comparison of different approaches to quantify the reliability of hydrological simulations
Clicks: 97
ID: 254257
2007
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
28.8
/100
97 views
24 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #60 of 65 articles by views in journal of the medical library association
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
The focus of this study was to compare different uncertainty estimation approaches to evaluate their ability to predict the total amount of uncertainty in hydrological model predictions. Three different approaches have been compared. Two of them were based on Monte-Carlo sampling and the third approach was based on fitting a probability model to the error series of an optimized simulation. These approaches have been applied to a lumped and a semi-distributed model variant, to investigate the effects of changes in the model structure on the uncertainty assessment. The probability model was not able to predict the total amount of uncertainty when compared with the Monte-Carlo based approaches. The uncertainty related to the simulation of flood events was systematically underestimated.
| Reference Key |
gattke2007advancescomparison
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;C. Gattke;A. Schumann |
| Journal | journal of the medical library association |
| Year | 2007 |
| DOI |
DOI not found
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.