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394434 - Depressional Threshold Control Proxy to Simulate Dynamic Hydrologic Connectivity in Depression-dominated Areas

Monday, June 4
2:00 PM - 3:30 PM
Location: Greenway IJ
Co-Authors: Xuefeng Chu, Fargo, ND – North Dakota State University

In traditional delineation methods, all depressions are fully filled, creating a depressionless surface with artificial drainage networks. Consequently, full hydrologic connectivity and well-connected drainage networks are assumed in hydrologic modeling. Such a method may be adequate when modeling dendritic surfaces. However, depression-dominated areas are often controlled by dynamic filling-spilling-merging processes and threshold behaviors associated with surface depressions. In this study, dynamic hydrologic connectivity was investigated using the normalized connected area function (NACf) and relative surface connection function (RSCf). This further understanding of surface hydrologic processes relating to topography and connectivity inspired the creation of the depressional threshold control proxy, which was a feature developed for improving traditional hydrologic models, such as HEC-HMS. Topographical details of depression-dominated areas were obtained and processed using a new D-cubed delineation method. A storage-discharge function, unique to each surface, was created via the modified Puls routing method and implemented into the traditional model structure. Three statistical measures, Nash Sutcliffe efficiency (NSE), percent bias (PBIAS), and ratio of the root mean square error to the standard deviation of measured data (RSR) were used to assess the performance of the modified modeling approach. The results highlighted the significant improvement in hydrologic modeling and demonstrated the importance of considering dynamic hydrologic connectivity for depression-dominated areas.

Kendall M. Grimm

Doctoral Candidate
North Dakota State University

Kendall is a Doctoral candidate at North Dakota State University in the Civil and Environmental Engineering Department. Her research focuses on hydrologic modeling and topographic analysis of depression-dominated regions like the Prairie Pothole Region (PPR). Kendall is looking to improve existing models so that dynamic hydrologic connectivity and puddle-to-puddle (P2P) processes can be represented and investigated when modeling depression-dominated landscapes.

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