Razi Sheikholeslami: Publications

Publications

Refereed Journal Papers

Global patterns and key drivers of stream nitrogen concentration: A machine learning approach.
R. Sheikholesl.ami, J.W. Hall. (2023).

Science of The Total Environment, 868, 161623. DOI:10.1016/j.scitotenv.2023.161623
Unpacking the modelling process via sensitivity auditing.
S. Lo Piano, R. Sheikholeslami, A. Puy, A. Saltelli. (2022).

Futures; 144, 103041, DOI:10.1016/j.futures.2022.103041
The delusive accuracy of global irrigation water withdrawal estimates.
A. Puy, R. Sheikholeslami, H.V. Gupta, et al. (2022).

Nature Communications; 13, 3183, DOI:10.1038/s41467-022-30731-8
Peering into agricultural rebound phenomenon using a global sensitivity analysis approach.
M. Ghoreishi, R. Sheikholeslami, A. Elshorbagy, S. Razavi, K. Belcher. (2021).

Journal of Hydrology; 602, 126739, DOI:10.1016/j.jhydrol.2021.126739
The future of sensitivity analysis: an essential discipline for systems modeling and policy support.
S. Razavi, A. Jakeman, A. Saltelli, et al. (2021).

Environmental Modelling & Software; 137, 104954, DOI:10.1016/j.envsoft.2020.104954
VISCOUS: Variance-based sensitivity analysis using copulas for efficient identification of dominant hydrological processes.
R. Sheikholeslami, S. Gharari, S.M. Papalexiou, M.P. Clark. (2021).

Water Resources Research; 57, e2020WR028435,DOI:10.1029/2020WR028435
A fresh look at variography: measuring dependence and possible sensitivities across geophysical systems from any given data.
R. Sheikholeslami, S. Razavi. (2020).

Geophysical Research Letters; 47, e2020GL089829, DOI:10.1029/2020GL089829
. Global sensitivity analysis for high dimensional problems: how to objectively group factors and measure robustness and convergence while reducing computational cost.
R. Sheikholeslami, S. Razavi, H.V. Gupta, W. Becker, A. Haghnegahdar. (2019).

Environmental Modelling and Software; 111:282-299, DOI:10.1016/j.envsoft.2018.09.002
What should we do when a model crashes? Recommendations for global sensitivity analysis of Earth and environmental systems models.
R. Sheikholeslami, S. Razavi, A. Haghnegahdar. (2019).

Geoscientific Model Development; 12:4275-4296, DOI:10.5194/gmd-12-4275-2019
Avoiding the guise of an anonymous review, Eos, Transactions.
R. Sheikholeslami, S. Razavi. (2018).

American Geophysical Union, 99, DOI:10.1029/2018EO098217. Published on 09 May 2018.
Multiple factors that shaped sustainability science journal: a 10-year review.
P. Rokaya, R. Sheikholeslami, S. Kurkute, M. Nazarbakhsh, F. Zhang, M.Gail. Reed. (2017).

Sustainability Science; 12(6):855-868, DOI:10.1007/s11625-017-0495-4
Improved understanding of river ice processes using global sensitivity analysis approaches.
R. Sheikholeslami, F. Yassin, K-E. Lindenschmidt, S. Razavi. (2017).

Journal of Hydrologic Engineering; 22(11):04017048, DOI:10.1061/(ASCE)HE.1943-5584.0001574
Progressive Latin hypercube sampling: An efficient approach for robust samplingbased analysis of environmental models.
R. Sheikholeslami, S. Razavi. (2017)

Environmental Modelling and Software; 93:109-126, DOI:10.1016/j.envsoft.2017.03.010
Developed swarm optimizer: A new method for sizing optimization of water distribution systems.
R. Sheikholeslami, S. Talatahari. (2016).

Journal of Computing in Civil Engineering; 30(5):04016005, DOI:10.1061/(ASCE)CP.1943-5487.0000552
A hybrid cuckoo–harmony search algorithm for optimal design of water distribution systems.
R. Sheikholeslami, A.C. Zecchin, F. Zheng, S. Talatahari. (2015)

Journal of Hydroinformatics; 18(3):544-563, DOI:10.2166/hydro.2015.174
Vulnerability assessment of water distribution networks: graph theory method.
R. Sheikholeslami, A. Kaveh. (2015).

International Journal of Optimization in Civil Engineering; 5(3): 283-99.
An improved firefly algorithm with harmony search scheme for optimization of water distribution systems.
A. Tahershamsi, A. Kaveh, R. Sheikholeslami, S. Kazemzadeh Azad. (2014).

