SCIESCOPUSQ1
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
SPRINGER, Germany
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT is an academic journal published by SPRINGER (Germany). Identifiers: ISSN 1436-3240, eISSN 1436-3259. Indexed in SCIE, SCOPUS. Metrics: JIF 3.6, CiteScore 7.4, SJR 0.885, SNIP 1.08. Subject areas: CIVIL, ENGINEERING, ENVIRONMENTAL, ENVIRONMENTAL SCIENCES.
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CiteScore
7.40
Scopus citation metric
SJR
0.885
SCImago rank
SNIP
1.08
Source normalized impact
Percentage rank
-
JIF percentile rank
Journal profile
- ISSN
- 1436-3240
- eISSN
- 1436-3259
- Abbreviation
- STOCH ENV RES RISK A
- Publisher
- SPRINGER
- Country
- Germany
Web of Science categories
SCIECIVIL, ENGINEERING, ENVIRONMENTAL, ENVIRONMENTAL SCIENCES, STATISTICS & PROBABILITY, WATER RESOURCES
Scopus ASJC categories
2213 Safety2300 General Environmental Science2304 Environmental Chemistry2305 Environmental Engineering2312 Water Science and Technology
Keywords
Engineering, Environmental | Engineering, Civil | Environmental Sciences | Statistics & Probability | Water Resources
Papers in this journal
Recent papers
- An integrated regionalization framework for incorporating flood seasonality into agricultural flood risk assessments
2026
- Quantifying epistemic uncertainty in deep learning models for quantitative precipitation forecasting using synthetic rainfall fields
2026
- Multi-temporal analysis of runoff evolution in the Poyang lake basin during 1953–2022
2026
- Hybrid data-driven modelling for statistical downscaling of discharge and sediment load in the upper Blue Nile Basin
2026 · 1 citations
- Integrated causal and information-theoretic analysis of teleconnection–dust relationships in Iran: identifying linear pathways and nonlinear dependencies
2026
Most cited papers
- Equifinality of formal (DREAM) and informal (GLUE) Bayesian approaches in hydrologic modeling?
2009 · 494 citations
- Drought forecasting using stochastic models
2005 · 485 citations
- Short-term water quality variable prediction using a hybrid CNN–LSTM deep learning model
2020 · 472 citations
- Maximum likelihood Bayesian averaging of uncertain model predictions
2003 · 444 citations
- Geometric approach to statistical analysis on the simplex
2001 · 419 citations