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Publications

The names of students/Postdoctoral fellows are underlined.

Books

[4] Kulshreshtha, S. and Elshorbagy, A. (Eds.) 2017. Current Perspective on Irrigation and Drainage. InTech, Rijeka, Croatia, ISBN 978-953-51-2952-3, pp. 110 (Book cover)

[3] Izadifar, Z. and Elshorbagy, A. 2010. Modeling and Analysis of Actual Evapotranspiration. Data Driven Modeling and Wavelet Analysis of Actual Evapotranspiration. VDM Verlag Dr. Muller, Saarbrucken, Germany, pp. 145 (Book cover).

[2] Jutla, A., Elshorbagy, A. and Kells, J. 2009. System Dynamics Watershed Model. Hydrologic Assessment of Reconstructed Watersheds. VDM Verlag Dr. Muller, Saarbrucken, Germany (Book cover).

[1] Bachu, L. and Elshorbagy, A. 2009. Hydrology of Reconstructed and Natural Watersheds. Modeling Based Comparative Analysis of Hydrological Performance. VDM Verlag Dr. Muller, Saarbrucken, Germany, pp. 118 (Book cover).

 

Refereed Book Chapters

[4] Izadifar, Z. and Elshorbagy, A. 2013. Chapter 9: Data Driven Techniques and Wavelet Analysis for the Modeling and Analysis of Actual Evapotranspiration. In: Alexandris, S. G. (Ed.), Evapotranspiration - An Overview, InTech, New York, 167 - 206 (invited) - Chapter 9.

[3] Elshorbagy, A. and Parasuraman, K. 2008. Chapter 28: Toward Bridging the Gap Between Data-driven and Mechanistic Models: Cluster-based Neural Networks for Hydrologic Processes. In: Abrahart, R., See, L., and Solomatine, D. (Eds.), Practical Hydroinformatics: computational intelligence and technological developments in water applications, Springer-Verlag, Berlin Heidelberg, 389-403 (invited).

[2] Elshorbagy, A., Barbour, L. and Qualizza, C. 2006. Chapter 14: Multi-criterion Decision Making Approach to Assess the Performance of Reconstructed Watersheds. In A. Castelletti and R. S. Sessa (Eds.), Topics on System Analysis and Integrated Water Resource Management (IWRM), Elsevier, The Netherlands, 257-269.

[1] Panu, U. S. , Khalil, M. and Elshorbagy, A. 2000. Chapter 12: Streamflow Data Infilling Techniques Based on Concepts of Groups and Neural Networks. In R. S. Govindaraju and R. Rao (Eds.), Artificial neural networks in hydrology, Kluwer Academic, The Netherlands, 235-258 (invited).


Refereed Journal Articles

[59] Hassanzadeh, E., Elshorbagy, A., Nazemi, A., Jardine, T., Wheater, H., and Lindenschmidt, K. 2016.The ecohydrological vulnerability of a large inland delta to changing regional streamflows and upstream irrigation expansion. Ecohydrology, Accepted.

[58] Elshorbagy, A., Wagener, T., Razavi, S., and Sauchyn, D. 2016. Correlation and Causation in Tree-ring Based Reconstruction of Paleohydrology in Cold Semi-arid Regions. Water Resources Research, accepted for publication.

[57] Ceola, S. et al. 2016. Adaptation of Water Resources Systems to changing society and environment - A statement by the International Association of Hydrological Sciences. Hydrological Sciences Journal, DOI:10.1080/02626667.2016.1230674.

[56] Hassanzadeh, E., Elshorbagy, A., Wheater, H., and Gober, P. 2016. A risk-based framework for water resource management under changing water availability, policy options, and irrigation expansion. Advances in Water Resources, 94: 291-306.

[55] Mount, N., Maier, H., Toth, E., Elshorbagy, A., Solomatine, D., Chang, F-J., Abrahart, R. 2016. Data-driven modelling approaches for socio-hydrology: Opportunities and challenges within the Panta Rhei Science Plan. Hydrological Sciences Journal, 61(7), 1192-1208, DOI: 10.1080/02626667.2016.1159683.

[54] Razavi, S., Elshorbagy, A., Wheater, H., and Sauchyn, D. 2016. Time scale effect and uncertainty in reconstruction of paleo-hydrology. Hydrological Processes, 30: 1985-1999, DOI: 10.1002/hyp.10754.

[53] Hassanzadeh, E., Elshorbagy, A., Wheater, H., Gober, P., and Nazemi, A. 2016. Integrating supply uncertainties from stochastic modeling into integrated water resource management: a case study of the Saskatchewan River Basin. ASCE's Journal of Water Resources Planning and Management, 142 (2): 05015006.

[52] Shahabul Alam, Md., and Elshorbagy, A. 2015. Quantification of the climate change-induced variations in Intensity-Duration-Frequency curves in the Canadian Prairies. Journal of Hydrology, 527: 990-1005 (click here).

[51] Razavi, S., Elshorbagy, A., Wheater, H., and Sauchyn, D. 2015. Towards understanding non-stationarity in climate and hydrology through tree-ring proxy records. Water Resources Research, 51, doi:10.1002/2014WR015696.

[50] Mekonnen, B., Nazemi, A., Mazurek, K., Elshorbagy, A., and Putz, G. 2015. Hybrid modelling approach to prairie hydrology: Fusing data-driven and process-based hydrological models. Hydrological Sciences Journal, DOI: 10.1080/02626667.2014.935778 (click here).