Scientia Iranica; 21(5):1591-1607.
Application of charged system search algorithm to water distribution networks optimization.
R. Sheikholeslami, A. Kaveh, A. Tahershamsi, S. Talatahari. (2014).

International Journal of Optimization in Civil Engineering; 4(1): 41-58.
Chaotic swarming of particles: A new method for size optimization of truss structures.
A. Kaveh, R. Sheikholeslami, S. Talatahari, M. Keshvari-Ilkhichi. (2014).

Advances in Engineering Software; 67:136-147, DOI:10.1016/j.advengsoft.2013.09.006
A survey of chaos embedded metaheuristic algorithms.
R. Sheikholeslami, A. Kaveh. (2013).

International Journal of Optimization in Civil Engineering; 3(4):617-33.
Optimal parameter estimation for Muskingum model using a CSS-PSO method.
S. Talatahari, R. Sheikholeslami, B. Farahmand Azar, H. Daneshpajouh. (2013).

Advances in Mechanical Engineering; 5:480954, DOI:10.1155/2013/480954
Engineering design optimization using chaotic enhanced charged system search algorithms.
S. Talatahari, A. Kaveh, R. Sheikholeslami. (2012).

Acta Mechanica; 223(10):2269-2285, DOI:10.1007/s00707-012-0704-2
Chaotic imperialist competitive algorithm for optimum design of truss structures.
S. Talatahari, A. Kaveh, R. Sheikholeslami. (2012).

Structural and Multidisciplinary Optimization; 46(3):355-67, DOI:10.1007/s00158-011-0754-4
Imperialist competitive algorithm combined with chaos for global optimization.
S. Talatahari, B. Farahmand Azar, R. Sheikholeslami, A. H. Gandomi. (2011).

Communications in Nonlinear Science and Numerical Simulation; 17:1312-1319, DOI:10.1016/j.cnsns.2011.08.021
Big bang-big crunch algorithm for least-cost design of water distribution systems.
A. Tahershamsi, A. Kaveh, R. Sheikholeslami, S. Talatahari. (2012).

International Journal of Optimization in Civil Engineering; 2(1):70-79.
Optimization to identify Muskingum model parameters using imperialist competitive algorithm.
A. Tahershamsi, R. Sheikholeslami. (2011).

International Journal of Optimization in Civil Engineering; 1(3):473-482.

Conference Publications/Presentations

Quantifying the Influence of Data Uncertainty on Manure Phosphorus Runoff Simulations: A Global Analysis of Major River Basins.
R. Sheikholeslami and K. Golkar.

AGU Fall Meeting, Dec 2023.
Estimating Variance-Based Sensitivity Indices Using Random Forests: A Convergence Analysis.
R. Sheikholeslami, M. Khanjani and S. Razavi.

AGU Fall Meeting, Dec 2023.
Uncertainty Quantification and Apportionment of Water Quality Index in South Florida Watershed.
F. Jahangiri, R. Sheikholeslami.

AGU Fall Meeting, Dec 2022.
Hall, et al. How Certain Are We about the Model-based Estimations of Global Irrigation Water Withdrawal?
A. Puy, R. Sheikholeslami, H. V. Gupta, J.W.

EGU General Assembly, May 2022.
The Role of Livestock in Nitrogen Pollution of Large River Basins: A Machine Learning- based Assessment.
R. Sheikholeslami and J.W. Hall.

EGU General Assembly, May 2022.
Decision-Making Under Deep Uncertainty: A Brief Review.
R. Sousanabadi Farahani, F. Jahangiri and R. Sheikholeslami.

13th National Congress on Civil Engineering Isfahan, Iran, May 10-11, 2022.
Why and How Uncertainty Matters for Estimating Dissolved Phosphorus in Runoff.
R. Sheikholeslami and K. Golkar.

10th International Conference on Sensitivity Analysis of Model Output, SAMO 2022, Florida, US, March 14-16, 2022.
A Machine Learning Approach to Identifying the Key Factors Influencing Global Water Quality.
R. Sheikholeslami and J.W. Hall.

AGU Fall Meeting, Dec 2021.
A Global Assessment of Non-Stationarity in Extreme Precipitation.
R. Sheikholeslami, S.M. Papalexiou and M. Clark.

EGU General Assembly, May 2020.
A New Way of Understanding Rebound Phenomenon in Agriculture Water Demand Using A Global Sensitivity Analysis Approach.
M. Ghoreishi, R. Sheikholeslami, S. Razavi and A. Elshorbagy.

