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A non-linear and stochastic response surface method for Bayesian estimation of uncertainty in soil moisture simulation from a land surface model
2004
Nonlinear Processes in Geophysics
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This study presents a simple and efficient scheme for Bayesian estimation of uncertainty in soil moisture simulation by a Land Surface Model (LSM). ...
The scheme is assessed within a Monte Carlo (MC) simulation framework based on the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. ...
The first author was supported by a NASA Earth System Science Fellowship. Edited by: B. Sivakumar Reviewed by: two referees ...
doi:10.5194/npg-11-427-2004
fatcat:2cfjngalxffcfnhvynl4s3yxpu
Evaluating the Temporal Dynamics of Uncertainty Contribution from Satellite Precipitation Input in Rainfall-Runoff Modeling Using the Variance Decomposition Method
2018
Remote Sensing
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For this purpose, the variance decomposition method was applied to disaggregate the total streamflow modeling uncertainty into seven components (uncertainties in model input, parameter, structure and their ...
This study provided new insights into the SPE's hydrological utility in the context of uncertainty, being significant for improving the suitability and adequacy of SPE to hydrological application. ...
Acknowledgments: Partial hydrological and meteorological data were provided by hydrological bureau of Jiangxi province, who we shall acknowledge for sharing data. ...
doi:10.3390/rs10121876
fatcat:5bnulh5uhrc2pi6ajjnhj4bch4
Applicability Assessment and Uncertainty Analysis of Multi-Precipitation Datasets for the Simulation of Hydrologic Models
2018
Water
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Hydrologic models are essential tools for understanding hydrologic processes, such as precipitation, which is a fundamental component of the water cycle. ...
The models are calibrated separately with different precipitation products, with the results showing that the CMADS product performs best based on the Nash–Sutcliffe efficiency, including a much better ...
A GLUE uncertainty analysis is applied to assess parameter uncertainty of hydrologic models here. ...
doi:10.3390/w10111611
fatcat:asxebrrz5ndzrjib5un2mwshea
Sensitivity and uncertainty analysis in spatial modelling based on GIS
2000
Agriculture, Ecosystems & Environment
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An example of analysis of a simple hydrologic model is described. ...
This research on GIS-based models, done at ISIS-JRC, provides effective tools for both the assessment of the quality of the model output and the optimisation of the resources to be allocated for the implementation ...
In this way a random sample of size N from the output distribution is obtained, which is then analysed to assess the uncertainty of the model. ...
doi:10.1016/s0167-8809(00)00169-9
fatcat:y7dvkir7sngapou5a2cjdguw2u
Assessing uncertainties in climate change impacts on runoff in Western Mediterranean basins
2015
Proceedings of the International Association of Hydrological Sciences
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The model was calibrated and validated according to a differential split-sample test over a 20-year period and four competing criterions aiming to represent model structural uncertainty based on the concept ...
Runoff simulations were based on a daily conceptual model including a snow module. ...
The model efficiency was evaluated following a differential split-sample test scheme (Klemeš, 1986) aiming to consider climatically contrasted sub-periods over a 20-year simulation period (1986) (1987 ...
doi:10.5194/piahs-371-75-2015
fatcat:wv3ftfli5resbb5st7jpqx2yti
Characterization and Evaluation of Elevation Data Uncertainty in Water Resources Modeling with GIS
2007
Water resources management
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The approach is implemented in a case study with a topography based hydrologic model on an experimental watershed to analyze both aspects of the uncertainty. ...
An ideal approach is to assess the effect of the DEM uncertainty by applying varying resolutions or accuracies of elevation data in the modeling. ...
For environmental applications, a viable approach to assessing the DEM vertical uncertainty is to apply stochastic analysis to the propagation of DEM uncertainty. ...
doi:10.1007/s11269-007-9204-x
fatcat:oppr4gcbfbhtpclniftmgkwlt4
Assessing uncertainties in flood forecasts for decision making: prototype of an operational flood management system integrating ensemble predictions
2009
Natural Hazards and Earth System Sciences
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The use of a computationally efficient hydrological model within a flood management system allows us to compute the hydro-meteorological model chain for all members of the sub-ensemble. ...
Parameter uncertainty of the model is represented by a parameter ensemble, which is a priori generated from a comprehensive uncertainty analysis during model calibration. ...
The research reported in this paper was carried out with support from the German Ministry for Education and Research (BMBF) under the initiative "Risk Management of Extreme Flood Events (RIMAX)". ...
doi:10.5194/nhess-9-1529-2009
fatcat:njq7ngaoo5cqbdlb6t7h3aooyi
Hydrological modelling in a changing world
2011
Progress in physical geography
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Top-down methods and analysis of spatial gradients of a variable of interest, instead of temporal gradients (a method termed 'Trading space for time') show much promise for validating more complex model ...
