J. Choi | Geology Reports

USGS2009

A prototype feature system for feature retrieval using relationships

Using a feature data model, geographic phenomena can be represented effectively by integrating space, theme, and time. This paper extends and implements a feature data model that supports query and visualization of geographic features using their non-spatial and temporal relationships. A prototype feature-oriented geographic information system (FOGIS) is then developed and storage of features named Feature Database is designed. Buildings from the U.S. Marine Corps Base, Camp Lejeune, North Carolina and subways in Chicago, Illinois are used to test the developed system. The results of the applications show the strength of the feature data model and the developed system 'FOGIS' when they utilize non-spatial and temporal relationships in order to retrieve and visualize individual features.

Cartography and Geographic Information Science↗

USGS2007

Innovations in individual feature history management - The significance of feature-based temporal model

A feature relies on three dimensions (space, theme, and time) for its representation. Even though spatiotemporal models have been proposed, they have principally focused on the spatial changes of a feature. In this paper, a feature-based temporal model is proposed to represent the changes of both space and theme independently. The proposed model modifies the ISO's temporal schema and adds new explicit temporal relationship structure that stores temporal topological relationship with the ISO's temporal primitives of a feature in order to keep track feature history. The explicit temporal relationship can enhance query performance on feature history by removing topological comparison during query process. Further, a prototype system has been developed to test a proposed feature-based temporal model by querying land parcel history in Athens, Georgia. The result of temporal query on individual feature history shows the efficiency of the explicit temporal relationship structure. ?? Springer Science+Business Media, LLC 2007.

GeoInformatica↗

USGS1998

Modeling CO2 degassing and pH in a stream-aquifer system

Pinal Creek, Arizona receives an inflow of ground water with high dissolved inorganic carbon (57-75 mg/l) and low pH (5.8-6.3). There is an observed increase of in-stream pH from approximately 6.0-7.8 over the 3 km downstream of the point of groundwater inflow. We hypothesized that CO2 gas-exchange was the most important factor causing the pH increase in this stream-aquifer system. An existing transport model, for coupled ground water-surface water systems (OTIS), was modified to include carbonate equilibria and CO2 degassing, used to simulate alkalinity, total dissolved inorganic carbon (C(T)), and pH in Pinal Creek. Because of the non-linear relation between pH and C(T), the modified transport model used the numerical iteration method to solve the non-linearity. The transport model parameters were determined by the injection of two tracers, bromide and propane. The resulting simulations of alkalinity, C(T) and pH reproduced, without fitting, the overall trends in downstream concentrations. A multi-parametric sensitivity analysis (MPSA) was used to identify the relative sensitivities of the predictions to six of the physical and chemical parameters used in the transport model. MPSA results implied that C(T) and pH in stream water were controlled by the mixing of ground water with stream water and CO2 degassing. The relative importance of these two processes varied spatially depending on the hydrologic conditions, such as stream flow velocity and whether a reach gained or lost stream water caused by the interaction with the ground water. The coupled transport model with CO2 degassing and generalized sensitivity analysis presented in this study can be applied to evaluate carbon transport and pH in other coupled stream-ground water systems.An existing transport model for coupled groundwater-surface water systems was modified to include carbonate equilibria and CO2 degassing. The modified model was used to simulate alkalinity, total dissolved inorganic carbon (CT) and pH in Pinal Creek. The model used the numerical iteration method to solve the nonlinear relation between pH and CT. A multi-parametric sensitivity analysis (MPSA) was used to identify the relative sensitivities of the predictions to six of the physical and chemical parameters used in the transport model. MPSA results implied that CT and pH in the stream water were controlled by the mixing of groundwater with stream water and CO2 degassing.

Journal of Hydrology↗