Research Seminars

Blue-green solutions for sustainable landscape planning

International Scientific Seminar of Smart Urban Nature research center

The Research center «Smart technologies for sustainable development of the urban environment in the global change» Agrarian and Technological Institute RUDN University organizes an international scientific seminar «Blue-green solutions for sustainable landscape planning», which will be held on April 19, 2023. The event will take place online on the Microsoft Teams platform.

During the workshop, experts and participants will discuss modern approaches to the analysis and modeling of the water balance in urban green infrastructure facilities, in particular the modeling of water and solute transport in layered soil structures. Particular attention will be paid to water and green solutions in arid zones (on the example of Oman and Australia), for which they are especially relevant against the background of water scarcity.

Event program:

17.30 – 18.00

Urban green-infrastructure: what do architects need?

by Ilya Zalivukhin, YUZA group, Russia

18.00 – 18.30

Urban Parks in Arid Climates: Commingling of Ecohydrology and Analytical Models Based on the Theory of Holomorphic Functions

by Prof Anvar Kasimov, Sultan Qaboos University, Oman

18.30 – 19.00

Advances in development and maintenance of urban green infrastructures in arid climate

by Prof. Marya Ignatieva, The University of Western Australia, Australia

 

Organizer: Department of Landscape Design and Sustainable Ecosystems, Smart Urban Nature research center, Agrarian and Technological Institute of RUDN University

Partner 

Area: Science, Education, International cooperation

Subarea: Ecology and nature management

Format: Seminar

Type: International

Date: April 19, 2023

Location: Microsoft Teams

Contact person: Kozyreva Marina Mikhailovna, 1142220016@rudn.ru

The links to the Seminar: https://teams.microsoft.com/l/meetup-join/19%3ameeting_OTM1YzRlMGUtNTZhMS00NTFmLWJjYTAtMTg2ZTM1MGE0NGM2%40thread.v2/0?context=%7b%22Tid%22%3a%222ae95c20-c675-4c48-88d3-f276b762bf52%22%2c%22Oid%22%3a%229157e80e-958f-4a30-be82-a3bcadb0bb71%22%7d

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