H038
Causal Inference in Hydrology: Inter-comparisons, Applications and Future Avenues
Session ID#: 157250
Session Description:
Significant methodological and algorithmic advancements in causal inference have recently found applications in several fields, including but not limited to epidemiology and neuroscience. Despite the growing availability of in-situ and remotely sensed hydrological data, the study of causal inference in complex hydrological systems is still in its infancy. In this session, we welcome presentations that: 1) inter-compare the performance of different causal inference methods using simulations or observations within the context of hydrologic systems, 2) formulate and evaluate hypotheses on the underlying structure and dynamics of hydrologic processes, or 3) utilize causal inference frameworks to make attribution statements regarding the impact of anthropogenic global warming on observed changes of hydrologic extremes (e.g., droughts and floods). We also encourage the submission of studies that seek to integrate deep learning within classical frameworks of causal inference (e.g., Granger causality).
Index Terms:
1872 Time series analysis [HYDROLOGY]
1914 Data mining [INFORMATICS]
1916 Data and information discovery [INFORMATICS]
1942 Machine learning [INFORMATICS]
Primary Convener: Mohammed Ombadi, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
Conveners: Peishi Jiang1, Leila Constanza Hernandez Rodriguez2 and Mark Daniel Risser2, (1)Pacific Northwest National Laboratory, Richland, WA, United States(2)Lawrence Berkeley National Laboratory, Berkeley, CA, United States
Causal Discovery of Agricultural Management and Reservoir Operation Induced River Water Quality Change (1079628)
Ting Liu, Arizona State University, School of Sustainable Engineering and the Built Environment, Ira A. Fulton Schools of Engineering, Tempe, AZ, United States, Paras Sheth, Arizona State University, School of Computing, Informatics, and Decision Systems Engineering, Tempe, United States, Yuhang Wei, Arizona State University, Future H2O, Knowledge Enterprise Development, Tempe, United States, John L Sabo, Tulane University, ByWater Institute, New Orleans, United States and Rebecca Logsdon Muenich, Arizona State University, School of Sustainable Engineering and the Built Environment, Ira A. Fulton Schools of Engineering, Tempe, United States
Understanding the Dynamics of Vegetation by Causal Delineation in Eco-hydrological Systems (1079856)
Tejasvi Chauhan, Indian Institute of Technology Bombay, Department of Civil Engineering, Mumbai, India and Subimal Ghosh, Indian Institute of Technology Bombay, Department of Civil Engineering, Interdisciplinary Program in Climate Studies, Mumbai, India; Indian Institute of Technology Bombay, Interdisciplinary Programme in Climate Studies, Mumbai, India
Assessing the Eco-hydro-meteorological Variables Influencing the Carbon Exchange Phenomenon of Pine-dominated Ecosystem of Himalaya (1080597)
Leena Khadke1, Sandipan Mukherjee2, Kireet Kumar2 and Subimal Ghosh3,4, (1)Indian Institute of Technology Bombay, Department of Civil Engineering, Mumbai, India, (2)G. B. Pant National Institute of Himalayan Environment, Kosi-Katarmal, Almora, India, (3)Indian Institute of Technology Bombay, Department of Civil Engineering, Interdisciplinary Program in Climate Studies, Mumbai, India, (4)Indian Institute of Technology Bombay, Interdisciplinary Programme in Climate Studies, Mumbai, India
A stochastic approach to causality (Invited) (1081471)
Demetris Koutsoyiannis, National Technical University of Athens (NTUA), Marousi Athens, Greece, Christian Onof, Imperial College London, Department of Civil and Environmental Engineering, London, United Kingdom, Zbigniew W. Kundzewicz, Institute for Agricultural and Forest Environment, Polish Academy of Sciences, Poznan, Poland and Antonis Christofides, National Technical University of Athens, Zographou, Greece
Causal Discovery-based analysis of Vegetation-Climate interaction in India (1102177)
Akash Verma1, Vikram Chandel1 and Subimal Ghosh2,3, (1)Indian Institute of Technology Bombay, Department of Civil Engineering, Mumbai, India, (2)Indian Institute of Technology Bombay, Department of Civil Engineering, Interdisciplinary Program in Climate Studies, Mumbai, India, (3)Indian Institute of Technology Bombay, Interdisciplinary Programme in Climate Studies, Mumbai, India
Investigate causal effects of hydrometeorological extremes on the frequency of protests in India (1162321)
Beichen Zhang1, Michael J Hayes1, Yuzhen Zhou2, Yawen Guan2, Daniel Schaefer3, Ashok Samal4, Regina Werum3, Kelly Helm Smith1 and Tsegaye Tadesse1, (1)University of Nebraska-Lincoln, School of Natural Resources, Lincoln, United States, (2)University of Nebraska-Lincoln, Department of Statistics, Lincoln, United States, (3)University of Nebraska–Lincoln, Department of Sociology, Lincoln, United States, (4)University of Nebraska-Lincoln, Computer Science Engineering, Lincoln, NE, United States
Information Content and Transmission of Catchment Hydrologic System (1172049)
Jiao Wang1, Lu Zhuo2, Miguel Angel Rico-Ramirez1 and Dawei Han1, (1)University of Bristol, Department of Civil Engineering, Bristol, United Kingdom, (2)University of Bristol, School of Geographical Sciences, Bristol, United Kingdom
Causal Attribution of Landscape versus Meteorological Drivers of Eddy Covariance Fluxes (1177411)
Allison Eva Goodwell1, Mozhgan Askarzadehfarahani1, Mushfika Zahan2 and Dawn URycki3, (1)University of Colorado Denver, Civil Engineering, Denver, CO, United States, (2)University of Colorado Denver, Denver, CO, United States, (3)University of Colorado Denver, Department of Civil Engineering, Denver, CO, United States
A Comparative Study of Estimating CO2 Outgassing from the Lower Mississippi River Using Gas Exchange Coefficient KT as a Constant KT, Velocity Dependent KT and Wind Dependent KT. (1181316)
Anamika Dristi1, Yi-Jun Xu2 and Lee Potter1, (1)Louisiana State University, Baton Rouge, LA, United States, (2)Louisiana State University, School of Renewable Natural Resources, Baton Rouge, LA, United States
Potential Drivers and Spatiotemporal Variability of Rain-on-Snow Events (1186169)
Sinan Rasiya Koya, University of Nebraska Lincoln, Civil and Environmental Engineering, Lincoln, NE, United States, Kanak Kanti Kar, University of Nebraska-Lincoln, Civil and Environmental Engineering, Omaha, United States and Tirthankar Roy, University of Nebraska Lincoln, Civil and Environmental Engineering, Omaha, United States
