Flood Forecasting Using Artificial Neural Networks

Read full text
Authors: Pichaid Varoonchotikul
Cited by: 44
References: 31

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 of salinity on nitrification. The results can be used to improve the sustainability of the exisisting wastewater treatment plants operated under salt stress.

Fields of Study & Subjects

Hydrological Forecasting Using AI Hydrology and Watershed Management Studies Flood Risk Assessment and Management

Publication details

Publisher
CRC Press
Publication date
2 February 2026
Language
EN
Document type
Book