
Comprehensive Search ◽  
The Wall Street Journal

This study has a two-fold purpose. First, it seeks to determine the importance of financial accounting information to railroad investors (and speculators) in 1880s America. Second, a further goal is to ascertain what financial accounting information was readily available for use by these investors. Based on a comprehensive search of books of the era, the 1880s were a time of expanding advice for railroad securities holders that required the use of financial accounting information. Furthermore, new information sources arose to help service investors' needs. Statistics by Goodsell and The Wall Street Journal were two such sources. This article reviews these publications along with the ongoing Commercial and Financial Chronicle and Poor's Manual of the Railroads of the United States. Each of these sources helped railroad investors to follow contemporary advice of gathering financial accounting and other information when investing.

The ideological divide in public perceptions of self-driving cars

2020 ◽  
Vol 29 (4) ◽  
pp. 436-451
Author(s):  
Yilang Peng
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Scientific Literacy ◽  
Autonomous Vehicles ◽  
The United States ◽  
Public Perceptions ◽  
New Information ◽  
Nationally Representative ◽  
Self Driving Cars ◽  
Social Conservatism

Applications in artificial intelligence such as self-driving cars may profoundly transform our society, yet emerging technologies are frequently faced with suspicion or even hostility. Meanwhile, public opinions about scientific issues are increasingly polarized along the ideological line. By analyzing a nationally representative panel in the United States, we reveal an emerging ideological divide in public reactions to self-driving cars. Compared with liberals and Democrats, conservatives and Republicans express more concern about autonomous vehicles and more support for restrictively regulating autonomous vehicles. This ideological gap is largely driven by social conservatism. Moreover, both familiarity with driverless vehicles and scientific literacy reduce respondents’ concerns over driverless vehicles and support for regulation policies. Still, the effects of familiarity and scientific literacy are weaker among social conservatives, indicating that people may assimilate new information in a biased manner that promotes their worldviews.

Third-party funding na arbitragem contra Estados: a relativização da imunidade executória na execução da sentença arbitral contra Estados

2019 ◽  
Vol 1 (1) ◽  
pp. 203-234
Author(s):  
Ana Monteiro ◽  
Daniel Ferreira
Keyword(s):  
United States ◽  
Risk Assessment ◽  
Asset Pricing ◽  
The United States ◽  
Third Party ◽  
State Immunity ◽  
The United Kingdom ◽  
Domestic Legislation ◽  
Current Context ◽  
Party Funding

The purpose of this article is to assess the risk for preventing the execution of arbitral awards made against Sovereign States due to the State’s immunity shield. Given the importance of an accurate asset pricing in the business of third-party funding (TPF), the topic entails a particular relevance to the current context of globalized litigation in light of its contribution to the promotion of TPF at the international arbitration community. After reviewing the literature on TPF, on the peculiarities of investment and commercial arbitrations against States and on the evolution of State immunity (also in terms of domestic legislation, considering the local laws passed by the United States, the United Kingdom and Australia), the article aims explore how the funder should incorporate into its risk assessment the risk of not executing awards rendered against Sovereign States.

scholarly journals Risk assessment of cartilaginous fish populations

2014 ◽  
Vol 72 (3) ◽  
pp. 1057-1068 ◽  
Author(s):  
Enric Cortés ◽  
Elizabeth N. Brooks ◽  
Kyle W. Shertzer
Keyword(s):  
United States ◽  
Risk Assessment ◽  
The United States ◽  
Cartilaginous Fish ◽  
Assessment Methods ◽  
Reference Points ◽  
Assessment Process ◽  
Model Complexity ◽  
Stock Assessments ◽  
Demographic Methods

Abstract We review three broad categories of risk assessment methodology used for cartilaginous fish: productivity-susceptibility analysis (PSA), demographic methods, and quantitative stock assessments. PSA is generally a semi-quantitative approach useful as an exploratory or triage tool that can be used to prioritize research, group species with similar vulnerability or risk, and provide qualitative management advice. Demographic methods are typically used in the conservation arena and provide quantitative population metrics that are used to quantify extinction risk and identify vulnerable life stages. Stock assessments provide quantitative estimates of population status and the associated risk of exceeding biological reference points, such as maximum sustainable yield. We then describe six types of uncertainty (process, observation, model, estimation, implementation, and institutional) that affect the risk assessment process, identify which of the three risk assessment methods can accommodate each type of uncertainty, and provide examples mostly for sharks drawn from our experience in the United States. We also review the spectrum of stock assessment methods used mainly for sharks in the United States, and present a case study where multiple methods were applied to the same species (dusky shark, Carcharinus obscurus) to illustrate differing degrees of model complexity and type of uncertainty considered. Finally, we address the common and problematic case of data-poor bycatch species. Our main recommendation for future work is to use Management Strategy Evaluation or similar simulation approaches to explore the effect of different sources of uncertainty, identify the most critical data to satisfy predetermined management objectives, and develop harvest control rules for cartilaginous fish. We also propose to assess the performance of data-poor and -rich methods through stepwise model construction.

scholarly journals A risk assessment of dietary Ochratoxin a in the United States

2017 ◽  
Vol 100 ◽  
pp. 265-273 ◽  
Author(s):  
Nicole J. Mitchell ◽  
Chen Chen ◽  
Jeffrey D. Palumbo ◽  
Andreia Bianchini ◽  
Jack Cappozzo ◽  
...  
Keyword(s):  
United States ◽  
Risk Assessment ◽  
Ochratoxin A ◽  
The United States

scholarly journals The use of cultural risk assessment within the 1994 Tribal land-grant colleges and universities

2020 ◽  
Vol 1 (1) ◽  
pp. 1-3
Author(s):  
Alvin L Young
Keyword(s):  
United States ◽  
Risk Assessment ◽  
Native Americans ◽  
Natural Resources ◽  
Waste Treatment ◽  
The United States ◽  
Decision Makers ◽  
Land Grant ◽  
United States Department ◽  
Cultural Issues

In 1994, the United States Congress established 35 Colleges or Universities on Reservation Lands of the Native Americans throughout the Midwest and Western United States. These new institutions were provided annual funds from the United States Department of Agriculture for education, research and extension, components of the Land-Grant system. Today, issues related to risk assessment and risk management confront tribal decision-makers as they cope with risks, both real and perceived, that include the transportation of hazardous materials through the reservation, the clean-up of contaminated sites within the reservation, the environmental restoration of Federal facilities, the siting of waste treatment, storage, and disposal facilities, the development of tribal mineral and other natural resources, and the construction and operation of industrial and commercial facilities within the reservation. Tribal decision-makers lack Indian-specific epidemiologic, genetic, and cultural information that impact current risk assessment models needed to incorporate tribal cultural issues. There is a need to enhance the science skills of tribal college faculty in assisting tribal councils and tribal colleges in the long-term planning and stewardship of natural resources on their reservations.

Sign in / Sign up

Export Citation Format

Share Document