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Chaopeng Shen, Ph.D. - Publications

Affiliations: 
2009 Michigan State University, East Lansing, MI 
Area:
Environmental Engineering, Hydrology
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39 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2023 Saha GK, Rahmani F, Shen C, Li L, Cibin R. A deep learning-based novel approach to generate continuous daily stream nitrate concentration for nitrate data-sparse watersheds. The Science of the Total Environment. 878: 162930. PMID 36934914 DOI: 10.1016/j.scitotenv.2023.162930  0.305
2022 Sadayappan K, Kerins D, Shen C, Li L. Nitrate concentrations predominantly driven by human, climate, and soil properties in US rivers. Water Research. 226: 119295. PMID 36323218 DOI: 10.1016/j.watres.2022.119295  0.324
2021 Zhi W, Feng D, Tsai WP, Sterle G, Harpold A, Shen C, Li L. From Hydrometeorology to River Water Quality: Can a Deep Learning Model Predict Dissolved Oxygen at the Continental Scale? Environmental Science & Technology. PMID 33533608 DOI: 10.1021/acs.est.0c06783  0.33
2020 Feng D, Fang K, Shen C. Enhancing streamflow forecast and extracting insights using long‐short term memory networks with data integration at continental scales Water Resources Research. 56. DOI: 10.1029/2019Wr026793  0.432
2019 Fang K, Shen C. Near-Real-Time Forecast of Satellite-Based Soil Moisture Using Long Short-Term Memory with an Adaptive Data Integration Kernel Journal of Hydrometeorology. 21: 399-413. DOI: 10.1175/Jhm-D-19-0169.1  0.4
2019 Fang K, Pan M, Shen C. The Value of SMAP for Long-Term Soil Moisture Estimation With the Help of Deep Learning Ieee Transactions On Geoscience and Remote Sensing. 57: 2221-2233. DOI: 10.1109/Tgrs.2018.2872131  0.414
2019 Fan Y, Clark M, Lawrence DM, Swenson S, Band LE, Brantley SL, Brooks PD, Dietrich WE, Flores A, Grant G, Kirchner JW, Mackay DS, McDonnell JJ, Milly PCD, Sullivan PL, ... ... Shen C, et al. Hillslope Hydrology in Global Change Research and Earth System Modeling Water Resources Research. 55: 1737-1772. DOI: 10.1029/2018Wr023903  0.347
2019 Ji X, Lesack LFW, Melack JM, Wang S, Riley WJ, Shen C. Seasonal and Interannual Patterns and Controls of Hydrological Fluxes in an Amazon Floodplain Lake With a Surface‐Subsurface Process Model Water Resources Research. 55: 3056-3075. DOI: 10.1029/2018Wr023897  0.457
2019 Fang K, Ji X, Shen C, Ludwig N, Godfrey P, Mahjabin T, Doughty C. 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: 12-28. DOI: 10.1016/J.Advwatres.2019.05.008  0.509
2018 Shen C, Laloy E, Elshorbagy A, Albert A, Bales J, Chang F, Ganguly S, Hsu K, Kifer D, Fang Z, Fang K, Li D, Li X, Tsai W. HESS Opinions: Incubating deep-learning-powered hydrologic science advances as a community Hydrology and Earth System Sciences. 22: 5639-5656. DOI: 10.5194/Hess-22-5639-2018  0.365
2018 Shen C, Laloy E, Albert A, Chang F, Elshorbagy A, Ganguly S, Hsu K, Kifer D, Fang Z, Fang K, Li D, Li X, Tsai W. HESS Opinions: Deep learning as a promising avenue toward knowledge discovery in water sciences Hydrology and Earth System Sciences Discussions. 1-21. DOI: 10.5194/Hess-2018-168  0.335
2018 Simon Wang S, Gillies RR, Chung O, Shen C. Cross-Basin Decadal Climate Regime Connecting the Colorado River with the Great Salt Lake Journal of Hydrometeorology. 19: 659-665. DOI: 10.1175/Jhm-D-17-0081.1  0.406
