Collective Ecology An Integrated Hydrological System for Arid Climates Mikaella Papadopoulou Nicolas Cabargas Andrew Haas Miguel Rus
Collective Ecology An Integrated Hydrological System for Arid Climates Mikaella Papadopoulou (Msc) Nicolas Cabargas (MArch) Andrew Haas (MArch) Miguel Rus (MArch) 2012 - 2013 EmTech: Emergent Technologies and Design / Architectural Association School of Architecture
4!Collective Ecologies
Architectural Association School of Architecture Graduate School Programmes Emergent Technologies and Design 2012-2013
Students:
Mikaella Papadopoulou (Msc) Nicolas Cabargas (MArch) Andrew Haas (MArch) Miguel Rus (MArch)
Title:
Collective Ecology, An Integrated Hydrological System for Arid Climates
Course:
Master of Science
Tutors: Advisors:
Michael Weinstock, George Jeronimidis Evan Greenberg, Mehran Gharleghi
Date:
20-09-2013
“I certify that this piece of work is entirely my/our own and that any quotation or paraphrase from the published or unpublished work of others is duly acknowledged.�
!Preface!5
Acknowledgements We owe deep gratitude to Mike and George. Through their continual encouragement and guidance, the development of this book was made possible. In addition, we would like to thank Evan, Mehran, and Wolf, as well as the members of Architectural Association for providing continuous inspiration throughout our studies. Lastly, we are profoundly grateful for our friends and loved ones, whose constant encouragement and support inspires us to continually strive to achieve great things.
8!Collective Ecologies
Table of Contents Acknowledgements Abstract Statistics
7 11 13
Introduction
15
Domain
29
Methods
41
Experiments
61
Design Proposal
87
Introduction Overview Metabolism Water Stress Qatar Introduction References Domain Overview Scalability of the City Wetlands Research Proposal Domain References Methods Overview City Samples Case Studies Computational Techniques Methods References Experiments Overview Wetlands Analysis of Streets and Public Spaces Subdivision and Integration Experiments References Design Proposal Overview Site Cells Public Spaces Network Development Test Patch Building Typologies Urban Wetland Integration Conclusions Seasonal Adaptive Behaviour
Appendix Algorithms Experiments
17 18 20 22 27 31 32 34 36 39 43 44 48 54 59
63 64 76 80 85
89 90 92 100 106 108 120 140 145 148
153
154 168
!Preface!9
Abstract COLLECTIVE ECOLOGY approaches the city as a series of associative processes developing form, organising relationships, and exchanging materials throughout an urban system. Focusing on hydrological flow, a systematic approach for the formation of novel architectural and infrastructural morphologies explores their collective relationships in the development of a new urban system. Within this context, we explore the potential to decrease hydrological flow in and out of the urban environment through localised water treatment processes, while also increasing the amount of total green space. The resulting urban model demonstrates the possibilities in which infrastructure can be integrated within the urban and architectural morphologies, serving as a component part within a larger collective system.
Statistics Population Statistics 1 Global population 2013: 7.2 Billion Developed countries: 1.25 billion (17.5%) Less developed countries: 5.04 billion (70%) Least developed countries: 898 million (12.5%) Global projected population 2050: 9.6 Billion Average Population Growth Rate (Percent Rate of Change per Year) Global: 1.2% Developed countries: 0.42% Less developed countries: 1.37% Least developed countries: 2.28% Urban Population Statistics (Percent of Total Population)2 Global urban population 2010: 50.6% (3.49 billion) Developed counties: 75% (937.5 million) Less developed countries: 44% (2.22 billion)
Least developed countries: 29% (260.42 million) Global projected urban population 2050: 70% (6.4 billion) Urban Growth Rate (Percent Rate of Change per Year) Global: 1.5% Developed: 1.9% Less developed: 2.3% Least developed: 4.0% Water Equivalences 1 k& = 1,000,000,000 & 1,000,000,000,000 litres = 264,000,000,000 U.S gallons 1 & = 1 ton
1.  World Population (2013) The Revision
2.  UN-Ha World Heal Organisatio Hidden Cit
Introduction Metabolism p.18 Water Stress p.20 Qatar p.22
Introduction Overview A fundamental shift from the current paradigm of cities to one guided through the associative logics inherent to biological systems provides the ability to utilise emergent, dynamic methods in the development of novel urban morphologies. Metabolic processes within organisms provide a conceptual and methodological framework to address the complex qualities of interaction, organisation, and material exchanges that characterise urban systems. Exponential acceleration of urban growth around the world brings with it unsustainable levels of increased material processing and flow, with water as the largest material flux within any urban system. Current urbanisation is often presumptuously confident that resources are secure and abundant. The dramatic growth seen in Doha, Qatar is the epitome of this heedlessness. Doha is one of the most water stressed nations, yet the largest consumer of water in the world. Addressing how to minimise the demands brought on by relentless urban growth is critical, not just for Doha, but for emerging urban centres around the world.
