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SPATIALLY DISTRIBUTED MODELING OF STREAM FLOW DURING STORM EVENTS 1
Author(s) -
Gorokhovich Yuri,
Khanbilvardi Reza,
Janus Lorraine,
Goldsmith Victor,
Stern David
Publication year - 2000
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/j.1752-1688.2000.tb04284.x
Subject(s) - storm , hydrology (agriculture) , surface runoff , watershed , environmental science , flow routing , routing (electronic design automation) , hydrograph , kinematic wave , distributed element model , hydrological modelling , flow (mathematics) , geology , computer science , geotechnical engineering , quantum mechanics , machine learning , biology , physics , climatology , ecology , computer network , oceanography , geometry , mathematics
The purpose of this paper is to present a new approach for the spatially distributed modeling of water flow during storm events. Distributed modeling of flow during storm events is an important basis for any environmental modeling, including turbidity or sediment transport. During the initial phase of a rainstorm, 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 were derived from GIS output for each segment of the stream and at each time interval of the rain storm and were routed using the kinematic routing equation. This approach is new in hydrological modeling and can be used to enhance many existing simulations. The model is also unique in the fine time scale (i.e., intervals are on the order of minutes). Model results showed good correlation with measured discharge values; however, further studies of contributing area behavior, its relationship with soil types and slope categories, and the influence of watershed size are needed to improve model performance. This model will be used in the future as the basis to model turbidity in streams.