[49] Hassanzadeh, E., Elshorbagy, A., Wheater, H., and Gober, P. 2014. Managing water in complex systems: An integrated water resources model for Saskatchewan, Canada. Journal Environmental Modelling & Software, 58: 12 - 26. DOI: 10.1016/j.envsoft.2014.03.015.

[48] Hassanzadeh, E., Nazemi, A., and Elshorbagy, A. 2014. Quantile-based downscaling of precipitation using genetic programming. Application to IDF curves in the City of Saskatoon. ASCE's Journal of Hydrologic Engineering, 19: 943-955.

[47] Nazemi, A., Wheater, H., Chun, K., and Elshorbagy, A. 2013. A stochastic reconstruction framework for analysis of water resource system vulnerability to climate-induced changes in river flow regime. Water Resources Research, 49, 1-15, doi: 10.1029/2012WR012755.

[46] Mingbin, H., Zettl, J., Barbour, L., Elshorbagy, A. and Si, B. 2013. The Impact of Soil Moisture Availability on Forest Growth Indices for Variably Layered Coarse Textured Soils. Ecohydrology, 6: 214-227.

[45] Keshta, N., Elshorbagy, A., and Carey, S. 2012. Impacts of Climate Change on Soil Moisture and Evapotranspiration in Reconstructed Watersheds in northern Alberta, Canada. Hydrological Processes, 26(9): 1321-1331.

[44] Nazemi, A., and Elshorbagy, A. 2012. Application of Copula Modeling to the Performance Assessment of Reconstructed Watersheds. Stochastic Environmental Research & Risk Assessment, 26(2): 189-205.

[43] Mingbin, H., Elshorbagy, A., Barbour, S. L., Zettl, J.D. and Si, B.C. 2011. System Dynamics Modeling of Infiltration and Drainage in Layered Coarse Soil. Canadian Journal of Soil Science, 91(2): 185-197.

[42] Mingbin, H., Barbour, S. L., Elshorbagy, A., Zettl, J.D. and Si, B.C. 2011. Water Availability and Forest Growth in coarse textured soils. Canadian Journal of Soil Science, 91(2): 199-210.

[41] Mingbin, H., Barbour, S. L., Elshorbagy, A., Zettl, J.D. and Si, B.C., and Zettl, J. 2011. Infiltration and Drainage Processes in multi-layered coarse soils. Canadian Journal of Soil Science, 91(2): 169-183.

[40] Keshta, N. and Elshorbagy, A. 2011. Utilizing North American Regional Reanalysis for Modeling Soil Moisture and Evapotranspiration in Reconstructed Watersheds. Physics and Chemistry of the Earth, 36: 31-41.

[39] Elshorbagy, A., Corzo, G.Srinivasulu, S. and Solomatine, D. 2010. Experimental Investigation of the Predictive Capabilities of Data Driven Modeling Techniques in Hydrology: I. Concepts and methodology. Hydrology and Earth System Sciences, 14: 1931-1941.

[38] Elshorbagy, A., Corzo, G.Srinivasulu, S. and Solomatine, D. 2010. Experimental Investigation of the Predictive Capabilities of Data Driven Modeling Techniques in Hydrology: II. Application. Hydrology and Earth System Sciences, 14: 1943-1961.

[37] Hossain, M. A., Elmoselhi, H., Elshorbagy, A. and Shoker, A. 2010. The Sask Formula to Estimate Glomerular Filtration Rate in Renal Transplant Patients. Nephron Clinical Practice, DOI: 10.1159/000319661, c135-c150.

[36] Izadifar, Z. and Elshorbagy, A. 2010. Prediction of Hourly Actual Evapotranspiration Using Neural Networks, Genetic Programming, and Statistical Models. Hydrological Processes, 24(23): 3413-3425.

[35] Keshta, N., Elshorbagy, A., Barbour, L. 2010. Comparative Probabilistic Assessment of the Hydrological Performance of Reconstructed and Natural Watersheds. Hydrological Processes, 24(10): 1333-1342.

[34] El-Baroudy, I., Elshorbagy, A., Carey, S., Giustolisi, O. and Savic, D. 2010. Comparison of Three Data-driven Techniques in Modelling Evapotranspiration Process. Journal of Hydroinformatics, 12(4): 365-379.

[33] Keshta, N., Elshorbagy, A., and Carey, S. 2009. A Generic System Dynamics Model For Simulating and Evaluating the Hydrological Performance of Reconstructed Watersheds. Hydrology and Earth System Sciences, 13(6): 865-881.

[32] Elshorbagy, A. and El-Baroudy, I. 2009. Investigating the Capabilities of Evolutionary Data-Driven Techniques Using the Challenging Estimation of soil Moisture Content . Extraordinary Issue of the Journal of Hydroinformatics, 11(3-4): 237-251.

[31] Parasuraman, K. and Elshorbagy, A. 2008. Model Structure Uncertainty and its Quantification Using Ensemble-Based Genetic Programming Framework . Water Resources Research, 44, W12406, doi:10.1029/2007WR006451.

[30] Elshorbagy, A. and Parasuraman, K. 2008. On the Relevance of Using Artificial Neural Networks For Estimating Soil Moisture Content. Journal of Hydrology, 362(1-2): 1-18.

[29] Elshorbagy, A. 2008. Accuracy and Uncertainty: A False Dichotomy in Engineering Education. A Case Study From Civil Engineering. International Journal of Engineering Education, 24(1): 137-143.

