Tianfang Xu

h-index

Research activity per year

If you made any changes in Pure these will be visible here soon.

Fingerprint

Dive into the research topics where Tianfang Xu is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

1 Similar Profiles

16 Article
2 Conference contribution
1 Review article

Development of a point-source model to improve simulations of manure lagoon interactions with the environment
Rudko, N., Muenich, R. L., Garcia, M. & Xu, T., Jan 1 2023, In: Journal of Environmental Management. 325, 116332.
Research output: Contribution to journal › Article › peer-review
Effects of meteorological forcing uncertainty on high-resolution snow modeling and streamflow prediction in a mountainous karst watershed
Tyson, C., Longyang, Q., Neilson, B. T., Zeng, R. & Xu, T., Apr 2023, In: Journal of Hydrology. 619, 129304.
Research output: Contribution to journal › Article › peer-review
1 Scopus citations
Estimating Irrigation Water Consumption Using Machine Learning and Remote Sensing Data in Kansas High Plains
Wei, S., Xu, T., Niu, G. Y. & Zeng, R., Jul 1 2022, In: Remote Sensing. 14, 13, 3004.
Research output: Contribution to journal › Article › peer-review

Open Access
3 Scopus citations
Hybrid Physically Based and Deep Learning Modeling of a Snow Dominated, Mountainous, Karst Watershed
Xu, T., Longyang, Q., Tyson, C., Zeng, R. & Neilson, B. T., Mar 2022, In: Water Resources Research. 58, 3, e2021WR030993.
Research output: Contribution to journal › Article › peer-review
5 Scopus citations
Multi-objective optimization of urban environmental system design using machine learning
Li, P., Xu, T., Wei, S. & Wang, Z. H., Jun 2022, In: Computers, Environment and Urban Systems. 94, 101796.
Research output: Contribution to journal › Article › peer-review

Open Access
4 Scopus citations

1 Finished
6 Active

Smart Tree Watering in Arizonas Urban Environment
Xu, T. & Wang, Z.
Arizona Board of Regents
1/17/23 → 1/16/25
Project: Research project
Opportunities to Enhance Recharge in Arizona
Mascaro, G. & Xu, T.
Arizona Board of Regents
1/17/23 → 6/30/26
Project: Research project
Designing nature to enhance resilience of built infrastructure in western US landscapes
Xu, T., Pavlic, T., Mascaro, G., Maciejewski, R., Liu, H., Wutich, A., Candan, K. & Muenich, R.
DOD-ARMY: Army Corps of Engineers (USACE)
9/24/21 → 9/28/23
Project: Research project
Collaborative Research: Quantifying Watershed Dynamics in Snow-Dominated Mountainous Karst Watersheds Using Hybrid Physically Based and Deep Learning Models
Xu, T.
National Science Foundation (NSF)
3/1/21 → 2/29/24
Project: Research project
Developing an irrigation dataset for assessment of anthropogenic impacts on terrestrial-atmosphere energy-water coupling using machine learning-based data fusion
Zeng, R. & Xu, T.
DOC: National Oceanic Atmospheric Administration (NOAA)
9/1/20 → 8/31/23
Project: Research project

Tianfang Xu

Fingerprint

Network

Dive into details

Development of a point-source model to improve simulations of manure lagoon interactions with the environment

Effects of meteorological forcing uncertainty on high-resolution snow modeling and streamflow prediction in a mountainous karst watershed

Estimating Irrigation Water Consumption Using Machine Learning and Remote Sensing Data in Kansas High Plains

Hybrid Physically Based and Deep Learning Modeling of a Snow Dominated, Mountainous, Karst Watershed

Multi-objective optimization of urban environmental system design using machine learning

Smart Tree Watering in Arizonas Urban Environment

Opportunities to Enhance Recharge in Arizona

Designing nature to enhance resilience of built infrastructure in western US landscapes

Collaborative Research: Quantifying Watershed Dynamics in Snow-Dominated Mountainous Karst Watersheds Using Hybrid Physically Based and Deep Learning Models

Developing an irrigation dataset for assessment of anthropogenic impacts on terrestrial-atmosphere energy-water coupling using machine learning-based data fusion

Tianfang Xu

Fingerprint

Network

Research output

Projects