Bio

Luwen is a Postdoctoral Fellow with the Stanford Institute for Human-Centered Artificial Intelligence, working with Dr. Kate Maher, Professor at Stanford University in the Department of Earth System Science. Her postdoctoral research focuses on developing tools for tracking the recovery and activity of the North American beaver from a computer version and evaluating beaver as a tool for fostering sustainable waterways. She received her Ph.D. in Earth and Environmental Science from Michigan State University, where she worked on nutrient transport modeling across the Great Lakes Basin and agricultural tile drainage mapping across the US Midwest region.

Institute Affiliations

Honors & Awards

  • Dissertation Completion Fellowship, Michigan State University (2022)
  • EES Alumni International Travel Award, EES, Michigan State University (2022)
  • The best student presentation in the Session, AGU Fall 2021 Meeting (2021)
  • KBS LTER Summer Research Fellowship, KBS LTER (2021)
  • Lucile Drake Pringle and Gordon H. Pringle Endowed Fellowship, EES, Michigan State University (2020)

Professional Education

  • Master of Science, South China Normal University (2017)
  • Doctor of Philosophy, Michigan State University (2023)
  • Bachelor of Management, Hunan Normal University (2014)
  • Doctor of Philosophy, Michigan State University, Earth and Environmental Sciences (2023)
  • Master of Science, South China Normal University, Human Geography (2017)
  • Bachelor of Management, Hunan Normal University, Land Resources Management (2014)

Stanford Advisors

Contact

  • Academic
    luwenwan@stanford.edu
    University - Scholar Department: Department of Earth System Science Position: Postdoctoral Scholar

Additional Info

Links

All Publications

  • Important Role of Overland Flows and Tile Field Pathways in Nutrient Transport. Environmental science & technology Wan, L., Kendall, A. D., Martin, S. L., Hamlin, Q. F., Hyndman, D. W. 2023

    Abstract

    Nitrogen and phosphorus pollution is of great concern to aquatic life and human well-being. While most of these nutrients are applied to the landscape, little is known about the complex interplay among nutrient applications, transport attenuation processes, and coastal loads. Here, we enhance and apply the Spatially Explicit Nutrient Source Estimate and Flux model (SENSEflux) to simulate the total annual nitrogen and phosphorus loads from the US Great Lakes Basin to the coastline, identify nutrient delivery hotspots, and estimate the relative contributions of different sources and pathways at a high resolution (120 m). In addition to in-stream uptake, the main novelty of this model is that SENSEflux explicitly describes nutrient attenuation through four distinct pathways that are seldom described jointly in other models: runoff from tile-drained agricultural fields, overland runoff, groundwater flow, and septic plumes within groundwater. Our analysis shows that agricultural sources are dominant for both total nitrogen (TN) (58%) and total phosphorus (TP) (46%) deliveries to the Great Lakes. In addition, this study reveals that the surface pathways (sum of overland flow and tile field drainage) dominate nutrient delivery, transporting 66% of the TN and 76% of the TP loads to the US Great Lakes coastline. Importantly, this study provides the first basin-wide estimates of both nonseptic groundwater (TN: 26%; TP: 5%) and septic-plume groundwater (TN: 4%; TP: 2%) deliveries of nutrients to the lakes. This work provides valuable information for environmental managers to target efforts to reduce nutrient loads to the Great Lakes, which could be transferred to other regions worldwide that are facing similar nutrient management challenges.

    View details for DOI 10.1021/acs.est.3c03741

    View details for PubMedID 37871005

  • The land use legacy effect: looking back to see a path forward to improve management ENVIRONMENTAL RESEARCH LETTERS Martin, S. L., Hamlin, Q. F., Kendall, A. D., Wan, L., Hyndman, D. W. 2021; 16 (3)

    View details for DOI 10.1088/1748-9326/abe14c

    View details for Web of Science ID 000619147800001

  • The effects of landscape pattern evolution on runoff and sediment based on SWAT model ENVIRONMENTAL EARTH SCIENCES Zhang, Z., Chen, S., Wan, L., Cao, J., Zhang, Q., Yang, C. 2021; 80 (1)

    View details for DOI 10.1007/s12665-020-09315-6

    View details for Web of Science ID 000606914700001

  • Impacts of international trade on global sustainable development NATURE SUSTAINABILITY Xu, Z., Li, Y., Chau, S. N., Dietz, T., Li, C., Wan, L., Zhang, J., Zhang, L., Li, Y., Chung, M., Liu, J. 2020; 3 (11): 964-971

    View details for DOI 10.1038/s41893-020-0572-z

    View details for Web of Science ID 000548446500002

  • Impacts of Climate Change and Human Activities on the Surface Runoff in the Wuhua River Basin SUSTAINABILITY Zhang, Z., Wan, L., Dong, C., Xie, Y., Yang, C., Yang, J., Li, Y. 2018; 10 (10)

    View details for DOI 10.3390/su10103405

    View details for Web of Science ID 000448559400047

  • Total Nitrogen and Total Phosphorus Pollution Reshaped the Relationship Between Water Supply and Demand in the Huaihe River Watershed, China CHINESE GEOGRAPHICAL SCIENCE Lu, Y., Liu, L., Qin, F., Wang, J., Liu, J., Li, Y., Wan, L. 2023

    View details for DOI 10.1007/s11769-023-1350-4

    View details for Web of Science ID 000946963800002

  • Exploring resilience interactions and its driving forces in the land-water-biodiversity nexus at the watershed scale WATER SUPPLY Li, Q., Zhang, Z., Li, C., Wan, L., Yang, Y. 2023; 23 (5): 2081-2104

    View details for DOI 10.2166/ws.2023.060

    View details for Web of Science ID 000941200000001

  • Ecosystem Services under Climate Change Impact Water Infrastructure in a Highly Forested Basin WATER Li, X., Zhang, L., J. O'Connor, P., Yan, J., Wang, B., Liu, D., Wang, P., Wang, Z., Wan, L., Li, Y. 2020; 12 (10)

    View details for DOI 10.3390/w12102825

    View details for Web of Science ID 000585415400001

  • Spatially explicit quantification of the interactions among ecosystem services LANDSCAPE ECOLOGY Li, Y., Zhang, L., Qiu, J., Yan, J., Wan, L., Wang, P., Hu, N., Cheng, W., Fu, B. 2017; 32 (6): 1181-1199

    View details for DOI 10.1007/s10980-017-0527-6

    View details for Web of Science ID 000401663900005

https://orcid.org/0000-0002-6414-4500