Metabolism The processing and flow of energy within every organism Photograph(1.1: Rain Forest Source: <www.daz3d. com>
Collective Metabolism Metabolism can also be seen in the allometric relationships of individuals within populations of a species and their surrounding environment.11 These higher levels of organisation begin to materialise through metabolic processes in the relationships between species, based on their density and distribution patterns, establishing a dynamic equilibrium within their ecosystem.12 The flow of energy and material is thus regulated by the collective metabolism of all the living forms within it, defining an ecosystem’s anatomical organisation,13 and over time modifying the fitness criteria for natural selection within it.14
Urban Metabolism Urban metabolism can be described as the flow and transformation of energy and material throughout an urban system into physical structures, biomass, and waste.15 It is the fundamental physical process that directs urban growth and organisation,16 in the forms of infrastructure, architectures and networks behaving in a similar branching fashion as biological metabolism.17 These network dynamics bring about economies of scale in cities, which require fewer infrastructures to operate as they increase in size, expanding only 85% as the population doubles, similar to the 75% scaling optimisation seen in biological systems.18
103 (kcal/h: log scale)
Biological Metabolism Biological metabolism can be described as the processing and flow of energy and material throughout an organism. It symbiotically develops with an organism’s morphology,3 emerging together through dynamic forces acting upon them4 in the conversion and movement of resources from the environment throughout the organism, and in the return of transformed materials back into the ecosystem.5 It functions through optimised, hierarchical branching networks6 that exhibit identical mathematical parameters in all species, at multiple scales,7 determining the rates at which energy is delivered, and setting the pace of physiological processes to regulate the size the organism.8 The rate of energy consumption per unit body mass declines at a scale of ¾ as the mass of an organism increases,9 establishing Kleibers Power Law, which adduces that the larger the organism, the less amount of energy in relation to body mass is required to sustain it. (Fig. 2.4) This symbiotic relationship of an organism’s metabolism with its morphology is the critical factor in developing their sublinear metabolic rate.10
Metabolic rate
nstock, M. Architecture Emergence ompson, D. On Growth and Form nstock, M. Architecture Emergence encourt L. 06) ‘Growth, on, Scaling, ce of Life in AS, Vol.104, No.17 nstock, M. Metabolism AD Vol. 81, Iss. 4 encourt L. 06) ‘Growth, on, Scaling, ce of Life in AS, Vol.104, No.17 t, G., et. al. ‘A General r the Origin tric Scaling in Biology’ ure, Vol. 413 nstock, M. Architecture Emergence G. (1997) ‘A odel for the Allometric ing Laws in Figure(1.1: Nature, Vol. 413 Graph, scalability of nstock, M any living organism. Metabolism ity’ AD, Vol. Source: Growth, 81, Iss. 4 innovation, scaling, nstock, M. Architecture and the pace of life in Emergence cities, Geoffrey West, et. al., 2007 nstock, M. Emergence he Forms of m’ AD, Vol. 80, Iss. 2 r, E., et. al. Energy and ow through Ecosystem 16. Ibid. nstock, M. Architecture Emergence ncourt L., ) ‘A Unified ry of Urban18!Collective Ecologies ure, Vol. 467
100 10-3 10-6 10-9 10-12 10-12 10-9
10-6
10-3
100
103
106
109
Mass(g, log scale) Metabolic Scalability in Organisms Kleibers Power Law Equation = Y=Y0Mb Y= Observable magnitude, Y0= Constant, M= Mass b = ~ 3/4 = scaling exponent
“
[Cities] are dynamic, spatial and material arrays of buildings that are constructed, reworked and rebuilt over time, decaying, collapsing and expanding in irregular episodes of growth and incorporation. As they grow and develop, their systems for the movement of food, material, water, people and manufactured artefacts must grow and extend with them. From this perspective, cities are not static arrays of material structures, but are regarded as analogous to living beings, as they consume energy, food, water and other materials, excrete wastes and maintain themselves down through the generations.” 28 Michael Weinstock
Urban Metabolic Capacities Urban metabolism can be measured spatially through the amount of land an urban system requires to meet its metabolic needs.19 Throughout most of history, urban systems developed and expanded to limits based on their capacity to extract energy and materials from their environment, and their ability to manage and distribute flows throughout their system.20 Similar to an organism reaching a stable size at maturity,21 urban systems developed and matured until they were close to their critical threshold of stability, imposing a self-regulating limit to population capacity. 22 Globalisation, particularly in the last century, has enabled
urban systems to no longer be self-reliant on their immediate environment to provide resources and absorb waste. 23 The removal of these critical, self-regulating, capacity limits have allowed for an escalation of urban population at unprecedented scales. Urban metabolisms, as a result, have developed independently from their morphologies as cities continue to mature and grow.24 This has led to increased energy and material flows in relation to the spatial patterns and forms of the city,25 and established a reliance on resources from outside their boundaries26 in order to meet urban demands at a super-linear metabolic rate. 27 With demographic pressures in cities increasing, these discrepancies of morphology and metabolic flows threaten the future sustainability of urban systems.
