Publications

Stable Alluvial Channel Design

MacKenzie, K. M., Gharabaghi, B., Binns, A. D., & Whiteley, H. R. (2022). Early detection model for the urban stream syndrome using specific stream power and regime theory. Journal of Hydrology, 604, 127167. https://doi.org/10.1016/j.jhydrol.2021.127167

Riahi-Madvar, H., & Gharabaghi, B. (2022). Pre-processing and Input Vector Selection Techniques in Computational Soft Computing Models of Water Engineering. In Computational Intelligence for Water and Environmental Sciences (pp. 429-447). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-19-2519-1_20

Riahi-Madvar, H., Gholami, M., & Gharabaghi, B. (2022). Improved explicit formulation of bedload transport using a novel multi-level multi-model data-driven ensemble approach. https://doi.org/10.21203/rs.3.rs-2120777/v1

Bonakdari, H., Ebtehaj, I., Gharabaghi, B., Sharifi, A., & Mosavi, A. (2021). Prediction of discharge capacity of labyrinth weir with gene expression programming. In Intelligent Systems and Applications: Proceedings of the 2020 Intelligent Systems Conference (IntelliSys) Volume 1 (pp. 202-217). Springer International Publishing. https://doi.org/10.1007/978-3-030-55180-3_17

Bonakdari, H., Gholami, A., Gharabaghi, B., Ebtehaj, I., & Akhtari, A. A. (2021). An Assessment of Extreme Learning Machine Model for Estimation of Flow Variables in Curved Irrigation Channels. In Intelligent Computing: Proceedings of the 2021 Computing Conference, Volume 3 (pp. 259-269). Springer International Publishing. https://doi.org/10.1007/978-3-030-80129-8_19

Ebtehaj, I., Bonakdari, H., Zaji, A. H., & Gharabaghi, B. (2021). Evolutionary optimization of neural network to predict sediment transport without sedimentation. Complex & Intelligent Systems, 7, 401-416.

https://doi.org/10.1007/s40747-020-00213-9

Bonakdari, H., Gharabaghi, B., Ebtehaj, I., & Sharifi, A. (2020). A New Approach to estimate the discharge coefficient in sharp-crested rectangular side orifices using gene expression programming. In Intelligent Computing: Proceedings of the 2020 Computing Conference, Volume 3 (pp. 77-96). Springer International Publishing. https://doi.org/10.1007/978-3-030-52243-8_7

Kazemian-Kale-Kale, A., Gholami, A., Rezaie-Balf, M., Mosavi, A., Sattar, A. A., Gharabaghi, B., & Bonakdari, H. (2020). A Bayesian Monte-Carlo Uncertainty Model for Assessment of Shear Stress Entropy. arXiv preprint arXiv:2001.04802. https://doi.org/10.48550/arXiv.2001.04802

MacKenzie, K., Foster, L., Gharabaghi, B., & Binns, A. D. (2020, December). Development and Application of New Stream Geomorphic Stability Assessment Procedure in Urbanizing Watersheds Using Advanced Machine Learning. In AGU Fall Meeting Abstracts (Vol. 2020, pp. EP051-06).

Bonakdari, H., Gholami, A., Sattar, A. M., & Gharabaghi, B. (2020). Development of robust evolutionary polynomial regression network in the estimation of stable alluvial channel dimensions. Geomorphology, 350, 106895. https://doi.org/10.1016/j.geomorph.2019.106895

Kazemian-Kale-Kale, A., Bonakdari, H., Gholami, A., & Gharabaghi, B. (2020). The uncertainty of the Shannon entropy model for shear stress distribution in circular channels. International Journal of Sediment Research, 35(1), 57-68. https://doi.org/10.1016/j.ijsrc.2019.07.001

Bonakdari, H., Qasem, S. N., Ebtehaj, I., Zaji, A. H., Gharabaghi, B., & Moazamnia, M. (2020). An expert system for predicting the velocity field in narrow open channel flows using self-adaptive extreme learning machines. Measurement, 151, 107202. https://doi.org/10.1016/j.measurement.2019.107202

Bonakdari, H., Gholami, A., & Gharabaghi, B. (2019, July). Modelling Stable Alluvial River Profiles Using Back Propagation-Based Multilayer Neural Networks. In Intelligent Computing-Proceedings of the Computing Conference (pp. 607-624). Springer, Cham. https://doi.org/10.1007/978-3-030-22871-2_41

Gholami, A., Bonakdari, H., Mohammadian, M., Zaji, A. H., & Gharabaghi, B. (2019). Assessment of geomorphological bank evolution of the alluvial threshold rivers based on entropy concept parameters. Hydrological Sciences Journal, 64(7), 856-872. https://doi.org/10.1080/02626667.2019.1608995

Gholami, A., Bonakdari, H., Samui, P., Mohammadian, M., & Gharabaghi, B. (2019). Predicting stable alluvial channel profiles using emotional artificial neural networks. Applied Soft Computing, 78, 420-437. https://doi.org/10.1016/j.asoc.2019.03.003

Gholami, A., Bonakdari, H., Zeynoddin, M., Ebtehaj, I., Gharabaghi, B., & Khodashenas, S. R. (2019). Reliable method of determining stable threshold channel shape using experimental and gene expression programming techniques. Neural Computing and Applications, 31(10), 5799-5817. https://doi.org/10.1007/s00521-018-3411-7

Bonakdari, H., Gharabaghi, B., & Ebtehaj, I. (2018, July). Extreme Learning Machines in Predicting the Velocity Distribution in Compound Narrow Channels. In Science and Information Conference (pp. 119-128). Springer, Cham. https://doi.org/10.1007/978-3-030-01177-2_9

Gholami, A., Bonakdari, H., Ebtehaj, I., Gharabaghi, B., Khodashenas, S. R., Talesh, S. H. A., & Jamali, A. (2018). A methodological approach of predicting threshold channel bank profile by multi-objective evolutionary optimization of ANFIS. Engineering Geology, 239, 298-309. https://doi.org/10.1016/j.enggeo.2018.03.030

Gholami, A., Bonakdari, H., Ebtehaj, I., Mohammadian, M., Gharabaghi, B., & Khodashenas, S. R. (2018). Uncertainty analysis of intelligent model of hybrid genetic algorithm and particle swarm optimization with ANFIS to predict threshold bank profile shape based on digital laser approach sensing. Measurement, 121, 294-303. https://doi.org/10.1016/j.measurement.2018.02.070

Shaghaghi, S., Bonakdari, H., Gholami, A., Kisi, O., Shiri, J., Binns, A. D., & Gharabaghi, B. (2018). Stable alluvial channel design using evolutionary neural networks. Journal of hydrology, 566, 770-782. https://doi.org/10.1016/j.jhydrol.2018.09.057

Shaghaghi, S., Bonakdari, H., Gholami, A., Kisi, O., Binns, A., & Gharabaghi, B. (2018). Predicting the geometry of regime rivers using M5 model tree, multivariate adaptive regression splines and least square support vector regression methods. International Journal of River Basin Management, 1-20. https://doi.org/10.1080/15715124.2018.1546731

Kazemian-Kale-Kale, A., Bonakdari, H., Gholami, A., Khozani, Z. S., Akhtari, A. A., & Gharabaghi, B. (2018). Uncertainty analysis of shear stress estimation in circular channels by Tsallis entropy. Physica A: Statistical Mechanics and its Applications, 510, 558-576. https://doi.org/10.1016/j.physa.2018.07.014

Stream Assessment and Restoration

Stajkowski, S., Zeynoddin, M., Farghaly, H., Gharabaghi, B., & Bonakdari, H. (2020). A methodology for forecasting dissolved oxygen in urban streams. Water, 12(9), 2568. https://doi.org/10.3390/w12092568

Aredah, A. S., Ertugrul, O. F., Sattar, A. A., Bonakdari, H., & Gharabaghi, B. (2022). Extreme Learning Machine model for assessment of stream health using the Qualitative Habitat Evaluation Index. Water Supply, 22(5), 5355-5375. https://doi.org/10.2166/ws.2022.166

Shirvani-Hosseini, S., Samadi-Koucheksaraee, A., Ahmadianfar, I., & Gharabaghi, B. (2022). Data Mining Methods for Modeling in Water Science. In Computational Intelligence for Water and Environmental Sciences (pp. 157-178). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-19-2519-1_8

Ahmed, S. I., Rudra, R., Goel, P., Khan, A., Gharabaghi, B., & Sharma, R. (2022). A Comparative Evaluation of Using Rain Gauge and NEXRAD Radar-Estimated Rainfall Data for Simulating Streamflow. Hydrology, 9(8), 133. https://doi.org/10.3390/hydrology9080133

MacKenzie, K. M., Singh, K., Binns, A. D., Whiteley, H. R., & Gharabaghi, B. (2022). Effects of urbanization on stream flow, sediment, and phosphorous regime. Journal of Hydrology, 612, 128283. https://doi.org/10.1016/j.jhydrol.2022.128283

Milukow, H. A., Binns, A. D., Adamowski, J., Bonakdari, H., & Gharabaghi, B. (2019). Estimation of the Darcy–Weisbach friction factor for ungauged streams using Gene Expression Programming and Extreme Learning Machines. Journal of hydrology, 568, 311-321. https://doi.org/10.1016/j.jhydrol.2018.10.073

Gharabaghi, B., & Sattar, A. M. (2017). Empirical models for longitudinal dispersion coefficient in natural streams. Journal of Hydrology. https://doi.org/10.1016/j.jhydrol.2017.01.022

Ou, X., Gharabaghi, B., McBean, E., & Doherty, C. (2017). Investigation of the Tank Model for Urban Storm Water Management. Journal of Water Management Modeling. https://doi.org/10.14796/JWMM.C421

Atieh, M., Taylor, G., Sattar, A. M., & Gharabaghi, B. (2017). Prediction of flow duration curves for ungauged basins. Journal of hydrology, 545, 383-394. https://doi.org/10.1016/j.jhydrol.2016.12.048