[28] Parasuraman, K., Elshorbagy, A., and Si, B. 2007. Estimating Saturated Hydraulic Conductivity Using Genetic Programming. Soil Science Society of America Journal, 71(5): 1676-1684. GP-Hyd Conductivity

[27] Parasuraman, K., Elshorbagy, A. and Carey, S. 2007. Modeling the Dynamics of Evapotranspiration process Using Genetic Programming. Hydrological Sciences Journal, 52(3): 563-578.

[26] Elshorbagy, A., Jutla, A. and Kells, J. 2007. Simulation of the Hydrological Processes on Reconstructed Watersheds Using System Dynamics. Hydrological Sciences Journal, 52(3): 538-562.

[25] Elshorbagy, A. and Barbour S. L. 2007. A Probabilistic Approach for Design and Hydrologic Performance Assessment of Reconstructed Watersheds. Journal of Geotechnical & Geoenvironmental Engineering, ASCE, 133(9): 1110-1118. Probabilistic soil moisture.

[24] Elshorbagy, A. 2006. Multi-criterion Decision Analysis Approach to Assess the Utility of Watershed Modeling for Management Decisions. Water Resources Research, 42, W09407, doi:10.1029/2005WR004264. MCDA.

[23] Elshorbagy, A., Parasuraman, K., Putz, G., and Ormsbee, L. 2007. Deterministic and Probabilistic Approaches to the Development of pH Total Maximum Daily Loads: A Comparative Analysis. Journal of Hydroinformatics, 9(3): 203-213.

[22] Parasuraman, K., Elshorbagy, A., and Si, B. 2006. Estimating Saturated Hydraulic Conductivity in Spatially-variable Fields Using Neural Network Ensembles. Soil Science Society of America Journal, 70: 1851-1859. ANN Ensemble

[21] Parasuraman, K., and Elshorbagy, A. 2007. Cluster-Based Hydrologic Prediction Using Genetic Algorithm-Trained Neural Networks. Journal of Hydrologic Engineering, ASCE, 12(1): 52 - 62.

[20] Parasuraman, K., Elshorbagy, A., and Carey, S.K. 2006. Spiking-Modular Neural Networks: A Neural Network Modeling Approach for Hydrological Processes. Water Resources Research, 42, W05412, doi:10.1029/2005WR004317. SMNNs

[19] Elshorbagy, A., Teegavarapu, R., Ormsbee, L. 2006. Assessment of Pathogen Pollution in Watersheds Using Object-Oriented Modeling and Probabilistic Analysis. Journal of Hydroinformatics, 8(1): 51-63.

[18] Elshorbagy, A., Ormsbee, L. 2006. Object-oriented Modeling Approach to Surface Water Quality Management. Environmental Modeling and Software, 21(5): 689-698. SD-WQ

[17] Elshorbagy, A. 2005. Learner-centered Approach to Teaching Watershed Hydrology Using System Dynamics. International Journal of Engineering Education, 21(6): 1203-1213. Teaching Hydrology using SD

[16] Elshorbagy, A., Jutla, A., Barbour, L., Kells, J. 2005. System Dynamics Approach to Assess the Sustainability of Reclamation of Disturbed Watersheds. Canadian Journal of Civil Engineering, 32(1): 144-158. SD reconstructed

[15] Elshorbagy, A., Teegavarapu, R. and Ormsbee, L. 2005. Total Maximum Daily Load (TMDL) Approach to Surface Water Quality Management: Concepts, Issues and Applications. Canadian Journal of Civil Engineering, 32(2): 442-448.

[14] Teegavarapu, R. Elshorbagy, A. 2005. Fuzzy Set Based Error Measure for Hydrologic Model Evaluation. Journal of Hydroinformatics, 7(3): 199-208.

[13] Elshorbagy, A., Teegavarapu, R. and Ormsbee, L. 2005. Framework for Assessment of Relative Pollutant Loads in Streams with Limited Data. Water International, 30(4): 477-486.

[12] Ormsbee, L., Elshorbagy, A. and Zechman, E. 2004. A Methodology for pH TMDLs: Application to Beech Creek Watershed. Journal of Environmental Engineering, ASCE, 130(2): 167-174. pH TMDL.

[11] Elshorbagy, A., Panu , U.S. and Simonovic, S.P. 2002. Reply to the Comment on: "Analysis of Cross-correlated Chaotic Streamflows" by Elshorbagy, A., Panu , U.S. and Simonovic, S.P., Hydrological Sciences Journal, 47(3): 529-532. [Discussion paper]

[10] Elshorbagy, A., Simonovic, S. P. and Panu , U. S. 2002. Noise Reduction in Chaotic Hydrologic Time Series: Facts and Doubts. Journal of Hydrology, 256(3-4): 147-165.

[9] Elshorbagy, A., Simonovic, S. P. and Panu , U. S. 2002. Estimation of Missing Streamflow Data Using Principles of Chaos Theory. Journal of Hydrology, 255(1-4): 123-133.

[8] Elshorbagy, A. and Schönwetter, D. 2002. Engineer Morphing: Bridging the Gap Between Classroom Teaching and the Engineering Profession. International Journal of Engineering Education, 18(3): 295-300. Engineer Morphing

[7] Elshorbagy, A., Panu , U.S. and Simonovic, S.P. 2001. Analysis of Cross-correlated Chaotic Streamflows. Hydrological Sciences Journal, 46(5): 781-794.

[6] Elshorbagy, A., 2001. Noise Reduction Approach in Chaotic Hydrologic Time Series Revisited. Canadian Water Resources Journal, 26 (4): 537-550.

