Yanlai Zhou

Image of Yanlai Zhou
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Visiting address Sem Sælands vei 1 Geologibygningen 0371 OSLO
Postal address Postboks 1047 Blindern 0316 OSLO

Academic interests

  • Non-stationary flood frequency analysis
  • Hydrology forecasting by means of Artificial Intelligence (AI) including machine & deep learning techniques
  • Reservoir operation by means of evolutionary optimization algorithms
  • Synergistic optimization of Water-Food-Energy (WFE) Nexus

Citations: ResearchGateGoogle schoolar

Background

Employment history

11/2018-present: Post doc of hydrology, Dept of Geosciences, University of Oslo

01/2017-10/2018: Post doc of artificial intelligence, Dept of Bioenvironmental Systems Engineering, National Taiwan University

07/2014-12/2016: Engineer of water resources management, Chang-Jiang (Yangtze River) Water Resources Commission, China

Higher education

Ph.D 2011-2014: Wuhan University, Wuhan City, China. Specialty: Hydrology forecast and reservoir operation.

M.S. 2009-2011: Wuhan University, Wuhan City, China. Specialty: Optimization operation of cascade reservoirs.

B.S. 2005-2009: Changsha University of Science and technology, China. Specialty: Hydrology and water resources.

Honor

2016-: China National Engineer of Water Resources Project (Nos. 20160130099).

2015: The dissertation entitled “Joint Optimal Operation of Cascade Reservoirs” was appraised as Best Doctoral Dissertation in Hubei Province of China (ranked top 5%).

2015: Excellent staff in Chang-Jiang River Scientific Research Institute (CRSRI), rank top 5%.

2014: The project “the key technique of optimal control and operation of flood utilization for mega cascade reservoirs” was appraised as Second Prize of National Science and Technology Progress Award (ranked 14th in 15).

Editorial appointment

02/2018-present: The Editorial Board Member of Journal Hydrology.

Tags: Hydrology, Reservoir operation, Artificial intelligence

Publications

Ngongondo, C., Zhou, Y.L, Xu, C-Y. (2020). Multivariate framework for the assessment of key forcing to Lake Malawi levels variations in non-stationary frequency analysis. Environmental Monitoring and Assessment, 593. (IMPACT FACTOR=1.959)

Li, H., Gao, H., Zhou, Y.L, Xu, C-Y, Ortega M, R.Z., Sælthun, N.R. (2020). Usage of SIMWE model to model urban overland flood: a case study in Oslo. Hydrology Research, 2020, 143264. (IMPACT FACTOR=2.475)

Zhou, Y.L, Chang, F-J., Chang, L-C., Lee, W-L., Huang, A., Xu, C-Y., Guo, S. (2020). An advanced complementary scheme of floating photovoltaic and hydropower generation flourishing water-food-energy nexus synergies. Applied Energy, 115389. (IMPACT FACTOR=8.484, TOP)

Zhou, Y.L. (2020). Exploring multidecadal changes in climate and reservoir storage for assessing nonstationarity in flood peaks and risks worldwide by an integrated frequency analysis approach. Water Research, 185, 116265. (IMPACT FACTOR =9.130, TOP)

Zhou, Y.L. (2020). Real-time probabilistic forecasting of river water quality under data missing situation: deep learning plus post-processing techniques. Journal of Hydrology, 587, 23106. (IMPACT FACTOR=4.500, TOP)

Zhou, Y.L, Chang, F-J., Chen, H., Li, H. (2020). Exploring Copula-based Bayesian Model Averaging with multiple ANNs for PM2.5 ensemble forecasts. Journal of Cleaner Production, 263, 121528. (IMPACT FACTOR=7.246, TOP)

Zhou, Y.L, Guo, S., Xu, C-Y., Chang, F-J., Chen, H., Liu, P., Ming, B. (2020). Stimulate hydropower output of mega cascade reservoirs using an improved Kidney Algorithm. Journal of Cleaner Production, 244, 118613. (IMPACT FACTOR=7.246, TOP)

Zhou, Y.L, Chang, L-C., Chang, F-J. (2020). Explore a Multivariate Bayesian Uncertainty Processor Driven by Artificial Neural Networks for Probabilistic PM2.5 Forecasting. Science of the Total Environment, 2020, 711, 134792. (IMPACT FACTOR=6.551, TOP)