EGU General Assembly, May 2020.
A New Approach for Global Sensitivity Analysis on any Given Data: Data-driven. Variogram Analysis of Response Surfaces.
R. Sheikholeslami and S. Razavi

9th International Conference on Sensitivity Analysis of Model Output, SAMO 2019, Barcelona, Spain, October 28-30, 2019.
Robustness and Convergence Assessment for Global Sensitivity Analysis of High- dimensional Hydrological Models.
R. Sheikholeslami and S. Razavi.

27th International Union of Geodesy and Geophysics General Assembly, IUGG 2019, Montreal, Canada, July 8-18, 2019.
Data-driven Variogram Analysis of Response Surfaces (D-VARS): A New Method for Global Sensitivity Analysis of Given Data.
R. Sheikholeslami and S. Razavi.

27th International Union of Geodesy and Geophysics General Assembly, IUGG 2019, Montreal, Canada, July 8-18, 2019.
trategies for Handling Simulation Model Crashes in Global Sensitivity Analysis.
R. Sheikholeslami, S. Razavi, and A. Haghnegahdar.

AGU Fall Meeting, Dec 2018.
Addressing Curse of Dimensionality in Global Sensitivity Analysis of Large Environmental Models: An Automated Grouping Strategy.
R. Sheikholeslami, S. Razavi, H. V. Gupta, W. Becker, and A. Haghnegahdar.

9th International Congress on Environmental Modelling and Software, iEMSs 2018, Fort Collins, USA, June 24-28, 2018.
Dynamics of Water-related Poverty Trap: Stochastic Modelling of the Interplay between Economic Growth and Water Security.
R. Sheikholeslami and S. Razavi.

Resilience 2017–Research Frontiers for Global Sustainability, Stockholm, Sweden, Aug 20-23, 2017.
Estimation of Rainfall Over the Canadian Rockies by Approximating the Water Balance Component.
S. Gharari, S. Safaei, R. Sheikholeslami, A. Haghnegahdar, and S. Razavi.

EGU General Assembly, April 2017.
Finding Positive Feedback Loops in Environmental Models: A Mathematical Investigation.
R. Sheikholeslami and S. Razavi.

AGU Fall Meeting, Dec 2016.
Novel Sampling Approach for Efficient and Robust Uncertainty and Sensitivity Analysis of Environmental Models.
R. Sheikholeslami and S. Razavi.

8th International Congress on Environmental Modelling and Software, iEMSs 2016, Toulouse, France, Jul 10-14, 2016.
On the Impact of Uncertainty in Initial Conditions of Hydrologic Models on Prediction.
R. Sheikholeslami and S. Razavi.

AGU Fall Meeting, Dec 2015.
A Novel Meta-heuristic for Solving NP-hard Problems: Chaotic Swarming of Particles.
A. Tahershamsi, R. Sheikholeslami.

6th International Conference of Iranian Operations Research Society, Research Center of Operations Research, Tehran, Iran, May 8-9, 2013.
Optimum Seismic Design of Gravity Retaining Walls Using the Heuristic Big Bang-Big Crunch Algorithm.
A. Kaveh, S. Talatahari, and R. Sheikholeslami.

Proceedings of the 2nd International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering, Civil- Comp Press, Stirlingshire, Scotland, Paper 4, 2011, DOI:10.4203/ccp.97.4.
Estimating the Optimal Parameters for Muskingum Flood Routing Model (Case Study: Gorganrood, Iran).
B. Gholipour Khalili, R. Sheikholeslami.

nd National Conference on Flood Management and Engineering, Tehran, Iran, Sep-Oct 30-1, 2014.
Determining the Optimum Installation Capacity of Small Hydro Power Plants Using Charged System Search Algorithm (Case Study: Kohnelahijan Power Plant, Iran).
A. Shamsai, S. Mehrvand, and R. Sheikholeslami.

13th Iranian Hydraulic Conference, Iranian Hydraulic Association, Tabriz, Iran, Nov 12-14, 2014.
Chaotic Time Series Analysis Using Phase- Space Reconstruction and Correlation Dimension (Case Study: The Monthly Rainfall Time Series of Lake Urmia).
S. Farzin, R. Sheikholeslami, and Y. Hasanzadeh.

4th Iran Water Resource Management Conference, Tehran, Iran, May 2011.

Razi Sheikholeslami

Publications

Refereed Journal Papers

Conference Publications/Presentations

Google Scholar

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