[5] Elshorbagy, A., Panu , U. S. and Simonovic, S. P. 2000. Group-based Estimation of Missing Hydrological Data. I. Approach and General Methodology. Hydrological Sciences Journal , 45(6): 849-866.

[4] Elshorbagy, A., Panu , U. S. and Simonovic, S. P. 2000. Group-based Estimation of Missing Hydrological Data. II. Application to Streamflows. Hydrological Sciences Journal, 45(6): 867-880.

[3] Elshorbagy, A., Simonovic, S. P. and Panu , U. S. 2000. Performance Evaluation of Artificial Neural Networks for Runoff Prediction. Journal of Hydrologic Engineering, ASCE, 5(4): 424-427.

[2] Simonovic, S. P., Fahmy, H. and Elshorbagy, A. 1997. The Use of Object-oriented Modeling for Water Resources Planning in Egypt. Water Resources Management, 11: 243-261.

[1] Fahmy, H., Elshorbagy, A. and Tawfik, M. 1995. A Multicriterion Approach for Equitable Utilization of International River Basins. Water Sciences Journal, NWRC, Egypt , 18: 43-51.

 

Conference Proceedings and Presentations

[76] Hossain, K., Elshorbagy, A. , Bharath, R., Davison, B., and Wheater, H. 2016. A Comparative Study of the Runoff Generation Algorithms in MESH Hydrological Model. 69th CWRA National Conf., Montreal, QC, Canada, May 25-27 (Abstract and oral presentation).

[75] Bharath, R., and Elshorbagy, A. 2016. Integrated Flood Risk Assessment and Zonation of a Prairie Watershed. 69th CWRA National Conf., Montreal, QC, Canada, May 25-27 (Abstract and oral presentation).

[74] Hassanzadeh, E., Elshorbagy, A., Wheater, H., and Gober, P. 2016. Towards Improved Water Resource Management Under Uncertainty. 69th CWRA National Conf., Montreal, QC, Canada, May 25-27 (Abstract and oral presentation).

[73] Elshorbagy, A., Wagener, T., Razavi, S., and Sauchyn, D. 2016. Reconstruction of paleohydrology in semi-arid regions for water resources management: Opportunities and challenges. General Assembly of the European Geosciences Union, Vienna, Austria, April 17-22 (Abstract and poster presentation EGU2016-4015).

[72] Gonda, J., Elshorbagy, A., and Wheater, H.. 2015.Environmental Flow and Economy in the Bow River Basin: Reaching a Compromise Through a Hydro-Economic Model. Proc. 22nd Canad. Hydrotech. Conf., Montreal, QC, Canada, Apr 29 - May 2, 8 pp.

[71] Hosseini Safa, H., Elshorbagy, A., and Wheater, H. 2015. Balancing Economic and Environmental Protection Goals in Water Resources Management in the Oldman River Basin.Proc. 22nd Canad. Hydrotech. Conf., Montreal, QC, Canada, Apr 29 - May 2, Poster.

[70] Hassanzadeh, E., Elshorbagy, A., Nazemi, A., Wheater, H., and Gober, P. 2015. Integrated Water Resource Management Under Water Supply and Irrigation Development Uncertainty. Proc. 22nd Canad. Hydrotech. Conf., Montreal, QC, Canada, Apr 29 - May 2, 4 pp.

[69] Elshorbagy, A., and Alam, S. 2015. Downscaling of Extreme Precipitation: Proposing a New Statistical Approach and Investigating a Taken-for-Granted Assumption. General Assembly of the European Geosciences Union, Vienna, Austria, April 12-17 (Abstract and oral presentation EGU2015-7872).
 
[68] Elshorbagy, A., Hassanzadeh, E., Wheater, H. and Gober, P. 2015. A Risk-Based Framework to Assess Long-term Effects of Policy and Water Supply Change on Water Resource Systems. General Assembly of the European Geosciences Union, Vienna, Austria, April 12-17 (Abstract and oral presentation EGU2015-7656).

[67] Gonda, J.Elshorbagy, A., Wheater, H. and Razavi, S. 2014. Scale vs. Complexity: A Multi Scale Water Resources Model. The 2014 AGU Fall Meeting, San Francisco, USA, December 15-19 (Poster presentation).

[66] Razavi, S., Elshorbagy, A., Wheater, H. and Sauchyn, D. 2014. Reconstruction of Paleo-hydrologic Data for Vulnerability Assessment of Water Resources Systems . The 11th International Conference on Hydroinformatics, New York City, USA, August 17-21, 4 pp. (paper 1378 & Oral presentation).

[65] Nazemi, A., Alam, S. and Elshorbagy, A. 2014. Uncertainties in Future Projections of Extreme Rainfall at Fine Scales: The Role of Various Sources . The 11th International Conference on Hydroinformatics, New York City, USA, August 17-21, 4 pp. (paper 1328 & Oral presentation).

[64] Razavi, S., Elshorbagy, A., Wheater, H., and Saushyn, D. 2014. On the Reconstruction of Paleo-hydrology: A Foundation for More Reliable Water Resources Management. General Assembly of the European Geosciences Union, Vienna, Austria, April 27- May 2 (Poster presentation EGU2014-7971).
 
[63] Alam, S., Nazemi, A., and Elshorbagy, A. 2014. Quantifying the Climate Change-induced Variations in Saskatoon's Intensity-Duration-Frequency Curves Using Stochastic Rainfall Generators and K-nearest neighbors. General Assembly of the European Geosciences Union, Vienna, Austria, April 27- May 2 (Poster presentation EGU2014-4536).
 