Sattar, A. M., Plesiński, K., Radecki-Pawlik, A., & Gharabaghi, B. (2017). Scour depth model for grade-control structures. Journal of Hydroinformatics, 20(1), 117-133. https://doi.org/10.2166/hydro.2017.149  

Gazendam, E., Gharabaghi, B., Ackerman, J. D., & Whiteley, H. (2016). Integrative neural networks models for stream assessment in restoration projects. Journal of hydrology, 536, 339-350. https://doi.org/10.1016/j.jhydrol.2016.02.057

Atieh, M., Mehltretter, S. L., Gharabaghi, B., & Rudra, R. (2015). Integrative neural networks model for prediction of sediment rating curve parameters for ungauged basins. Journal of Hydrology, 531, 1095-1107. https://doi.org/10.1016/j.jhydrol.2015.11.008

Atieh, M., Gharabaghi, B., & Rudra, R. (2015). Entropy-based neural networks model for flow duration curves at ungauged sites. Journal of Hydrology, 529, 1007-1020. https://doi.org/10.1016/j.jhydrol.2015.08.068

Sattar, A. M., & Gharabaghi, B. (2015). Gene expression models for prediction of longitudinal dispersion coefficient in streams. Journal of Hydrology, 524, 587-596. https://doi.org/10.1016/j.jhydrol.2015.03.016

Disley, T., Gharabaghi, B., Mahboubi, A. A., & McBean, E. A. (2015). Predictive equation for longitudinal dispersion coefficient. Hydrological processes, 29(2), 161-172. https://doi.org/10.1002/hyp.10139

Gazendam, E., Gharabaghi, B., Jones, F. C., & Whiteley, H. (2011). Evaluation of the Qualitative Habitat Evaluation Index as a planning and design tool for restoration of rural Ontario waterways. Canadian Water Resources Journal, 36(2), 149-158. https://doi.org/10.4296/cwrj3602827

Inkratas, C., Gharabaghi, B., Beltaos, S., & Krishnappan, B. (2009). 3D modelling of ice-covered flows in the vicinity of a deep hole in the East Channel of the Mackenzie Delta, NWT. Canadian Journal of Civil Engineering, 36(5), 791-800. https://doi.org/10.1139/L09-031

Gazendam, E., Gharabaghi, B., McBean, E., Whiteley, H., & Kostaschuk, R. (2009). Ranking of waterways susceptible to adverse stormwater effects. Canadian Water Resources Journal, 34(3), 205-228. https://doi.org/10.4296/cwrj3403205

Gharabaghi, B., Inkratas, C., Beltaos, S., & Krishnappan, B. (2007). Modelling of three-dimensional flow velocities in a deep hole in the East Channel of the Mackenzie Delta, Northwest Territories. Canadian Journal of Civil Engineering, 34(10), 1312-1323. https://doi.org/10.1139/l07-054

Gharabaghi, B., Inkratas, C., Krishnappan, B. G., & Rudra, R. P. (2007). Flow characteristics in a rotating circular flume. Open Civil Engineering Journal, 1(1), 30-36. https://doi.org/10.2174/1874149500701010030

Flood Forecasting and Management

Oliveira Santos, V., Costa Rocha, P. A., Scott, J., Thé, J. V. G., & Gharabaghi, B. (2023). A New Graph-Based Deep Learning Model to Predict Flooding with Validation on a Case Study on the Humber River. Water, 15(10), 1827. https://doi.org/10.3390/w15101827

Zhang, Y., Pan, D., Van Griensven, J., Yang, S. X., & Gharabaghi, B. (2023). Intelligent flood forecasting and warning: a survey. https://doi.org/10.20517/ir.2023.12

Taraky, Y. M., Liu, Y., Gharabaghi, B., McBean, E., Daggupati, P., & Shrestha, N. K. (2022). Influence of headwater reservoirs on climate change impacts and flood frequency in the Kabul River Basin. Canadian Journal of Civil Engineering, 49(7), 1300-1309. https://doi.org/10.1139/cjce-2020-0840

Zhang, Y., Gu, Z., Thé, J. V. G., Yang, S. X., & Gharabaghi, B. (2022). The Discharge Forecasting of Multiple Monitoring Station for Humber River by Hybrid LSTM Models. Water, 14(11), 1794. https://doi.org/10.3390/w14111794

Kaur, B., Binns, A., Sandink, D., Gharabaghi, B., & McBean, E. (2022, June). Reducing the risk of basement flooding through building-and lot-scale flood mitigation approaches: performance of foundation drainage systems. In Proceedings of the Canadian Society of Civil Engineering Annual Conference 2021: CSCE21 Hydrotechnical and Transportation Track (pp. 471-477). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-19-1065-4_39

Elkurdy, M., Binns, A. D., Bonakdari, H., Gharabaghi, B., & McBean, E. (2022). Early detection of riverine flooding events using the group method of data handling for the Bow River, Alberta, Canada. International Journal of River Basin Management, 20(4), 533-544. https://doi.org/10.1080/15715124.2021.1906261

Grambow, K., Gharabaghi, B., & Van Griensven, J. (2022, December). Investigating River Ice Thickness and Analyzing Ice Breakup Flooding Events for Canadian Rivers. In AGU Fall Meeting Abstracts (Vol. 2022, pp. H32A-05).

Jiang, A. Z., McBean, E. A., Binns, A. D., & Gharabaghi, B. (2022). Guidance on field survey programme design for basement flooding assessment. Hydrological Sciences Journal, 67(16), 2524-2533. https://doi.org/10.1080/02626667.2020.1782412

Taraky, Y. M., Liu, Y., McBean, E., Daggupati, P., & Gharabaghi, B. (2021). Flood risk management with transboundary conflict and cooperation dynamics in the Kabul River Basin. Water, 13(11), 1513. https://doi.org/10.3390/w13111513

Bonakdari, H., Zaji, A. H., Soltani, K., & Gharabaghi, B. (2020). Improving the accuracy of a remotely-sensed flood warning system using a multi-objective pre-processing method for signal defects detection and elimination. Comptes Rendus. Géoscience, 352(1), 73-86. https:/doi.org/10.5802/crgeos.4

Bonakdari, H., Zaji, A. H., Soltani, K., & Gharabaghi, B. (2020). Amélioration de la précision d'un système d'alerte de crue par télédétection à l'aide d'une méthode de prétraitement multi-objectifs pour la détection et l'élimination des défauts de signal. Comptes Rendus Géosciences, 352, 73-86.

Nguyen, D., Binns, A. D., & Gharabaghi, B. (2020, December). Laboratory Modeling of the Morphological Development and Flood Event Response of Skewed Meandering Rivers. In AGU Fall Meeting Abstracts (Vol. 2020, pp. EP004-0004).

Grambow, K., Bandroomi Khiaban, S., Taraky, Y., & Gharabaghi, B. (2020, December). Assessment of the flood risk reduction in the Jalalabad area due to the proposed large dams in the headwaters of the Kabul River Basin. In AGU Fall Meeting Abstracts (Vol. 2020, pp. H218-0005).

Kaur, B., Szentimrey, Z., Binns, A. D., McBean, E. A., & Gharabaghi, B. (2020, December). Urban flood susceptibility mapping using supervised regression and machine learning models in Toronto, Canada. In AGU Fall Meeting Abstracts (Vol. 2020, pp. NH012-07).

Langridge, M., Gharabaghi, B., Bonakdari, H., & Walton, R. (2019). Understanding the Dynamic Nature of Catchment Response Time through Machine Learning Analysis. https://doi.org/10.1002/essoar.10501417.1

Jiang, A. Z., McBean, E. A., Binns, A., & Gharabaghi, B. (2019). Quantifying Rainfall-Derived Inflow from Private Foundation Drains in Sanitary Sewers: Case Study in London, Ontario, Canada. Journal of Hydrologic Engineering, 24(9), 05019023. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001814

Walton, R., Binns, A., Bonakdari, H., Ebtehaj, I., & Gharabaghi, B. (2019). Estimating 2-year flood flows using the generalized structure of the Group Method of Data Handling. Journal of Hydrology, 575, 671-689. https://doi.org/10.1016/j.jhydrol.2019.05.068

Bonakdari, H., Zaji, A. H., Binns, A. D., & Gharabaghi, B. (2019). Integrated Markov chains and uncertainty analysis techniques to more accurately forecast floods using satellite signals. Journal of Hydrology, 572, 75-95. https://doi.org/10.1016/j.jhydrol.2019.02.027

Sattar, A., Bonakdari, H., Gharabaghi, B., & Radecki-Pawlik, A. (2019). Hydraulic Modeling and Evaluation Equations for the Incipient Motion of Sandbags for Levee Breach Closure Operations. Water, 11(2), 279. https://doi.org/10.3390/w11020279

Zaji, A. H., Bonakdari, H., & Gharabaghi, B. (2018). Applying upstream satellite signals and a 2-D error minimization algorithm to advance early warning and management of flood water levels and river discharge. IEEE Transactions on Geoscience and Remote Sensing, 57(2), 902-910. https://doi.org/10.1109/tgrs.2018.2862640

Zaji, A. H., Bonakdari, H., & Gharabaghi, B. (2018). Remote sensing satellite data preparation for simulating and forecasting river discharge. IEEE Transactions on Geoscience and Remote Sensing, 56(6), 3432-3441. https://doi.org/10.1109/tgrs.2018.2799901

Vrban, S., Wang, Y., McBean, E. A., Binns, A., & Gharabaghi, B. (2018). Evaluation of Stormwater Infrastructure Design Storms Developed Using Partial Duration and Annual Maximum Series Models. Journal of Hydrologic Engineering, 23(12), 04018051. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001712

Perdikaris, J., Gharabaghi, B., & Rudra, R. (2018). Evaluation of the simplified dynamic wave, diffusion wave and the full dynamic wave flood routing models. Earth Sci. Res, 7(2), 14. https://doi.org/10.5539/esr.v7n2p14

