Publications

Scientific Research Articles

1. Latif, S.D.; Ehteram, M.; Ahmed, A.N.; Ling, L.; Fai, C.M.; Afan, H.A.; Banadkooki, F.B.; El-Shafie, A. (2020). Pipeline Scour Rates Prediction-Based Model Utilizing a Multilayer Perceptron-Colliding Body Algorithm. Water. https://doi.org/10.3390/w12030902

2. Latif, S.D.; Lai, V.; Malek, M.A.; Abdullah, S.; Ahmed, A.N. (2020). Time-Series Prediction of Sea Level Change in the East Coast of Peninsular Malaysia from the Supervised Learning Approach. International Journal of Design & Nature and Ecodynamics. https://doi.org/10.18290/ijdne.150314

3. Latif, S.D.; Ehteram, M.; Ahmed, A.N.; Huang, Y.F.; Alizamir, M.; Kisi, O.; Mert, C.; El-Shafie, A. (2020). Design of a hybrid ANN multi-objective whale algorithm for suspended sediment load prediction. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-020-10421-y

4. Latif, S.D.; Ehteram, M.; Yenn, F.; Najah, A.; Feng, Y.; Abozweita, O.; Al-ansari, N.; El-shafie, A. (2020). Performance improvement for infiltration rate prediction using hybridized Adaptive Neuro-Fuzzy Inferences System (ANFIS) with optimization algorithms. Ain Shams Engineering Journal. https://doi.org/10.1016/j.asej.2020.08.019

5. Latif, S.D.; Najah Ahmed, A.; Sherif, M.; Sefelnasr, A.; El-shafie. (2020). A. Reservoir water balance simulation model utilizing machine learning algorithm. Alexandria Engineering Journal. https://doi.org/10.1016/j.aej.2020.10.057

6. Latif, S.D.; Usman, F.; Pirot, B.M. (2020). Implementation of Value Engineering in Optimizing Project Cost for Sustainable Energy Infrastructure Asset Development. International Journal of Sustainable Development and Planning. https://doi.org/10.18280/ijsdp.150709

7. Latif, S.D.; Azmi, M.S.B.N.; Ahmed, A.N.; Fai, C.M.; El-shafie, A. (2020). Application of Artificial Neural Network for Forecasting Nitrate Concentration as a Water Quality Parameter: A Case Study of Feitsui Reservoir, Taiwan. International Journal of Design & Nature and Ecodynamics. https://doi.org/10.18280/ijdne.150505

8. Latif, S.D.; Jumin, E.; Basaruddin, F.B.; Yusoff, Y.B.; Ahmed, A.N. (2021). Solar Radiation Prediction Using Boosted Decision Tree Regression Model: A Case Study in Malaysia. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-021-12435-6

9. Latif, S.D.; Najah, A.; Teo, F.Y; Chow, M.F.; Huang, Y.F.; Abdullah, S.; Ismail, M.; El-Shafie, A. (2021). Surface water quality status and prediction during movement control operation order under COVID-19 pandemic: Case studies in Malaysia. International Journal of Environmental Science and Technology.  https://doi.org/10.1007/s13762-021-03139-y

10. Latif, S.D. (2021). Concrete compressive strength prediction modeling utilizing deep learning long short-term memory algorithm for a sustainable environment. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-021-12877-y

11. Latif, S.D.; Marhain, S. Hossain, S. Najah, A.A.; Sherif, M.; Sefelnasr, A.; El-Shafie. (2021). Optimizing the Operation Release Policy Using Charged System Search Algorithm: A Case Study of Klang Gates Dam, Malaysia. Sustainability. https://doi.org/10.3390/su13115900

12. Latif, S.D.; Ahmed, A.N.; Sathiamurthy, E.; Huang, Y.F.; El-Shafie, A. (2021). Evaluation of deep learning algorithm for inflow forecasting: a case study of Durian Tunggal Reservoir, Peninsular Malaysia. Natural Hazards. https://doi.org/10.1007/s11069-021-04839-x

