Lecture

River Hydraulics and Modeling: Semi-Distributed Approach

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In course

CIVIL-410: Fluvial hydraulics and river engineering

Le cours donne aux étudiants des solides connaissances théoriques en hydraulique fluviale, et enseigne les bases de l'ingénierie fluviale dans le but de concilier la protection contre les crues et la protection de l'environnement. Le cours est illustré par ...

Description

This lecture covers the concepts of river hydraulics, waterway development, and modeling using the semi-distributed approach. Topics include the SOCONT model, hydraulic modeling, calibration of hydrological models, and the integration of snow data. The presentation emphasizes the division of basins into altitude bands, incorporation of hydraulic structures, and the calibration process. The instructor showcases the use of RS MINERVE software for modeling and forecasting in hydrology. Real-time data assimilation, operational monitoring, and risk management procedures are also discussed, highlighting the importance of accurate forecasting for flood protection and water resource management.

Instructors (3)

Giovanni De Cesare

Expertise Numerical simulation and physical modeling of hydraulic works and schemes; reservoir sedimentation and turbidity currents; reservoir sediment management; Ultrasonic Doppler flow measurement; river training work and restoration; soil bioengineering and nature based solutions; fluvial eco-morphology; rapid transients in pressurized waterways; technology transfer, commissioned studies and expert reports in applied hydraulics, hydraulic constructions and infrastructures; organization of continuous edu

Stéphanie Joëlle André

Azin Amini

Education: MSc.: Structural Engineering, University of Tehran, Iran, 2002 Master Thesis: "Three dimensional analysis of crack propagation in Latiyan butress dam using smeard crack model" BSc.: Civil Engineering, University of Tehran, Iran, 2000

Official source

Related concepts (32)

Risk management

Risk management is the identification, evaluation, and prioritization of risks (defined in ISO 31000 as the effect of uncertainty on objectives) followed by coordinated and economical application of resources to minimize, monitor, and control the probability or impact of unfortunate events or to maximize the realization of opportunities.

Database model

A database model is a type of data model that determines the logical structure of a database. It fundamentally determines in which manner data can be stored, organized and manipulated. The most popular example of a database model is the relational model, which uses a table-based format. Common logical data models for databases include: Hierarchical database model This is the oldest form of database model. It was developed by IBM for IMS (information Management System), and is a set of organized data in tree structure.

Relational database

A relational database is a (most commonly digital) database based on the relational model of data, as proposed by E. F. Codd in 1970. A system used to maintain relational databases is a relational database management system (RDBMS). Many relational database systems are equipped with the option of using SQL (Structured Query Language) for querying and updating the database. The term "relational database" was first defined by E. F. Codd at IBM in 1970. Codd introduced the term in his research paper "A Relational Model of Data for Large Shared Data Banks".

Category of modules

In algebra, given a ring R, the category of left modules over R is the whose are all left modules over R and whose morphisms are all module homomorphisms between left R-modules. For example, when R is the ring of integers Z, it is the same thing as the . The category of right modules is defined in a similar way. One can also define the category of bimodules over a ring R but that category is equivalent to the category of left (or right) modules over the enveloping algebra of R (or over the opposite of that).

Database design

Database design is the organization of data according to a database model. The designer determines what data must be stored and how the data elements interrelate. With this information, they can begin to fit the data to the database model. A database management system manages the data accordingly. Database design involves classifying data and identifying interrelationships. This theoretical representation of the data is called an ontology. The ontology is the theory behind the database's design.

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