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.

Preferential flow (PF) is a subsurface bypass flow that rapidly transports water, impacting aquifer recharge, soil health, and contaminant spreads. However, there is currently no effective way to predict its occurrence and magnitude. This project addresses the fundamental question of where and when PF occurs by leveraging high-frequency and multi-depth soil moisture data from monitoring networks, that have become increasingly available globally in recent years. (c) Illustration: Matthitas Sprenger

(Under construction)

Our team suggests hydrologic signatures, metrics representing watershed dynamics, as a new approach to estimating dominant processes. Using large-sample streamflow datasets (CAMELS) from the U.S., U.K., Brazil, and Australia, we investigate the links between hydrologic signatures and watershed processes.

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 knowledge sharing in hydrology.

Our team has conducted research on rainfall-runoff processes in humid tropics. Despite the presence of thick clayey soil layers, typically known for being impermeable, our team has found that groundwater tables respond quickly with large magnitudes in Indonesia, even in hillslopes with such soil characteristics. Through fieldwork and modeling, we have identified soil aggregation as the possible mechanism that allows for large infiltration flux in the soil layer.

These findings shed light on the behavior of rainfall infiltration in humid tropical forests, where previous studies were lacking. They will serve as a useful foundation for modeling hydrological processes in this area.

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 the 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.

Debris from rivers is a major contaminant in the San Diego coastal areas. We conduct field and lab works to model the “trash-balance” model in the San Diego River watershed – to quantify and identify the sources and the destinations of debris. I supervised three undergraduate students and led fieldwork 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. Our group aims to assess the effectiveness and uncertainties of the PIV technique in small rivers (the river width around less than 10 meters).

I supervised two undergraduate students in setting up field sites, implementing the fieldwork, and analyzing the data with PIV.