[62] Hassanzadeh, E., Elshorbagy, A., Nazemi, A., and Wheater, H. 2014. Performance Assessment of Saskatchewan's Water Resource System Under Uncertain Inter-provincial Water Supply. General Assembly of the European Geosciences Union, Vienna, Austria, April 27- May 2 (Poster presentation EGU2014-4731).
 
[61] Nazemi, A. and Elshorbagy, A. 2014. A Stochastic Disaggregation Algorithm for Analysis of Change in the Sub-daily Extreme Rainfall. General Assembly of the European Geosciences Union, Vienna, Austria, April 27- May 2 (Poster presentation EGU2014-7827).
 
[60] Hassanzadeh, E., Elshorbagy, A., and Wheater, H. 2013. Value-based Water Resources Management Model: Application to the Saskatchewan River Basin. 2013 Joint Congress of the CMOS, CGU, and CWRA, Saskatoon, Canada, May 26-30 (Abstract and oral presentation ID:6393).
 
[59] Hassanzadeh, E., Nazemi, A. and Elshorbagy, A. 2013. A Novel Quantile-Quantile Downscaling Approach to Updating IDF Curves in the City of Saskatoon. 2013 Joint Congress of the CMOS, CGU, and CWRA, Saskatoon, Canada, May 26-30 (Abstract and oral presentation ID:6352).
 
[58] Nazemi, A. and Elshorbagy, A. 2013. A Stochastic Rainfall Disaggregation Framework for Simulating the Sub-daily Extreme Rainfall Values in the City of Saskatoon. 2013 Joint Congress of the CMOS, CGU, and CWRA, Saskatoon, Canada, May 26-30 (Abstract and oral presentation ID:6353).
 
[57] Azinfar, H., Nazemi, A. Hassanzadeh, E., Elshorbagy, A., and Hilderbrandt, A. 2013. The Vulnerability of Saskatoon's Storm Collection System to the Alteration in Future Rainfall Characteristics. 2013 Joint Congress of the CMOS, CGU, and CWRA, Saskatoon, Canada, May 26-30 (Abstract and oral presentation ID:6354).

[56] Nazemi, A., Wheater, H. and Elshorbagy, A. 2013. Toward Emulating Complex Water Resource Systems: Linking Inflow Characteristics and System Response at the Annual Time Scale. 2013 Joint Congress of the CMOS, CGU, and CWRA, Saskatoon, Canada, May 26-30 (Abstract and oral presentation ID:6648).
.
[55] Hassanzadeh, E., Elshorbagy, A., and Wheater, H. 2013. Scenario-based Water Resources Management Using the Water Value Concept. General Assembly of the European Geosciences Union, Vienna, Austria, April 7-12 (Abstract and oral presentation EGU2013-1847).

[54] Huang, M., Barbour, S. L., Elshorbagy, A., Zettl, J., and Si, B. C. 2013. Responses of Plant Available Water and Forest Productivity to Variably Layered Coarse Textured Soils. International Conference onFour Decades of Progress in Monitoring and Modeling of Processes in the Soil-Plant-Atmosphere System: Applications and Challenges, Naples, Italy, June 19-20.

[53] Hassanzadeh, E., Nazemi, A., and Elshorbagy, A. 2012. A Framework For Downscaling extreme Rainfall Quantiles Using Genetic Programming. The 10th International Conference on Hydroinformatics, Hamburg, Germany, July 14-18, 8 pp. (paper HYA00134-00231).

[52] Nazemi, A., Wheater, H., and Elshorbagy, A. 2012. A Novel Approach to Vulnerability Assessment of Water Resources Systems: Preliminary Results For Southern Alberta, Canada. The 10th International Conference on Hydroinformatics, Hamburg, Germany, July 14-18, 8 pp. (paper HYA00134-00232).

[51] Wheater, H., Nazemi, A., and Elshorbagy, A. 2012. How Can Possible Climate Change Impacts on Flow Regime Affect Water Security in Southern Alberta? The 2012 CWRA/CGU National Conference, Banff, Canada, June 5-8,  (Abstract and oral presentation)

[50] Mekonnen, B., Nazemi, A., Elshorbagy, A., Mazurek, K., and Putz, G. 2012. Hybrid modeling approach to Prairie hydrology: Fusing data driven and process-based hydrological models. General Assembly of the European Geosciences Union, Vienna, Austria, April 22-27 (Abstract and oral presentation EGU2012-6562).

[49] Nazemi, A.-R, Elshorbagy, A. and Pingale, S. 2011. Identifying the IDF curves under climate change effects for the city of Saskatoon. 20th Canadian Hydrotechnical Conference, Ottawa, Canada, June 14-17.

[48] Elshorbagy, A. and Izadifar, Z. 2010. Optimum input selection for data driven modeling. Mirage or reality? General Assembly of the European Geosciences Union, Vienna, Austria, May 2-7 (Oral presentation EGU2010-2543).

[47] Huang, M., Barbour, L., Elshorbagy, A., Si, B., and Zettl, J. 2010. Responses of plant available water and forest productivity to variably layered coarse textured soils. General Assembly of the European Geosciences Union, Vienna, Austria, May 2-7 (Poster presentation EGU2010-2868).