2018 Shen C. A Transdisciplinary Review of Deep Learning Research and Its Relevance for Water Resources Scientists Water Resources Research. 54: 8558-8593. DOI: 10.1029/2018Wr022643  0.361
2018 Ji X, Shen C. The introspective may achieve more: Enhancing existing Geoscientific models with native-language emulated structural reflection Computers & Geosciences. 110: 32-40. DOI: 10.1016/J.Cageo.2017.09.014  0.313
2017 Niu J, Shen C, Chambers JQ, Melack JM, Riley WJ. Interannual Variation in Hydrologic Budgets in an Amazonian Watershed with a Coupled Subsurface–Land Surface Process Model Journal of Hydrometeorology. 18: 2597-2617. DOI: 10.1175/Jhm-D-17-0108.1  0.625
2017 Fang K, Shen C, Kifer D, Yang X. Prolongation of SMAP to Spatiotemporally Seamless Coverage of Continental U.S. Using a Deep Learning Neural Network Geophysical Research Letters. 44: 11,030-11,039. DOI: 10.1002/2017Gl075619  0.4
2017 Fang K, Shen C. Full-flow-regime storage-streamflow correlation patterns provide insights into hydrologic functioning over the continental US Water Resources Research. 53: 8064-8083. DOI: 10.1002/2016Wr020283  0.499
2016 Liu X, Chen Y, Shen C. Coupled Two-Dimensional Surface Flow and Three-Dimensional Subsurface Flow Modeling for Drainage of Permeable Road Pavement Journal of Hydrologic Engineering. 21: 04016051. DOI: 10.1061/(Asce)He.1943-5584.0001462  0.541
2016 Fatichi S, Vivoni ER, Ogden FL, Ivanov VY, Mirus B, Gochis D, Downer CW, Camporese M, Davison JH, Ebel B, Jones N, Kim J, Mascaro G, Niswonger R, Restrepo P, ... ... Shen C, et al. An overview of current applications, challenges, and future trends in distributed process-based models in hydrology Journal of Hydrology. 537: 45-60. DOI: 10.1016/J.Jhydrol.2016.03.026  0.498
2016 Fang K, Shen C, Fisher JB, Niu J. Improving Budyko curve-based estimates of long-term water partitioning using hydrologic signatures from GRACE Water Resources Research. 52: 5537-5554. DOI: 10.1002/2016Wr018748  0.608
2016 Shen C, Wang S, Liu X. Geomorphological significance of at-many-stations hydraulic geometry Geophysical Research Letters. 43: 3762-3770. DOI: 10.1002/2016Gl068364  0.516
2016 Shen C, Riley WJ, Smithgall KR, Melack JM, Fang K. The fan of influence of streams and channel feedbacks to simulated land surface water and carbon dynamics Water Resources Research. DOI: 10.1002/2015Wr018086  0.403
2016 Pau GSH, Shen C, Riley WJ, Liu Y. Accurate and efficient prediction of fine-resolution hydrologic and carbon dynamic simulations from coarse-resolution models Water Resources Research. DOI: 10.1002/2015Wr017782  0.446
2015 Ji X, Shen C, Riley WJ. Temporal evolution of soil moisture statistical fractal and controls by soil texture and regional groundwater flow Advances in Water Resources. 86: 155-169. DOI: 10.1016/J.Advwatres.2015.09.027  0.466
2015 Clark MP, Fan Y, Lawrence DM, Adam JC, Bolster D, Gochis DJ, Hooper RP, Kumar M, Leung LR, Mackay DS, Maxwell RM, Shen C, Swenson SC, Zeng X. Improving the representation of hydrologic processes in Earth System Models Water Resources Research. 51: 5929-5956. DOI: 10.1002/2015Wr017096  0.466
