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Oral

394661 - Topo-statistical analyses of ponding area versus ponding storage of depression-dominated regions for macro-scale hydrologic modeling

Tuesday, June 5
10:30 AM - 12:00 PM
Location: Greenway IJ
Co-Authors: Xuefeng Chu, North Dakota State University – North Dakota State University

Depression-dominated regions have a unique undulating topography which contains depressions, potholes, and wetlands. These topographic features are periodically ponded and have different functions such as flood mitigation, nutrient and sediment retention, and habitat provision. Accounting for such detailed topographic features alters the hydrologic modeling results. However, the structure of many macro-scale hydrologic models requires adequately lumped or simplistic approaches rather than detailed, process-based approaches. This study is aimed to identify a relationship between ponding area and ponding storage of depression-dominated regions by conducting a set of topo-statistical analyses. The Red River of the North Basin was chosen in this study to represent a depression-dominated watershed. To extract topographic characteristics of the selected study area and establish topographic indices, the depression-dominated delineation (D-cubed) algorithm was utilized. Based on the topographic analyses, a regression model was developed and the utility of the model was tested by the analysis of variance (F test) and other statistics. Delineation results highlighted the presence of a hierarchical relationship among depressions which led to proposing a regression model between ponding area and ponding storage. Testing global usefulness of the regression model indicated that it was statistically helpful for prediction of ponding area. The results also suggest that variations in ponding area over the study area can be explained by ponding storage and other topographic indices. The topo-statistical analyses used to develop the regression model can be used in macro-scale hydrologic models to improve the modeling for depression-dominated regions.

Mohsen Tahmasebi Nasab

Doctoral Candidate/ Graduate Research and Teaching Assistant
NDSU

Mohsen Tahmasebi Nasab is a doctoral candidate and a graduate research and teaching assistant in the Department of Civil and Environmental Engineering at North Dakota State University (NDSU). He received his master’s degree in Hydraulics from the University of Tehran, Iran, in 2014 and started his Ph.D. studies in Civil Engineering at NDSU in 2015. His research project is concerned with topographic analyses and macro-scale modeling of hydrologic processes. Specifically, he is developing a macro-scale hydrologic model which possesses a unique modeling framework and accounts for the cold climate condition in North Dakota.

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394661 - Topo-statistical analyses of ponding area versus ponding storage of depression-dominated regions for macro-scale hydrologic modeling



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