Perdikaris, J., Gharabaghi, B., & Rudra, R. (2018). Reference time of concentration estimation for ungauged catchments. Earth Sci. Res, 7, 58-73. https://doi.org/10.5539/esr.v7n2p58

Perdikaris, J., Gharabaghi, B., & McBean, E. (2011). A methodology for undertaking vulnerability assessments of flood susceptible communities. International journal of safety and security engineering, 1(2), 126-146. https://doi.org/10.2495/SAFE-V1-N2-126-146

Urban Stormwater Management

Stajkowski, S., Hotson, E., Zorica, M., Farghaly, H., Bonakdari, H., McBean, E., & Gharabaghi, B. (2023). Modeling stormwater management pond thermal impacts during storm events. Journal of Hydrology, 620, 129413. https://doi.org/10.1016/j.jhydrol.2023.129413

Panjabi, K., Rudra, R., Goel, P., Ahmed, S., & Gharabaghi, B. (2021). A Modified Distributed CN-VSA Method for Mapping of the Seasonally Variable Source Areas. Water, 13(9), 1270. https://doi.org/10.3390/w13091270

Soltani, K., Ebtehaj, I., Amiri, A., Azari, A., Gharabaghi, B., & Bonakdari, H. (2021). Mapping the spatial and temporal variability of flood susceptibility using remotely sensed normalized difference vegetation index and the forecasted changes in the future. Science of the Total Environment, 770, 145288. https://doi.org/10.1016/j.scitotenv.2021.145288

Stajkowski, S., Laleva, A., Farghaly, H., Bonakdari, H., & Gharabaghi, B. (2021). Modelling dry-weather temperature profiles in urban stormwater management ponds. Journal of Hydrology, 598, 126206. https://doi.org/10.1016/j.jhydrol.2021.126206

Jahanfar, A., Drake, J., Gharabaghi, B., & Sleep, B. (2020). An experimental and modeling study of evapotranspiration from integrated green roof photovoltaic systems. Ecological Engineering, 152, 105767. https://doi.org/10.1016/j.ecoleng.2020.105767

Stajkowski, S., Gharabaghi, B., & Farghaly, H. (2020, December). Forecasting Stormwater Pond Dry-Weather Water Temperature Profiles Using the Group Method of Data Handling. In AGU Fall Meeting Abstracts (Vol. 2020, pp. H166-0015).

Trenouth, W. R., Gharabaghi, B., & Farghaly, H. (2018). Enhanced roadside drainage system for environmentally sensitive areas. Science of The Total Environment, 610, 613-622. https://doi.org/10.1016/j.scitotenv.2017.08.081

Ebtehaj, I., Bonakdari, H., & Gharabaghi, B. (2018). Development of more accurate discharge coefficient prediction equations for rectangular side weirs using adaptive neuro-fuzzy inference system and generalized group method of data handling. Measurement, 116, 473-482. https://doi.org/10.1016/j.measurement.2017.11.023

Azimi, H., Bonakdari, H., Ebtehaj, I., Gharabaghi, B., & Khoshbin, F. (2018). Evolutionary design of generalized group method of data handling-type neural network for estimating the hydraulic jump roller length. Acta Mechanica, 229(3), 1197-1214. https://doi.org/10.1007/s00707-017-2043-9

Sattar, A. M. A., Gharabaghi, B., Sabouri, F., & Thompson, A. M. (2017). Urban stormwater thermal gene expression models for protection of sensitive receiving streams. Hydrological processes, 31(13), 2330-2348. https://doi.org/10.1002/hyp.11170

Sattar, A. M. A., & Gharabaghi, B. (2017). Gene Expression Programming in Open Channel Hydraulics. In Open Channel Hydraulics, River Hydraulic Structures and Fluvial Geomorphology (pp. 196-211). CRC Press. https://doi.org/10.1201/9781315120584-11

Trenouth, W. R., & Gharabaghi, B. (2016). Highway runoff quality models for the protection of environmentally sensitive areas. Journal of hydrology, 542, 143-155. https://doi.org/10.1016/j.jhydrol.2016.08.058

Sabouri, F., Gharabaghi, B., Sattar, A. M. A., & Thompson, A. M. (2016). Event-based stormwater management pond runoff temperature model. Journal of Hydrology, 540, 306-316. https://doi.org/10.1016/j.jhydrol.2016.06.017

Sabouri, F., Gharabaghi, B., McBean, E., & Tu, C. (2016). Thermal investigation of stormwater management ponds. Journal of Water Management Modeling. https://doi.org/10.14796/JWMM.C397

Trenouth, W. R., & Gharabaghi, B. (2015). Soil amendments for heavy metals removal from stormwater runoff discharging to environmentally sensitive areas. Journal of Hydrology, 529, 1478-1487. https://doi.org/10.1016/j.jhydrol.2015.08.034

Sabouri, F., Gharabaghi, B., Mahboubi, A. A., & McBean, E. A. (2013). Impervious surfaces and sewer pipe effects on stormwater runoff temperature. Journal of hydrology, 502, 10-17. https://doi.org/10.1016/j.jhydrol.2013.08.016

Sabouri, F., Gharabaghi, B., Perera, N., & McBean, E. (2013). Evaluation of the thermal impact of stormwater management ponds. CHI Journal of Water Management Modeling. https://doi.org/10.14796/JWMM.R246-12

Finney, K., & Gharabaghi, B. (2011). Using the PCSWMM 2010 SRTC tool to design a compost biofilter for highway stormwater runoff treatment. Journal of Water Management Modeling. https://www.doi.org/10.14796/JWMM.R241-09

Finney, K., Gharabaghi, B., McBean, E., Rudra, R., & MacMillan, G. (2010). Compost biofilters for highway stormwater runoff treatment. Water Quality Research Journal, 45(4), 391-402.

Ahmed, S. I., Rudra, R. P., Gharabaghi, B., & Pedikaris, J. (2007). Change in IDF curves for a River basin in southern Ontario. In 2007 ASAE Annual Meeting (p. 1). American Society of Agricultural and Biological Engineers. https://doi.org/10.13031/2013.23207

Bradford, A., & Gharabaghi, B. (2004). Evolution of Ontario’s stormwater management planning and design guidance. Water Quality Research Journal, 39(4), 343-355. https://doi.org/10.2166/wqrj.2004.047

Construction Site Stormwater Management

Binns, A. D., Fata, A., Ferreira da Silva, A. M., Bonakdari, H., & Gharabaghi, B. (2019). Modeling Performance of Sediment Control Wet Ponds at Two Construction Sites in Ontario, Canada. Journal of Hydraulic Engineering, 145(4), 05019001. https://doi.org/10.1061/(ASCE)HY.1943-7900.0001581

Thompson, J., Sattar, A. M., Gharabaghi, B., & Warner, R. C. (2016). Event-based total suspended sediment particle size distribution model. Journal of hydrology, 536, 236-246. https://doi.org/10.1016/j.jhydrol.2016.02.056

Trenouth, W. R., & Gharabaghi, B. (2015). Event-based design tool for construction site erosion and sediment controls. Journal of hydrology, 528, 790-795. https://doi.org/10.1016/j.jhydrol.2015.06.054

Trenouth, W. R., & Gharabaghi, B. (2015). Event-based soil loss models for construction sites. Journal of Hydrology, 524, 780-788. https://doi.org/10.1016/j.jhydrol.2015.03.010

Trenouth, W. R., Gharabaghi, B., MacMillan, G., & Bradford, A. (2013). Better management of construction sites to protect inland waters. Inland Waters, 3(2), 167-178. https://doi.org/10.5268/IW-3.2.515

Taleban, V., Finney, K., Gharabaghi, B., McBean, E., Rudra, R., & Van Seters, T. (2009). Effectiveness of compost biofilters in removal of sediments from construction site runoff. Water Quality Research Journal, 44(1), 71-80. https://doi.org/10.2166/wqrj.2009.008

Gharabaghi, B., Fata, A., Seters, T. V., Rudra, R. P., MacMillan, G., Smith, D., & Tesa, G. (2006). Evaluation of sediment control pond performance at construction sites in the Greater Toronto Area. Canadian Journal of Civil Engineering, 33(11), 1335-1344. https://doi.org/10.1139/l06-074

Identification and Protection of Salt Vulnerable Areas

Tabrizi, S. E., Pringle, J., Moosavi, Z., Amouzadeh, A., Farghaly, H., Trenouth, W. R., & Gharabaghi, B. (2022). Protecting Salt Vulnerable Areas Using an Enhanced Roadside Drainage System (ERDS). Water, 14(22), 3773. https://doi.org/10.3390/w14223773

Tabrizi, S. E., Xiao, K., Thé, J. V. G., Saad, M., Farghaly, H., Yang, S. X., & Gharabaghi, B. (2021). Hourly road pavement surface temperature forecasting using deep learning models. Journal of Hydrology, 603, 126877. https://doi.org/10.1016/j.jhydrol.2021.126877

Emami Tabrizi, S., Gharabaghi, B., & Farghaly, H. (2020, December). Development of the salt application rate tool for winter road maintenance. In AGU Fall Meeting Abstracts (Vol. 2020, pp. H166-0011).