Understanding hydrological processes and how they respond to change, along with quantification of parameter estimation and modelling process uncertainty will continue to be active areas of research within ...
Funding to support the first author's visit to the University of Technology, Vienna, as part of this work was provided by the Australian Academy of Science International Research Staff Exchange Scheme ...
doi:10.1177/0309133311402550
fatcat:3er46cjemzhy3k4rjzmyy3qxvm
Modelling catchment inflows into Lake Victoria: uncertainties in rainfall–runoff modelling for the Nzoia River
2011
Hydrological Sciences Journal
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Keith Beven for introducing the first author to the concept of dealing with uncertainty in environmental modelling, which formed the basis for this work. ...
Acknowledgements This work is part of the PhD programme of the first author, with sponsorship of the Swedish International Development Cooperation Agency (Sida) through the Department for Research Cooperation ...
the parameters based
on 500 000 model runs for a likelihood threshold of
NS ≥ 0.6. ...
doi:10.1080/02626667.2011.610323
fatcat:l3dy53gizbaivc2xk6f6ka67hm
Challenges in modeling and predicting floods and droughts: A review
2021
WIREs Water
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Modeling challenges arise in frequency analysis, stochastic, hydrological, earth system, and hydraulic modeling. ...
continuous stochastic models or non-stationary models, and obtaining stakeholder feedback. ...
Continuous stochastic models: We need to develop continuous stochastic simulation approaches for joint drought and flood assessments because event-based approaches currently only focus on one type of extreme ...
doi:10.1002/wat2.1520
fatcat:wg5nmeo36feehebxbwjwheeiom
Downscaling transient climate change using a Neyman–Scott Rectangular Pulses stochastic rainfall model
2010
Journal of Hydrology
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The provision of locally-relevant transient climate change scenarios for use as input to hydrological models of both water quality and quantity will ultimately provide a valuable resource for planning ...
An ensemble of 100 continuous daily rainfall time series, with steadily varying stochastic properties which model these projections of transient climate change, was then simulated using a new transient ...
Some of these uncertainties have been analysed by running perturbedphysics climate model simulations in which model parameters are varied within their range of uncertainty (e.g. ...
doi:10.1016/j.jhydrol.2009.10.031
fatcat:kddqrvju5bbnlh7dqbpudz7ugq
Describing the catchment-averaged precipitation as a stochastic process improves parameter and input estimation
2016
Water Resources Research
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Rainfall input uncertainty is one of the major concerns in hydrological modeling. ...
We formulate the average precipitation over the watershed as a stochastic input process (SIP) and, together with a model of the hydrosystem, include it in the likelihood function. ...
The authors are very grateful to Tobias Doppler for data collection and compilation, and Hans Rudolf K€ unsch for stimulating discussions. ...
doi:10.1002/2015wr017871
fatcat:mr2rcapwuranddi6cbjo2dyrom
Ensemble forecasting system for the management of the Senegal River discharge: application upstream the Manantali dam
2020
Applied Water Science
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A number of 61 forecasted rainfall time series are then used to run already calibrated hydrological model to produce hydrological ensemble forecasts called raw ensemble. ...
Cyclical errors that are within rainfall cyclical behavior from the stochastic modeling are settled and processed using multivariate statistic tools to dress a rainfall ensemble forecast. ...
Statistic tools such as stochastic processes and resampling methods based on estimating of a kernel density for interested data are often used in hydrological fields (Lall et al. 1996; Wang et al. 2005 ...
doi:10.1007/s13201-020-01199-y
fatcat:sjrs6x65m5g3jl63bm5a2q4dfu
A continuous modelling approach for design flood estimation on sub-daily time scale
2019
Hydrological Sciences Journal
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In this study, a continuous hydrological modelling approach on an hourly time scale, driven by a multi-site weather generator in combination with a k-nearest neighbour resampling procedure, based on the ...
Design flood estimation is an essential part of flood risk assessment. ...
Disclosure statement No potential conflict of interest was reported by the authors.
Funding ...
doi:10.1080/02626667.2019.1593419
fatcat:h5obcm2yljcg5cq6wyivktii4y
Probabilistic Groundwater Flow, Particle Tracking and Uncertainty Analysis for Environmental Receptor Vulnerability Assessment of a Coal Seam Gas Project
2020
Water
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stochastic contaminant transport modelling. ...
A probabilistic particle tracking approach was developed as a computationally efficient screening analysis of contamination pathways for a planned CSG development near Narrabri in northern New South Wales ...
The authors also acknowledge the Bioregional Assessment Programme for providing the initial version of the groundwater model and spatial data used in this study. ...
doi:10.3390/w12113177
fatcat:oqldhrz6x5cjncb5ghzm5ruj3e
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