CC BY
109. Москвитин А.А., Данные, информация, знания: методология, теория, технологии. - СПб.: Лань, 2019. - 232 с.
10. Тельнов Ю.Ф., Трембач В.М. Интеллектуальные информационные системы. - М.: МЭСИ, 2008. - 222 с.
УДК 556 :004.9
doi:10.18720/SPBPU/2/id21 -408
Васильев Константин Николаевич1,
старший консультант, магистр
ЭВОЛЮЦИЯ МЕТОДОВ ВИЗУАЛИЗАЦИИ ПРИ МОДЕЛИРОВАНИИ РИСКА НАВОДНЕНИЙ
1 Великобритания, Бристоль, «Джейкобс», kostyavasiliev@hotmail. com
Аннотация. Визуализация результатов моделирования риска наводнений очень важна для повышения понимания различными заинтересованными сторонами значимости оценки риска наводнений и помогает донести до них «плюсы» и «минусы» мер по снижению риска наводнений. В данной статье автор знакомит читателя с основными этапами эволюции методов визуализации при моделировании риска наводнений. В конце работы автор также делится мыслями о том, как в будущем изменяться подходы к визуализации подобных моделей.
Keywords, визуализация, управление рисками наводнений, гидравлическое моделирование.
Konstantin N. Vasilyev1, MSc, MCIWEM, C.WEM, CSci, CEnv, Senior Hydraulic Modeller
EVOLUTION OF VISUALISATION TECHNIQUES IN FLOOD RISK MODELLING
1 Bristol, UK, Jacobs, kostyavasiliev@hotmail.com
Abstract. Visualisation of the results of flood risk simulations is very important for increasing the appreciation of various stakeholders of the importance of understanding flood risk and helps convey to them the pros and cons of flood risk mitigation measures. In this paper, author takes you through the main milestones in evolution of visualisation techniques in flood risk modelling. In the end the author also provides thoughts on what the future holds for visualisation of such an output.
Keywords: visualisation, flood risk management, hydraulic modelling.
Introduction
Flood risk modelling is a field of science that is heavily reliant on visualization of its output. Representing flood risk is best done via visualisation. It is difficult to imagine nowadays that a community is told about the
fact that they are at risk of flooding just by giving them a water level or depth information in a number in meters, without giving an information about the extent of flooding on a map. However, this is what was happening when flood risk modelling was just appearing as a technique about 50 years ago. Presenting stakeholders with a flood extent map would however illustrate better how many and which houses will be flooded, thus giving some idea of what likely the damage will be.
In this paper the author will take you briefly through the history of evolution of visualisation techniques in flood risk modelling. This history is closely interlinked with the evolution of flood risk modelling software as well as the advances of computer science.
1. Flood risk on paper/design drawings
Prior to the 1970s and 1980s, when flood risk modelling was carried out in the form of mainly physical modelling (i. e. not numerical modelling), the results of such modelling were presented on paper in terms of calculated flows in cubic meters per second, levels in meters above datum, or depth — in meters or just by showcasing the whole experiment live. This was not quite sustainable. In fact, very rarely the results in meters would represent the actual flood risk (i. e. how many houses will be affected). Mostly the results of such modelling were used for hydraulic design (i. e. when constructing a new hydraulic structure or modifying an existing one). In the 1980s when the numerical engines such as MIKE by DHI in Denmark, HEC RAS in the United States or early versions of Flood Modeller in the UK started to be used, the nature of the presentation of the results had not changed. These were still primarily the results of hydraulic calculations presented in numbers or design drawings for various engineering structures. From the early 1990s such results could be represented using computer-aided design software.
2. Flood risk on cross section plots or long section plots in 1D
With the advances in one-dimensional (1D) hydraulic modelling software, namely development of user interfaces in the 1990s it became a lot easier to visualise the so called 1D hydraulic modelling results via cross section or long sections plots. These helped visualise flood risk to the areas near the banks of the rivers, however due to the 1D nature of the results (representing flows in river channels in one direction from the upstream end to the downstream end only, i. e. not representing two directional flows on flood plains) such results were not easy to be used for having a representation of flood extents on a map. Another factor here was that the Geographic Information System (GIS) software was not powerful enough yet.
Fig. 1. UK's Flood Modeller's cross section plot [1]
3. Flood risk on GIS layers (Ordnance Survey maps, satellite images)
In 2000s the following two major developments took place: commercial versions of 2D modelling software became available on the market thus allowing for more meaningful two-dimensional (2D) results (representing flows on the floodplain) and there was a significant improvement of the GIS software that allowed to visualise these 2D results on maps. Also it became possible to overlay these results on GIS layers such as ground data (LIDAR or SAR) at first and then Ordnance Survey maps (showing streets, park areas, some or all of the houses), satellite images (these had to be fed in to the GIS software as pre-obtained files). The latter occurred later in the 2000s. In 2010s it also became possible to automatically download the latest and most uptodate Ordnance Survey maps and satellite images as web services online.
4. Flood risk on a phone
From early 2010s it also became possible to use to view flood risk information incl. maps on one's phone, via specially developed apps starting from those that replicate the functionality of similar GIS computer programs but on a phone device or a tablet and ending with the software that allows one to get notifications that their property is at immediate flood risk. The latter would use the 1D and 2D flood risk modelling software in the background on the server side. These notifications would then be transmitted to the app on one's phone/table via Internet.
Fig. 2. An example of an urban flood extents map overlaid to a satellite image layer [2]
Carrier^ 10:27 AM
FLOODING IN ENGLAND & WALES
No Severe Flood Warnings >
5 Flood Warnings >
31 Flood Alerts >
FLOOD WARNINGS BY ...