2%
50%
Energy Consumption / Body Mass Lifespan
60 years
% of Energy Consumption / Body Mass 2-3 years
28. Weins 2011, The M of the City
19. Decke al., (2000) E Material Flo the Urban E 20. Weins (2010) ‘Eme the Forms o AD, Vol. 80 21. ‘Bette et. al. (2010) Theory of U Living’ Nat Figure(1.2: 22. Weins Graph, energy (2010) ‘Eme consumption versus the Forms o body mass and lifespan AD, Vol. 80 of an elephant 23. Decke (2000) Ener Material Flo Figure(1.3: the Urban E Graph, energy consumption versus 24. Weins body mass and lifespan(2008) ‘Met and Morph of a mouse Vol. 78, Iss. 25. Weins (2011) ‘The of the City’ 81, Iss. 4 26. Decke (2000) Ener Material Flo the Urban E 27. Weins (2008) ‘Met and Morph Vol. 78, Iss. !Introduction!19
Water Stress Scarcity of the largest component in terms of sheer mass in the urban metabolism Photograph(1.2: Aral Sea, actual state. Source: Documentary “Aral, el mar perdido” / Aral, the lost sea. < http://www. palmyrasculpturecentre.com/?attachment_id=3053>
Excessive Demand In 2013, the world population reached 7.2 billion, with one fifth of people living in areas of water scarcity.29 The UN estimates growth of an additional 3 billion people by 2050, with a majority living in developing countries that already suffer water stress.30 Demographic, economic and social activities and process can all exert excessive pressures on already limited water resources directly and indirectly. The ever demanding requirements for water to meet these increasing needs worldwide threaten the continued sustainability and growth of fragile ecosystems, both natural and urban.
UN-Water Programme vocacy and unication 2 NW-DPAC) 0. World n Prospects 12 Revision, 2013 he United World Water ment Report 3, 2009 UN-Water Programme vocacy and unication 4 NW-DPAC) 20!Collective Ecologies
Demographic Drivers Pressures on freshwater resources brought on by shifting population dynamics (growth, gender and age distribution, migration) inevitably alter water demands and pollution levels. Transformations of the natural landscape associated with population dynamics can create additional pressures on local water networks and resources, and often lead to the necessity of more water-related services and infrastructures. Economic Drivers International economic growth and trade can both aggravate water stress in some areas and relieve it in others in the form of embedded water used in the production of consumer goods and agriculture.31 History has often demonstrated a link between how water has contributed to economic development and how, in turn, development has demanded an increased use of water resources. This urban growth often generates additional pressure on the local 33. The United environment and hydrological networks, leading to financial Nations World Water competitiveness among consumers be able to obtain it. DevelopmenttoReport 3, 2009
Social Drivers With increased affluence in Asia, Latin America and the Middle East, accelerating rates of water consumption will inevitably occur as new urban centres continue to develop and expand, influencing changes in lifestyles and consumption patterns. With 95% of urban population growth taking place in the developing world32, this rapid global rise in living standards threatens the sustainability of local water resources and environments that may be incapable handling dramatic influxes of demand.
