[cosc-grad-students-list] DISSERTATION SEMINAR NOTICE - Lapone Techapinyawat

[Eulenfeld, Menda]

DISSERTATION SEMINAR NOTICE

GEOSPATIAL COMPUTER SCIENCE PROGRAM

COLLEGE OF ENGINEERING AND COMPUTER SCIENCE

TEXAS A&M UNIVERSITY-CORPUS CHRISTI


SUBJECT:                  Development of Integrated Hydrological and Geospatial Methods for Urban Stormwater Management

SPEAKER:                 Lapone Techapinyawat

ADVISOR:                 Dr. Hua Zhang

COMMITTEE:           Dr. Yuxia Huang, Dr. Wenlu Wang, Dr. Ruby Mehrubeoglu, Dr. Lon Seiger

DATE:                         Tuesday, October 14, 2025

TIME:                         11:00 AM

PLACE:                      University Center (UC) Building, Bayview Room 320

ZOOM LINK:      https://tamucc.zoom.us/j/91422561649?pwd=3j1U5qiqWxWCbTix8DgR5XPbleRv9m.1<https://nam12.safelinks.protection.outlook.com/?url=https%3A%2F%2Ftamucc.zoom.us%2Fj%2F91422561649%3Fpwd%3D3j1U5qiqWxWCbTix8DgR5XPbleRv9m.1&data=05%7C02%7Ccosc-grad-students-list%40listserv.tamucc.edu%7C196c2ad60957420b931608de05ef7555%7C34cbfaf167a64781a9ca514eb2550b66%7C0%7C0%7C638954723194043563%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=guNK4DSOEkUmohitkvOb85fH0umr40h%2B5e7fNbdMehA%3D&reserved=0>



ABSTRACT

Urbanization alters hydrologic processes by increasing impervious surface coverage and introducing engineered drainage infrastructure, fundamentally transforming how rainfall partitions into infiltration and runoff. Conventional urban hydrologic models rely heavily on lumped metrics such as the total impervious area and the effective impervious area. They quantify the extent of non-infiltrating surfaces but overlook the spatial arrangement of natural and built features, local patterns of microtopography, and the hydrologic connectivity across surface and subsurface domains. In particular, three important factors are often neglected or simplified: the control of surface depression storage, the dynamics of surface runoff pathways, and the linkage between hydrologic and hydraulic processes. Such knowledge gaps limit the analysis of the spatiotemporal characteristics of urban stormwater runoff, as well as the design and management of stormwater infrastructure systems. This dissertation presents an integrated hydrologic and geospatial modeling framework for systematically improving the characterization of urban watersheds and the simulation of stormwater runoff processes. This approach highlights the incorporation of advanced geospatial data and tools, machine learning, and distributed hydrologic-hydraulic simulations, comprising four key components: (1) the identification of urban surface depressions using high-resolution digital elevation models derived from small unmanned aircraft systems; (2) the development of a classification-correction method for improving the delineation and quantification of urban impervious surfaces; (3) the development of a deep learning model for efficiently estimating parcel-level surface imperviousness; and (4) the development of a new depression-oriented, fill-and-spill hydrologic model. The framework is computationally efficient and highlights spatially explicit inputs and physically based dynamics. It connects comprehensive watershed characterization to process-based stormwater modeling, providing an improved scientific basis for urban stormwater management.

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