Photo of Chaopeng Shen

Chaopeng Shen

Associate Professor

Affiliation(s):

  • Civil and Environmental Engineering

231C Sackett Building

cxs1024@psu.edu

814-863-5844

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

 
 

 

Education

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

Publications

Journal Articles

  • 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
  • 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
  • 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, 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
  • 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
  • Chaopeng Shen, , "Deep learning: A next-generation big-data approach for hydrology", Eos

Conference Proceedings

  • Savinay Nagendra, Srikanth Banagere Manjunatha, Chaopeng Shen, Daniel Kifer and TE PEI, 2020, "An efficient deep learning mechanism for cross-region generalization of landslide events"
  • Jiangtao Liu, Ashutosh Sharma, Wen-Ping Tsai, Kai Ma, Dapeng Feng, Kathryn Lawson and Chaopeng Shen, 2020, "Automated deep-learning-based soil moisture planning and forecast system for planning against natural disasters"
  • Wei Zhi, Dapeng Feng, Wen-Ping Tsai, Gary Sterle, Adrian Adam Harpold, Chaopeng Shen and Li Li, 2020, "Capturing continental-scale dissolved oxygen patterns using deep learning and big data"
  • TE PEI, Savinay Nagendra, Srikanth Banagere Manjunatha, Guanlin He, Tong Qiu, Daniel Kifer and Chaopeng Shen, 2020, "Cloud-based interactive database management suite integrated with deep learning-based annotation tool for landslide mapping"
  • Rajesh Gupta, Mila Sherman, Dezhi Hong, Judy P Che-Castaldo, Ryan Michael McGranaghan, Deborah A Sunter, Chaopeng Shen, Cousin, R\'emi, David Matteson, Lan Wang and others, 2020, "Critical Risk Indicators (CRIs) for the electric power grid: A survey and discussion of interconnected effects"
  • Wei Ren, Ryan Michael McGranaghan, Chaopeng Shen, Cousin and R\'emi, 2020, "Data-Driven Exploration of Interconnected Risks in Complex Human--Natural Systems II"
  • Ashutosh Sharma and Chaopeng Shen, 2020, "Improving multi-month streamflow forecast in CONUS using Long-Short Term Memory (LSTM) networks"
  • Chaopeng Shen, Dapeng Feng, Kai Ma, Wenyu Ouyang, Farshid Rahmani, Wen-Ping Tsai and Kathryn Lawson, 2020, "Mapping the challenges of deep-learning-powered flood forecasting: from data-rich region to data-scarce regions"
  • Chaopeng Shen, Farshid Rahmani, Wei Zhi, Kuai Fang, Wen-Ping Tsai, Li Li and Kathryn Lawson, 2020, "Transcending the uniqueness of places with large-sample multi-physics catchment modeling based on machine learning"
  • Kai Ma, Dapeng Feng, Kathryn Lawson, Wen-Ping Tsai, Chuan Liang, Xiaorong Huang and Chaopeng Shen, 2020, "Transferring hydrologic data across the continent--how do data from US catchments benefit flood prediction in other countries?"
  • 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
  • Kurt R Smithgall, Peggy A Johnson and Chaopeng Shen, , "Impacts and Functioning of In-Stream Structures", World Environmental and Water Resources Congress 2017

Research Projects

Honors and Awards

Service

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
 


 

About

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