Spatially distributed hydrological modeling of storm events using a geographic information system (GIS) with insight into turbidity.
Item
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Title
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Spatially distributed hydrological modeling of storm events using a geographic information system (GIS) with insight into turbidity.
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Identifier
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AAI9917653
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identifier
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9917653
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Creator
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Gorokhovich, Yuri.
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Contributor
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Adviser: Victor Goldsmith
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Date
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1999
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Language
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English
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Publisher
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City University of New York.
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Subject
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Environmental Sciences | Hydrology
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Abstract
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Distributed hydrological modeling of turbidity in streams is important because turbidity is an optical indicator of water clarity and indirectly linked with different kinds of pollutants in streams. One of the fortuitous properties of turbidity monitoring is that measurements can be recorded continuously.;As an optical measured parameter turbidity can be linked with suspended sediment concentration. This relationship is based on statistical regression. Regression allows one to predict suspended sediment concentration continuously during storms. It also allows one to apply modeling techniques available for suspended sediment concentration, for turbidity. Because these techniques are based on flow rate, such an approach requires development of a spatially distributed model of flow.;Spatially distributed modeling of flow during storm events is an important basis for any environmental modeling. During the initial phase of a rain storm surface runoff is the main contributor of flow. To provide the spatial components for distributed hydrological modeling a Geographic Information System (GIS) was used to map and visualize contributing areas around a stream channel. Stream segments were defined using the hydrologic response unit (HRU) concept. Lateral flows used in the kinematic routing equation were derived from GIS output for each segment of the stream and at each time interval of the rain storm. This approach is new in hydrological modeling and can be used to enhance many existing simulations.;After flow values were calculated, suspended sediment concentration was estimated through the Yang's unit stream power equation (Yang, 1972) and afterwards was used to estimate turbidity values.;Model estimates of turbidity showed high correlation with measured discharge values and low correlation with turbidity. In most cases the accuracy of modeling, expressed as root mean square error, did not exceed 100%, but ranged from a minimum value of 25% to a maximum value of 534% for the verification dataset.;Based upon "in situ" measurements of discharge, a good comparisons with model computations of discharge, it is concluded that the methodology presented can be used in its current form for spatially distributed modeling of flow during storm events, and therefore provides a solid basis for turbidity or sediment transport modeling.
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Type
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dissertation
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Source
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PQT Legacy CUNY.xlsx
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degree
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Ph.D.