13. Latif, S.D.; Ahmed, A.N. (2021). Application of Deep Learning Method for Daily Streamflow Time-Series Prediction: A Case Study of the Kowmung River at Cedar Ford, Australia. International Journal of Sustainable Development and Planning. https://doi.org/10.18280/ijsdp.160310

14. Latif, S.D.; Parsaie, A.; Haghiabi, A.H.; Tripathi, R.P. (2021). Predictive modelling of piezometric head and seepage discharge in earth dam using soft computational models. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-021-15029-4

15. Sarmad Dashti Latif. (2021). Developing a boosted decision tree regression prediction model as a sustainable tool for compressive strength of environmentally friendly concrete. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-021-15662-z

16. Latif, S.D.; Birima, A.H.; Ahmed. A.N.; Hatem, D.H.; Al-Ansari, N.; Fai, C.M.; El-Shafie, A. (2021). Development of prediction model for phosphate in reservoir water system based machine learning algorithms. Ain Shams Engineering Journal. https://doi.org/10.1016/j.asej.2021.06.009

17. Latif, S.D.; Bazrafshan, O.; Ehteram, M.; Huang, Y.F.; Teo, F.Y.; Ahmed, A.N.; El-Shafie, A. (2022). Predicting crop yields using a new robust Bayesian averaging model based on multiple hybrid ANFIS and MLP models. Ain Shams Engineering Journal. https://doi.org/10.1016/j.asej.2022.101724

18. Ehteram, M.; Ahmed, A. N.; Fai, C. M.; Latif, S.D.; Chau, K. W.; Kai Lun. (2022). Optimal operation of hydropower reservoirs under climate change. Environment, Development and Sustainability. https://doi.org/10.1007/s10668-022-02497-y

19. Sami, B. F. Z.; Latif, S. D.; Ahmed, A.N.; Chow, M. F.; Murti, M. A.; Suhendi, A.; Sami, B. H. Z.; Wong, J. K.; Birima, A. H.; El-Shafie, A. (2022). Machine learning algorithm as a sustainable tool for dissolved oxygen prediction: a case study of Feitsui Reservoir, Taiwan. Scientific Reports (nature). https://doi.org/10.1038/s41598-022-06969-z

20. Tofiq, Y. M.; Latif, S. D.: Ahmed, A. N.; Kumar, P.; El-Shafie, A. (2022). Optimized Model Inputs Selections for Enhancing River Streamflow Forecasting Accuracy Using Different Artificial Intelligence Techniques. Water Resources Management. https://doi.org/10.1007/s11269-022-03339-2

21. Hama, A. R.; Ghafour, Z.; Al Suhili, R.; Latif, S. D. (2022). Optimization model for cost estimation of decentralized wastewater treatment units. Ain Shams Engineering Journal. https://doi.org/10.1016/j.asej.2022.101751

22. Khomri, Z.; Chabaca, M. N.; Boudibi, S.; Latif, S. D. (2022). Assessment of groundwater vulnerability using remote sensing, susceptibility index, and WetSpass model in an arid region (Biskra, SE Algeria). Environmental Monitoring and Assessment. https://doi.org/10.1007/s10661-022-10189-3

23. Nou, M. R. G.; Foroudi, A.; Latif, S. D.; Parsaie, A. (2022). Prognostication of scour around twin and three piers using efficient outlier robust extreme learning machine. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-022-20681-5

24. Latif, S. D.; Chong KL; Ahmed. A. N.; Huang, Y. F.; Sherif, M.; El-Shafie, A. (2023). Sediment load prediction in Johor river: deep learning versus machine learning models. Applied Water Science. https://doi.org/10.1007/s13201-023-01874-w

25. Latif. S. D.; Ahmed, A. N. (2023). A review of deep learning and machine learning techniques for hydrological inflow forecasting. Environment, Development and Sustainability. https://doi.org/10.1007/s10668-023-03131-1

26. Latif. S. D.; Ahmed, A. N. (2023). Streamflow Prediction Utilizing Deep Learning and Machine Learning Algorithms for Sustainable Water Supply Management. Water Resources Management. https://doi.org/10.1007/s11269-023-03499-9

