Model diagnostic tools for soil moisture data (‘soil moisture signatures‘) has been increasingly developed. However, the soil moisture signatures have been tested under limited types of land-uses, which must be a strong control factor on the dynamics. Then, my question becomes, Are soil moisture signatures useful to describe the different dynamics under contrasting land-uses? We summarized 9 soil moisture signature behaviors for 12 different land-use types.
To assess the impact of deforestation on floods in Indonesia, we first need to understand the rainfall-runoff processes. Our team found an interesting phenomenon in the humid tropical hillslope: groundwater tables respond quickly with large magnitude, despite the hillslope being characterized by a thick clayey soil layer, which is typically highly impermeable. We investigated the mechanisms through fieldwork and modelings.
Our team suggest hydrologic signature, a metrics that represent watershed dynamics, as a new approach to estimate dominant processes. We investigate the links between hydrologic signatures and watershed process using large-scale streamflow dataset from the U.S., U.K., Brazil, and Australia.
National Water Model (NWM) is a hydrologic model that simulates the streamflow over the entire continental United States. The project aims to assess and improve the prediction of rapid snowmelt caused by Rain-on-Snow events in the Sierra Nevada and Cascade mountains by NWM.
I worked on reviewing literature, compiling hydro-climatic data, and analyzing the soil moisture data. Moreover, I created a real-time webmap to visualize the rain-on-snow risks to inform decision-makers.
Our team is investigating on how hydrologists perceive watershed systems by analyzing their conceptual illustrations in literature. Such illustrations are called ‘perceptual models,’ and are often used as blueprints of computational models. We explore the best guidelines to create perceptual models for the better knowedge sharing in hydrology.
Debris from rivers is a major contaminant in the San Diego coastal areas. The project team is conducting fieldwork, laboratory, and modeling works in the San Diego River watershed to quantify and identify the source of marine debris. I supervise three undergraduate students and leading a fieldwork module in the project.
Traditional measurements of river flow rates require contact with the flow. With the PIV (particle image velocimetry) technique, we can obtain the river surface’s 2-D velocity field without entering the river. PIV cross-correlates the particle in sequential images of the flowing river surface. Out group aims to assess the effectiveness and uncertainties of the PIV technique in small rivers (the river width around less than 10 metres).
I supervised two undergraduate students on the setting up field sites, implementing the fieldwork, and analyzing the data with PIV.
Our group worked on the identifying source of water in highly modified urban rivers in arid San Diego with isotope analysis EMMA. I assisted the data cleaning and literature review about uncertainty in EMMA procedure.