Zhou, Y.L, Guo, S., Xu, C-Y, Chang, F-J., Yin, J. (2020). Improving the Reliability of Probabilistic Multi-Step-Ahead Flood Forecasting by Fusing Unscented Kalman Filter with Recurrent Neural Network. Water, 12(2), 578. (IMPACT FACTOR=2.524)

Kao, I-F., Zhou, Y.L, Chang, L-C., Chang, F-J. (2020). Exploring a Long Short-Term Memory based Encoder-Decoder Framework for Multi-Step-Ahead Flood Forecasting. Journal of Hydrology, 124631. (IMPACT FACTOR=4.500, TOP)

He, S., Guo, S., Yang, G., Chen, K., Liu, D., Zhou, Y.L. (2020). Optimizing operation rules of cascade reservoirs for adapting climate change. Water Resources Management, 1-12. (IMPACT FACTOR=2.987)

Zhou, Y.L, Chang, L-C., Uen, T-S., Guo, S., Xu, C-Y., Chang, F-J. (2019). Prospect for small-hydropower installation settled upon optimal water allocation: An action to stimulate synergies of water-food-energy nexus. Applied Energy, 238, 668-682. (IMPACT FACTOR=8.484, TOP)

Zhou, Y.L, Chang, F-J., Chang, L-C., Kao, I-F., Wang, Y-S. (2019). Explore a deep learning multi-output neural network for regional multi-step-ahead air quality forecasts. Journal of Cleaner Production, 209, 134-145. (IMPACT FACTOR=7.246, TOP)

Zhou, Y.L, Chang, F-J., Chang, L-C., Kao, I-F., Wang, Y-S., Kang, C-C. (2019). Multi-output support vector machine for regional multi-step-ahead PM2.5 forecasting. Science of the Total Environment,  651, 230-240. (IMPACT FACTOR=6.551, TOP)

Zhou, Y.L, Guo, S., Chang, F-J,. (2019). Explore an evolutionary recurrent ANFIS for modelling multi-step-ahead flood forecasts. Journal of Hydrology, 570, 343-355. (IMPACT FACTOR=4.500, TOP)

Tsai, W-P., Cheng, C-L., Uen, T-S., Zhou, Y.L, Chang, F-J. (2019). Drought mitigation under urbanization through an intelligent water allocation system. Agricultural Water Management, 213, 87-96. (IMPACT FACTOR=4.021, TOP)

Zhou, Y.L, Guo, S., Chang, F. J., Xu, C-Y. (2018). Boosting hydropower output of mega cascade reservoirs using an evolutionary algorithm with successive approximation. Applied energy, 228, 1726-1739. (IF=7.90, Top)

Zhou, Y.L, Guo, S., Chang, F. J., Liu, P., Chen, A. B. (2018). Methodology that improves water utilization and hydropower generation without increasing flood risk in mega cascade reservoirs. Energy, 143, 785-796. (IF=4.97, Top)

Zhou, Y.L, Chang, F. J., Chang, L. C., Kao, I. F., Wang, Y. S. (2018). Explore a deep learning multi-output neural network for regional multi-step-ahead air quality forecasts. Journal of Cleaner Production, 209, 134-145. (IF=5.65)

Zhou, Y.L, Chang, F. J., Chang, L. C., Kao, I. F., Wang, Y. S., Kang, C. C. (2018). Multi-output support vector machine for regional multi-step-ahead PM2. 5 forecasting. Science of the Total Environment, 651, 230-240. (IF=4.61)

Zhou, Y.L., Guo, S., Hong, X., Chang, F. J. (2018). Systematic impact assessment on inter-basin water transfer projects of the Hanjiang River Basin in China. Journal of Hydrology, 553, 584-595. (IF=3.72, Top)

Zhou, Y.L., Guo, S., Xu, C. Y., Liu, P., Qin, H. (2015). Deriving joint optimal refill rules for cascade reservoirs with multi-objective evaluation. Journal of Hydrology, 524, 166-181. (IF=3.72, Top)

Zhou, Y.L, Guo, S., Xu, C. Y., Liu, D., Chen, L., Ye, Y. (2015). Integrated optimal allocation model for complex adaptive system of water resources management (I): Methodologies. Journal of Hydrology, 531, 964-976. (IF=3.72, Top)

Zhou, Y.L., Guo, S., Xu, C. Y., Liu, D., Chen, L., Wang, D. (2015). Integrated optimal allocation model for complex adaptive system of water resources management (II): Case study. Journal of Hydrology, 531, 977-991. (IF=3.72, Top)

Zhou, Y.L., Guo, S. Liu, P., Xu, C. (2014). Joint operation and dynamic control of flood limiting water levels for mixed cascade reservoir systems. Journal of hydrology, 519, 248-257. (IF=3.72, Top)

Zhou, Y.L., Guo, S. (2013). Incorporating ecological requirement into multipurpose reservoir operating rule curves for adaptation to climate change. Journal of hydrology, 498, 153-164. (IF=3.72, Top)

Book

Zhou, Y.L. (2016). Joint optimal operation of cascade reservoirs, Yangtze River Press.

