{"id":15,"date":"2023-06-21T19:50:19","date_gmt":"2023-06-21T19:50:19","guid":{"rendered":"https:\/\/labs.engineering.asu.edu\/txu\/?page_id=15"},"modified":"2025-08-08T21:24:26","modified_gmt":"2025-08-08T21:24:26","slug":"publications","status":"publish","type":"page","link":"https:\/\/labs.engineering.asu.edu\/txu\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"\n
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2025<\/h3>\n\n\n\n

Su X., Dai Q., Yao C., Gupta N., Korgaonkar Y., Milczarek M., Tong D., Xu T. Stormwater capture as a Pathway to enhance groundwater recharge: A potential assessment in arid to semi-Arid urban landscapes. City and Environment Interactions, Volume 26, 2025<\/p>\n\n\n\n

Wei S., Xu T. An LSTM approach to deciphering irrigation operations from remote sensing and groundwater levels records. Agricultural Water Management, Volume 308, 2025<\/p>\n\n\n\n

2024<\/h3>\n\n\n\n

S. Wei, R. Richard, D. Hogue, I. Mondal, T. Xu, T.H. Boyer, K.A. Hamilton. High resolution data visualization and machine learning prediction of free chlorine residual in a green building water system. Water Research X.
Volume 24. 2024,100244.<\/p>\n\n\n\n

Longyang\u00a0Q.,\u00a0Choi\u00a0S.,\u00a0Tennant\u00a0H.,\u00a0Hill\u00a0D.,\u00a0Ashmead\u00a0N.,\u00a0Neilson\u00a0B. T., et al.\u00a0An attention-based explainable deep learning approach to spatially distributed hydrologic modeling of a snow dominated mountainous karst watershed.\u00a0Water Resources Research,\u00a060, e2024WR037878. Nov, 2024.<\/p>\n\n\n\n

Thurber D., Lane B., Xu T., Neilson B.T. Dissolving the mystery of subsurface controls on snowmelt\u2013discharge dynamics in karst mountain watersheds using hydrologic timeseries. Hydrological Processes. 2024.<\/p>\n\n\n\n

Tennant H., Neilson B.T., Hill D., Newell D.L., Evans J.P., Choi S., McNamara J.P., Ashmead N. and Xu T., Karst Hydrologic Memory Supplements Streamflow During Dry Periods in Snow-Dominated, Mountainous Watersheds. Hydrological Processes, 38: e70019. 2024.\u00a0<\/p>\n\n\n\n

2023<\/h3>\n\n\n\n

Hou H, Longyang Q, Su H, Zeng R, Xu T, Wang ZH. Prioritizing environmental determinants of urban heat islands: A machine learning study for major cities in China. International Journal of Applied Earth Observation and Geoinformation. 2023 Aug 1;122:103411.<\/p>\n\n\n\n

Tyson C, Longyang Q, Neilson BT, Zeng R, Xu T. Effects of Meteorological Forcing Uncertainty on High-Resolution Snow Modeling and Streamflow Prediction in a Mountainous Karst Watershed. Journal of Hydrology. 2023 :129304. <\/p>\n\n\n\n

Rudko N, Muenich RL, Garcia M, Xu T. Development of a point-source model to improve simulations of manure lagoon interactions with the environment. Journal of Environmental Management. 2023;325 :116332. <\/p>\n\n\n\n

2022<\/h3>\n\n\n\n

Wei S, Xu T, Niu G-Y, Zeng R. Estimating Irrigation Water Consumption Using Machine Learning and Remote Sensing Data in Kansas High Plains. Remote Sensing. 2022;14 (13) :3004.<\/p>\n\n\n\n

Xu T, Longyang Q, Tyson C, Zeng R, Neilson BT. Hybrid physically based and deep learning modeling of a snow dominated, mountainous, karst watershed. Water Resources Research. 2022.<\/p>\n\n\n\n

Li P, Xu T, Wei S, Wang Z. Multi-objective optimization of urban environmental system design using machine learning. Computers, Environment and Urban Systems. 2022.<\/p>\n\n\n\n