[46] Keshta, N. and Elshorbagy, A. 2010. Use of the North Americal regional reanalysis data for hydrological modeling in reconstructed watersheds. General Assembly of the European Geosciences Union, Vienna, Austria, May 2-7 (Poster presentation EGU2010-2255).

[45] Nazemi, A. and Elshorbagy, A. 2010. Automatic calibration of hydrological models in the newly reconstructed catchments: Issues, methods, and uncertainties. General Assembly of the European Geosciences Union, Vienna, Austria, May 2-7 (Poster presentation EGU2010-2253).

[44] Keshta, N., and Elshorbagy, A. 2009. A comparative Application of SWAT and a System Dynamics Watershed Model Using a Lumped Set of Data. Proc. the 33rd IAHR Congress, Vancouver, Canada, Aug 9 -14, 9 pp. (paper 11420).

[43] Izadifar, Z., and Elshorbagy, A. 2009. Comparative Analysis of Two Different Techniques for Estimation of Hourly Actual Evapotranspiration. Proc. the 33rd IAHR Congress, Vancouver, Canada, Aug 9 -14, 10 pp. (paper 10741).

[42] Elshorbagy, A., Corzo, G., Srinivasulu, S., and Solomatine, D. 2009. Data driven techniques scrutinized: is there one better than the rest? General Assembly of the European Geosciences Union, Vienna, Austria, April 19-24 (Oral presentation EGU2009-4282).

[41] Srinivasulu, S., Elshorbagy, A., and Keshta, N. 2009. Integration of system theoretic and system dynamics modeling techniques for prediction of soil moisture. General Assembly of the European Geosciences Union, Vienna, Austria, April 13-18 (Oral presentation EGU2008-2659).

[40] El-Baroudy, I.,  and Elshorbagy, A. 2009. Utility of the Wavelet Analysis in Assessing the Performance of Different Soil Moisture Models. The 8th International Conference on Hydroinformatics, Concepcion, Chile, Jan 11-16, 10 pp. (paper conf188a11).

[39] Keshta, N., and Elshorbagy, A. 2009. Probabilistic Assessment of the Hydrologic Performance of Reconstructed Watersheds. The 8th International Conference on Hydroinformatics, Concepcion, Chile, Jan 11-16, 10 pp. (paper conf188a14).

[38] El-Baroudy, I., Elshorbagy, A., Carey, S., Guistolisi, O. and Savic, D. 2008. Predictive Data-driven Models of the Evapotranspiration Process. General Assembly of the European Geosciences Union, Vienna, Austria, April 13-18 (Oral presentation EGU2008-A-01512).

[37] Keshta, N., Elshorbagy, A. and El-Baroudy, I. 2008. Developing a Generic System Dynamics Watershed (GSDW) Model to Assess the Hydrologic Performance of Reconstructed and Natural Watersheds. General Assembly of the European Geosciences Union, Vienna, Austria, April 13-18 (poster EGU2008-A-01513).

[36] Bachu, L., Elshorbagy, A., Carey, S. and Barr, A. 2008. Evaluation of Comparative Hydrological Sustainability of Reconstructed and Natural Watersheds. General Assembly of the European Geosciences Union, Vienna, Austria, April 13-18 (poster EGU2008-A-02900).

[35] Bachu, L. and Elshorbagy, A. 2007. Data-driven Approach for Assessing the Hydrological Performance of Reconstructed Watersheds. Proc. 18th Canad. Hydrotech. Conf., Winnipeg, MB, Canada, August 22-24, 10 pp. (Paper GC-054).

[34] Elshorbagy, A. 2007. Can We Rely on Hydrologic Models to Make the Right Decision? An MCDA Approach. Proc. 32nd IAHR Congress., Venice, Italy, July 1-6, 10 pp. (Paper B2.d-069-O).

[33] Elshorbagy, A. and Parasuraman, K. 2007. Neural Networks in Hydrology: Data Mining for Learning or Modeling for Prediction? International Workshop on Advances in Hydroinformatics, Niagara Falls, ON, Canada, June 4-7.

[32] Bachu, L. and Elshorbagy, A.A. 2007. Comparison Between Mechanistic and Data Driven Approaches in Assessing the Hydrologic Performance of Reconstructed Watersheds, Canadian Water Resources Association Conference, Saskatoon, SK, Canada, June 25-28.

[31] Parasuraman, K. and Elshorbagy, A.A. (2007). Model Structure Uncertainty and its Significance in Improving the Reliability of Hydrological Models For Reconstructed Watersheds, Canadian Water Resources Association Conference, Saskatoon, SK, Canada, June 25-28.

[30] Parasuraman, K. and Elshorbagy, A. 2007. Model structure uncertainty in characterizing hydrological processes and its quantification using genetic-programming. General Assembly of the European Geosciences Union , Vienna, Austria, April 15-20 (Abstract & oral presentation, HS46-1TU3O-001).

[29] Parasuraman, K., Elshorbagy, A., Bachu, L. and Keshta, N. 2007. Evaluating the Performance of Neural Networks in Modeling Soil Moisture. General Assembly of the European Geosciences Union , Vienna, Austria, April 15-20 (poster A0265).

[28] Elshorbagy, A. 2006. Uncertainty Analysis in Engineering Education: Bridging the Gap Between Theory and Practice. Proceedings of The 7th InternationalConference on Hydroinformatics HIC 2006, Nice, France, September 4 - 8, V4, 3127-3134.

[27] Parasuraman, K., Elshorbagy, A., and Carey, S. 2006. Genetic Programming as a Model Induction Engine for Characterizing The Evapotranspiration Process. Proceedings of The 7th International Conference on Hydroinformatics HIC 2006, Nice, France, September 4 - 8, V2, 815-822.

