Photo of Chaopeng Shen

Chaopeng Shen

Associate Professor


  • Civil and Environmental Engineering

231C Sackett Building


Personal or Departmental Website

Research Areas:

Water Resources Engineering

Interest Areas:

Large-scale computational hydrology, hydrologic big data and machine learning, water-ecosystem interactions, floodplain and riparian systems




  • BS, Environmental Engineering, Sichuan University, 2003
  • Ph D, Environmental Engineering, Michigan State University, 2009


Journal Articles

  • Yongen Lin, Dagang Wang, Jinxin Zhu, Wei Sun, Chaopeng Shen and Wei Shangguan, 2024, "Development of objective function-based ensemble model for streamflow forecasts", Journal of Hydrology, 632
  • Tadd Bindas, Wen-Ping Tsai, Jiangtao Liu, Farshid Rahmani, Dapeng Feng, Yuchen Bian, Kathryn Lawson and Chaopeng Shen, 2024, "Improving large-basin river routing using a differentiable Muskingum-Cunge model and physics-informed machine learning", Water Resources Research, 60, (1)
  • Yalan Song, Wen-Ping Tsai, Jonah Gluck, Alan Rhoades, Colin Zarzyckie, Rachel McCrary, Kathryn Lawson and Chaopeng Shen, 2024, "LSTM-based data integration to dramatically improve one-month-ahead snow water equivalent forecast and diagnose error sources", Journal of Hydrometeorology, 25, (1), pp. 223-237
  • Farshid Rahmani, Alison Appling, Dapeng Feng, Kathryn Lawson and Chaopeng Shen, 2023, "Identifying structural priors in a hybrid differentiable model for stream water temperature modeling.", Water Resources Research, 59, (12)
  • Dapeng Feng, Hylke Beck, Kathryn Lawson and Chaopeng Shen, 2023, "The suitability of differentiable, learnable hydrologic models for ungauged regions and climate change impact assessment", Hydrology and Earth System Sciences, 27, (12), pp. 2357-2373
  • Yingying Yao, Yufeng Zhao, Xin Li, Dapeng Feng, Chaopeng Shen, Chuankun Liu, Xingxing Kuang and Chunmiao Zhang, 2023, "Can Transfer Learning Improve Hydrological Predictions in the Alpine Regions?", Journal of Hydrology, 625
  • Yegane Khoshkalam, Alain N. Rousseau, Farshid Rahmani, Chaopeng Shen and Kian Abbasnezhadi, 2023, "Applying Transfer Learning Techniques to Enhance the Accuracy of Streamflow Prediction Produced by Long Short-term Memory Networks with Data Integration", Journal of Hydrology, 622
  • Chaopeng Shen, Alison Appling, Pierre Gentine, Toshiyuki Bandai, Hoshin Gupta, Alexandre Tartakovsky, Marco Baity-Jesi, Fabrizio Fenicia, Daniel Kifer, Li Li , Xiaofeng Liu, Wei Ren, Yi Zheng, Ciaran Harman, Martyn Clark, Matthew Farthing, Dapeng Feng, Praveen Kumar, Doaa Aboelyazeed, Farshid Rahmani, Hylke Beck, Tadd Bindas, Dipankar Dwivedi, Kuai Fang, Marvin Höge, Chris Rackauckas, Tirthankar Roy, Chonggang Xu and Kathryn Lawson, 2023, "Differentiable modeling to unify machine learning and physical models and advance Geosciences", Nature Reviews Earth and Environment, 4, (8), pp. 552-567
  • Jiangtao Liu, David Hughes, Farshid Rahmani, Kathryn Lawson and Chaopeng Shen, 2023, "Evaluating a global soil moisture dataset from a multitask model (GSM3 v1.0) for current and emerging threats to crops", Geoscientific Model Development Discussions
  • Doaa Aboelyazeed, Chonggang Xu, Forrest M. Hoffman, Alex Jones, Chris Rackauckas, Kathryn Lawson and Chaopeng Shen, 2023, "A differentiable ecosystem modeling framework for large-scale inverse problems: demonstration with photosynthesis simulations", Biogeosciences Discussions
  • Gourab Saha, Farshid Rahmani, Cibin Raj, Chaopeng Shen and Li Li, 2023, "A deep learning-based novel approach to generate continuous daily stream nitrate concentration for nitrate data-sparse watersheds", Science of the Total Environment
  • Louise Slater, Louise Arnal, Marie-Amélie Boucher, Annie Y.-Y. Chang, Simon Moulds, Conor Murphy, Grey Nearing, Guy Shalev, Chaopeng Shen, Linda Speight, Gabriele Villarini, Robert L. Wilby, Andrew Wood and Massimiliano Zappa, 2023, "Hybrid forecasting: blending climate predictions with AI models", Hydrology and Earth System Sciences, 27, (9), pp. 1865-1889
