My research interests: land surface hydrology, land surface modeling, and nitrogen modeling.
My current research is to couple a nitrogen model with the Noah-MP land surface model to support environmental modeling and prediction.

Current Research Projects

Developing and Applying an Integrated Multi-scale Earth System Modeling Framework to Study the Impacts of Changing Climate, Local Weather, and Land Use on Watersheds and Downstream Coastal Ecosystems (funded by NASA IDS Program , PI: Zong-Liang Yang) ( view )

Past Research Projects

Consortium of Universities for the Advancement of Hydrologic Science (CUAHSI) Hydrologic Information System (funded by NSF, PI: David Maidment)

Hai Basin Integrated Water Management and Environment Project (funded by the Global Environmental Fund, sub-project PI: Zongxue Xu)

South-to-North Water Transfer Project, Highway bridge design for the middle route

Graduate Student Visitor Grant, Advanced Study Program - The National Center for Atmospheric Research (NCAR) (2013)

Collaborative Seed Grant of the Strategic University Research Partnership (SURP) Program - NASA Jet Propulsion Laboratory (JPL), California Institute of Technology (2013)

Visiting Scholar of NOAA/NCEP/EMC (Off-Campus Research) Supported by the Ronald K. DeFord Field Scholarship - Jackson School of Geosciences, The University of Texas at Austin (2012)

Chair, Noah-MP Technical Note Writing Committee, Land Environment and Atmospheric Dynamics Group at UT-Austin (2011)

Cai, X.T., Y.L. Xia, Z.-L. Yang, M.Y. Huang, H.L. Wei, and M. Ek, 2013: Evaluation of Advanced Land Surface Models in the NLDAS Testbed (oral). American Meteorological Society Annual Meeting 2013, 4B.8, 8 January, Austin, TX.,

Cai, X.T., Z.L. Yang and J.W. Nielsen-Gammon, 2012: Noah-MP Land Surface Model in Supporting Drought Forecast for Texas (poster), Water Forum II: Texas Drought and Beyond, 22-23 October, Austin, TX.,

Cai, X.T., Z.L. Yang, C.H. David and A.A. Tavakoly, 2011: Evaluation of a Newly Augmented Land Surface Model (Noah-MP) Over the Mississippi River Basin Using Available Observational Datasets (poster), American Geophysical Union Fall meeting, H43A-1183, 8 ,


Visiting NASA JPL in summer 2013

CaltechCity Hall


Land Environment and Atmospheric Dynamics Group
The Land Environment and Atmospheric Dynamics Group at UT-Austin consists of graduate research assistants, postdoctoral fellows, research scientists and visiting scholars. We view the earth system in a holistic way, linking the atmosphere, ocean, biosphere, cryosphere, and solid earth as an integrated system. We use powerful methodologies such as satellite remote sensing, earth system modeling, and high performance computing which are now profoundly changing research in earth system sciences. We place a strong emphasis on the societal impact of the research in earth system sciences. Specifically, we are working to answer a wide variety of earth science questions below.

Center for Integrated Earth System Science
The Center for Integrated Earth System Science (CIESS) is a cooperative effort between the Jackson School of Geosciences and the Cockrell School of Engineering. The center fosters collaborative study of Earth as a coupled system with focus on land, atmosphere, water, environment, and society. The center integrates the university’s strengths in earth system modeling, observing and monitoring, computational science and engineering, supercomputing, air resources engineering, hydrology and water resources, sedimentology and depositional processes, energy/policy, outreach/communications, and other fields.

Noah-MP User's Site
Noah-MP was developed in order to facilitate climate predictions with physically based ensembles. Multi-physics options allows for isolation and analysis of specific parameter schemes ultimately allowing 4,584 combinations to be assessed. In addition, to better predict climate, Noah MP is capable of coupling NCEP Global Forecasting System (GFS) and Climate Forecasting System (CFS) and in the near future, coupling will improve weather predictions with the Weather Research and Forecasting (WRF) modeling system. Some flaws in Noah-LSM have also been modified to better represent several parameters including: surface layer radiation balances, snow depth, soil moisture and heat fluxes, leaf area-rainfall interaction, vegetation and canopy temperature distinction, soil column and drainage of soil, and runoff.