Flood Forecasting Using Artificial Neural Networks
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A01=P Varoonchotikul
artificial neural network rainfall runoff modelling
Author_P Varoonchotikul
catchment hydrology
Category=KNB
environmental modelling
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
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extreme event prediction
hydroinformatics
stormwater management
time series analysis
Product details
- ISBN 9781138475076
- Weight: 453g
- Dimensions: 156 x 234mm
- Publication Date: 02 Oct 2017
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Hardback
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This dissertation considers various questions with respect to the effects of salinity on nutrification: what are the main inhibiting factors causing the effects, do all salts have similar effects, what is the maximum acceptable salt level, are ammonia oxidisers or nitrite oxidizers most sensitive to salt stress, can nitrifiers adapt to long term salt stress and are some specific nitrifiers more resistant to salt stress than others? Research was carried out at laboratory scale and in full-scale plants and modelling was employed in both phases to provide a mathematical description for salt inhibition on nitrification and to facilitate the comparison. The result has led to an improved understanding of the effect of salinity on nitrification. The results can be used to improve the sustainability of the exisisting wastewater treatment plants operated under salt stress.