[26] Elshorbagy, A. and Barbour, S.L. 2006. Probabilistic Assessment of the Sustainability of Restored Watersheds. Proceedings of The 7th International Conference on Hydroinformatics HIC 2006, Nice, France, September 4 - 8, V4, 3039-3046.

[25] Parasuraman, K., Elshorbagy, A., and Si, B. 2006. Estimating Saturated Hydraulic Conductivity in Spatially-Variable Fields Using Neural Network Ensembles. Unsaturated Soils Conference, Arizona, U.S.A., April 2 - 6 (poster).

[24] Elshorbagy, A. and Jutla, A. 2006. Hydrological Modeling of Reconstructed Watersheds Using System Dynamics. General Assembly of the European Geosciences Union , Vienna, Austria, April 2-7 (Abstract & oral presentation).

[23] Kelln, C. J., Barbour, S. L., Elshorbagy, A., and Qualizza, C. 2005. Long-term Performance of a Reclamation Cover: The Evolution of Hydraulic Properties and Hydrologic Response. Unsaturated Soils Conference, Arizona, U.S.A., April 2 - 6 (accepted).

[22] Jutla, A., Elshorbagy, A., and Kells, J. 2005. Beyond Rainfall-Runoff Modeling: Hydrologic simulation of Reconstructed Watersheds Using System Dynamics. 17th Canadian Hydrotechnical Conference, Edmonton, AB, Canada, August 17-19, 11-20.

[21] Elshorbagy, A. 2005. Predicting the Uncertainty of Watershed Models Using a Simple Bayesian Approach. 17th Canadian Hydrotechnical Conference, Edmonton, AB, Canada, August 17-19, 1-10.

[20] Parasuraman, K. and Elshorbagy, A. 2005. Wavelet Networks: An Alternative to Neural Networks. International Joint Conference on Neural Networks, Montreal, QC, Canada, July 31-Aug 4 (poster).

[19] Parasuraman, K. and Elshorbagy, A. 2005. Modeling the Dynamics of Evaporation by Recurrent Artificial Neural Networks. 58th Annual CWRA NationalConference, Banff, AB, Canada, June 15-18 (poster).

[18] Parasuraman, K. and Elshorbagy, A. 2005. Cluster-based streamflow prediction using genetic algorithm-trained neural networks. General Assembly of the European Geosciences Union , Vienna, Austria, April 23-29 (poster & oral presentation).

[17] Elshorbagy, A. 2004. Multi-criterion Decision Analysis Approach to Assess the Performance of Reconstructed Watersheds. IFAC Workshop on Modelling and Control for Participatory Planning and Managing Water Systems. Sept 29-Oct 1, Venice, Italy.

[16] Elshorbagy, A. and Ormsbee, L. 2004. Water quality management using the TMDL approach: application in southern Kentucky. Proceedings of the Annual Conference of Canadian Society of Civil Engineers, Saskatoon , Saskatchewan , June 2-5.

[15] Parasuraman, K. and Elshorbagy, A. 2004. Performance of various heuristic methods in estimation of parameters for model calibration. Proceedings of the Annual Conference of Canadian Society of Civil Engineers, Saskatoon , Saskatchewan , June 2-5.

[14] Jutla, A., Elshorbagy, A. and Kells, J. 2004. Predicting spring runoff in the Canadian Prairies using artificial neural networks. Proceedings of the Annual Conference of Canadian Society of Civil Engineers, Saskatoon , Saskatchewan , June 2-5.

[13] Alabi, P., Kells, J. and Elshorbagy, A. 2004. Use of artificial neural networks in describing complex flow field conditions. Proceedings of the Annual Conference of Canadian Society of Civil Engineers, Saskatoon , Saskatchewan, June 2-5.

[12] Azinfar, H., Kells, J. and Elshorbagy, A. 2004. Use of neural networks in the prediction of local scour below a sluice gate. Proceedings of the Annual Conference of Canadian Society of Civil Engineers, Saskatoon , Saskatchewan, June 2-5.

[11] Elshorbagy, A., Teegavarapu, R. and Ormsbee, L. 2002. System dynamics approach to water quality management in Southeastern Kentucky. XIV International Conference on Computational Methods in Water Resources, June 23-28, 2002 , Delft , The Netherlands, Elsevier, Vol.2, 1557-1564.

[10] Teegavarapu, R. and Elshorbagy, A. 2002. A new error statistic for performance evaluation of models in hydrology. XIV International Conference on Computational Methods in Water Resources, June 23-28, 2002 , Delft , The Netherlands, Elsevier, Vol.1, 787-794.

[9] Elshorbagy, A., Teegavarapu, R. and Ormsbee, L. 2002. System dynamics, GIS, and inductive models: A tool-kit for water quality management. Proceedings of American Water Resources Association, Middleburg, Virginia, TPS-02-4, Edited by Welty, Claire, 64.(abstract)

[8] Teegavarapu, R., Elshorbagy, A. and Ormsbee, L. 2002. Characterizing pollutant loadings in streams using system dynamics simulation. Proceedings of American Water Resources Association, Middleburg, Virginia, TPS-02-4, Edited by Welty, Claire, 247. (abstract)

[7] Teegavarapu, R., Elshorbagy, A. and Ormsbee, L. 2002. Inductive modeling of nutrient loadings in streams. Mississippi River Climate and hydrology Conference, May 13-17, New Orleans, LA, U.S.A. (abstract).