“
Our requirements for water to meet our fundamental needs and our collective pursuit of higher living standards, coupled with the need for water to sustain our planet’s fragile ecosystems, make water unique among our planet’s natural resources.”33 UN World Water
Figure(1.4: Water Stress World map showing a projection for 2025. Source: The WBCSD Water and Sustainable Development Program, Facts and Trends, 2006,
2025 less than 10%
20% to 10%
40% to 20%
more than 40%
“
In terms of sheer mass, water is by far the largest component of urban metabolism.”34
34. Kenne et.el (2007) changing m of cities’ Jo Industrial E
Chris Kennedy
2,5% 0,5%
20%
Figure(1.5: Graph, water percentage in urban metabolism Figure(1.6: Graph, available fresh water in the world Source: The WBCSD Water and Sustainable Development Program, Facts and Trends, 2006,
97%
80%
Fresh Water Available
Water in Urban Metabolism Water
Fresh
Frozen
Seawater
!Introduction!21
Qatar The most water stressed nation and the highest water consumption in the world Photograph(1.3: Aerial view of Qatar’s most dense area, diplomatic quarters (Westbay) Source: Alexander Cheek <https:// www.flickr.com/ groups/1599245@ N24/>
Figure(1.7: Qatar’s location map
bal Water 2011) Qatar l Indicators p.571 SDP (2011) ar National ent Strategy 1–2016 p.214 CWA (2012) emographic file of Qatar d Nations 2013) World Prospects 12 Revision ohannadi, et. al. (2003) Residential Demand in Qatar SDP (2011) ar National ent Strategy 1–2016 p.218 41. Ibid. AHRAMAA Report 2008 (2009) 22!Collective Ecologies
Introduction The State of Qatar is a small, desert peninsula located halfway along the south coast of the Persian Gulf, bordered to the south by Saudi Arabia. This once quiet State has been transformed by the discovery of the world’s third largest natural gas reserves beneath its landscape,35 creating one of the fastest growing economies, and providing Qataris with the highest average individual incomes in the world.36 These investments have spurred development in both the urban and once rural sectors of Qatar, increasing its population tenfold in the last 30 years, to nearly 1.9 million people,37 making it the world’s fastest growing country.38 Water Use Population growth, coupled with increased standards of living has led to a hyper-dramatic acceleration of water consumption in Qatar within the last few decades. The average Qatari nationals, in spite of being 10% minority of the population,39 consume 40% of total daily fresh water used within Qatar, nearly 1,200 litres per capita per day.40 Expatriate residents however, consume on average only 150 litres per day,41 on par with most westernised nations. Taking these numbers into consideration for the total population, water use averages to 430 litres per person, per day, the highest rate in the world.42 The leading factor for this high consumption rate is the Qatari government’s subsidisation of water costs for Qatari citizens and
Mediterranean sea
QATAR
Indian Ocean
Average Monthly Temperature 1901 to 2009 (oC)
Average Monthly Rainfall 1901 to 2009 (mm)
35
12
30
9
25
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0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Figure(1.8: Graph, average monthly temperature in Qatar from 1901 to 2009 Figure(1.9: Graph, average monthly rainfall in Qatar from 1901 to 2009
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Source: World Data Bank <http://data. worldbank.org/ country/qatar>, March 2013
Water Use Per Household 43
200 175
Source: M.A. Darwish & Rabi Mohtar, Qatar water challenges, Desalination and Water Treatment, Qatar Environment and Energy Research Institute, 2012
Floor Cleaning
Clothes Washing
5
Bathing
3%
Personal Washing
3%
11%
Toilet
2%
10% %
Garden Watering
2%
Car Washing
100 75
Dish Washing
21%
Cooking & Drinking
Litres
150 125
50 25
Figure(1.10: Graph, water breakdown per household in Qatar
%
Use
Figure(1.11: Regional subdivision map of Qatar
residents, leading to high levels of waste and network inefficiency. Acquisition Stress Excessive fresh water use has led to the depletion and contamination of once sufficient underground water reserves, creating a supply deficit and requiring substantial investment in desalination and wastewater treatment programmes. With an average annual rainfall of only 70-90mm a year,43 and no natural surface bodies of fresh water,44 desalination is currently the only viable option. However current approaches are far from a long term solution. This method is highly reliant on uninterrupted service and requires long lead times to expand production. Currently 99.9% of Qatar’s fresh water comes from desalination processes, with only 0.1% derived from ground water.45 Existing desalination throughout Qatar can offer 1,600,000m3 of water a day,46 with facilities running at 71% capacity.47 Construction of an additional plant is underway, but will not be operational until 2015, adding only an additional 320,000m3 of water a day.48 Contributing these issues even further, the required decommission of an aging desalination plant is expected in 2020, at which time the population is expected to have reached over 2.2 million.49 These figures suggest that continued population growth and resultant water demand will soon outpace desalination plant capacities.
