Investigating Hydrologic Connectivity of a Drained Prairie Pothole Region Wetland Complex using a Fully Integrated, Physically-Based Model

Wetlands ◽  
2016 ◽  
Vol 38 (2) ◽  
pp. 233-245 ◽  
Author(s):  
Antonio Arenas Amado ◽  
Marcela Politano ◽  
Keith Schilling ◽  
Larry Weber
2017 ◽  
Author(s):  
Qiusheng Wu ◽  
Charles R. Lane

Abstract. In traditional watershed delineation and topographic modeling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM) to enforce flow continuity of water across the topographic surface to the watershed outlets. In reality, however, many depressions in the DEM are actual wetland landscape features that are seldom fully filled with water. For instance, wetland depressions in the Prairie Pothole Region (PPR) are seasonally to permanently flooded wetlands characterized by nested hierarchical structures with dynamic filling-spilling-merging surface-water hydrological processes. The objectives of this study were to delineate hierarchical wetland catchments and model their hydrologic connectivity using high-resolution LiDAR data and aerial imagery. The graph theory-based contour tree method was used to delineate the hierarchical wetland catchments and characterize their geometric and topological properties. Potential hydrologic connectivity between wetlands and streams were simulated using the least-cost path algorithm. The resulting flow network delineated putative temporary or seasonal flow paths connecting wetland depressions to each other or to the river network at scales finer than available through the National Hydrography Dataset. The results demonstrated that our proposed framework is promising for improving overland flow simulation and hydrologic connectivity analysis.


2017 ◽  
Vol 21 (3) ◽  
pp. 1791-1808 ◽  
Author(s):  
Ali A. Ameli ◽  
Irena F. Creed

Abstract. Hydrologic connectivity among wetlands is poorly characterized and understood. Our inability to quantify this connectivity compromises our understanding of the potential impacts of wetland loss on watershed structure, function and water supplies. We develop a computationally efficient, physically based subsurface–surface hydrologic model to characterize both the subsurface and surface hydrologic connectivity of geographically isolated wetlands and explore the time and length variations in these connections to a river within the Prairie Pothole Region of North America. Despite a high density of geographically isolated wetlands (i.e., wetlands without surface inlets or outlets), modeled connections show that these wetlands are not hydrologically isolated. Subsurface connectivity differs significantly from surface connectivity in terms of timing and length of connections. Slow subsurface connections between wetlands and the downstream river originate from wetlands throughout the watershed, whereas fast surface connections were limited to large events and originate from wetlands located near the river. This modeling approach provides first ever insight on the nature of geographically isolated wetland subsurface and surface hydrologic connections to rivers, and provides valuable information to support watershed-scale decision making for water resource management.


2016 ◽  
Author(s):  
Ali A. Ameli ◽  
Irena F. Creed

Abstract. Hydrologic connectivity of wetlands is poorly characterized and understood. Our inability to quantify this connectivity compromises our understanding of the potential impacts of wetland loss on watershed structure, function and water supplies. We develop a computationally efficient physically-based subsurface-surface hydrological model to characterize both the subsurface and surface hydrologic connectivity of "geographically isolated" wetlands and explore the time and length variations in these connections to a river within the Prairie Pothole Region of North America. Despite a high density of geographically isolated wetlands (i.e., wetlands without surface outlets), modeled connections show that these wetlands are not hydrologically isolated. Hydrologic subsurface connectivity differs significantly from surface connectivity in terms of timing and length of connections. Slow subsurface connections between wetlands and the downstream river originate from wetlands throughout the watershed, whereas fast surface connections were limited to large events and originate from wetlands located near the river. This modeling approach provides first ever insight on the nature of geographically isolated wetland subsurface and surface hydrological connections to rivers, and provides valuable information to support watershed-scale decision making for water resource management.