  • Michael Palese, Te Pei, Allan Zarembski, Tong Qiu, Chaopeng Shen and Joseph Palese, 2023, "Hazard assessment framework for statistical analysis of cut slopes using track inspection videos and geospatial information", Georisk
  • Te Pei, Tong Qiu and Chaopeng Shen, 2023, "Applying Physics-Guided Machine Learning to Slope Stability Prediction", Journal of Geotechnical and Geoenvironmental Engineering, 149, (10)
  • Nikunj Mangukiya, Ashutosh Sharma and Chaopeng Shen, 2023, "How to enhance hydrological predictions in hydrologically distinct watersheds of the Indian subcontinent?", Journal of Hydrology, 37, (7)
  • Wei Zhi, Wenyu Ouyang, Chaopeng Shen and Li Li, 2023, "Temperature as the predominant driver of dissolved oxygen in US rivers", Nature Water, 1, (3), pp. 249-260
  • Yalan Song, Chaopeng Shen and Xiaofeng Liu, 2023, "A Surrogate Model for Shallow Water Equations Solvers with Deep Learning", Journal of Hydraulic Engineering, 149, (11), pp. 04023045
  • Jiangtao Liu, Farshid Rahmani, Kathryn Lawson and Chaopeng Shen, 2022, "A multiscale deep learning model for soil moisture integrating satellite and in-situ data", Geophysical Research Letters, 49, (7)
  • Dapeng Feng, Jiangtao Liu, Kathryn Lawson and Chaopeng Shen, 2022, "Differentiable, learnable, regionalized process-based models with physical outputs can approach state-of-the-art hydrologic prediction accuracy", Water Resources Research
  • Olukunle Oladipo, Deborah Sunter, Mila Sherman, Sanhita Sengupta, Kathryn Lawson and Chaopeng Shen, 2022, "A robust statistical analysis of the role of hydropower on the system electricity price and price volatility", Environmental Research Communications
  • Savinay Nagendra, Daniel Kifer, Benjamin Mirus, Te Pei, Kathryn Lawson, Srikanth Banagere Manjunatha, Weixin Li, Hien Nguyen, Tong Qiu, Sarah Tran and Chaopeng Shen, 2022, "Constructing a large-scale landslide database across heterogeneous environments using learning without forgetting", IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15
  • Binxiao Li, Qiuhong Tang, Gang Zhao, Liang Gao and Chaopeng Shen, 2022, "Physics-guided long short-term memory network for streamflow and flood simulations in the Lancang-Mekong River Basin", Water
  • Kayalvizhi Sadayappan, Devon Kerins, Chaopeng Shen and Li Li, 2022, "Riverine nitrate concentrations predominantly driven by human, climate, and soil property in the Contiguous United States", Water Research
  • X Chen, Sheng Wang, Hongkai Gao, Jiaxu Huang, Chaopeng Shen, Qingli Li, Honggang Qi, Laiwen Zheng and Min Liu, 2022, "Comparison of deep learning models and a typical process-based model in glacio-hydrology simulation", Journal of Hydrology
  • Farshid Rahmani, Chaopeng Shen, Samantha Oliver, Kathryn Lawson and Alison Appling, 2021, "Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins", Hydrological Processes, 35, (11)
  • Wen-Ping Tsai, Ming Pan, Kathryn Lawson, Jiangtao Liu, Dapeng Feng and Chaopeng Shen, 2021, "From calibration to parameter learning: Harnessing the scaling effects of big data in geoscientific modeling", Nature Communications, 12, (5988)
  • Kang Xie, Pan Liu , Jianyun Zhang, Dongyang Han, Guoqing Wang and Chaopeng Shen, 2021, "Physics-guided deep learning for rainfall-runoff modeling by considering extreme events and monotonic relationships", Journal of Hydrology, 603, (C)
  • Wenyu Ouyang, Kathryn Lawson, Dapeng Feng, Lei Ye, Chi Zhang and Chaopeng Shen, 2021, "Continental-scale streamflow modeling of basins with reservoirs: Towards a coherent deep-learning-based strategy", Journal of Hydrology, 599, pp. 126455
  • Dapeng Feng, Kathryn Lawson and Chaopeng Shen, 2021, "Mitigating Prediction Error of Deep Learning Streamflow Models in Large Data-Sparse Regions With Ensemble Modeling and Soft Data", Geophysical Research Letters, 48, (14)
