Lujun Zhang

A field investigation on rill development and flow hydrodynamics under different upslope inflow and slope gradient conditions

Tiantian Yang, Pei Tian, Xinyi Xu, 2020, Hydrology Research.

A large-scale comparison of Artificial Intelligence and Data Mining (AI&DM) techniques in simulating reservoir releases over the Upper Colorado Region

Taereem Kim, Qidong Peng, Tiantian Yang, 2021 .

Improving Subseasonal-to-Seasonal Forecasts in Predicting the Occurrence of Extreme Precipitation Events Over the Contiguous U.S. Using Machine Learning Models

Q. Zhang, Chun-tian Cheng, Shang Gao, 2022, SSRN Electronic Journal.

Can artificial intelligence and data-driven machine learning models match or even replace process-driven hydrologic models for streamflow simulation?: A case study of four watersheds with different hydro-climatic regions across the CONUS

Yang Hong, Jonathan J. Gourley, Taereem Kim, 2021, Journal of Hydrology.

Investigation of hydrometeorological influences on reservoir releases using explainable machine learning methods

Siyan Liu, Dawei Lu, Lujun Zhang, 2023, Frontiers in Water.

Identifying Hydrometeorological Factors Influencing Reservoir Releases Using Machine Learning Methods

Siyan Liu, Dawei Lu, Lujun Zhang, 2022, 2022 IEEE International Conference on Data Mining Workshops (ICDMW).

Near real-time hurricane rainfall forecasting using convolutional neural network models with Integrated Multi-satellitE Retrievals for GPM (IMERG) product

Taereem Kim, Lujun Zhang, Tiantian Yang, 2022, Atmospheric Research.

Evaluation of Subseasonal-to-Seasonal (S2S) Precipitation Forecast from the North American Multi-Model Ensemble Phase II (NMME-2) over the contiguous U.S

Qian Zhu, Taereem Kim, Lujun Zhang, 2021, Journal of Hydrology.