McTaggart, D., Trenouth, W. R., Stajowski, S., Farghaly, H., & Gharabaghi, B. (2018). Compost Biofilters for Protection of Environmentally Sensitive Areas Receiving Roadway Runoff. Earth Science Research, 7(2), 88. https://doi.org/10.5539/esr.v7n2p88  

Delbari, M., Afrasiab, P., Gharabaghi, B., Amiri, M., & Salehian, A. (2019). Spatial variability analysis and mapping of soil physical and chemical attributes in a salt-affected soil. Arabian Journal of Geosciences, 12(3), 68. https://doi.org/10.1007/s12517-018-4207-x

Salek, M., Levison, J., Parker, B., & Gharabaghi, B. (2018). CAD-DRASTIC: chloride application density combined with DRASTIC for assessing groundwater vulnerability to road salt application. Hydrogeology Journal, 26(7), 2379-2393. https://doi.org/10.1007/s10040-018-1801-7

Trenouth, W. R., Gharabaghi, B., & Perera, N. (2015). Road salt application planning tool for winter de-icing operations. Journal of Hydrology, 524, 401-410. https://doi.org/10.1016/j.jhydrol.2015.03.004

Betts, A., Gharabaghi, B., McBean, E., Levison, J., & Parker, B. (2015). Salt vulnerability assessment methodology for municipal supply wells. Journal of Hydrology, 531, 523-533. https://doi.org/10.1016/j.jhydrol.2015.11.004

Betts, A. R., Gharabaghi, B., & McBean, E. A. (2014). Salt vulnerability assessment methodology for urban streams. Journal of hydrology, 517, 877-888. https://doi.org/10.1016/j.jhydrol.2014.06.005

Kilgour, B. W., Gharabaghi, B., & Perera, N. (2013). Ecological benefit of the road salt code of practice. Water quality research journal of Canada, 49(1), 43-52. https://doi.org/10.2166/wqrjc.2013.129

Perera, N., Gharabaghi, B., & Howard, K. (2013). Groundwater chloride response in the Highland Creek watershed due to road salt application: A re-assessment after 20 years. Journal of Hydrology, 479, 159-168. https://doi.org/10.1016/j.jhydrol.2012.11.057

Perera, N., Gharabaghi, B., Noehammer, P., & Kilgour, B. (2010). Road salt application in Highland Creek watershed, Toronto, Ontario-chloride mass balance. Water Quality Research Journal, 45(4), 451-461. https://doi.org/10.2166/wqrj.2010.044

Perera, N., Gharabaghi, B., & Noehammer, P. (2009). Stream chloride monitoring program of City of Toronto: implications of road salt application. Water Quality Research Journal, 44(2), 132-140. https://doi.org/10.2166/wqrj.2009.014

Urban Water & Wastewater Infrastructure Management

Siwakoti, S., Binns, A., Bradford, A., Bonakdari, H., & Gharabaghi, B. (2023). A Prediction Model to Cost-Optimize Clean-Out of Permeable Interlocking Concrete Pavers. Water, 15(11), 2135. https://doi.org/10.3390/w15112135

Noori, A., Bonakdari, H., Hassaninia, M., Morovati, K., Khorshidi, I., Noori, A., & Gharabaghi, B. (2022). A reliable GIS-based FAHP-FTOPSIS model to prioritize urban water supply management scenarios: A case study in semi-arid climate. Sustainable Cities and Society, 81, 103846. https://doi.org/10.1016/j.scs.2022.103846

Bonakdari, H., Azimi, H., Ebtehaj, I., Gharabaghi, B., Jamali, A., & Talesh, S. H. A. (2022, July). Estimation of Velocity Field in Narrow Open Channels by a Hybrid Metaheuristic ANFIS Network. In Intelligent Computing: Proceedings of the 2022 Computing Conference, Volume 1 (pp. 1-24). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-031-10461-9_1

Samadi-Koucheksaraee, A., Shirvani-Hosseini, S., Ahmadianfar, I., & Gharabaghi, B. (2022). Optimization Algorithms Surpassing Metaphor. In Computational Intelligence for Water and Environmental Sciences (pp. 3-33). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-19-2519-1_1

Dusolt, S., Binns, A., McBean, E., Gharabaghi, B., & Sandink, D. (2021). Characterization of backwater valves in sanitary sewer laterals and associated failures in a Canadian context. Canadian Journal of Civil Engineering, 48(7), 829-837. https://doi.org/10.1139/cjce-2020-0026

Ahmadianfar, I., Kheyrandish, A., Jamei, M., & Gharabaghi, B. (2021). Optimizing operating rules for multi-reservoir hydropower generation systems: An adaptive hybrid differential evolution algorithm. Renewable Energy, 167, 774-790. https://doi.org/10.1016/j.renene.2020.11.152

Kazemian-Kale-Kale, A., Gholami, A., Rezaie-Balf, M., Mosavi, A., Sattar, A. A., Azimi, A. H., & Bonakdari, H. (2021). Uncertainty Assessment of Entropy-Based Circular Channel Shear Stress Prediction Models Using a Novel Method. Geosciences, 11(8), 308. https://doi.org/10.3390/geosciences11080308

Soltani, K., Azari, A., Zeynoddin, M., Amiri, A., Ebtehaj, I., Ouarda, T. B.,  & Bonakdari, H. (2021). Lake surface area forecasting using integrated satellite-SARIMA-long-short-term memory model. https://doi.org/10.21203/rs.3.rs-631247/v1

Bonakdari, H., Ebtehaj, I., Mosavi, A., Talesh, S. H. A., Jamali, A., & Gharabaghi, B. (2020). Hybrid Model of Singular Value Decomposition, ANFIS and Genetic Algorithm for Prediction of Sediment Transport in Sewers. https://doi.org/10.20944/preprints202001.0312.v1

Salimi, A. H., Noori, A., Bonakdari, H., Masoompour Samakosh, J., Sharifi, E., Hassanvand, M., & Agharazi, M. (2020). Exploring the role of advertising types on improving the water consumption behavior: An application of integrated fuzzy AHP and fuzzy VIKOR method. Sustainability, 12(3), 1232. https://doi.org/10.3390/su12031232

Ebtehaj, I., Bonakdari, H., Safari, M. J. S., Gharabaghi, B., Zaji, A. H., Madavar, H. R., & Mehr, A. D. (2020). Combination of sensitivity and uncertainty analyses for sediment transport modeling in sewer pipes. International Journal of Sediment Research, 35(2), 157-170. https://doi.org/10.1016/j.ijsrc.2019.08.005

Noori, A., Bonakdari, H., Morovati, K., & Gharabaghi, B. (2020). Development of optimal water supply plan using integrated fuzzy Delphi and fuzzy ELECTRE III methods—Case study of the Gamasiab basin. Expert Systems, 37(5), e12568. https://doi.org/10.1111/exsy.12568

Lotfi, K., Bonakdari, H., Ebtehaj, I., Delatolla, R., Zinatizadeh, A. A., & Gharabaghi, B. (2020). A novel stochastic wastewater quality modeling based on fuzzy techniques. Journal of Environmental Health Science and Engineering, 18, 1099-1120. https://doi.org/10.1007/s40201-020-00530-8

Bonakdari, H. O. S. S. E. I. N., Gharabaghi, B. A. H. R. A. M., & Ebtehaj, I. (2019). A highly efficient gene expression programming for velocity distribution at compound sewer channel. In The 38th IAHR World Congress from September 1st to 6th, Panama City, Panama (pp. 2019-0221). https://doi.org/10.3850/38WC092019-0221

Bonakdari, H. O. S. S. E. I. N., Gharabaghi, B. A. H. R. A. M., & Ebtehaj, I. (2019). Firefly optimization algorithm effect on adaptive neuro-fuzzy inference systems prediction improvement of sediment transport in sewer systems. In the 38 th IAHR World Congress from September (Vol. 1). https://doi.org/10.3850/38WC092019-0220

Brown, D., Farrow, C., McBean, E. A., Gharabaghi, B., & Beauchamp, J. (2019). Advancing performance evaluation standards for household water treatment technologies. Journal of Water and Health, 17(2), 266-273. https://doi.org/10.2166/wh.2018.266

Lotfi, K., Bonakdari, H., Ebtehaj, I., Mjalli, F. S., Zeynoddin, M., Delatolla, R., & Gharabaghi, B. (2019). Predicting wastewater treatment plant quality parameters using a novel hybrid linear-nonlinear methodology. Journal of environmental management, 240, 463-474. https://doi.org/10.1016/j.jenvman.2019.03.137

Sattar, A. A., Elhakeem, M., Rezaie-Balf, M., Gharabaghi, B., & Bonakdari, H. (2019). Artificial intelligence models for prediction of the aeration efficiency of the stepped weir. Flow Measurement and Instrumentation, 65, 78-89. https://doi.org/10.1016/j.flowmeasinst.2018.11.017

Bonakdari, H., Ebtehaj, I., Gharabaghi, B., Vafaeifard, M., & Akhbari, A. (2019). Calculating the energy consumption of electrocoagulation using a generalized structure group method of data handling integrated with a genetic algorithm and singular value decomposition. Clean Technologies and Environmental Policy, 21(2), 379-393. https://doi.org/10.1007/s10098-018-1642-z

Akhbari, A., Ibrahim, S., Zinatizadeh, A. A., Bonakdari, H., Ebtehaj, I., S. Khozani, Z., & Gharabaghi, B. (2019). Evolutionary prediction of biohydrogen production by dark fermentation. CLEAN–Soil, Air, Water, 47(1), 1700494. https://doi.org/10.1002/clen.201700494

Sattar, A. M., Ertuğrul, Ö. F., Gharabaghi, B., McBean, E. A., & Cao, J. (2019). Extreme learning machine model for water network management. Neural Computing and Applications, 31(1), 157-169. https://doi.org/10.1007/s00521-017-2987-7

Bonakdari, H., Zaji, A. H., Gharabaghi, B., Ebtehaj, I., & Moazamnia, M. (2018). More accurate prediction of the complex velocity field in sewers based on uncertainty analysis using extreme learning machine technique. ISH Journal of Hydraulic Engineering, 1-12. https://doi.org/10.1080/09715010.2018.1498753

Bostan, M., Akhtari, A. A., Bonakdari, H., Gharabaghi, B., & Noori, O. (2018). Investigation of a new shock damper system efficiency in reducing water hammer excess pressure due to the sudden closure of a control valve. ISH Journal of Hydraulic Engineering, 1-9. https://doi.org/10.1080/09715010.2018.1479665

Gharabaghi, B., Bonakdari, H., & Ebtehaj, I. (2018, July). Hybrid evolutionary algorithm based on PSOGA for ANFIS designing in prediction of no-deposition bed load sediment transport in sewer pipe. In Science and information conference (pp. 106-118). Springer, Cham. https://doi.org/10.1007/978-3-030-01177-2_8

Post, Y. L., McBean, E., & Gharabaghi, B. (2018). Using Probabilistic Neural Networks to Analyze First Nations’ Drinking Water Advisory Data. Journal of Water Resources Planning and Management, 144(11), 05018015. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000988

Sattar, A. M. A., Bonakdari, H., Negm, A., Gharabaghi, B., & Elhakeem, M. (2018). Soil Aquifer Treatment System Design Equation for Organic Micropollutant Removal. In Groundwater in the Nile Delta (pp. 307-326). Springer, Cham. https://doi.org/10.1007/698_2017_136

Uduma, U. A., McBean, E. A., & Gharabaghi, B. (2017). Risk assessment of cyanobacteria-toxins for small drinking water treatment plants with lake water intakes. International Journal of Water Resources and Environmental Engineering, 9(6), 121-126. https://doi.org/10.5897/ijwree2016.0669

Abbassi, B.E., Abu Saleem, M., Zytner, R.G., Gharabaghi, B., & Rudra R. (2016). Antibiotics in wastewater: Their degradation and effect on wastewater treatment efficiency. Food, Agriculture and Environment (JFAE), Vol. 14, Issue 3&4, pages 95-99. Online ISSN: 1459-0263.