  • Judy P Che-Castaldo, Cousin, R\'emi, Stefani Daryanto, Grace Deng, Mei-Ling E Feng, Rajesh K Gupta, Dezhi Hong, Ryan M McGranaghan, Olukunle O Owolabi, Tianyi Qu, Wei Ren, Toryn Schafer, Ashutosh Sharma, Chaopeng Shen, Mila Getmansky Sherman, Deborah A. Sunter, Lan Wang and David S. Matteson, 2021, "Critical Risk Indicators (CRIs) for the electric power grid: A survey and discussion of interconnected effects", Environment Systems and Decisions, 41
  • Kuai Fang, Daniel Kifer, Kathryn Lawson, Dapeng Feng and Chaopeng Shen, 2021, "The data synergy effects of time-series deep learning models in hydrology", Water Resources Research
  • Kai Ma, Dapeng Feng, Kathryn Lawson, Wen-Ping Tsai, Chuan Liang, Xiaorong Huang, Ashutosh Sharma and Chaopeng Shen, 2021, "Transferring hydrologic data across continents--leveraging US data to improve hydrologic prediction in other countries", Water Resources Research
  • Chaopeng Shen, Xingyuan Chen and Eric Laloy, 2021, "Editorial: Broadening the Use of Machine Learning in Hydrology", Frontiers in Water, 3, pp. 38
  • Farshid Rahmani, Kathryn Lawson, Wenyu Ouyang, Alison Appling, Samantha Oliver and Chaopeng Shen, 2021, "Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data", Environmental Research Letters, 16, (2), pp. 024025
  • Wei Zhi, Dapeng Feng, Wen-Ping Tsai, Gary Sterle, Adrian Harpold, Chaopeng Shen and Li Li, 2021, "From Hydrometeorology to River Water Quality: Can a Deep Learning Model Predict Dissolved Oxygen at the Continental Scale?", Environmental Science & Technology, 55, (4), pp. 2357--2368
  • Fuxin Zhu, Xin Li, Jun Qin, Kun Yang, Lan Cuo, Wenjun Tang and Chaopeng Shen, 2021, "Integration of Multisource Data to Estimate Downward Longwave Radiation Based on Deep Neural Networks", IEEE Transactions on Geoscience and Remote Sensing, 60, pp. 1-15
  • Wen-Ping Tsai, Kuai Fang, Xinye Ji, Kathryn Lawson and Chaopeng Shen, 2020, "Revealing causal controls of storage-streamflow relationships with a data-centric Bayesian framework combining machine learning and process-based modeling", Frontiers in Water, 2, pp. 40
  • Kuai Fang and Chaopeng Shen, 2020, "Near-real-time forecast of satellite-based soil moisture using long short-term memory with an adaptive data integration kernel", Journal of Hydrometeorology, (2020)
  • Dapeng Feng, Kuai Fang and Chaopeng Shen, 2020, "Enhancing streamflow forecast and extracting insights using long-short term memory networks with data integration at continental scales", Water Resources Research, 56, (9), pp. e2019WR026793
  • Kuai Fang, Daniel Kifer, Kathryn Lawson and Chaopeng Shen, 2020, "Evaluating the Potential and Challenges of an Uncertainty Quantification Method for Long Short-Term Memory Models for Soil Moisture Predictions", Water Resources Research, 56, (12), pp. e2020WR028095
  • Kuai Fang, Xinye Ji, Chaopeng Shen, Noel Ludwig, Peter Godfrey, Tasnuva Mahjabin and Christine Doughty, 2019, "Combining a land surface model with groundwater model calibration to assess the impacts of groundwater pumping in a mountainous desert basin", Advances in Water Resources, 130, pp. 12-28
  • Nuan Sun, Kuai Fang and Chaopeng Shen, 2019, "Toward a Priori Evaluation of Relative Worth of Head and Conductivity Data as Functions of Data Densities in Inverse Groundwater Modeling", Water, 11, (6), pp. 1202
  • Xinye Ji, John M Melack, Lance Lesack, Shilong Wang, William J Riley and Chaopeng Shen, 2019, "Seasonal patterns and controls of hydrological fluxes in an Amazon floodplain lake with a surface-subsurface processes model", Water Resources Research
