bookFeb 2, 2026Closed access

Flood Forecasting Using Artificial Neural Networks

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Abstract

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…

Citation impact

44
total citations
FWCI
0.00
Percentile
98%
References
31
Citations per year

Authors

1

Topics & keywords

Keywords
  • Flood myth
  • Flood warning
  • Artificial neural network
  • Warning system
  • Computer science
  • Extrapolation
  • Process (computing)
  • Flood forecasting
UN Sustainable Development Goals
  • Climate action
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