Sattar, A. M., Gharabaghi, B., & McBean, E. A. (2016). Prediction of timing of watermain failure using gene expression models. Water resources management, 30(5), 1635-1651. https://doi.org/10.1007/s11269-016-1241-x

Harvey, R., Murphy, H. M., McBean, E. A., & Gharabaghi, B. (2015). Using data mining to understand drinking water advisories in small water systems: A case study of Ontario First Nations drinking water supplies. Water resources management, 29(14), 5129-5139. https://doi.org/10.1007/s11269-015-1108-6

Harvey, R., McBean, E. A., & Gharabaghi, B. (2013). Predicting the timing of water main failure using artificial neural networks. Journal of Water Resources Planning and Management, 140(4), 425-434. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000354

Asnaashari, A., McBean, E. A., Gharabaghi, B., & Tutt, D. (2013). Forecasting watermain failure using artificial neural network modelling. Canadian Water Resources Journal, 38(1), 24-33. https://doi.org/10.1080/07011784.2013.774153

Asnaashari, A., McBean, E., Gharabaghi, B., Pourrajab, R., & Shahrour, I. (2010). Survival rate analyses of watermains: a comparison of case studies for Canada and Iran. Journal of Water Management Modeling. https://doi.org/10.14796/JWMM.R236-30 

Asnaashari, A., McBean, E. A., Shahrour, I., & Gharabaghi, B. (2009). Prediction of watermain failure frequencies using multiple and Poisson regression. Water Science and Technology: Water Supply, 9(1), 9-19. https://doi.org/10.2166/ws.2009.020

Agricultural Soil & Water Management

Ebtehaj, I., Bonakdari, H., Samui, P., & Gharabaghi, B. (2023). Multi-depth daily soil temperature modeling: meteorological variables or time series? Theoretical and Applied Climatology, 151(3-4), 989-1012. https://doi.org/10.1007/s00704-022-04314-y

Alizamir, M., Kim, S., Zounemat-Kermani, M., Heddam, S., Shahrabadi, A. H., & Gharabaghi, B. (2021). Modelling daily soil temperature by hydro-meteorological data at different depths using a novel data-intelligence model: deep echo state network model. Artificial Intelligence Review, 54, 2863-2890. https://doi.org/10.1007/s10462-020-09915-5

Seifi, A., Ehteram, M., Nayebloei, F., Soroush, F., Gharabaghi, B., & Haghighi, A. T. (2021). Hourly soil temperature prediction using integrated machine learning methods, GLUE uncertainty analysis, Taguchi search, and wavelet coherence analysis.  https://doi.org/10.21203/rs.3.rs-285852/v1

Seifi, A., Ehteram, M., Nayebloei, F., Soroush, F., Gharabaghi, B., & Torabi Haghighi, A. (2021). GLUE uncertainty analysis of hybrid models for predicting hourly soil temperature and application wavelet coherence analysis for correlation with meteorological variables. Soft Computing, 25, 10723-10748. https://doi.org/10.1007/s00500-021-06009-4

Riahi-Madvar, H., Gholami, M., Gharabaghi, B., & Seyedian, S. M. (2021). A predictive equation for residual strength using a hybrid of subset selection of maximum dissimilarity method with Pareto optimal multi-gene genetic programming. Geoscience Frontiers, 12(5), 101222. https://doi.org/10.1016/j.gsf.2021.101222

Mundi, G., Zytner, R. G., Warriner, K., Bonakdari, H., & Gharabaghi, B. (2021). Machine learning models for predicting water quality of treated fruit and vegetable wastewater. Water, 13(18), 2485. https://doi.org/10.3390/w13182485

Kyle, D. M., Roy, S. K., Sheshukov, A. Y., Biswas, A., Gharabaghi, B., Binns, A.,  & Daggupati, P. (2020). A comprehensive review of ephemeral gully erosion models. https://doi.org/10.1016/j.catena.2020.104901

Douglas-Mankin, K. R., Roy, S. K., Sheshukov, A. Y., Biswas, A., Gharabaghi, B., Binns, A.,  & Daggupati, P. (2020). A comprehensive review of ephemeral gully erosion models. Catena, 195, 104901. https://doi.org/10.1016/j.catena.2020.104901

Jahanfar, A., Drake, J., Sleep, B., & Gharabaghi, B. (2018). A modified FAO evapotranspiration model for refined water budget analysis for Green Roof systems. Ecological Engineering, 119, 45-53. https://doi.org/10.1016/j.ecoleng.2018.04.021

Noori, A., Bonakdari, H., Morovati, K., & Gharabaghi, B. (2018). The optimal dam site selection using a group decision-making method through fuzzy TOPSIS model. Environment Systems and Decisions, 38(4), 471-488. https://doi.org/10.1007/s10669-018-9673-x

Mundi, G. S., Zytner, R. G., Warriner, K., & Gharabaghi, B. (2018). Predicting fruit and vegetable processing wash-water quality. Water Science and Technology, 2017(1), 256-269.  https://doi.org/10.2166/wst.2018.109

Atieh, M., Rudra, R., Gharabaghi, B., Golmohammadi, G., Mohammadi, K. (2017). Investigating solutions for irrigation water deficiency in Lebanon. Food, Agriculture and Environment, 15(2), 86-96. https://doi.org/10.1234/4.2017.1122

Mattar, M. A., Alazba, A. A., Alblewi, B., Gharabaghi, B., & Yassin, M. A. (2016). Evaluating and calibrating reference evapotranspiration models using water balance under hyper-arid environment. Water resources management, 30(11), 3745-3767. https://doi.org/10.1007/s11269-016-1382-y

Alblewi, B., Gharabaghi, B., Alazba, A. A., & Mahboubi, A. A. (2015). Evapotranspiration models assessment under hyper-arid environment. Arabian Journal of Geosciences, 8(11), 9905-9912. https://doi.org/10.1007/s12517-015-1867-7

Sayyad, G., Vasel, L., Besalatpour, A. A., Gharabaghi, B., & Golmohammadi, G. (2015). Modeling Blue and Green Water Resources Availability in an Iranian Data Scarce Watershed Using SWAT. Journal of Water Management Modeling. https://doi.org/10.14796/JWMM.C391

Ahmed, S. I., Singh, A., Rudra, R., & Gharabaghi, B. (2013). Comparison of CANWET and HSPF for water budget and water quality modeling in rural Ontario. Water Quality Research Journal of Canada, 49(1), 53-71. https://doi.org/10.2166/wqrjc.2013.044

Singh, A., Rudra, R. P., & Gharabaghi, B. (2012). Evaluation of CANWET model for hydrologic simulations for upper Canagagigue Creek watershed in southern Ontario. Canadian Biosystems Engineering, 54(1), 7-18. Part of ISSN: 14929058

Das, S., Rudra, R. P., Gharabaghi, B., Gebremeskel, S., Goel, P. K., & Dickinson, W. T. (2008). Applicability of AnnAGNPS for Ontario conditions. Canadian Biosystems Engineering, 50(1), 1-11. EID:2-s2.0-77951848798

Ricketts, D. D., Rudra, R. P., & Gharabaghi, B. (2007). An irrigation management model for a multi‐cropping and multi‐pattern setting. Irrigation and Drainage: The journal of the International Commission on Irrigation and Drainage, 56(4), 451-462. https://doi.org/10.1002/ird.311

Motiee, H., Mcbean, E., Semsar, A., Gharabaghi, B., & Ghomashchi, V. (2006). Assessment of the contributions of traditional qanats in sustainable water resources management. International Journal of Water Resources Development, 22(4), 575-588. https://doi.org/10.1080/07900620600551304

Rural Basin Water Quality Management

Taraky, Y. M., McBean, E., Liu, Y., Daggupati, P., Shrestha, N. K., Jiang, A., & Gharabaghi, B. (2021). The role of large dams in a transboundary drought management co-operation framework—case study of the Kabul River Basin. Water, 13(19), 2628. https://doi.org/10.3390/w13192628

Noori, A., Bonakdari, H., Salimi, A. H., & Gharabaghi, B. (2021). A group Multi-Criteria Decision-Making method for water supply choice optimization. Socio-Economic Planning Sciences, 77, 101006. https://doi.org/10.1016/j.seps.2020.101006

Gupta, A. K., Rudra, R. P., Gharabaghi, B., Daggupati, P., Goel, P. K., & Shukla, R. (2019). CoBAGNPS: A toolbox for simulating water and sediment control basin, WASCoB through AGNPS model. Catena, 179, 49-65. https://doi.org/10.1016/j.catena.2019.02.003

Liu, Y., Yang, W., Yu, Z., Lung, I., & Gharabaghi, B. (2015). Estimating sediment yield from upland and channel erosion at a watershed scale using SWAT. Water resources management, 29(5), 1399-1412. https://doi.org/10.1007/s11269-014-0729-5