  • Ying Fan, Martyn Clark, David Lawrence, Sean Swenson, Lawrence E Band, Susan Brantley, Paul Brooks, William Dietrich, Alejandro Flores, Gordon Grant, James Kirchner, Scott Mackay, Jeffrey McDonnell, Paul Milly, Pamela Sullivan, Christina Tague, Hoori Ajami, Nathaniel Chaney, Andreas Hartmann, Pieter Hazenberg, James McNamara, Jon Pelletier, Justin Perket, Elham Rouholahnejad, Thorsten Wagener, Xubin Zeng, Edward R. Beighley, Jonathan Buzan, Maoyi Huang, Ben Livneh, Binayak Mohanty, Bart Nijssen, Mohammad Safeeq, Chaopeng Shen, Willem van Verseveld, John Volk and Dai Yamazaki, 2019, "Hillslope Hydrology in Global Change Research and Earth System Modeling", Water Resources Research
  • Chaopeng Shen, Eric Laloy, Amin Elshorbagy, Adrian Albert, Jerad Bales, Fi-John Chang, Sangram Ganguly, Kuo-lin Hsu, Daniel Kifer, Zheng Fang, Kuai Fang, Dongfeng Li, Xiaodong Li and Wen-Ping Tsai, 2018, "HESS Opinions: Incubating deep-learning-powered hydrologic science advances as a community", Hydrology and Earth System Sciences
  • Kuai Fang, Ming Pan and Chaopeng Shen, 2018, "The value of SMAP for long-term soil moisture estimation with the help of deep learning", Transactions on Geoscience and Remote Sensing
  • Chaopeng Shen, 2018, "A trans-disciplinary review of deep learning research and its relevance for water resources scientists", Water Resources Research
  • Shih-Yu Wang, Robert Gilles, Oi-Yu Chung and Chaopeng Shen, 2018, "Cross-basin decadal climate regime connecting the Colorado River and the Great Salt Lake", Journal of Hydrometeorology, 19, (4), pp. 659-665
  • Chaopeng Shen, 2018, "Deep learning: A next-generation big-data approach for hydrology", Eos
  • XY Ji and Chaopeng Shen, 2018, "The introspective may achieve more: Enhancing existing Geoscientific models with native-language emulated structural reflection", Computers and Geosciences, 110, (1), pp. 32-40
  • Jie Niu, Chaopeng Shen, Jeffery Chambers, John M Melack and William J Riley, 2017, "Interannual Variation in Hydrologic Budgets in an Amazonian Watershed with a Coupled Subsurface - Land Surface Process Model", Journal of Hydrometerology, 18, (9), pp. 2597-2617
  • Kuai Fang and Chaopeng Shen, 2017, "Full-flow-regime storage-streamflow correlation patterns provide insights into hydrologic functioning over the continental US", Water Resources Research, 53, (9), pp. 8064-8083
  • Xiaofeng Liu, Yunxiang Chen and Chaopeng Shen, 2016, "Coupled Two-dimensional Surface Flow and Three-dimensional Sub-surface Flow Modeling for the Drainage of Permeable Road Pavement", Journal of Hydrologic Engineering, 04016051, pp. 1-13
  • Kuai Fang, Chaopeng Shen, Joshua B Fisher and Jie Niu, 2016, "Improving estimates of long-term water partitioning using hydrologic signatures from GRACE", Water Resources Research, 52, (7), pp. 5537–5554
  • Chaopeng Shen, Shilong Wang and Xiaofeng Liu, 2016, "Geomorphological significance of at-many-stations hydraulic geometry", Geophysical Research Letters, 43, (8), pp. 3762–3770
  • Simone Fatichi, Enrique Vivoni, Fred Ogden, Valeriy Ivanov, Benjamin Mirus, David Gochis, Charles Downer, Matteo Camporese, Jason Davison, Brian Ebel, Norm Jones, Jongho Kim, Giuseppe Mascaro, Richard Niswonger, Pedro Restrepo, Riccardo Rigon, Chaopeng Shen, Mauro Sulis and David Tarboton, 2016, "An overview of challenges, current applications and future trends of distributed process-based models in hydrology", Journal of Hydrology, 537, pp. 45–60
  • Chaopeng Shen, W J Riley, Kurt M Smithgall, John M Melack and Kuai Fang, 2016, "The fan of influence of streams and channel feedbacks to simulated land surface water and carbon dynamics", Water Resources Research, 52, (2), pp. 880–902
  • George SH Pau, Chaopeng Shen, W J Riley and Yaning Liu, 2016, "Accurate and efficient prediction of fine-resolution hydrologic and carbon dynamics from coarse-resolution models", Water Resources Research, 52, (2), pp. 22
  • XY Ji, Chaopeng Shen and W J Riley, 2015, "Temporal evolution of soil moisture statistical fractal and controls by soil texture and regional groundwater flow", Advances in Water Resources, 86, (A), pp. 15