[6] Artificial Neural Network Experiment Group. 2002. An International Comparative Study of Artificial Neural Network Techniques for River Stage Forecasting. 8th British Hydrological Society's National Symposium, September 8-11, Birmingham, UK.

[5] Elshorbagy, A., Panu, U. and Simonovic, S. 2000. Group-based estimation of missing data in chaotic hydrologic time series (abstract). AIH Annual Meeting and International Conference: Atmospheric, Surface and Subsurface Hydrology and Interactions. Research Triangle Park, NC, November 5-8, 25-26.

[4] Teegavarapu, R., Elshorbagy, A. and Simonovic, S. 2000. Disaggregation of hydrological time series using neural networks (abstract). AIH Annual Meeting and International Conference: Atmospheric, Surface and Subsurface Hydrology and Interactions. Research Triangle Park, NC, November 5-8, 51.

[3] Elshorbagy, A., Panu , U. S. and Simonovic, S. P. 1999. Investigations into group-based data in-filling techniques. Proceedings of the Annual Conference of Canadian Society of Civil Engineers, Regina , Saskatchewan , June 2-5, 337 -348.

[2] Elshorbagy, A. 1998. Is sustainability at risk? Case study of the Egyptian New Valley Project. Proceedings of the 2nd International Conference on the Role of Engineering Towards Better Environment, 12-15 Dec., Alexandria , Egypt .

[1] Elshorbagy, A. and Sharifi, A. 1996. Environment-oriented water related projects appraisal. Proceedings of the 16th International Congress on Irrigation and Drainage (ICID), Sept. 15-22, Cairo , Egypt .

 

Technical Reports

 

[10] Elshorbagy, A., Nazemi, A., and Alam, S. 2015. Analyzing the variations in intensity-duration-frequency (IDF) curves in the city of Saskatoon under climate change. CANSIM Series Report No. CAN-15-01, Centre for Advanced Numerical simulation (CANSIM), Department of Civil & Geological Engineering, University of Saskatchewan, Saskatoon, SK, Canada, pp. 167. CAN-15-01.pdf

[9] Elshorbagy, A. and Carey, S. 2009. Risk-based assessment of the sustainability of reclamation strategy. Final Report. CANSIM Series Report No. CAN-09-02, Centre for Advanced Numerical simulation (CANSIM), Department of Civil & Geological Engineering, University of Saskatchewan, Saskatoon, SK, Canada, pp. 48.

[8] Elshorbagy, A. Corzo, G., Srinivasulu, S. and Solomatine, D. 2009. Experimental investigation of the predictive capabilities of soft computing techniques in hydrology. CANSIM Series Report No. CAN-09-01, Centre for Advanced Numerical simulation (CANSIM), Department of Civil & Geological Engineering, University of Saskatchewan, Saskatoon, SK, Canada, pp. 49. CAN-09-01.pdf 

[7] Elshorbagy, A. and Carey, S. 2008. Risk-based assessment of the sustainability of reclamation strategy. Second Progress Report. CANSIM Series Report No. CAN-07-01, Centre for Advanced Numerical simulation (CANSIM), Department of Civil & Geological Engineering, University of Saskatchewan, Saskatoon, SK, Canada, pp. 19. CAN-08-02.pdf

[6] L. Bachu and Elshorbagy, A., S. 2008. A comparative analysis of the hydrological performance of reconstructed and natural watersheds. CANSIM Series Report No. CAN-08-01, Centre for Advanced Numerical simulation (CANSIM), Department of Civil & Geological Engineering, University of Saskatchewan, Saskatoon, SK, Canada, pp. 138. CAN-08-01.pdf

[5] Elshorbagy, A. and Carey, S. 2007. Risk-based assessment of the sustainability of reclamation strategy. CANSIM Series Report No. CAN-07-01, Centre for Advanced Numerical simulation (CANSIM), Department of Civil & Geological Engineering, University of Saskatchewan, Saskatoon, SK, Canada, pp. 21. CAN-07-01.pdf.

[4] Jutla, A., Elshorbagy, A. and Kells, J. 2006. Simulation of the hydrological processes on reconstructed watersheds using system dynamics. CANSIM Series Report No. CAN-06-01, Centre for Advanced Numerical simulation (CANSIM), Department of Civil & Geological Engineering, University of Saskatchewan, Saskatoon, SK, Canada, pp. 139. CAN-06-01.pdf

[3] Elshorbagy, A. 2006. Performance assessment of hydrologic models based on the uncertainty of measurements. CANSIM Series Report No. CAN-06-02, Centre for Advanced Numerical simulation (CANSIM), Department of Civil & Geological Engineering, University of Saskatchewan, Saskatoon, SK, Canada, pp. 21. CAN-06-02.pdf

[2] Elshorbagy, A. and Jutla, A. 2006. Tracing the evolution of reconstructed watersheds using the parameters of the system dynamics watershed model. CANSIM Series Report No. CAN-06-03, Centre for Advanced Numerical simulation (CANSIM), Department of Civil & Geological Engineering, University of Saskatchewan, Saskatoon, SK, Canada, pp. 32. CAN-06-03.pdf

[1] Keshta, N. and Elshorbagy, A. 2006. Wetland hydrology: A literature review. CANSIM Series Report No. CAN-06-04, Centre for Advanced Numerical simulation (CANSIM), Department of Civil & Geological Engineering, University of Saskatchewan, Saskatoon, SK, Canada, pp. 33.