Jun Yang is a Ph.D. student in the Department of Civil Engineering at North Dakota State University. He received a B.S. degree in Hydrology and Water Resources Engineering from Jilin University, China in 2006, and M.S. degree in Water Resources from China University of Geosciences (Beijing), China in 2009. His current research focuses on surface delineation, hydrologic connectivity analysis, and microtopography-controlled overland flow modeling.
Toward Understanding the Hydrologic Processes on Topographic Surfaces with Depressions - Development of a Physical-based Distributed Puddle-to-Puddle (P2P) Hydrologic Model
Advisor: Xuefeng Chu, Ph.D., Assistant Professor, Department of Civil Engineering, North Dakota State University
Matching Support:North Dakota State University
Degree Progress:Ph.D. in Civil Engineering expected graduation in fall 2013
The Prairie Pothole Region (PPR) is located in northern United States and southern Canada. The PPR contains roughly 25 million ponds, wetlands, and lakes. Due to their important roles in water retention, flood-peak reduction, groundwater recharge and discharge, and water-quality regulation, these depressions have received increasing attention. However, hydrologic functions and behaviors of these depressions are poorly understood, which has raised a series of regional hydrologic issues concerning water supply, water pollution, and agriculture and natural resources management. In addition, little work has been conducted to physically quantify the effects of those depressions on overland flow generation and the dynamic surface runoff processes. Depressions are rarely explicitly incorporated into hydrologic modeling due to the complexity of simulating these hydrologic processes.
The above discussions raise some interesting questions: how does the water stored in depressions interact with soil water, atmosphere water and change spatially and temporally? How do the depressions interact with others when they are fully filled? How do the depressions on a topographic surface affect runoff generation? Is it possible to develop a numerical model to simulate the related hydrologic processes and address these issues?
The proposed study aims to address the related issues by developing a physically-based, distributed hydrologic model, which can be used to simulate the spatially and temporally varied hydrologic processes of depressions and their dynamic interactions. The model is expected to improve the understanding of the regional hydrologic processes with focus on microtopography-controlled overland flow, evaluate and manage water resources, and serve as a prediction tool for water-related decisions.
I have completed extensive literature review on my research topic. A series of lab- and field-scale overland flow experiments have been conducted in the past several years in Dr. Chu's research group. The structure of the P2P hydrologic model has been set up with detailed procedures and flow charts.
Expected Outcomes and Significance:
A physically-based, distributed hydrologic model will be developed. The new modeling methodology will improve the understanding of how the water stored in depressions interacts with soil water, precipitation, and changes spatially and temporally and how the depressions on a topographic surface affect runoff generation.
The results from this study may benefit future research and help address a series of hydrologic issues, such as (1) effects of rough topographic surfaces on overland flow generation and infiltration processes, (2) effects of surface topography, rainfall, and infiltration on hydrologic connectivity analysis, and (3) effects of DEM resolutions on overland flow generation for rough topographic surfaces.
The proposed research may also help address the regional hydrologic issues related to: (1) natural resources management, (2) prairie pothole wetlands, (3) prediction of water levels in depressions and flood protection, (4) chemical and biological characteristics of water bodies, and (5) non-point source pollution.
Yang, Jun, Xuefeng Chu, Yaping Chi, and Leif Sande. 2010. Effects of Rough Surface Slopes on Surface Depression Storage. World Environmental and Water Resources Congress, Providence, RI, May, 16-20, 2010.
Yang, Jun and Xuefeng Chu. 2011. Surface Delineation and Hydrologic Connectivity Analysis. ND-SD 2011 Joint EPSCoR Conference, Fargo, ND, October 4, 2011.
Yang, Jun and Xuefeng Chu. 2011. Surface Microtopography and Hydrologic Connectivity Analysis. AGU 2012 Fall Meeting, San Francisco, December 5-9, 2011.
Yang, Jun, Xuefeng Chu, Yaping Chi, and Leif Sande. 2010. Effects of Rough Surface Slopes on Surface Depression Storage, p4427-4436. In: Proceedings of the 2010 ASCE World Environmental and Water Resources Congress.
Xuefeng Chu, Jun Yang, and Yaping Chi. 2011. Quantification of Soil Random Roughness and Surface Depression Storage: Methods, Applicability, and Limitations. Transactions of the ASABE. In review.
Advisor: Xuefeng Chu
Assistant Professor, Department of Civil
Engineering, North Dakota State University