  • Martyn P Clark, Ying Fan, David M Lawrence, Jennifer C Adam, Diogo Bolster, David J Gochis, Richard P Hooper, Mukesh Kumar, L. Ruby Leung, D. Scott Mackay, Reed M Maxwell, Chaopeng Shen, Sean C Swenson and Xubin Zeng, 2015, "Improving the representation of hydrologic processes in Earth System Models", Water Resources Research, 51, (8), pp. 5929–5956
  • D Trebotich, M Adams, S Molins, C I Steefel and Chaopeng Shen, 2014, "High resolution simulation of pore scale reactive transport processes associated with carbon sequestration", Computing in Science and Engineering, 16, (6), pp. 22 - 31
  • S Molins, D Trebotich, J B Ajo-Franklin, T J Ligocki, Chaopeng Shen and C I Steefel, 2014, "Pore-scale controls on Calcite dissolution rates from flow-through laboratory and numerical experiments", Environmental Science & Technology, 48, (13), pp. 7453–7460
  • Chaopeng Shen, J Niu and K Fang, 2014, "Quantifying the effects of data integration algorithms on the outcomes of a subsurface–land surface processes model", Environmental Modelling & Software, 59, pp. 7359–7377
  • R M Maxwell, M Putti, S B Meyerhoff, J Delfs, I Ferguson, V Ivanov, J Kim, O Kolditz, S Kollet, M Kumar, S Lopez, J Niu, C Paniconi, M S Phanikumar, Chaopeng Shen, E Sudicky and M Sulis, 2014, "Surface-subsurface model inter-comparison: A first set of benchmark results to diagnose integrated hydrology and feedbacks", Water Resources Research, 50, (2), pp. 1531–1549
  • W J Riley and Chaopeng Shen, 2014, "Characterizing coarse-resolution watershed soil moisture heterogeneity using fine-scale simulations", Hydrology and Earth System Sciences, 18, (7), pp. 2463-2483
  • J. Niu, Chaopeng Shen, S. G. Li and M. S. Phanikumar, 2014, "Quantifying storage changes in regional Great Lakes watersheds using a coupled subsurface-land surface process model and GRACE, MODIS products", Water Resources Research, 50, (9), pp. 7359–7377
  • Chaopeng Shen, J. Niu and M. S. Phanikumar, 2013, "Evaluating controls on coupled hydrologic and vegetation dynamics in a humid continental climate watershed using a subsurface - land surface processes model", Water Resources Research, 49, (5), pp. 2552–2572
  • S. Molins, D. Trebotich, C. I. Steefel and Chaopeng Shen, 2012, "An investigation of the effect of pore scale flow on average geochemical reaction rates using direct numerical simulation", Water Resources Research, 48, (3), pp. 11
  • Chaopeng Shen, J.-M Qiu and A. Christlieb, 2011, "Adaptive mesh refinement based on high order finite difference WENO scheme for multi-scale simulations", Journal of Computational Physics, 230, (10), pp. 23
  • Chaopeng Shen and M. S. Phanikumar, 2010, "A process-based, distributed hydrologic model based on a large-scale method for surface–subsurface coupling", Advances in Water Resources, 33, (12), pp. 18
  • Chaopeng Shen, J. Niu, E. J. Andersen and M. S. Phanikumar, 2010, "Estimating longitudinal dispersion in rivers using Acoustic Doppler Current Profilers", Advances in Water Resources, 33, (6), pp. 9
  • Chaopeng Shen and M. S. Phanikumar, 2009, "An efficient space-fractional dispersion approximation for stream solute transport modeling", Advances in Water Resources, 32, (10), pp. 13
  • Chaopeng Shen, M. S. Phanikumar, T. T. Fong, I. Aslam, S. L. Molloy and J. B. Rose, 2008, "Evaluating bacteriophage P22 as a tracer in a complex surface water system: The Grand River, Michigan", Environmental Science & Technology, 42, (7), pp. 2426–2431
  • M. S. Phanikumar, I. Aslam, Chaopeng Shen, D. T. Long and T. C. Voice, 2007, "Separating surface storage from hyporheic retention in natural streams using wavelet decomposition of acoustic Doppler current profiles", Water Resources Research, 43, (5), pp. 16
  • Xiaofeng Liu, Yalan Song and Chaopeng Shen, , "Bathymetry Inversion using a Deep-Learning-Based Surrogate for Shallow Water Equations Solvers", Water Resources Research