Patent

Zhou, Y.L., Xu, J., Wang, B., Huo, J., Chen, G., Yang, C. (2018). Dynamic control for flood-limited water level of cascade reservoirs, 01/2016, China, Nos: 201610041886.3.

Zhou, Y.L., Guo, S., Chen, H., Liu, P., Wang, Y. (2015). Optimal operating curves of multi-objective reservoir operation for adaption to climate change, China, Nos: 201310025962.8.

Guo, S., Zhou, Y.L., Liu, P., Chen, H., Wang, Y. (2015). Real-time dynamic control of flood operating water level of cascade reservoirs, China, Nos: 201310022222.9.

  • Ngongondo, Cosmo; Zhou, Yanlai & Xu, Chong-Yu (2020). Multivariate framework for the assessment of key forcing to Lake Malawi levels variations in non-stationary frequency analysis. Environmental Monitoring & Assessment.  ISSN 0167-6369.  192(593) . doi: https://doi.org/10.1007/s10661-020-08519-4
  • Zhou, Yanlai; Guo, Shenglian; Xu, Chong-Yu; Chang, Fi‐John & Yin, Jiabo (2020). Improving the Reliability of Probabilistic Multi‐Step‐Ahead Flood Forecasting by Fusing Unscented Kalman Filter with Recurrent Neural Network. Water.  ISSN 2073-4441.  12(578) . doi: doi:10.3390/w12020578
  • Chen, Guiya; Zhao, Xiaofeng; Zhou, Yanlai; Guo, Shenglian; Xu, Chong-Yu & Chang, Fi-John (2019). Emergency Disposal Solution for Control of a Giant Landslide and Dammed Lake in Yangtze River, China. Water.  ISSN 2073-4441.  11(9) . doi: 10.3390/w11091939 Full text in Research Archive.
  • Gong, Yu; Liu, Pan; Cheng, Lei; Chen, Guiya; Zhou, Yanlai; Zhang, Xiaoqi & Xu, Weifeng (2019). Determining dynamic water level control boundaries for a multi‐reservoir system during flood seasons with considering channel storage. Journal of Flood Risk Management.  ISSN 1753-318X.  s 1- 17 . doi: 10.1111/jfr3.12586 Full text in Research Archive.
  • Zhou, Yanlai; Chang, Li-Chiu & Chang, Fi-John (2019). Explore a Multivariate Bayesian Uncertainty Processor driven by artificial neural networks for probabilistic PM2.5 forecasting. Science of the Total Environment.  ISSN 0048-9697.  711 . doi: 10.1016/j.scitotenv.2019.134792
  • Zhou, Yanlai; Chang, Li-Chiu; Uen, Tin-Shuan; Guo, Shenglian; Xu, Chong-Yu & Chang, Fi-John (2019). Prospect for small-hydropower installation settled upon optimal water allocation: An action to stimulate synergies of water-food-energy nexus. Applied Energy.  ISSN 0306-2619.  238, s 668- 682 . doi: 10.1016/j.apenergy.2019.01.069
  • Zhou, Yanlai; Guo, Shenglian & Chang, Fi-John (2019). Explore an evolutionary recurrent ANFIS for modelling multi-step-ahead flood forecasts. Journal of Hydrology.  ISSN 0022-1694.  570, s 343- 355 . doi: 10.1016/j.jhydrol.2018.12.040
  • Chen, Lu; Sun, Na; Zhou, Chao; Zhou, Jianzhong; Zhou, Yanlai; Zhang, Junhong & Zhou, Qing (2018). Flood Forecasting Based on an Improved Extreme Learning Machine Model Combined with the Backtracking Search Optimization Algorithm. Water.  ISSN 2073-4441.  10(10) . doi: 10.3390/w10101362 Full text in Research Archive.
Published Nov. 19, 2018 1:22 PM - Last modified Sep. 3, 2020 4:11 PM