Non-Stationary Bayesian Modeling of Annual Maximum Floods in a Changing Environment and Implications for Flood Management in the Kabul River Basin, Pakistan
Published 2019 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Non-Stationary Bayesian Modeling of Annual Maximum Floods in a Changing Environment and Implications for Flood Management in the Kabul River Basin, Pakistan
Authors
Keywords
-
Journal
Water
Volume 11, Issue 6, Pages 1246
Publisher
MDPI AG
Online
2019-06-14
DOI
10.3390/w11061246
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Quantifying Changes in Future Intensity-Duration-Frequency Curves Using Multimodel Ensemble Simulations
- (2018) Elisa Ragno et al. WATER RESOURCES RESEARCH
- Scenario analysis of land use change in Kabul River Basin – A river basin with rapid socio-economic changes in Afghanistan
- (2017) Omaid Najmuddin et al. PHYSICS AND CHEMISTRY OF THE EARTH
- Flood modeling and simulations using hydrodynamic model and ASTER DEM—A case study of Kalpani River
- (2016) Sana Ullah et al. Arabian Journal of Geosciences
- Reducing uncertainty in flood frequency analyses: A comparison of local and regional approaches involving information on extreme historical floods
- (2016) K. Halbert et al. JOURNAL OF HYDROLOGY
- A hierarchical Bayesian GEV model for improving local and regional flood quantile estimates
- (2016) Carlos H.R. Lima et al. JOURNAL OF HYDROLOGY
- The influence of non-stationarity in extreme hydrological events on flood frequency estimation
- (2016) Mojca Šraj et al. Journal of Hydrology and Hydromechanics
- Spatial assessment of forest cover and land-use changes in the Hindu-Kush mountain ranges of northern Pakistan
- (2016) Sami Ullah et al. Journal of Mountain Science
- Evaluation of High-Resolution Satellite-Based Real-Time and Post-Real-Time Precipitation Estimates during 2010 Extreme Flood Event in Swat River Basin, Hindukush Region
- (2016) Muhammad Naveed Anjum et al. Advances in Meteorology
- Floodplain Mapping Using HEC-RAS and ArcGIS: A Case Study of Kabul River
- (2015) Muhammad Shahzad Khattak et al. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
- A climate informed model for nonstationary flood risk prediction: Application to Negro River at Manaus, Amazonia
- (2015) Carlos H.R. Lima et al. JOURNAL OF HYDROLOGY
- Non-Stationary Annual Maximum Flood Frequency Analysis Using the Norming Constants Method to Consider Non-Stationarity in the Annual Daily Flow Series
- (2015) Lihua Xiong et al. WATER RESOURCES MANAGEMENT
- Hierarchical Bayesian clustering for nonstationary flood frequency analysis: Application to trends of annual maximum flow in Germany
- (2015) Xun Sun et al. WATER RESOURCES RESEARCH
- A hierarchical Bayesian regional model for nonstationary precipitation extremes in Northern California conditioned on tropical moisture exports
- (2015) Scott Steinschneider et al. WATER RESOURCES RESEARCH
- Precipitation Trends over Time Using Mann-Kendall and Spearman’s rho Tests in Swat River Basin, Pakistan
- (2015) Ijaz Ahmad et al. Advances in Meteorology
- Carbon stocks of different land uses in the Kumrat valley, Hindu Kush Region of Pakistan
- (2015) Adnan Ahmad et al. JOURNAL OF FORESTRY RESEARCH
- Non-stationary extreme value analysis in a changing climate
- (2014) Linyin Cheng et al. CLIMATIC CHANGE
- A general regional frequency analysis framework for quantifying local-scale climate effects: A case study of ENSO effects on Southeast Queensland rainfall
- (2014) Xun Sun et al. JOURNAL OF HYDROLOGY
- A risk-based approach to flood management decisions in a nonstationary world
- (2014) Ana Rosner et al. WATER RESOURCES RESEARCH
- Trends in Extreme Precipitation Events in the Indus River Basin and Flooding in Pakistan
- (2013) Heike Hartmann et al. ATMOSPHERE-OCEAN
- Rainfall–runoff–inundation analysis of the 2010 Pakistan flood in the Kabul River basin
- (2012) Takahiro Sayama et al. HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES
- Flood frequency hydrology: 3. A Bayesian analysis
- (2012) Alberto Viglione et al. WATER RESOURCES RESEARCH
- Accelerating Markov Chain Monte Carlo Simulation by Differential Evolution with Self-Adaptive Randomized Subspace Sampling
- (2011) J. A. Vrugt et al. INTERNATIONAL JOURNAL OF NONLINEAR SCIENCES AND NUMERICAL SIMULATION
- Nonstationarity: Flood Magnification and Recurrence Reduction Factors in the United States1
- (2011) Richard M. Vogel et al. JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
- Floods and flood management in Pakistan
- (2011) Muhammad Atiq Ur Rehman Tariq et al. PHYSICS AND CHEMISTRY OF THE EARTH
- Statistics of extremes in climate change
- (2010) Richard W. Katz CLIMATIC CHANGE
- Comparison of regional and at-site approaches to modelling probabilities of heavy precipitation
- (2010) Jan Kyselý et al. INTERNATIONAL JOURNAL OF CLIMATOLOGY
- Has streamflow changed in the Nordic countries? – Recent trends and comparisons to hydrological projections
- (2010) Donna Wilson et al. JOURNAL OF HYDROLOGY
- Flood frequency analysis for nonstationary annual peak records in an urban drainage basin
- (2009) Gabriele Villarini et al. ADVANCES IN WATER RESOURCES
- Impacts of Urbanization and Climate Variability on Floods in Northeastern Illinois
- (2009) Mohamad I. Hejazi et al. JOURNAL OF HYDROLOGIC ENGINEERING
- On the stationarity of annual flood peaks in the continental United States during the 20th century
- (2009) Gabriele Villarini et al. WATER RESOURCES RESEARCH
- Climate informed flood frequency analysis and prediction in Montana using hierarchical Bayesian modeling
- (2008) Hyun-Han Kwon et al. GEOPHYSICAL RESEARCH LETTERS
- Stationarity Is Dead: Whither Water Management?
- (2008) P. C. D. Milly et al. SCIENCE
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started