Doha
43. Globa Market (201 - General In p.571 44. Kardo Dr. (2009) Q Biodiversity 45. Globa Market (201 - General In p.577 46. GSDP Qatar Natio Developme 2011–2016 p 47. Globa Market (201 - General In p.577 48. Qatar Electricty & (2013) Ras A Plant to Op 49. The Demograph Qatar (2012 Annual Rep !Introduction!23
Photograph(1.4: Aerial view of Doha and the main desalination plant: Ras Abu Fontas Kahrama. Source: Google Earth Photograph(1.5: Qatar â&#x20AC;&#x2DC;s main desalination plant and storage containers. Source: <http://www. utilities-me.com/ article-745-24bn-rasal-zour-contract-forsaudi-chinese-jv/#. UgkjNRY0pLw>
Doha
Plant
Storage Stress Qatar uses various means of water storage including reservoirs, ground tanks, elevated tanks and water towers. Capacities for water storage facilities have increased alongside population growth patterns over the last decade, but even with these expansions, water storage capacity is estimated at less than 2.0 million m3, providing an emergency supply of only 2 days.50 As the Qatari population continues to escalate, preparations are underway for expanding the emergency storage capacity to 7.0 million m3 within the next decade.51 This will provide up to 7 days of storage, alleviating some risk of supply interruption, but is still a short term solution to a larger, long term water emergency storage problem. Figure(1.12: Qatar solar map, showing available renewable resource coming from sun irradiance. Source: Rabi H. Mohtar, Qatar Foundation Vision in Energy Efficiency and Renewable Energy, Qatar Environment and Energy Research Institute 2012
SDP (2009) onal Vision 2030 Malki, A.S. er Network Affairs 24!Collective Ecologies
Reintegration Possibilities Qatar now reintegrates about 24% of its total amount of grey water, a good start when compared to other Gulf States which average only 16%. However, this reintegrated water is primarily utilised for agriculture that is located often long distances from the supplying urban areas. The remaining treated water is used for landscape irrigation and reservoir top-off within the Abu Nakhla Reserve, located 20km away from central Doha.
Direct normal irradiance (kWh/m2 p.a.) >2,225 2,201 - 2,225 2,176 - 2,220 2,151 - 2,175 2,126 - 2,150 2,101 - 2,125 2,076 - 2,100 <= 2,075 Doha
250 200
300 250
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100 50
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Production in Millions m3
Desalination Production in Relation to Availablity Per Capita
Figure(1.13: Graph, increasing desalinated water production versus decreasing water availability per person. Population is growing faster than additional plants can be built: Decreasing total amount of water available per capita. Source: KAHRAMAA Statistics Report 2008, 2007/ Qatar National Vision 2030, 2009
Water Availability Per Capita
Population of Qatar
Figure(1.14: Graph, population growth versus fresh water availability in Qatar.
Year
Fresh Water
Source: World Data Bank <http://data. worldbank.org/ country/qatar>, March 2013
2012
2010
2008
2006
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1998
1996
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0.5 0.25 1970
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1 0.75
1966
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m3
2 1.75
1962
Population in Millions
Renewable internal freshwater resources per capita
Population
17%
Figure(1.15: Graphs, wastewater use in Qatar
17%
9.8 million m3 / yr
Source: KAHRAMAA Statistics Report 2008, 2007/ Qatar National Vision 2030, 2009
20% 57.7 million m3 / yr 2005
53%
20% 11.6 million m3 / yr
57.7 million m3 / yr 2005
63% 36.4 million m3 / yr
10% Use of Treated Wastewater
Location of Used Treated Wastewater El-Rakeya Farms
Doha Landscape
Abu Nakhla Lake
El-Refaa Farms
Agriculture Irrigation
Landscape Irrigation
Lake Top-Up
!Introduction!25
