Prospects for the open treatment of uncertainty in environmental research
Data processing ; Decision making process ; Environment ; Forecast ; Model ; Research ; Risk ; Uncertainty
. A review of current treatments of uncertainty is followed by an analysis of the source-based approach to assessing uncertainty. Prospects for the open treatment of uncertainty are then discussed in terms of circumventing the three ‘myths of uncertainty
This paper argues for more open treatments of uncertainty in environmental research. Such openness requires an appreciation of the social and psychological causes of uncertainty, the role of observations as imperfect and contingent expressions
of visible events, and the myriad ways in which scientific information can be misinterpreted, misused, or sidelined in environmental decision-making. The paper begins with a discussion of the nature and causes of uncertainty in environmental research
Research policy and review 34 : the development of ideas of uncertainty representation
. This review of the literature highlights the need for additional research on a number of topics, and the synthesis of new approaches to uncertainty with more traditional decision analysis techniques.
Numerous ideas are adressed, which can supplement the basic approaches to uncertainty associated with objective and subjective probability. They are gleaned from many disciplines, including philosophy, mathematics, and artificial intelligence
The representation of knowledge and uncertainty in database of GIS geological maps
In this paper an analysis is carried out on the phases that characterize the acquisition of structural-geological knowledge and related different levels of uncertainty. Methodologies to represent geological uncertainty in GIS databases
Uncertainty in regional climate modelling : a review
Climate ; Climatic change ; Global change ; Greenhouse effect ; Human impact ; Model ; Regional climate ; Scale ; Statistical bias ; Uncertainty
. In the second part of the discussion, uncertainties associated with climate modelling are explored with emphasis on the implications for regional scale analysis. Such uncertainties include parameterizations and resolutions, initial and boundary conditions
In this paper, the cascade of uncertainty from emissions scenario to global model to regional climate model is explored. The initial part of the discussion focuses on uncertainties associated with human action, such as emissions of greenhouse gases
inherited from the driving global model, intermodel variability and issues surrounding the validation or verification of models. The paper concludes with a critique of approaches employed to quantify or cater for uncertainties highlighting the strengths
Advances in the study of uncertainty quantification of large-scale hydrological modeling system
Algorithm ; Concept ; Hydrology ; Land atmosphere interaction ; Methodology ; Model ; Quantitative analysis ; Uncertainty
This paper systematically reviewed the recent advances in the study of the uncertaintyanalysis approaches in the large-scale complex hydrological model on the basis of uncertainty sources (input data and parameters, model structure, analysis method
and the initial and boundary conditions). Also, the shortcomings and insufficiencies in the uncertaintyanalysis for complex hydrological models are pointed out. And then a new uncertainty quantification platform PSUADE and its uncertainty quantification methods
were introduced, which will be a powerful tool and platform for uncertaintyanalysis of large-scale complex hydrological models. Finally, some future perspectives on uncertainty quantification are put forward.
The AA. propose a statistical model for incorporating location error into spatial data analysis. They investigate the effect of location error on the spatial lag, the covariance function, and optimal spatial linear prediction.
Entropy ; Estimation ; Household ; Methodology ; Model ; Modelling ; Population ; Spatial analysis ; Spatial distribution ; Tennessee ; Uncertainty ; United States of America
This article presents a new dasymetric methodology—the penalized maximum entropy dasymetric model that enables sources of uncertainty to be represented and modeled. It allows a rich array of data to be included, with disparate spatial resolutions
, attribute resolutions, and uncertainties. It also allows a rich array of data to be included, with disparate spatial resolutions, attribute resolutions, and uncertainties. It concludes by presenting an application that that includes household-level survey
Uncertainties of public opinion on energy consumption across enlarged European Union : an explanatory analysis
concerned with their opinion on energy politics. The analysis in this paper indicates that in view of the current public opinion the development of energy policies at the EU level is seemingly also beset by considerable uncertainties and risks of insuficient
This paper presents a global dataset for soil erodibility factor, (K), compiled from the literature and investigates the predictability of K and the related uncertainty using soil textural parameters and organic matter content.
Deterministic complexity (chaos) may be common in geomorphic systems, but traditional definitions may have limited practical utility for empirical geomorphology. Further, chaos analysis depends on distinguishing deterministic complexity from
uncertainty is more useful in process geomorphology than that of chaos.
Target-density weighting interpolation and uncertainty evaluation for temporal analysis of census data
Error ; Information system ; Interpolation ; Population distribution ; Regression analysis ; Spatial analysis ; Spatial distribution ; United States of America
Decision making and uncertainty : Bayesian analysis of potential flood heights
Coastal environment ; Decision making process ; Flood ; Forecast ; Geographical information system ; Global change ; Methodology ; Monte Carlo analysis ; Natural hazards ; Sea level ; Spatial analysis
This research examines decision making about flooding by joining geographic information system (GIS) methods and spatial analysis to implement Bayesian decision theory. This paper demonstrates the procedure as applied by a hypothetical decision
the decision maker to ascertain the potential value of additional survey information in terms of its ability to reduce uncertainty about flood damage.
Uncertainty assessment of soil erodibility factor for revised universal soil loss equation
values from a set of soil samples. A case study, in Bell and Coryell Counties 256 km southwest of Dallas, for spatial prediction and uncertaintyanalysis of soil erodibility was carried out by a sequential Gaussian simulation procedure in order to support
The AA. discuss the use of published soil erodibility values from the national soil survey in spatial prediction of soil loss by traditional methods, and assess the uncertainty of the published values by comparing them with the soil erodibility