27. I Mehdaoui; S Boudibi; SD Latif, B Sakaa; H Chaffai; A Hani. (2023). Prediction of nitrate concentrations using multiple linear regression and radial basis function neural network in the Cheliff River basin, Algeria. Journal of Applied Water Engineering and Research. https://doi.org/10.1080/23249676.2023.2207838

28. A Gharehbaghi; R Ghasemlounia; SD Latif; AH Haghiabi; A Parsaie. (2023). Application of data-driven models to predict the dimensions of flow separation zone. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-023-27024-y

29. Latif. S. D. (2023). Evaluating deep learning and machine learning algorithms for forecasting daily pan evaporation during COVID-19 pandemic. Environment, Development and Sustainability. https://doi.org/10.1007/s10668-023-03469-6

30. Latif et al. (2023). Prediction of atmospheric carbon monoxide concentration utilizing different machine learning algorithms: A case study in Kuala Lumpur, Malaysia. Environmental Technology & Innovation. https://doi.org/10.1016/j.eti.2023.103387

31. Latif et al. (2023). Assessing rainfall prediction models: Exploring the advantages of machine learning and remote sensing approaches. Alexandria Engineering Journal. https://doi.org/10.1016/j.aej.2023.09.060

32. Latif et al. (2023). Evaluating different machine learning models for predicting municipal solid waste generation: a case study of Malaysia. Environment, Development and Sustainability. https://doi.org/10.1007/s10668-023-03882-x

33. Sarmad Dashti Latif & Ali Najah Ahmed (2023). Ensuring a generalizable machine learning model for forecasting reservoir inflow in Kurdistan region of Iraq and Australia. Environment, Development and Sustainability. https://doi.org/10.1007/s10668-023-03885-8 

34. Almubaidin, M.A.A., Latif, S.D., Balan, K., Ahmed, A.N., El-Shafie, A (2023). Enhancing sediment transport predictions through machine learning-based multi-scenario regression models. Results in Engineering. https://doi.org/10.1016/j.rineng.2023.101585 

35. Dahmani, S., Latif, S.D. Streamflow Data Infilling Using Machine Learning Techniques with Gamma Test. Water Resources Management (2023). https://doi.org/10.1007/s11269-023-03694-8

36. Latif et al., (2024). Ozone concentration forecasting utilizing leveraging of regression machine learnings: A case study at Klang Valley, Malaysia. Results in Engineering (2024). https://doi.org/10.1016/j.rineng.2024.101872 

37. Jamshidzadeh, Z., Latif, S.D., Ehteram, M. et al. An advanced hybrid deep learning model for predicting total dissolved solids and electrical conductivity (EC) in coastal aquifers. Environmental Sciences Europe 36, 20 (2024). https://doi.org/10.1186/s12302-024-00850-8 

38. Osman, A.I.A., Latif, S.D., Boo, K.B.W., Ahmed, A.N., Huang, Y.F., El-Shafie, A. Advanced machine learning algorithm to predict the implication of climate change on groundwater level for protecting aquifer from depletion.  Groundwater for Sustainable Development (2024). https://doi.org/10.1016/j.gsd.2024.101152 

39. Almubaidin, M.A.,Ismail, N.S., Latif, S.D. et al. (2024). Machine learning predictions for carbon monoxide levels in urban environments. Results in Engineering. https://doi.org/10.1016/j.rineng.2024.102114 

40. Sapitang, M., Dullah, H., Latif, S.D et al. (2024). Application of integrated artificial intelligence geographical information system in managing water resources: A review. Remote Sensing Applications: Society and Environment. https://doi.org/10.1016/j.rsase.2024.101236 

41. Latif, et al., (2024). Developing an innovative machine learning model for rainfall prediction in a semi-arid region. Journal of Hydroinformatics. https://doi.org/10.2166/hydro.2024.014

42. Miran Hikmat Mohammed & Sarmad Dashti Latif. Forecasting daily rainfall in a humid subtropical area: an innovative machine learning approach. Journal of Hydroinformatics. https://doi.org/10.2166/hydro.2024.016 

43. Latif, et al., (2024). Improving sea level prediction in coastal areas using machine learning techniques. Ain Shams Engineering Journal. https://doi.org/10.1016/j.asej.2024.102916 

