Search Results - "Water resources"

Journal of water resources planning and management

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MERIT Hydro: A High‐Resolution Global Hydrography Map Based on Latest Topography Dataset by Yamazaki, Dai, Ikeshima, Daiki, Sosa, Jeison, Bates, Paul D., Allen, George H., Pavelsky, Tamlin M.

“…High‐resolution raster hydrography maps are a fundamental data source for many geoscience applications. Here we introduce MERIT Hydro, a new global flow…”
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A Transdisciplinary Review of Deep Learning Research and Its Relevance for Water Resources Scientists by Shen, Chaopeng

“…Deep learning (DL), a new generation of artificial neural network research, has transformed industries, daily lives, and various scientific disciplines in…”
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What Role Does Hydrological Science Play in the Age of Machine Learning? by Nearing, Grey S., Kratzert, Frederik, Sampson, Alden Keefe, Pelissier, Craig S., Klotz, Daniel, Frame, Jonathan M., Prieto, Cristina, Gupta, Hoshin V.

“…This paper is derived from a keynote talk given at the Google's 2020 Flood Forecasting Meets Machine Learning Workshop. Recent experiments applying deep…”
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A Rainfall‐Runoff Model With LSTM‐Based Sequence‐to‐Sequence Learning by Xiang, Zhongrun, Yan, Jun, Demir, Ibrahim

“…Rainfall‐runoff modeling is a complex nonlinear time series problem. While there is still room for improvement, researchers have been developing physical and…”
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Global and Regional Increase of Precipitation Extremes Under Global Warming by Papalexiou, Simon Michael, Montanari, Alberto

“…Global warming is expected to change the regime of extreme precipitation. Physical laws translate increasing atmospheric heat into increasing atmospheric water…”
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Toward Improved Predictions in Ungauged Basins: Exploiting the Power of Machine Learning by Kratzert, Frederik, Klotz, Daniel, Herrnegger, Mathew, Sampson, Alden K., Hochreiter, Sepp, Nearing, Grey S.

“…Long short‐term memory (LSTM) networks offer unprecedented accuracy for prediction in ungauged basins. We trained and tested several LSTMs on 531 basins from…”
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U-FNO—An enhanced Fourier neural operator-based deep-learning model for multiphase flow by Wen, Gege, Li, Zongyi, Azizzadenesheli, Kamyar, Anandkumar, Anima, Benson, Sally M.

“…Numerical simulation of multiphase flow in porous media is essential for many geoscience applications. Machine learning models trained with numerical…”
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The Future of Evapotranspiration: Global Requirements for Ecosystem Functioning, Carbon and Climate Feedbacks, Agricultural Management, and Water Resources by Fisher, Joshua B., Melton, Forrest, Middleton, Elizabeth, Hain, Christopher, Anderson, Martha, Allen, Richard, McCabe, Matthew F., Hook, Simon, Baldocchi, Dennis, Townsend, Philip A., Kilic, Ayse, Tu, Kevin, Miralles, Diego D., Perret, Johan, Lagouarde, Jean-Pierre, Waliser, Duane, Purdy, Adam J., French, Andrew, Schimel, David, Famiglietti, James, Stephens, Graeme, Wood, Eric F.

“…The fate of the terrestrial biosphere is highly uncertain given recent and projected changes in climate. This is especially acute for impacts associated with…”
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Physics‐Informed Deep Neural Networks for Learning Parameters and Constitutive Relationships in Subsurface Flow Problems by Tartakovsky, A. M., Marrero, C. Ortiz, Perdikaris, Paris, Tartakovsky, G. D., Barajas‐Solano, D.

“…We present a physics‐informed deep neural network (DNN) method for estimating hydraulic conductivity in saturated and unsaturated flows governed by Darcy's…”
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ECOSTRESS: NASA's Next Generation Mission to Measure Evapotranspiration From the International Space Station by Fisher, Joshua B., Lee, Brian, Purdy, Adam J., Halverson, Gregory H., Dohlen, Matthew B., Cawse‐Nicholson, Kerry, Wang, Audrey, Anderson, Ray G., Aragon, Bruno, Arain, M. Altaf, Baldocchi, Dennis D., Baker, John M., Barral, Hélène, Bernacchi, Carl J., Bernhofer, Christian, Biraud, Sébastien C., Bohrer, Gil, Brunsell, Nathaniel, Cappelaere, Bernard, Castro‐Contreras, Saulo, Chun, Junghwa, Conrad, Bryan J., Cremonese, Edoardo, Demarty, Jérôme, Desai, Ankur R., De Ligne, Anne, Foltýnová, Lenka, Goulden, Michael L., Griffis, Timothy J., Grünwald, Thomas, Johnson, Mark S., Kang, Minseok, Kelbe, Dave, Kowalska, Natalia, Lim, Jong‐Hwan, Maïnassara, Ibrahim, McCabe, Matthew F., Missik, Justine E.C., Mohanty, Binayak P., Moore, Caitlin E., Morillas, Laura, Morrison, Ross, Munger, J. William, Posse, Gabriela, Richardson, Andrew D., Russell, Eric S., Ryu, Youngryel, Sanchez‐Azofeifa, Arturo, Schmidt, Marius, Schwartz, Efrat, Sharp, Iain, Šigut, Ladislav, Tang, Yao, Hulley, Glynn, Anderson, Martha, Hain, Christopher, French, Andrew, Wood, Eric, Hook, Simon