3. Weinstock, M. (2010) The Architecture of Emergence 4. Thompson, D. (1917, 1961) On Growth and Form 5. Weinstock, M. (2010) The Architecture of Emergence 6. Bettencourt L. et. al. (2006) ‘Growth, Innovation, Scaling, and the Pace of Life in Cities’ PNAS, Vol.104, No.17 7. Weinstock, M. (2011) ‘The Metabolism of the City’ AD Vol. 81, Iss. 4 8. Bettencourt L. et. al. (2006) ‘Growth, Innovation, Scaling, and the Pace of Life in Cities’ PNAS, Vol.104, No.17 9. West, G., et. al. (1997) ‘A General Model for the Origin of Allometric Scaling Laws in Biology’ Nature, Vol. 413 10. Weinstock, M. (2010) The Architecture of Emergence 11. West, G. (1997) ‘A General Model for the Origin of Allometric Scaling Laws in Biology’ Nature, Vol. 413 12. Weinstock, M (2011) ‘The Metabolism of the City’ AD, Vol. 81, Iss. 4 13. Weinstock, M. (2010) The Architecture of Emergence 14. Weinstock, M. (2010) ‘Emergence and the Forms of Metabolism’ AD, Vol. 80, Iss. 2 15. Decker, E., et. al. (2000) Energy and Material Flow through the Urban Ecosystem
16. Ibid. 17. Weinstock, M. (2010) The Architecture of Emergence 18. Bettencourt L., et. al. (2010) ‘A Unified Theory of Urban Living’ Nature, Vol. 467 28. Weinstock, M. 2011, The Metabolism of the City 19. Decker, E., et. al., (2000) Energy and Material Flow through the Urban Ecosystem 20. Weinstock, M. (2010) ‘Emergence and the Forms of Cities’ AD, Vol. 80, Iss. 3 21. ‘Bettencourt L., et. al. (2010) A Unified Theory of Urban Living’ Nature, Vol. 467 22. Weinstock, M. (2010) ‘Emergence and the Forms of Cities’ AD, Vol. 80 23. Decker, E., et. al. (2000) Energy and Material Flow through the Urban Ecosystem 24. Weinstock, M. (2008) ‘Metabolism and Morphology’ AD, Vol. 78, Iss. 2 25. Weinstock, M. (2011) ‘The Metabolism of the City’ AD, Vol. 81, Iss. 4 26. Decker, E., et. al. (2000) Energy and Material Flow through the Urban Ecosystem 27. Weinstock, M. (2008) ‘Metabolism and Morphology’ AD Vol. 78, Iss. 2
Introduction References 29. UN-Water Decade Programme on Advocacy and Communication 2 (UNW-DPAC) 30. World Population Prospects - The 2012 Revision, 2013 31. The United Nations World Water Development Report 3, 2009 32. UN-Water Decade Programme on Advocacy and Communication 4 (UNW-DPAC) 33. The United Nations World Water Development Report 3, 2009 34. Kennedy, C. et.el (2007) ‘The changing metabolism of cities’ Journal of Industrial Ecology 35. Global Water Market (2011) Qatar - General Indicators p.571 36. GSDP (2011) Qatar National Development Strategy 2011–2016 p.214 37. ESCWA (2012) The Demographic Profile of Qatar 38. United Nations (2013) World Population Prospects - The 2012 Revision 39. Al-Mohannadi, et. al. (2003) Controlling Residential Water Demand in Qatar 40. GSDP (2011) Qatar National Development Strategy 2011–2016 p.218 41. Ibid. 42. KAHRAMAA Statistics Report 2008 (2009) 43. Global Water Market (2011) Qatar - General Indicators p.571
44. Kardousha, M. Dr. (2009) Qatar Biodiversity 45. Global Water Market (2011) Qatar - General Indicators p.577 46. GSDP (2011) Qatar National Development Strategy 2011–2016 p.218 47. Global Water Market (2011) Qatar - General Indicators p.577 48. Qatar Electricty & Water (2013) Ras Abu Fontas Plant to Open in 2015 49. The Demographic Profile of Qatar (2012) ESCWA Annual Report 50. GSDP (2009) Qatar National Vision 2030 51. Al Malki, A.S. (2009) Water Network Affairs
Domain Scalability of the City p.32 Wetlands p.34 Research Proposal p.36
Domain Overview Concentrating on urban growth and metabolic rates within cities, initial research focuses on theories proposed by Geoffrey West and others on the scalability of the city and the establishment of a science-based understanding of the dynamics, growth, and organisation of urban systems. To address these urban dynamics, subsequent research focuses on passive infrastructural systems for cleansing and reintegrating the cityâ&#x20AC;&#x2122;s largest component, water. Investigations of localised water treatment through constructed wetlands provide guidelines and establish limits to which water re-integration is possible within an urban centre. These precedents are crucial for determining various parameters in the research and how urban metabolic rates are linked to urban growth.