Chapi, K., Rudra, R. P., Ahmed, S. I., Khan, A. A., Gharabaghi, B., Dickinson, W. T., & Goel, P. K. (2015). Spatial-temporal dynamics of runoff generation areas in a small agricultural watershed in southern Ontario. Journal of Water Resource and Protection, 7(1), 14-40. https://doi.org/10.4236/jwarp.2015.71002

Ahmed, S. I., Rudra, R. P., Gharabaghi, B., Mackenzie, K., & Dickinson, W. T. (2012). Within-storm rainfall distribution effect on soil erosion rate. ISRN Soil Science, 2012. https://doi.org/10.13031/2013.39243  

Ahmed, I., Rudra, R., McKague, K., Gharabaghi, B., & Ogilvie, J. (2007). Evaluation of the root zone water quality model (RZWQM) for southern ontario: part I. Sensitivity analysis, calibration, and validation. Water Quality Research Journal, 42(3), 202-218. https://doi.org/10.2166/wqrj.2007.024

Ahmed, I., Rudra, R., McKague, K., Gharabaghi, B., & Ogilvie, J. (2007). Evaluation of the Root Zone Water Quality Model (RZWQM) for Southern Ontario: Part II. Simulating long-term effects of nitrogen management practices on crop yield and subsurface drainage water quality. Water Quality Research Journal, 42(3), 219-230. https://doi.org/10.2166/wqrj.2007.025

Das, S., Rudra, R. P., Goel, P. K., Gharabaghi, B., & Gupta, N. (2006). Evaluation of AnnAGNPS in cold and temperate regions. Water science and technology, 53(2), 263-270. https://doi.org/10.2166/wst.2006.060

Rudra, R. P., Gharabaghi, B., Gebremeskel, S., Das, S., & Bai, H. (2006). Hydrological and water quality modeling in the Ontario River basins: comparison of model results. WIT Transactions on Ecology and the Environment, 95. https://doi.org/10.2495/WP060171

McKague, K., Rudra, R. P., Ahmed, S. I., Gharabaghi, B., & Ogilvie, J. R. (2006). Simulating effects of MERN and other BMPs on subsurface drainage water quality and crop yield in southern Ontario. Canadian Biosystems Engineering, 48, 1.31-1.40. EID: 2-s2.0-33846217011 Rudra, R. P., Dickinson, W. T., & Gharabaghi, B. (2005). Hydrological concepts critical for water quality modeling.International Agricultural Engineering Journal, 14(4), 245-253.

Agricultural BMP Assessment and Design

Gupta, A. K., Rudra, R. P., Gharabaghi, B., Goel, P. K., Sebti, S., Shukla, R., & Daggupati, P. (2019). A Modeling Approach for Evaluating Watershed-scale Water Quality Benefits of Vegetative Filter Strip-A Case Study in Ontario. Applied Engineering in Agriculture, 35(3), 271-281. https://doi.org/10.13031/aea.13121

Gupta, A. K., Rudra, R. P., Gharabaghi, B., Daggupati, P., Parkin, G., Goel, P. K., & Shukla, R. (2018) CoBAGNPS: A Toolbox to Estimate Sediment Removal Efficiency of WASCoBs–Pipe Risers and Blind Inlets. Environment and Natural Resources Research, 8(3), 84. https://doi.org/10.5539/enrr.v8n3p84

Gupta, A. K., Rudra, R. P., Gharabaghi, B., Daggupati, P., Goel, P. K., & Shukla, R. (2018). Predicting the Impact of Drainage Ditches upon Hydrology and Sediment Loads Using KINEROS 2 Model: A Case Study in Ontario. Canadian Biosystems Engineering/Le génie des biosystèmes au Canada, 60, 1-1. https://doi.org/10.7451/CBE.2018.60.1.1

DeLay, E., & Gharabaghi, B. (2018). A review of low-grade weirs as an agri-environmental best management practice in the Elginfield Municipal Drain watershed, Ontario, Canada. Journal of Soil and Water Conservation, 73(2), 42A-48A. https://doi.org/10.2489/jswc.73.2.42A

Singh, H. V., Thompson, A. M., & Gharabaghi, B. (2016). Event runoff and sediment-yield neural network models for assessment and design of management practices for small agricultural watersheds. Journal of Hydrologic Engineering, 22(2), 04016056. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001457

Stang, C., Gharabaghi, B., Rudra, R., Golmohammadi, G., Mahboubi, A. A., & Ahmed, S. I. (2016). Conservation management practices: success story of the Hog Creek and Sturgeon River watersheds, Ontario, Canada. Journal of Soil and Water Conservation, 71(3), 237-248. https://doi.org/10.2489/jswc.71.3.237

Rudra, R. P., Gharabaghi, B., Sebti, S., Gupta, N., & Moharir, A. (2010). GDVFS: A new toolkit for analysis and design of vegetative filter strips using VFSMOD. Water Quality Research Journal, 45(1), 59-68. https://doi.org/10.2166/wqrj.2010.007

Gharabaghi, B., Rudra, R. P., & Goel, P. K. (2006). Effectiveness of vegetative filter strips in removal of sediments from overland flow. Water Quality Research Journal, 41(3), 275-282. https://doi.org/10.2166/wqrj.2006.031

Gharabaghi, B., Rudra, R. P., Whiteley, H. R., & Dickinson, W. T. (2002). Development of a management tool for vegetative filter strips. Best Modeling Practices for Urban Water Systems, Monograph, 10, 289. https://doi.org/10.14796/JWMM.R208-18

Gharabaghi, B., Dickinson, W. T., Rudra, R. P., Snodgrass, W. J., & Krishnappan, B. G. (1999). Performance analysis of reinforced vegetative channel lining systems. Computers & Structures, 72(1-3), 149-164. https://doi.org/10.1016/S0045-7949(99)00005-X

Contaminant Transport in Porous Media

Safadoust, A., Amiri Khaboushan, E., Mahboubi, A. A., Gharabaghi, B., Mosaddeghi, M. R., Ahrens, B., & Hassanpour, Y. (2016). Comparison of three models describing bromide transport affected by different soil structure types. Archives of Agronomy and Soil Science, 62(5), 674-687. https://doi.org/10.1080/03650340.2015.1074184

Gharabaghi, B., Safadoust, A., Mahboubi, A. A., Mosaddeghi, M. R., Unc, A., Ahrens, B., & Sayyad, G. (2015). Temperature effect on the transport of bromide and E. coli NAR in saturated soils. Journal of Hydrology, 522, 418-427. https://doi.org/10.1016/j.jhydrol.2015.01.003

Safadoust, A., Doaei, N., Mahboubi, A. A., Mosaddeghi, M. R., Gharabaghi, B., Voroney, P., & Ahrens, B. (2016). Long-term cultivation and landscape position effects on aggregate size and organic carbon fractionation on surface soil properties in semi-arid region of Iran. Arid Land Research and Management, 30(4), 345-361. https://doi.org/10.1080/15324982.2015.1016244

Yousefi, G., Safadoust, A., Mahboubi, A. A., Gharabaghi, B., Mosaddeghi, M. R., Ahrens, B., & Shirani, H. (2014). Bromide and lithium transport in soils under long-term cultivation of alfalfa and wheat. Agriculture, Ecosystems & Environment, 188, 221-228. https://doi.org/10.1016/j.agee.2014.02.031

Sheklabadi, M., Mahmoudzadeh, H., Mahboubi, A. A., Gharabaghi, B., & Ahrens, B. (2015). Long-term land-use change effects on phosphorus fractionation in Zrêbar Lake margin soils. Archives of Agronomy and Soil Science, 61(6), 737-749. https://doi.org/10.1080/03650340.2014.954106

Sheklabadi, M., Mahmoudzadeh, H., Mahboubi, A. A., Gharabaghi, B., & Ahrens, B. (2014). Land use effects on phosphorus sequestration in soil aggregates in western Iran. Environmental monitoring and assessment, 186(10), 6493-6503. https://doi.org/10.1007/s10661-014-3869-4

Arshad, R. R., Sayyad, G., Mosaddeghi, M., & Gharabaghi, B. (2013). Predicting saturated hydraulic conductivity by artificial intelligence and regression models. ISRN Soil Science, 2013. https://doi.org/10.1155/2013/308159

Safadoust, A., Feizee, P., Mahboubi, A. A., Gharabaghi, B., Mosaddeghi, M. R., & Ahrens, B. (2014). Least limiting water range as affected by soil texture and cropping system. Agricultural Water Management, 136, 34-41. https://doi.org/10.1016/j.agwat.2014.01.007

Safadoust, A., Mahboubi, A. A., Mosaddeghi, M. R., Gharabaghi, B., Unc, A., Voroney, P., & Heydari, A. (2012). Effect of regenerated soil structure on unsaturated transport of Escherichia coli and bromide. Journal of hydrology, 430, 80-90. https://doi.org/10.1016/j.jhydrol.2012.02.003

Safadoust, A., Mahboubi, A. A., Mosaddeghi, M. R., Gharabaghi, B., Voroney, P., Unc, A., & Khodakaramian, G. (2012). Significance of physical weathering of two-texturally different soils for the saturated transport of Escherichia coli and bromide. Journal of environmental management, 107, 147-158. https://doi.org/10.1016/j.jenvman.2012.04.007

Safadoust, A., Mahboubi, A. A., Gharabaghi, B., Mosaddeghi, M. R., Voroney, P., Unc, A., & Sayyad, G. (2011). Bacterial filtration rates in repacked and weathered soil columns.Geoderma, 167, 204-213. https://doi.org/10.1016/j.geoderma.2011.08.014

Solid Waste Management

Jahanfar, A., Amirmojahedi, M., Gharabaghi, B., Dubey, B., McBean, E., & Kumar, D. (2017). A novel risk assessment method for landfill slope failure: Case study application for Bhalswa Dumpsite, India. Waste Management & Research, 35(3), 220-227. https://doi.org/10.1177/0734242X16686412