2019 ◽  
Vol 19 (11) ◽  
pp. 2477-2495
Author(s):  
Ronda Strauch ◽  
Erkan Istanbulluoglu ◽  
Jon Riedel

Abstract. We developed a new approach for mapping landslide hazards by combining probabilities of landslide impacts derived from a data-driven statistical approach and a physically based model of shallow landsliding. Our statistical approach integrates the influence of seven site attributes (SAs) on observed landslides using a frequency ratio (FR) method. Influential attributes and resulting susceptibility maps depend on the observations of landslides considered: all types of landslides, debris avalanches only, or source areas of debris avalanches. These observational datasets reflect the detection of different landslide processes or components, which relate to different landslide-inducing factors. For each landslide dataset, a stability index (SI) is calculated as a multiplicative result of the frequency ratios for all attributes and is mapped across our study domain in the North Cascades National Park Complex (NOCA), Washington, USA. A continuous function is developed to relate local SI values to landslide probability based on a ratio of landslide and non-landslide grid cells. The empirical model probability derived from the debris avalanche source area dataset is combined probabilistically with a previously developed physically based probabilistic model. A two-dimensional binning method employs empirical and physically based probabilities as indices and calculates a joint probability of landsliding at the intersections of probability bins. A ratio of the joint probability and the physically based model bin probability is used as a weight to adjust the original physically based probability at each grid cell given empirical evidence. The resulting integrated probability of landslide initiation hazard includes mechanisms not captured by the infinite-slope stability model alone. Improvements in distinguishing potentially unstable areas with the proposed integrated model are statistically quantified. We provide multiple landslide hazard maps that land managers can use for planning and decision-making, as well as for educating the public about hazards from landslides in this remote high-relief terrain.


Author(s):  
Abderrazzak El Boukili

Purpose – The purpose of this paper is to provide a new three dimension physically based model to calculate the initial stress in silicon germanium (SiGe) film due to thermal mismatch after deposition. We should note that there are many other sources of initial stress in SiGe films or in the substrate. Here, the author is focussing only on how to model the initial stress arising from thermal mismatch in SiGe film. The author uses this initial stress to calculate numerically the resulting extrinsic stress distribution in a nanoscale PMOS transistor. This extrinsic stress is used by industrials and manufacturers as Intel or IBM to boost the performances of the nanoscale PMOS and NMOS transistors. It is now admitted that compressive stress enhances the mobility of holes and tensile stress enhances the mobility of electrons in the channel. Design/methodology/approach – During thermal processing, thin film materials like polysilicon, silicon nitride, silicon dioxide, or SiGe expand or contract at different rates compared to the silicon substrate according to their thermal expansion coefficients. The author defines the thermal expansion coefficient as the rate of change of strain with respect to temperature. Findings – Several numerical experiments have been used for different temperatures ranging from 30 to 1,000°C. These experiments did show that the temperature affects strongly the extrinsic stress in the channel of a 45 nm PMOS transistor. On the other hand, the author has compared the extrinsic stress due to lattice mismatch with the extrinsic stress due to thermal mismatch. The author found that these two types of stress have the same order (see the numerical results on Figures 4 and 12). And, these are great findings for semiconductor industry. Practical implications – Front-end process induced extrinsic stress is used by manufacturers of nanoscale transistors as the new scaling vector for the 90 nm node technology and below. The extrinsic stress has the advantage of improving the performances of PMOSFETs and NMOSFETs transistors by enhancing mobility. This mobility enhancement fundamentally results from alteration of electronic band structure of silicon due to extrinsic stress. Then, the results are of great importance to manufacturers and industrials. The evidence is that these results show that the extrinsic stress in the channel depends also on the thermal mismatch between materials and not only on the material mismatch. Originality/value – The model the author is proposing to calculate the initial stress due to thermal mismatch is novel and original. The author validated the values of the initial stress with those obtained by experiments in Al-Bayati et al. (2005). Using the uniaxial stress generation technique of Intel (see Figure 2). Al-Bayati et al. (2005) found experimentally that for 17 percent germanium concentration, a compressive initial stress of 1.4 GPa is generated inside the SiGe layer.


1999 ◽  
Vol 15 (2) ◽  
pp. 217-221 ◽  
Author(s):  
Alessandro Sarti ◽  
Roberto Gori ◽  
Claudio Lamberti

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