Research Overview

Our research primarily focuses on improving understanding and prediction of water resources and their sustainability through coupled numerical and data-driven models, improved model parameterization and uncertainty quantifications, integrated hydro-climatology and biogeochemical modeling, and statistical analysis of extreme hydro-climatology events including heavy storms, floods, and droughts. Specifically, we are actively working on the following three main research areas:

1) Reduction of uncertainties through integration of model and data: We believe that the continued progress in our understanding of natural processes, such as hydrologic cycle and its interaction with ecology and human activities, relies on making the best possible use of advanced modeling techniques to represent and solve the complex processes, as well as increasingly available data products and advances in data-mining and statistical algorithms. To this end, we are developing:

• complementary modeling frameworks to couple hydrological models and data-driven models

• inverse modeling techniques to account for the different sources of uncertainties during model calibration

• model averaging techniques that allow adjusting the models’ weights depending on the dominant spatial and temporal processes

• uncertainty quantification and propagation approaches for integrated hydrologic and earth system models

 

• model diagnosis metrics for comprehensive evaluations of hydrologic models performance

2) Characterization and management of extreme hydroclimatic events: The increasing trend in magnitude and frequency of extreme hydroclimatic events prompt various research needs to help prepare society and ecology for such events. Our research group has been actively developing and applying statistical and numerical approaches to characterize and understand the underlying physical processes associated with heavy storms, floods and droughts. The specific research includes developing and applying:

• multivariate regional frequency analysis methodologies to characterize heavy storms and droughts

• flood frequency analysis taking into consideration effects of the different flood causing mechanisms (such as soil moisture, heavy rainfall, snowmelt, rain on snow)

• stormwater drainage and flood risk analysis under non-stationarity climate and hydrology

3) Characterization of the dynamic interactions among water, energy production, land use, and climate change: The increasing demand for water, energy, and land resources and their vulnerability to climate changes make integrated assessment and management of these resources critical for their sustainability and economical use. Our research group has been actively involved in developing integrated numerical models and experimental analyses to characterize the interactions and feedbacks among energy, water, land, and climate at various temporal and spatial scales. Particularly, we have been conducting research using:

• integrated watershed, climate, and economic modeling to study the potential impact of large-scale biofuel production and climate changes on regional water quality and availability.

• Impact of severe drought on electric power generation