Jahanfar, A., Gharabaghi, B., McBean, E. A., & Dubey, B. K. (2017). Municipal solid waste slope stability modeling: a probabilistic approach. Journal of Geotechnical and Geoenvironmental Engineering, 143(8), 04017035. https://doi.org/10.1061/(ASCE)GT.1943-5606.0001704

De Stefano, M., Gharabaghi, B., Clemmer, R., & Jahanfar, M. A. (2016). Berm design to reduce risks of catastrophic slope failures at solid waste disposal sites. Waste Management & Research, 34(11), 1117-1125. https://doi.org/10.1177/0734242X16662332

Jahanfar, A., Dubey, B., Gharabaghi, B., & Movahed, S. B. (2016). Landfill failure mobility analysis: a probabilistic approach. International Journal of Environmental, Chemical, Ecological, Geological and Geophysical Engineering, 10, 476-484. SOURCE-WORK-ID: 062616112227-259

Gharabaghi, B., Singh, M. K., Inkratas, C., Fleming, I. R., & McBean, E. (2008). Comparison of slope stability in two Brazilian municipal landfills. Waste management, 28(9), 1509-1517. https://doi.org/10.1016/j.wasman.2007.07.006

Air Quality Management

Oliveira Santos, V., Costa Rocha, P. A., Scott, J., Van Griensven Thé, J., & Gharabaghi, B. (2023). Spatiotemporal Air Pollution Forecasting in Houston-TX: A Case Study for Ozone Using Deep Graph Neural Networks. Atmosphere, 14(2), 308. https://doi.org/10.3390/atmos14020308

Santos, V. O., Rocha, P. A. C., Scott, J., Thé, J. V. G., & Gharabaghi, B. (2023). Spatiotemporal analysis of bidimensional wind speed forecasting: Development and thorough assessment of LSTM and ensemble graph neural networks on the Dutch database. Energy, 278, 127852. https://doi.org/10.1016/j.energy.2023.127852

Kia, S., Nambiar, M. K., Thé, J., Gharabaghi, B., & Aliabadi, A. A. (2022). Machine Learning to Predict Area Fugitive Emission Fluxes of GHGs from Open-Pit Mines. Atmosphere, 13(2), 210. https://doi.org/10.3390/atmos13020210

Clement, D., Aliabadi, A. A., Mackey, J., Thé, J., & Gharabaghi, B. (2021). Dust emissions management model for construction sites. Journal of Construction Engineering and Management, 147(8), 04021092. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002121

Freeman, B., Thé, J., Gharabaghi, B. (2020). Estimating on-road vehicle density using crowdsourced data and Monte Carlo analysis. A&WMA’s 113 th Annual Conference & Exhibition June 29 - July 2, 2020, Paper #809377.

Poursorkhabi, V., Abdelwahab, M. A., Misra, M., Khalil, H., Gharabaghi, B., & Mohanty, A. K. (2020). Processing, carbonization, and characterization of lignin based electrospun carbon fibers: a review. Frontiers in Energy Research, 8, 208. https://doi.org/10.3389/fenrg.2020.00208

Aliabadi, A. A., Moradi, M., Clement, D., Lubitz, W. D., & Gharabaghi, B. (2019). Flow and temperature dynamics in an urban canyon under a comprehensive set of wind directions, wind speeds, and thermal stability conditions. Environmental Fluid Mechanics, 19(1), 81-109. https://doi.org/10.1007/s10652-018-9606-8

Freeman, B., & Gharabaghi, B. (2019). Estimating annual air emissions from nargyla water pipes in cafés and restaurants using Monte Carlo analysis. International Journal of Environmental Science and Technology, 16(6), 2539-2548. https://doi.org/10.1007/s13762-018-1662-6

Freeman, B. S., Al Matawah, J. A., Al Najjar, M., Gharabaghi, B., & Thé, J. (2019). Vehicle stacking estimation at signalized intersections with unmanned aerial systems. International Journal of Transportation Science and Technology, 8(2), 231-249. https://doi.org/10.1016/j.ijtst.2018.12.002

Sattar, A. M., Elhakeem, M., Gerges, B. N., Gharabaghi, B., & Gultepe, I. (2018). Wind-Induced Air-Flow Patterns in an Urban Setting: Observations and Numerical Modeling. Pure and Applied Geophysics, 175(8), 3051-3068. https://doi.org/10.1007/s00024-018-1846-5

Freeman, B. S., Taylor, G., Gharabaghi, B., & Thé, J. (2018). Forecasting air quality time series using deep learning. Journal of the Air & Waste Management Association, 68(8), 866-886. https://doi.org/10.1080/10962247.2018.1459956

Freeman, B., Gharabaghi, B., Thé, J., Munshed, M., Faisal, S., Abdullah, M., & Al Aseed, A. (2017). Mapping air quality zones for coastal urban centers. Journal of the Air & Waste Management Association, 67(5), 565-581. https://doi.org/10.1080/10962247.2016.1265025

Freeman, B., McBean, E., Gharabaghi, B., & Thé, J. (2017). Evaluation of air quality zone classification methods based on ambient air concentration exposure. Journal of the Air & Waste Management Association, 67(5), 550-564. https://doi.org/10.1080/10962247.2016.1263585

Freeman, B., Gharabaghi, B., & Thé, J. (2015). Estimation of mixed traffic densities in congested road using Monte Carlo analysis. EM: Air & Waste Management Association’s magazine for environmental managers, April 2015:8-13.

Freeman, B., Gharabaghi, B., Faisal, S., & Thé, J. (2015). Vehicle I/M Programs for Developing Nations. EM: Air & Waste Management Association’s magazine for environmental managers, April 2015:14-18.

Weiss, L., Thé, J., Winter, J., & Gharabaghi, B. (2018). Optimizing best management practices to control anthropogenic sources of atmospheric phosphorus deposition to inland lakes. Journal of the Air & Waste Management Association, 68(10), 1025-1037. https://doi.org/10.1080/10962247.2018.1463929

Weiss, L. (2018). A New Methodology to Manage Anthropogenic Sources of Phosphorus Deposition to Lakes: Lake Simcoe Case Study (Doctoral dissertation).

Weiss, L., Gharabaghi, B., & Thé, J. (2015). Modelling and Management of PM10 from Mobile Sources. EM: Air & Waste Management Association’s magazine for environmental managers, April 2015:24-28.

Weiss, L., Thé, J., Gharabaghi, B., Stainsby, E. A., & Winter, J. G. (2014). A new dust transport approach to quantify anthropogenic sources of atmospheric PM10 deposition on lakes. Atmospheric environment, 96, 380-392. https://doi.org/10.1016/j.atmosenv.2014.07.060

Weiss, L., Stainsby, E. A., Gharabaghi, B., Thé, J., & Winter, J. G. (2013). Mapping key agricultural sources of dust emissions within the Lake Simcoe airshed. Inland Waters, 3(2), 153-166. https://doi.org/10.5268/IW-3.2.515

Brown, L. J., Taleban, V., Gharabaghi, B., & Weiss, L. (2011). Seasonal and spatial distribution patterns of atmospheric phosphorus deposition to Lake Simcoe, ON. Journal of Great Lakes Research, 37, 15-25. https://doi.org/10.1016/j.jglr.2011.01.004

Ramkellawan, J., Gharabaghi, B., & Winter, J. G. (2009). Application of weather radar in estimation of bulk atmospheric deposition of total phosphorus over Lake Simcoe. Canadian Water Resources Journal, 34(1), 37-60. https://doi.org/10.4296/cwrj3401037

Climate Variability and Change

Panjabi, K., Rudra, R. P., Shukla, R., Shrestha, N. K., Goel, P. K., Daggupati, P., & Gharabaghi, B. (2023). Spatiotemporal variability of minimum runoff generating areas: a field investigation. Hydrological Sciences Journal, (just-accepted). https://doi.org/10.1080/02626667.2023.2195558

Livingston, T., McBean, E., Marchildon, M., & Gharabaghi, B. (2021). Hydrologic impacts of climate change in relation to Ontario’s source water protection planning program. Canadian Journal of Civil Engineering, 48(8), 1037-1045. https://doi.org/10.1139/cjce-2019-0649

Taraky, Y., Gharabaghi, B., McBean, E. A., Daggupati, P., Liu, Y., & Shrestha, N. (2020, December). Identification of Opportunities for International Cooperation over Proposed Series of Large Freshwater Reservoirs to Capture the Melting Glaciers in the Hindu Kush Himalayan (HKH) maountains. In AGU Fall Meeting Abstracts (Vol. 2020, pp. H118-11).

Gultepe, I., Sharman, R., Williams, P. D., Zhou, B., Ellrod, G., Minnis, P.,  & Neto, F. A. (2019). A review of high impact weather for aviation meteorology. Pure and applied geophysics, 176, 1869-1921. https://doi.org/10.1007/s00024-019-02168-6

Langridge, M., Gharabaghi, B., & Bonakdari, H. (2019, December). Understanding the Dynamic Nature of Catchment Response Time through Large-Scale Machine Learning Analysis. In AGU Fall Meeting Abstracts (Vol. 2019, pp. H31I-1822).