Scalability of the City Quantifying urban systems Photograph(2.6: Aerial view of Manhattan, New York, US Source:Tim Sklyarov < http://timsklyarov. com/new-york-cityaerial/#more-1351>
“
Cities are the crucible of human civilization, the drivers towards potential disaster, and the source of the solution to humanity’s problems. It is therefore crucial that we understand their dynamics, growth and evolution in a scientifically predictable, quantitative way.”
encourt L. 06) ‘Growth, on, Scaling, Source: Bettencourt L. ce of Life in et. al. (2006) ‘Growth, Innovation, Scaling, AS, Vol.104, No.17 and the Pace of Life in 53. Ibid. Cities’ PNAS, Vol.104, 54. Ibid. No.17 t G., et. al. ‘A General Ontogenetic Nature, Vol. 413 32!Collective Ecologies
Urban Scaling West and his colleagues were intrigued to find whether this scaling phenomenon was also found in urban systems. Their analysis is based on large urban data sets, from hundreds of cities around the world, spanning several 103 (kcal/h: log scale)
Figure(2.16: Graph, scalability of any living organism., sub-linear behaviour
Unified Theory of Scaling This transdisciplinary team of physicists and biologists is in the process of developing a unified theory and predictive framework of scaling in urban systems applicable to cities around the world. Their work hypothesises in part that the solutions to problems associated with urban scaling can be found in the structural and organisational principals found within scaling phenomena among organisms. Through natural selection, the expectation for any degree of correlation between organisms of differing scales seems improbable, since each organism and it’s subsystem evolved in its own unique environmental niche. However, looking at all the elements comprising a mouse and all the elements of an elephant, they have remarkably similar power laws in relation to one another in terms of scale and the processing of flows within their systems.53 This consistency
is sustained through hierarchical, branching network structures, and can be measured in any physiological variable, such as energy consumption, heart rates, life span, and diffusion rates across surfaces. The variables follow a ¼ scaling law, either increasing by ¼ or decreasing by ¼,54 and reflect the general mathematical, physical, and topological properties of all organisms, regardless of each individual’s morphology and size.55
Metabolic rate
Urban Transitions As population and urbanisation continue to increase throughout the world, cities are facing challenges as they continue to develop and grow. Health concerns, habitat destruction, and environmental impacts imposed through over densification presents what Geoffrey West and his colleagues describe as an urgent requirement for establishing a science-based understanding of the dynamics, growth and organisation of cities for future sustainable development.52
100 10-3 10-6 10-9 10-12 10-12 10-9
10-6
10-3
100
Mass(g, log scale)
103
106
109
Y
ß
95% CI
Adj-R2
Observations
Country–year
New patents
1.27
[1.25,1.29]
0.72
331
U.S. 2001
Inventors
1.25
[1.22,1.27]
0.76
331
U.S. 2001
Private R&D employment
1.34
[1.29,1.39]
0.92
266
U.S. 2002
“Supercreative” employment
1.15
[1.11,1.18]
0.89
287
U.S. 2003
R&D employment
1.26
[1.18,1.43]
0.93
295
China 2002
Total wages
1.12
[1.09,1.13]
0.96
361
U.S. 2002
Total bank deposits
1.08
[1.03,1.11]
0.91
267
U.S. 1996
GDP
1.13
[1.03,1.23]
0.94
37
Germany 2003
Total electrical consumption
1.07
[1.03,1.11]
0.88
392
Germany 2002
New AIDS cases
1.23
[1.18,1.29]
0.76
93
U.S. 2002–2003
Serious crimes
1.16
[1.11,1.18]
0.89
287
U.S. 2003
Total housing
1
[0.99,1.01]
0.99
316
U.S. 1990
Total employment
1.01
[0.99,1.02]
0.98
331
U.S. 2001
Household electrical consumption
1
[0.94,1.06]
0.88
377
Germany 2002
Household water consumption
1.01
[0.89,1.11]
0.96
295
China 2002
Gasoline stations
0.77
[0.74,0.81]
0.93
318
U.S. 2001
Gasoline sales
0.79
[0.73,0.80]
0.94
318
U.S. 2001
Length of electrical cables
0.87
[0.82,0.92]
0.75
380
Germany 2002
Road surface
0.83
[0.74,0.92]
0.87
29
Germany 2002
Scaling exponent
Driving force
Organization
Growth
ß < 1 (Sub Linear)
Optimization, efficiency
Biological
Sigmoidal: long-term population limit
ß > 1 (Super Linear)
Creation of information, wealth and resources
Sociological
Boom/collapse: finite-time singularity/unbounded growth; accelerating growth rates/discontinuities
ß = 1 (linear)
Individual maintenance
Individual
Exponential
These researchers have made great discoveries in the development of this theoretical framework on urban scaling, demonstrating two main systematic characteristics in relation to population growth. The first is that the space required per capita is sub-linear, minimised through denser development and utilisation of branching network infrastructures. Second, they demonstrate that the pace of socio-economic activity accelerates, leading to superlinear productivity and cultural growth. This combination of densification and economies of scale with and increased productivity, diversification, interdependence and cultural expression, clearly outline the benefits to continued global urbanisation. 63
