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CRC Press Flood Prediction with Crowdsourced Data - IHE Delft PhD Thesis

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Description

This IHE Delft PhD thesis explores innovative methods for improving flood prediction by integrating uncertain crowdsourced data into hydrologic and hydraulic models. The research addresses critical challenges in water resource management and environmental monitoring, focusing on how real-time data from public sources can enhance forecasting accuracy and inform better decision-making in flood risk management. The thesis combines theoretical frameworks with practical applications, offering insights into data assimilation techniques and model validation strategies. Essential reading for researchers, hydrologists, and environmental engineers working on water prediction systems, climate adaptation, and urban water management challenges.

Key Features

IHE Delft PhD thesis series publication focusing on flood prediction modelling and data integration methods.

Examines techniques for assimilating crowdsourced data into hydrologic and hydraulic models.

Addresses challenges in flood forecasting accuracy using uncertain real-time data sources.

Provides frameworks for water resource management and environmental monitoring applications.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
09 October 2017
Listed Since
08 December 2017

Barcode

No barcode data available

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