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231223s2005 xx ||||| 00| ||eng c |
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|a pubmed25n0536.xml
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|a (DE-627)NLM160712815
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|a (NLM)16477974
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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| 100 |
1 |
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|a Chung, S W
|e verfasserin
|4 aut
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|a Development of water quality models for supporting NH3-N control in a dam regulated river
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|c 2005
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|a Text
|b txt
|2 rdacontent
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|a ohne Hilfsmittel zu benutzen
|b n
|2 rdamedia
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| 338 |
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|a Band
|b nc
|2 rdacarrier
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| 500 |
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|a Date Completed 25.05.2006
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|a Date Revised 10.12.2019
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|a published: Print
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|a Citation Status MEDLINE
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|a A seasonal occurrence of high ammonia nitrogen (NH3-N) concentrations has hampered chemical treatment processes of a water plant in Geum river of Korea. Monthly flow allocation from upstream dam is important for downstream NH3-N control. In this study, water quality models based on multiple regression (MR) and artificial neural network (ANN) methods were developed to support dam operations through providing forecasted NH3-N concentrations. The models were calibrated with 7 years of monthly data, and verified with another 3 years of independent data. In the models, the NH3-N concentration for next time step is dependent on dam outflow, river water quality such as alkalinity, temperature, and NH3-N of previous time step. During the calibration phase, the ANN models compared to MR models showed a better agreement with observed data as indicated with small RMSE and high R2 values. However, in the verification phase, the performance of ANN models was decreased and showed a little difference to MR models. From the model comparisons, it is recommended for both ANN and MR models to include the autocorrelation of NH3-N concentrations up to 3-lag months to avoid overestimation during low flow season
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|a Journal Article
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| 650 |
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|a Research Support, Non-U.S. Gov't
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| 650 |
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7 |
|a Water Pollutants, Chemical
|2 NLM
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| 650 |
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7 |
|a Ammonia
|2 NLM
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| 650 |
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|a 7664-41-7
|2 NLM
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| 700 |
1 |
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|a Kim, J H
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Water science and technology : a journal of the International Association on Water Pollution Research
|d 1986
|g 52(2005), 12 vom: 01., Seite 83-90
|w (DE-627)NLM098149431
|x 0273-1223
|7 nnas
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| 773 |
1 |
8 |
|g volume:52
|g year:2005
|g number:12
|g day:01
|g pages:83-90
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| 912 |
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|a AR
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| 952 |
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|d 52
|j 2005
|e 12
|b 01
|h 83-90
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