Fuzzy-probabilistic calculations of water-balance uncertainty
Abstract
Hydrogeological systems are often characterized by imprecise, vague, inconsistent, incomplete, or subjective information, which may limit the application of conventional stochastic methods in predicting hydrogeologic conditions and associated uncertainty. Instead, redictions and uncertainty analysis can be made using uncertain input parameters expressed as probability boxes, intervals, and fuzzy numbers. The objective of this paper is to present the theory for, and a case study as an application of, the fuzzyprobabilistic approach, ombining probability and possibility theory for simulating soil water balance and assessing associated uncertainty in the components of a simple waterbalance equation. The application of this approach is demonstrated using calculations with the RAMAS Risk Calc code, to ssess the propagation of uncertainty in calculating potential evapotranspiration, actual evapotranspiration, and infiltration-in a case study at the Hanford site, Washington, USA. Propagation of uncertainty into the results of water-balance calculations was evaluated by hanging he types of models of uncertainty incorporated into various input parameters. The results of these fuzzy-probabilistic calculations are compared to the conventional Monte Carlo simulation approach and estimates from field observations at the Hanford site.
- Authors:
- Publication Date:
- Research Org.:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Sponsoring Org.:
- Earth Sciences Division
- OSTI Identifier:
- 981522
- Report Number(s):
- LBNL-3004E
TRN: US201013%%761
- DOE Contract Number:
- DE-AC02-05CH11231
- Resource Type:
- Journal Article
- Journal Name:
- Stochastic Environmental Research and Risk Analysis
- Additional Journal Information:
- Journal Name: Stochastic Environmental Research and Risk Analysis
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54; 58; BALANCES; HAZARDS; POTENTIALS; PROBABILITY; SIMULATION; SOILS; USA; WASHINGTON; WATER
Citation Formats
Faybishenko, B. Fuzzy-probabilistic calculations of water-balance uncertainty. United States: N. p., 2009.
Web.
Faybishenko, B. Fuzzy-probabilistic calculations of water-balance uncertainty. United States.
Faybishenko, B. 2009.
"Fuzzy-probabilistic calculations of water-balance uncertainty". United States. https://www.osti.gov/servlets/purl/981522.
@article{osti_981522,
title = {Fuzzy-probabilistic calculations of water-balance uncertainty},
author = {Faybishenko, B},
abstractNote = {Hydrogeological systems are often characterized by imprecise, vague, inconsistent, incomplete, or subjective information, which may limit the application of conventional stochastic methods in predicting hydrogeologic conditions and associated uncertainty. Instead, redictions and uncertainty analysis can be made using uncertain input parameters expressed as probability boxes, intervals, and fuzzy numbers. The objective of this paper is to present the theory for, and a case study as an application of, the fuzzyprobabilistic approach, ombining probability and possibility theory for simulating soil water balance and assessing associated uncertainty in the components of a simple waterbalance equation. The application of this approach is demonstrated using calculations with the RAMAS Risk Calc code, to ssess the propagation of uncertainty in calculating potential evapotranspiration, actual evapotranspiration, and infiltration-in a case study at the Hanford site, Washington, USA. Propagation of uncertainty into the results of water-balance calculations was evaluated by hanging he types of models of uncertainty incorporated into various input parameters. The results of these fuzzy-probabilistic calculations are compared to the conventional Monte Carlo simulation approach and estimates from field observations at the Hanford site.},
doi = {},
url = {https://www.osti.gov/biblio/981522},
journal = {Stochastic Environmental Research and Risk Analysis},
number = ,
volume = ,
place = {United States},
year = {Thu Oct 01 00:00:00 EDT 2009},
month = {Thu Oct 01 00:00:00 EDT 2009}
}