2021<\/h3>\n\n\n\n

Xu T, Liang F. Machine learning for hydrologic sciences: An introductory overview . WIREs Water. 2021.<\/p>\n\n\n\n

Xu T, Guan K, Peng B, Wei S, Zhao L. Machine Learning-based Modeling of Spatio-temporally Varying Responses of Rainfed Corn Yield to Climate, Soil and Management in the US Corn Belt . Frontiers in Artificial Intelligence. 2021;4 (40).<\/p>\n\n\n\n

Wang Y, Shi L, Xu T, Zhang Q, Ye M, Zha Y. A nonparametric sequential data assimilation scheme for soil moisture flow . Journal of Hydrology. 2021;593.<\/p>\n\n\n\n

Tennant H, Neilson BT, Miller MP, Xu T. Ungaged inflow and loss patterns in urban and agricultural sub\u2010reaches of the Logan River Observatory . Hydrological Processes. 2021;35 (4).<\/p>\n\n\n\n

2019<\/h3>\n\n\n\n

Xu T, Deinies JM, Kendall A, Hyndman DH, Basso B. Addressing Challenges for Remotely Sensing Irrigation in Humid Temperate Regions by Incorporating Remote Sensing and Hydroclimatic Data. Remote Sensing . 2019;11 (3).<\/p>\n\n\n\n

Cai Y, Guan K, Lobell D, Potgieter AB, Wang S, Peng J, Xu T, Asseng S, Zhang Y, You L, et al. Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches. Agricultural and Forest Meteorology. 2019;274.<\/p>\n\n\n\n

2017<\/h3>\n\n\n\n

Hyndman DW, Xu T, Deines JM, Cao G, Nagelkirk R, Vinas A, McConnel W, Basso B, Kendall AD, Li S, et al. Quantifying Changes in Water Use and Groundwater Availability in a Megacity using Novel Integrated Systems Modeling: Changing water availability in megacity. Geophysical Research Letters. 2017;44 (16). DOI<\/p>\n\n\n\n

Xu T, Valocchi AJ, Ye M, Liang F. Quantifying model structural error: Efficient Bayesian calibration of a regional groundwater flow model using surrogates and a data\u2010driven error model. Water Resources Research. 2017;53 (5).<\/p>\n\n\n\n

Xu T, Valocchi AJ, Ye M, Liang F, Lin Y. Bayesian calibration of groundwater models with input data uncertainty. Water Resources Research. 2017;53 (4).<\/p>\n\n\n\n

2015<\/h3>\n\n\n\n

Xu T, Valocchi AJ. A Bayesian approach to improved calibration and prediction of groundwater models with structural error. Water Resources Research. 2015;51 (11). DOI<\/p>\n\n\n\n

Xu T, Valocchi AJ. Data-driven methods to improve baseflow prediction of a regional groundwater model. Computers & geosciences. 2015;85. DOI<\/p>\n\n\n\n

Choi J, Amir E, Xu T, Valocchi AJ. Learning relational kalman filtering, in Twenty-Ninth AAAI Conference on Artificial Intelligence<\/em>. ; 2015. PDF<\/p>\n\n\n\n

2014<\/h3>\n\n\n\n

Xu T, Valocchi AJ, Choi J, Amir E. Use of machine learning methods to reduce predictive error of groundwater models. Groundwater. 2014;52 (3). DOI<\/p>\n<\/div>\n\n\n\n

<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

2025 Su X., Dai Q., Yao C., Gupta N., Korgaonkar Y., Milczarek M., Tong D., Xu T. Stormwater capture as a Pathway to enhance groundwater recharge: A potential assessment in arid to semi-Arid urban landscapes. City and Environment Interactions, Volume 26, 2025 Wei S., Xu T. An LSTM approach to deciphering irrigation operations from remote…<\/p>\n","protected":false},"author":228,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-15","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"\nPublications - Groundwater Sustainability and Data Sciences<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/labs.engineering.asu.edu\/txu\/publications\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Publications - Groundwater Sustainability and Data Sciences\" \/>\n<meta property=\"og:description\" content=\"2025 Su X., Dai Q., Yao C., Gupta N., Korgaonkar Y., Milczarek M., Tong D., Xu T. 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