Conference Proceedings

  • Kurt R Smithgall, Peggy Johnson and Chaopeng Shen, 2017, "Impacts and Functioning of In-Stream Structures", World Environmental and Water Resources Congress 2017
  • C. I. Steefel, D. Trebotich, S. Molins, Y. Li and Chaopeng Shen, 2012, "Investigation of coupled flow and geochemical reactions at the pore scale by direct numerical simulation", Mineralogical Magazine, 76, (6), pp. 2125
  • Chaopeng Shen, D. Trebotich, S. Molins, D. T. Graves, B. Van Straalen, T. Ligocki and C. I. Steefel, 2011, "High performance computations of subsurface reactive transport processes at the pore scale", SciDAC meeting, pp. 5
  • Savinay Nagendra, Daniel Kifer and Chaopeng Shen, , "PatchRefineNet: Improving Binary Segmentation by Incorporating Signals from Optimal Patch-wise Binarization", Winter Conference on Applications of Computer Vision (WACV)

Research Projects

Honors and Awards

  • 2021 WRR Editors’ Choice Award, Water Resources Research, January 2023
  • Outstanding Research Award, Penn State Engineering Alumni Society, October 2022


Service to Penn State:

Service to External Organizations:

  • Service to Public and Private Organizations, Organizer, Soil moisture prediction and forecast for planning against locust swarms, United Nations Food and Agricultural Organization, February 2020
  • Participation in or Service to Professional and Learned Societies, Organizer, Broadening the use of machine learning in Hydrology, Special Topic in Frontiers in Water, February 2020
  • Participation in or Service to Professional and Learned Societies, Organizer, Big Data & Machine Learning in Water Sciences, Special Section in Water Resources Research, April 2019 - December 2020



The Penn State Civil and Environmental Engineering Department, established in 1881, is internationally recognized for excellence in the preparation of undergraduate and graduate engineers through the integration of education, research, and leadership.

Department of Civil & Environmental Engineering

212 Sackett Building

The Pennsylvania State University

University Park, PA 16802-1408

Phone: 814-863-3084