“…The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) was launched to the International Space Station on 29 June 2018 by the…”
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Global GRACE Data Assimilation for Groundwater and Drought Monitoring: Advances and Challenges by Li, Bailing, Rodell, Matthew, Kumar, Sujay, Beaudoing, Hiroko Kato, Getirana, Augusto, Zaitchik, Benjamin F., Goncalves, Luis Gustavo, Cossetin, Camila, Bhanja, Soumendra, Mukherjee, Abhijit, Tian, Siyuan, Tangdamrongsub, Natthachet, Long, Di, Nanteza, Jamiat, Lee, Jejung, Policelli, Frederick, Goni, Ibrahim B., Daira, Djoret, Bila, Mohammed, Lannoy, Gabriëlle, Mocko, David, Steele‐Dunne, Susan C., Save, Himanshu, Bettadpur, Srinivas

“…The scarcity of groundwater storage change data at the global scale hinders our ability to monitor groundwater resources effectively. In this study, we…”
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Sociohydrology: Scientific Challenges in Addressing the Sustainable Development Goals by Di Baldassarre, Giuliano, Sivapalan, Murugesu, Rusca, Maria, Cudennec, Christophe, Garcia, Margaret, Kreibich, Heidi, Konar, Megan, Mondino, Elena, Mård, Johanna, Pande, Saket, Sanderson, Matthew R., Tian, Fuqiang, Viglione, Alberto, Wei, Jing, Wei, Yongping, Yu, David J., Srinivasan, Veena, Blöschl, Günter

“…The Sustainable Development Goals (SDGs) of the United Nations Agenda 2030 represent an ambitious blueprint to reduce inequalities globally and achieve a…”
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If Precipitation Extremes Are Increasing, Why Aren't Floods? by Sharma, Ashish, Wasko, Conrad, Lettenmaier, Dennis P.

“…Despite evidence of increasing precipitation extremes, corresponding evidence for increases in flooding remains elusive. If anything, flood magnitudes are…”
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Hillslope Hydrology in Global Change Research and Earth System Modeling by Fan, Y., Clark, M., Lawrence, D. M., Swenson, S., Band, L. E., Brantley, S. L., Brooks, P. D., Dietrich, W. E., Flores, A., Grant, G., Kirchner, J. W., Mackay, D. S., McDonnell, J. J., Milly, P. C. D., Sullivan, P. L., Tague, C., Ajami, H., Chaney, N., Hartmann, A., Hazenberg, P., McNamara, J., Pelletier, J., Perket, J., Rouholahnejad‐Freund, E., Wagener, T., Zeng, X., Beighley, E., Buzan, J., Huang, M., Livneh, B., Mohanty, B. P., Nijssen, B., Safeeq, M., Shen, C., Verseveld, W., Volk, J., Yamazaki, D.

“…Earth System Models (ESMs) are essential tools for understanding and predicting global change, but they cannot explicitly resolve hillslope‐scale terrain…”
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Combined Modeling of US Fluvial, Pluvial, and Coastal Flood Hazard Under Current and Future Climates by Bates, Paul D., Quinn, Niall, Sampson, Christopher, Smith, Andrew, Wing, Oliver, Sosa, Jeison, Savage, James, Olcese, Gaia, Neal, Jeff, Schumann, Guy, Giustarini, Laura, Coxon, Gemma, Porter, Jeremy R., Amodeo, Mike F., Chu, Ziyan, Lewis‐Gruss, Sharai, Freeman, Neil B., Houser, Trevor, Delgado, Michael, Hamidi, Ali, Bolliger, Ian, McCusker, Kelly, Emanuel, Kerry, Ferreira, Celso M., Khalid, Arslaan, Haigh, Ivan D., Couasnon, Anaïs, Kopp, Robert, Hsiang, Solomon, Krajewski, Witold F.

“…This study reports a new and significantly enhanced analysis of US flood hazard at 30 m spatial resolution. Specific improvements include updated hydrography…”
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Enhancing Streamflow Forecast and Extracting Insights Using Long‐Short Term Memory Networks With Data Integration at Continental Scales by Feng, Dapeng, Fang, Kuai, Shen, Chaopeng

“…Recent observations with varied schedules and types (moving average, snapshot, or regularly spaced) can help to improve streamflow forecasts, but it is…”
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Process‐Guided Deep Learning Predictions of Lake Water Temperature by Read, Jordan S., Jia, Xiaowei, Willard, Jared, Appling, Alison P., Zwart, Jacob A., Oliver, Samantha K., Karpatne, Anuj, Hansen, Gretchen J. A., Hanson, Paul C., Watkins, William, Steinbach, Michael, Kumar, Vipin

“…The rapid growth of data in water resources has created new opportunities to accelerate knowledge discovery with the use of advanced deep learning tools…”
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Satellite Remote Sensing for Water Resources Management: Potential for Supporting Sustainable Development in Data‐Poor Regions by Sheffield, J., Wood, E. F., Pan, M., Beck, H., Coccia, G., Serrat‐Capdevila, A., Verbist, K.

“…Water resources management (WRM) for sustainable development presents many challenges in areas with sparse in situ monitoring networks. The exponential growth…”
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Physics-informed neural networks for multiphysics data assimilation with application to subsurface transport by He, QiZhi, Barajas-Solano, David, Tartakovsky, Guzel, Tartakovsky, Alexandre M.

“…•Standard DNN methods might lead to highly uncertain and inaccurate predictions.•Multiphysics-informed neural network (MPINN) method is proposed.•Multiphisics…”
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