Nalley, D., Adamowski, J., Biswas, A., Gharabaghi, B., & Hu, W. (2019). A multiscale and multivariate analysis of precipitation and streamflow variability in relation to ENSO, NAO and PDO. Journal of Hydrology, 574, 288-307. https://doi.org/10.1016/j.jhydrol.2019.04.024

Wang, Y., McBean, E., & Gharabaghi, B. (2018). Increased risks of waterborne disease outbreaks in northern Ontario due to climate change. Journal of Water Management Modeling. https://doi.org/10.14796/jwmm.c436

Atieh, M., Rudra, R., Gharabaghi, B., & Lubitz, D. (2017). Investigating the Spatial and Temporal Variability of Precipitation using Entropy Theory. Journal of Water Management Modeling. https://doi.org/10.14796/jwmm.c420

Atieh, M., Rudra, R., & Gharabaghi, B. (2015). Investigation of Spatial and Temporal Variability of Precipitation using an Entropy Theory. In ASABE 1st Climate Change Symposium: Adaptation and Mitigation Conference Proceedings (pp. 1-3). American Society of Agricultural and Biological Engineers. https://doi.org/10.13031/cc.20152141843

Asnaashari, A., Gharabaghi, B., McBean, E., & Mahboubi, A. A. (2015). Reservoir management under predictable climate variability and change. Journal of Water and Climate Change, 6(3), 472-485. https://doi.org/10.2166/wcc.2015.053

Rudra, R., Dickinson, W.T., Ahmed, S. I., Patel, P., Zhou, J., & Gharabaghi, B. (2015).  Changes in Rainfall Extremes in Ontario.   International Journal of Environmental Research, 9 (4), 1117-1372. https://doi.org/10.22059/ijer.2015.1000

Vasiljevic, B., McBean, E., & Gharabaghi, B. (2012). Trends in rainfall intensity for stormwater designs in Ontario. Journal of Water and Climate Change, 3(1), 1-10. https://doi.org/10.2166/wcc.2012.125

McBean, E., deJong, A., & Gharabaghi, B. (2011). Groundwater in Bangladesh: implications in a climate-changing world. Water Res Manage, 1(3), 3-8.

deJong, A., McBean, E., & Gharabaghi, B. (2010). Projected climate conditions to 2100 for Regina, Saskatchewan. Canadian Journal of Civil Engineering, 37(9), 1247-1260. https://doi.org/10.1139/L10-061 McKague, K., Rudra, R., Ogilvie, J., Ahmed, I., & Gharabaghi, B. (2005). Evaluation of weather generator ClimGen for southern Ontario.Canadian Water Resources Journal, 30(4), 315-330. https://doi.org/10.4296/cwrj3004315

Hydrologic Time Series Forecasting

Costa Rocha, P. A., Johnston, S. J., Oliveira Santos, V., Aliabadi, A. A., Thé, J. V. G., & Gharabaghi, B. (2023). Deep Neural Network Modeling for CFD Simulations: Benchmarking the Fourier Neural Operator on the Lid-Driven Cavity Case. Applied Sciences, 13(5), 3165. https://doi.org/10.3390/app13053165

Ebtehaj, I., Bonakdari, H., Gharabaghi, B., & Khelifi, M. (2023). Time-Series-Based Air Temperature Forecasting Based on the Outlier Robust Extreme Learning Machine. Environmental Sciences Proceedings, 25(1), 51. https://doi.org/10.3390/ECWS-7-14236

Ebtehaj, I., Bonakdari, H., Gharabaghi, B., & Khelifi, M. (2023). Short-Term Precipitation Forecasting Based on the Improved Extreme Learning Machine Technique. Environmental Sciences Proceedings, 25(1), 50. https://doi.org/10.3390/ECWS-7-14237

Langridge, M., Gharabaghi, B., Bonakdari, H., & Walton, R. (2022). Understanding the Dynamic Nature of Catchment Response Time through Machine Learning Analysis. Authorea Preprints. 10.1002/essoar.10501417.1

Soltani, K., Amiri, A., Zeynoddin, M., Ebtehaj, I., Gharabaghi, B., & Bonakdari, H. (2021). Forecasting monthly fluctuations of lake surface areas using remote sensing techniques and novel machine learning methods. Theoretical and Applied Climatology, 143, 713-735. https://doi.org/10.1007/s00704-020-03419-6

Langridge, M., McBean, E., Bonakdari, H., & Gharabaghi, B. (2021). A dynamic prediction model for time‐to‐peak. Hydrological Processes, 35(1), e14032. https://doi.org/10.1002/hyp.14032

Lotfi, K., Bonakdari, H., Ebtehaj, I., Rezaie-Balf, M., Samui, P., Sattar, A. A., & Gharabaghi, B. (2021). River flow forecasting using stochastic and neuro-fuzzy-embedded technique: a comprehensive preprocessing-based assessment. In Water Eng. Modeling and Mathematic Tools (pp. 519-549). Elsevier. https://doi.org/10.1016/B978-0-12-820644-7.00010-4

Riahi-Madvar, H., Dehghani, M., Memarzadeh, R., & Gharabaghi, B. (2021). Short to long-term forecasting of river flows by heuristic optimization algorithms hybridized with ANFIS. Water Resources Management, 35, 1149-1166. https://doi.org/10.1007/s11269-020-02756-5

Azari, A., Zeynoddin, M., Ebtehaj, I., Sattar, A. M., Gharabaghi, B., & Bonakdari, H. (2021). Integrated preprocessing techniques with linear stochastic approaches in groundwater level forecasting. Acta Geophysica, 69(4), 1395-1411. https://doi.org/10.1007/s11600-021-00617-2

Ebtehaj, I., Bonakdari, H., Zeynoddin, M., Gharabaghi, B., & Azari, A. (2020). Evaluation of preprocessing techniques for improving the accuracy of stochastic rainfall forecast models. International Journal of Environmental Science and Technology, 17, 505-524. https://doi.org/10.1007/s13762-019-02361-z

Langridge, M., Gharabaghi, B., McBean, E., Bonakdari, H., & Walton, R. (2020). Understanding the dynamic nature of Time-to-Peak in UK streams. Journal of Hydrology, 583, 124630. https://doi.org/10.1016/j.jhydrol.2020.124630

Zeynoddin, M., Bonakdari, H., Ebtehaj, I., Azari, A., & Gharabaghi, B. (2020). A generalized linear stochastic model for lake level prediction. Science of The Total Environment, 723, 138015. https://doi.org/10.1016/j.scitotenv.2020.138015

Stajkowski, S., Kumar, D., Samui, P., Bonakdari, H., & Gharabaghi, B. (2020). Genetic-algorithm-optimized sequential model for water temperature prediction. Sustainability, 12(13), 5374. https://doi.org/10.3390/su12135374

Bonakdari, H., Binns, A. D., & Gharabaghi, B. (2020). A comparative study of linear stochastic with nonlinear daily river discharge forecast models. Water Resources Management, 34, 3689-3708. https://doi.org/10.1007/s11269-020-02644-y

Elkurdy, M., Binns, A. D., & Gharabaghi, B. (2020, December). Improved Streamflow Forecasting Using Variational Mode Decomposition and Extreme Gradient Boosting. In AGU Fall Meeting Abstracts (Vol. 2020, pp. H165-0003).

Bonakdari, H., Ebtehaj, I., Samui, P., & Gharabaghi, B. (2019). Lake water-level fluctuations forecasting using minimax probability machine regression, relevance vector machine, Gaussian process regression, and extreme learning machine. Water Resources Management, 33, 3965-3984. https://doi.org/10.1007/s11269-019-02346-0

Zaji, A. H., Bonakdari, H., & Gharabaghi, B. (2019). Developing an AI-based method for river discharge forecasting using satellite signals. Theoretical and Applied Climatology, 138, 347-362. https://doi.org/10.1007/s00704-019-02833-9

Zaji, A. H., Bonakdari, H., & Gharabaghi, B. (2019). Advancing Freshwater Lake Level Forecast Using King’s Castle Optimization with Training Sample Adaption and Adaptive Neuro-Fuzzy Inference System. Water Resources Management, 33(12), 4215-4230. https://doi.org/10.1007/s11269-019-02356-y

Ebtehaj, I., Bonakdari, H., & Gharabaghi, B. (2019). A reliable linear method for modeling lake level fluctuations. Journal of hydrology, 570, 236-250. https://doi.org/10.1016/j.jhydrol.2019.01.010

Zeynoddin, M., Bonakdari, H., Ebtehaj, I., Esmaeilbeiki, F., Gharabaghi, B., & Haghi, D. Z. (2019). A reliable linear stochastic daily soil temperature forecast model. Soil and Tillage Research, 189, 73-87. https://doi.org/10.1016/j.still.2018.12.023

Bonakdari, H., Moeeni, H., Ebtehaj, I., Zeynoddin, M., Mahoammadian, A., & Gharabaghi, B. (2019). New insights into soil temperature time series modeling: linear or nonlinear?. Theoretical and Applied Climatology, 135(3-4), 1157-1177. https://doi.org/10.1007/s00704-018-2436-2

Zeynoddin, M., Bonakdari, H., Azari, A., Ebtehaj, I., Gharabaghi, B., & Madavar, H. R. (2018). Novel hybrid linear stochastic with non-linear extreme learning machine methods for forecasting monthly rainfall a tropical climate. Journal of environmental management, 222, 190-206. https://doi.org/10.1016/j.jenvman.2018.05.072

Zaji, A. H., Bonakdari, H., & Gharabaghi, B. (2018). Reservoir water level forecasting using group method of data handling. Acta Geophysica, 66(4), 717-730. https://doi.org/10.1007/s11600-018-0168-4

Kozyn, A., Songin, K., Gharabaghi, B., & Lubitz, W. D. (2018). Predicting Archimedes Screw Generator Power Output Using Artificial Neural Networks. Journal of Hydraulic Engineering, 144(3), 05018002. https://doi.org/10.1061/(ASCE)HY.1943-7900.0001433

Coastal Engineering

Bonakdari, H., Ebtehaj, I., Azimi, A. H., Samui, P., Sattar, A. A., Jamali, A.,  & Gharabaghi, B. (2021). Pareto design of multiobjective evolutionary neuro-fuzzy system for predicting scour depth around bridge piers. In Water Engineering Modeling and Mathematic Tools (pp. 491-517). Elsevier. https://doi.org/10.1016/B978-0-12-820644-7.00012-8

Ahmadianfar, I., Jamei, M., Karbasi, M., Sharafati, A., & Gharabaghi, B. (2021). A novel boosting ensemble committee-based model for local scour depth around non-uniformly spaced pile groups. Engineering with Computers, 1-23. https://doi.org/10.1007/s00366-021-01370-2

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