Improving Flood Prediction Assimilating Uncertain Crowdsourced Data into Hydrologic and Hydraulic Models...

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Maurizio Mazzoleni

Improving Flood Prediction Assimilating Uncertain Crowdsourced Data into Hydrologic and Hydraulic Models

Maurizio Mazzoleni

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English

CRC Press
09 October 2017

Environmental economics; Flood control

Series: IHE Delft PhD Thesis Series

On a global scale, sewage represents the main point-source of water pollution and is also the predominant source of nitrogen contamination in urban regions. The present research is focused on the study of the main challenges that need to be addressed in order to achieve a successful inorganic nitrogen post-treatment of anaerobic effluents in the mainstream. The post-treatment is based on autotrophic nitrogen removal. The challenges are classified in terms of operational features and system configuration, namely: (i) the short-term effects of organic carbon source, the COD/N ratio and the temperature on the autotrophic nitrogen removal; the results from this study confirms that the Anammox activity is strongly influenced by temperature, in spite of the COD source and COD/N ratios applied. (ii) The long-term performance of the Anammox process under low nitrogen sludge loading rate (NSLR) and moderate to low temperatures; it demonstrates that NSLR affects nitrogen removal efficiency, granular size and biomass concentration of the bioreactor. (iii) The Anammox cultivation in a closed sponge-bed trickling filter (CSTF) and (iv) the autotrophic nitrogen removal over nitrite in a sponge-bed trickling filter (STF). Both types of Anammox sponge-bed trickling filters offer a plane technology with good nitrogen removal efficiency.

By: Maurizio Mazzoleni
Imprint: CRC Press
Country of Publication: United Kingdom
Dimensions: Height: 240mm, Width: 170mm,
Weight: 453g
ISBN: 9781138474420
ISBN 10: 1138474428
Series: IHE Delft PhD Thesis Series
Pages: 240
Publication Date: 09 October 2017
Audience: College/higher education , Primary
Format: Hardback
Publisher's Status: Active

Summary1 Introduction2 Case studies and models3 Data assimilation methods4 Assimilation of synchronous data in hydrological models5 Assimilation of asynchronous data in hydrological models6 Assimilation of synchronous data in hydraulic models7 Assimilation of synchronous data in a cascade of models8 Conclusions and recommendationsReferences

Maurizio Mazzoleni was born in Brescia in November 1986. Mr. Mazzoleni graduated from University of Brescia, in Brescia, Italy, in May 2011. During his university studies he continued to pursue his interest in the flood protection by moving to UNESCO-IHE with the support of a scholarship awarded by University of Brescia to carry out his Master Thesis. Afterwards, he cooperate for 1 year within the KULTURisk Project as research fellow of the University of Brescia. Currently, Mr. Mazzoleni is a PhD candidate at UNESCO-IHE Institute for Water Education under the Department of Integrated Water Systems and Governance, Delft, The Netherlands. His research interest include hydrologic and hydrodynamic modelling, in particular he dealt with issue related to flood forecasting, data assimilation, flood inundation mapping, flood risk and uncertainty analysis, flood defence systems design and reliability analysis, statistical hydrology.