2014 Molins S, Trebotich D, Yang L, Ajo-Franklin JB, Ligocki TJ, Shen C, Steefel CI. Pore-scale controls on calcite dissolution rates from flow-through laboratory and numerical experiments. Environmental Science & Technology. 48: 7453-60. PMID 24865463 DOI: 10.1021/Es5013438  0.4
2014 Riley WJ, Shen C. Characterizing coarse-resolution watershed soil moisture heterogeneity using fine-scale simulations Hydrology and Earth System Sciences. 18: 2463-2483. DOI: 10.5194/Hess-18-2463-2014  0.417
2014 Trebotich D, Adams MF, Molins S, Steefel CI, Shen C. High-Resolution Simulation of Pore-Scale Reactive Transport Processes Associated with Carbon Sequestration Computing in Science & Engineering. 16: 22-31. DOI: 10.1109/Mcse.2014.77  0.392
2014 Shen C, Niu J, Fang K. Quantifying the effects of data integration algorithms on the outcomes of a subsurface–land surface processes model Environmental Modelling & Software. 59: 146-161. DOI: 10.1016/J.Envsoft.2014.05.006  0.626
2014 Niu J, Shen C, Li S, Phanikumar MS. Quantifying storage changes in regional Great Lakes watersheds using a coupled subsurface-land surface process model and GRACE, MODIS products Water Resources Research. 50: 7359-7377. DOI: 10.1002/2014Wr015589  0.727
2014 Maxwell RM, Putti M, Meyerhoff S, Delfs JO, Ferguson IM, Ivanov V, Kim J, Kolditz O, Kollet SJ, Kumar M, Lopez S, Niu J, Paniconi C, Park YJ, Phanikumar MS, ... Shen C, et al. Surface-subsurface model intercomparison: A first set of benchmark results to diagnose integrated hydrology and feedbacks Water Resources Research. 50: 1531-1549. DOI: 10.1002/2013Wr013725  0.725
2013 Shen C, Niu J, Phanikumar MS. 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: 2552-2572. DOI: 10.1002/Wrcr.20189  0.712
2012 Molins S, Trebotich D, Steefel CI, Shen C. An investigation of the effect of pore scale flow on average geochemical reaction rates using direct numerical simulation Water Resources Research. 48. DOI: 10.1029/2011Wr011404  0.313
2011 Shen C, Qiu JM, Christlieb A. Adaptive mesh refinement based on high order finite difference WENO scheme for multi-scale simulations Journal of Computational Physics. 230: 3780-3802. DOI: 10.1016/J.Jcp.2011.02.008  0.322
2010 Shen C, Phanikumar MS. A process-based, distributed hydrologic model based on a large-scale method for surface–subsurface coupling Advances in Water Resources. 33: 1524-1541. DOI: 10.1016/J.Advwatres.2010.09.002  0.709
2010 Shen C, Niu J, Anderson EJ, Phanikumar MS. Estimating longitudinal dispersion in rivers using Acoustic Doppler Current Profilers Advances in Water Resources. 33: 615-623. DOI: 10.1016/J.Advwatres.2010.02.008  0.696
2009 Shen C, Phanikumar MS. An efficient space-fractional dispersion approximation for stream solute transport modeling Advances in Water Resources. 32: 1482-1494. DOI: 10.1016/J.Advwatres.2009.07.001  0.667
2008 Shen C, Phanikumar MS, Fong TT, Aslam I, McElmurry SP, Molloy SL, Rose JB. Evaluating bacteriophage P22 as a tracer in a complex surface water system: the Grand River, Michigan. Environmental Science & Technology. 42: 2426-31. PMID 18504976 DOI: 10.1021/Es702317T  0.681
2007 Phanikumar MS, Aslam I, Shen C, Long DT, Voice TC. Separating surface storage from hyporheic retention in natural streams using wavelet decomposition of acoustic Doppler current profiles Water Resources Research. 43. DOI: 10.1029/2006Wr005104  0.689
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