Region V
Anglian No alerts >
* Midlands 1 warning >
* North East 4 warnings >
* CD £>erview Mytocaliofis © Near me
Fig. 3. UK's Flood Alert App Interface [3]
5. Flood risk in 3D
3D visualisation of flood risk was becoming possible from the end of 2000s. For example, first in the form of strategic game environment that allowed decision makers simulate the current epoch and state of flood risk defenses to look deeper into various flood intervention or climate change scenarios of mitigating flood risk in a given area.
In the 2010s with the development and availability of sensor techniques, it became possible to use a combined physio and numerical devices as sandboxes, that allow one to simulate changes in terrain via shapes of sand in a physical box and introduce "virtual" rainfall on it via a projector shedding a light on the sand and a software that reads hands movements giving it information of where the modelled rainfall is to occur, and then feeding all these data electronically to a flood risk modelling package.
From the end of the 2010s visualisation packages allowing one to view the flood risk information in augmented reality format started to be trialed with a good level of success.
Fig. 4. UK's JBA's Augmented Reality Sandbox in use [4]. Hand movement over the sand under the projector light sends a message to a computational numerical engine to add in rainfall in the specified location
Combining the above with the advances in computer processing speed (utilisation of graphical processing units for hydraulic modelling calculations) to be able to obtain the more representative results (such as from 2D modelling), it became possible to have very meaningful stakeholder engagement sessions. This improves flood risk interventions on economic, societal, and environmental levels.
6. What is the future?
The progress achieved to date and the current state of visualisation techniques provides enormous opportunities for various purposes (stakeholder engagement, checking and reviewing the results as these are produced, easier reporting, facilitation of discussions between clients and developers of flood risk models). With the ongoing great speed of computer science (improvements of processing speed, including graphical data processing and ongoing imporvementof fit for purpose software tools, there will be lots of opportunities for enhancemet of visualisation techniques. Such improvements already make it easier to collaborate between the stakeholders thus benefiting to a more streamlined and timely flood risk management interventions.
With the regards to the future outlook, the following items need to be noted:
1) future improvement has to bear in mind the accessibility of flood risk modelling in different geographies, and look into the ways of promotion and establishment of the use of flood risk modelling in the most needing locations of the world taking into account the local variations in how engineering work is done in the countries as well any different communication strategies used in other countries. Easier visualization methods should significantly help establish the necessary processes such as regulation of flood risk modelling (origination of the modelling work — checking of the flood risk models — external reviewing and verification of the results) and necessary economic model (sale of the software and expertise on mutually beneficial terms).
2) easier communication of flood risk information will make any flood risk interventions (incl. evacuation of population) or discussion of the options for intervention during public consultations more effective. There is a hope that the "walking through" option (similar to the Google's Street View option) through the river (perhaps with augmented reality), a river view option, will become a reality. As this will tremendously help flood risk engineers with hy-drodynamic model development with having the possibility to view the hydraulic cross section shapes, locations of properties and assets as well as hydraulic modelling structures and later on with the discussion and communication of the modelling software output.
3) flood risk modelling system should soon become fully an all-in-one package flood risk management system, with the architecture open enough for linking with newly developed components thus allowing for competition on the market of hydroinformatics tools for flood risk management.
Conclusion
In the paper the author has looked at the development of flood risk visualisation techniques in time and concluded that a lot of progress has taken place with these. The author also noted that there is more to take out of visualisation techniques and outlined what, in his opinion, needs to be taken into account when enhancing the visualisation techniques further in the not so far future.
References
1. Flood Modeller's help file. - URL: www.floodmodeller.com (date of access: 10.10.2021).
2. Flood Modeller website. Case Studies section. - URL: www.floodmodeller.com (date of access: 10.10.2021).
3. Web site AppAdvice LLC. - URL: https://appadvice.com/app/flood-alert/420666016 (date of access: 10.10.2021).
4. Woodhouse Joanne. Flood impacts brought to life through science and technology // www.jbaconsulting.com. 23rd October 2017. - URL: https://www.jbaconsulting.com/knowledge-hub/flood-impacts-science-technology (date of access: 10.10.2021).
УДК 004.9
:10.18720^РВРи/2М21 -409
Руссков Олег Владимирович1,
соискатель;
Сараджишвили Сергей Эрикович2,
доцент, канд. техн. наук, доцент
ЦИФРОВАЯ МОДЕЛЬ ДЛЯ ПРОГНОЗИРОВАНИЯ МАКСИМАЛЬНОГО ЭНЕРГОПОТРЕБЛЕНИЯ ЭНЕРГЕТИЧЕСКОГО РЕГИОНА
1 2
' Россия, Санкт-Петербург, Санкт-Петербургский политехнический
университет Петра Великого, 12 zenit-che@mail.ru, ssaradg@mail.ru
Аннотация. Многие процессы в промышленности описываются неравномерными временными рядами. Трудности прогнозирования неравномерных временных рядов создают необходимость разработки новых моделей прогнозирования. В статье обоснованы процессы цифровой трансформации отрасли. Показана важность создания и применения цифровых моделей прогнозирования. Рассмотрены преимущества и недостатки существующих моделей временных рядов. Предложен методический подход к прогнозированию неравномерных и изменчивых временных рядов. Рассмотрена цифровая модель прогнозирования неравномерного энергопотребления. Алгоритм работы модели показан в деталях. Описаны испытания и внедрение данной модели на промышленном предприятии. Анализируются преимущества предлагаемой модели по сравнению с существующими. Описаны экономические и экологические аспекты применения модели. Показано снижение углеродного следа в производимой продукции в результате использования предложенной модели в промышленности. Сделан вывод о применимости предложенного метода для прогнозирования неравномерных и изменчивых временных рядов.
Ключевые слова, неравномерный временной ряд, прогноз электроэнергии, цифровая модель, энергопотребление, энергосбережение.