44. Hamid Abdolabadi & Sarmad Dashti Latif. Trophic Predictability Analysis: Employing Constancy and Contingency – a Case Study of Ilam Reservoir. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2024.143325 

45. Arsalan Ahmed Othman, Salahalddin S Ali, Sarmad Dashti Latif et al., (2024). Satellite-Derived Shallow Water Depths Estimation Using Remote Sensing and Artificial Intelligence Models, A Case Study: Darbandikhan Lake Upper, Kurdistan Region, Iraq. Remote Sensing Applications: Society and Environment. https://doi.org/10.1016/j.rsase.2024.101432 

46. Hashim, N.S.B., Malek, M.B.A., Latif, S.D. et al., (2025). Water Footprint Assessment to Map and Quantify Water Consumption and Water Pollution Incurred: A Case Study of Malaysia. Water, Air, & Soil Pollution 236, 156. https://doi.org/10.1007/s11270-025-07786-6 

47. Irwan, D., Ibrahim, SL.L, Latif, S.D., et al., (2025). River water quality monitoring using machine learning with multiple possible in-situ scenarios. Environmental and Sustainability Indicators, Volume 26, ISSN 2665-9727, https://doi.org/10.1016/j.indic.2025.100620 

48. Latif, S.D., Hui, L.E., Ahmed, A.N. et al., (2025). Forecasting solar power generation as a renewable energy utilizing various machine learning models. Theoretical and Applied Climatology 156, 369. https://doi.org/10.1007/s00704-025-05596-8 

49. Latif, S. D., Ahmed, A. N., & Elshafie, A. (2025, July 9). Editorial: Ensuring water security for sustainable development. AQUA - Water Infrastructure, Ecosystems and Society. https://doi.org/10.2166/aqua.2025.042 

50. Latif, S. D. (2025). Protect Iraq’s Mesopotamian Marshes. Science, 390(6773), 581. https://doi.org/10.1126/science.aeb1912 

51. Latif, S.D., Anson, W., Ahmed, A.N. et al. Novel advances in real-time pluvial flash flood forecasting under climate change through combination of various machine learning models. Theor Appl Climatol 157, 104 (2026). https://doi.org/10.1007/s00704-026-06037-w 

52. Latif, S. D. 2026. “ Bridging Technology and Diplomacy: The Role of AI in Managing Water Scarcity in the Mesopotamian Region.” World Water Policy 12, no. 1: e70065. https://doi.org/10.1002/wwp2.70065 

Conference Paper

1. Abdoulhdi A. Borhana; Mustaffa Kamal D. D.; Sarmad Dashti Latif; Yasir Hassan Ali; Ali Najah Ahmed Almahfoodh; Ahmed El-Shafie (2020). Fault Detection of Bearing using Support Vector Machine-SVM. IEEE. https://doi.org/10.1109/ICIMU49871.2020.9243507

Scientific Book

1. Sarmad Dashti Latif; Ali Najah Ahmed; Ahmed El-Shafie (2021). Research Series in Civil Engineering: Soft Computing Applications in Hydro-Environment. UNITEN PRESS, Universiti Tenaga Nasional (UNITEN), Malaysia. http://dspace.uniten.edu.my/jspui/handle/123456789/18733

2. Sarmad Latif (2023). Implementation of Deep Learning Technique for Streamflow Prediction: Case Studies of Dokan Dam, Kurdistan Region of Iraq and Warragamba Dam, Sydney, Australia. LAMBERT Academic Publishing, Germany. https://www.morebooks.shop/shop-ui/shop/product/9786206844822 

Policy Report

1. Latif, S., Hamamin, D. F., & Ali, S. S. (2025). Addressing water shortages in Sulaimani: Policy approaches and recommendations. Vision Foundation for Strategic Studies. https://visionfoundationiq.org/pdf-detail?id=1002 

2. Enabling Peace in Iraq Center (EPIC). (2025). Making Every Drop Count: Water Security in Iraq (featuring an interview with Sarmad Latif). Retrieved from https://enablingpeace.org/wp-content/uploads/2025/10/Making-Every-Drop-Count_EPIC.pdf