27 β=1.12
26 (log scale)
Total Wages
decades, and has revealed remarkably universal, quantifiable scaling features of urban systems.56 Their findings indicate systematic behaviour in urban growth patterns and processes, shared among all cities throughout differing nations and points in time, following specific power law functions.57 Looking across infrastructural aspects of cities, they find a clear similarity to biology. Road networks and utilities such as electrical, water and sewer networks, among other aspects, all require fewer infrastructures as cities get larger, signifying efficiency found in economies of scale per capita.58 This demonstrated growth occurs in a sub-linear fashion, meaning as a population doubles the infrastructure only increases at a scale of 85%, similar to systems found within biological organisms59. However, in socio-economic aspects of cities, they find the opposite is true. Quantities and pace grow at an increased rate in relation to population growth.60 This proves both problematic and beneficial for urban systems. Aspects such as energy consumption, disease, crime, waste production and pollution all increase in a super-linear fashion, demonstrating that as a population doubles these elements increase at a scale of 115%.61 West explains that cities may hold these negative features, but the answer to these problems can also be found in cites themselves, through their increased productivity, innovation, wealth creation and education all reflecting the same 115% scaling ratio.62
R2=0.97
25 24 23 22 21 20
10
11
12
13
14
15
Population(millions, log scale)
16
17
Table(2.1: Classification of scaling exponents for urban properties and their implications. CI, confidence interval; Adj-R2, adjusted R2; GDP, gross domestic product; RD: Research Development Table(2.2: Scaling exponents for urban indicators vs city size Source: Bettencourt L. et. al. (2006) ‘Growth, Innovation, Scaling, and the Pace of Life in Cities’ PNAS, Vol.104, No.17
56. Bette et. al. (2010) Theory of U Living’ Nat 57. Ibid. 58. Bette et. al. (2006 Innovation, and the Pac Cities’ PNA No.17 59. Bette et. al. (2010) Scaling and Deviations’ Vol. 5, Iss. 1 60. Bette Figure(2.17: et. al. (2006 Graph showing the Innovation, super-linear behaviour and the Pac of some socio-econom- Cities’ PNA ic parameter in cities: No.17 61. Betten Wages. et. al. (2010) Source: Bettencourt L. Scaling and et. al. (2006) ‘Growth, Deviations’ Vol. 5, Iss. 1 Innovation, Scaling, 62. Ibid. and the Pace of Life in 63. Bette Cities’ PNAS, Vol.104, et. al. (2010) No.17 Theory of U Living’ Nat !Domain!33
Wetlands Ecosystems use for purifying water. Photograph(2.7: Natural wetland (Moscu, Russia) Source: < http://red6747. pbworks.com/w/ page/26462365/ Wetlands%204>
-HABITAT, Constructed ds Manual". TAT Water Asian Cities mme Nepal, Kathmandu.
Photograph(2.8: Constructed Wetland, Renaissance Park, (Chattanooga, uise Davis, Tennessee) Handbook Constructed Source: < http://red6747. ds, Volume pbworks.com/w/ DA-Natural page/26462365/ Resources Wetlands%204> ion Service uise Davis, Handbook Constructed ds, Volume DA-Natural Resources ion Service Melbourne 005. Water itive Urban ngineering ures: Storm water 34!Collective Ecologies
â&#x20AC;&#x153;
[Constructed Wetlands (CWs) are a natural, low-cost, eco-technological biological wastewater treatment technology designed to mimic processes found in natural wetland ecosystemsâ&#x20AC;?67 UN-HABITAT, 2008.
Natural processes have always passively cleansed water in a multitude of efficient ways. Rivers, lakes, and streams are absorbed through wetlands and sedimentary rock aquifers, acting as natural filters that trap or utilise sediment and micro-organisms to provide natural water purification. Utilising these strategies, constructed wetlands allow for the break down and transformation of pollutants and bacteria into nutrients and cleansed water through a combination of vascular plants and communities of microbes and invertebrates.64 Acting as a self-adjusting system, constructed wetlands are tolerant of fluctuations in flow cycles prevalent in most urban hydrological systems.65 This ensures low operation and maintenance expenses, which are periotic rather than continuous as in conventional treatment systems. Performance may be less consistent than in conventional treatment processes, leading constructed wetlands to primarily be utilised for non-potable water needs and not suitable for potable water. While constructed wetlands act primarily as water treatment systems, they also provide other benefits such as enhancing the landscape for recreation, remediating progressive effects of desertification and helping create habitats for wildlife.66 These additional factors allow for their integration into urban landscapes, incorporating the large amount of land required to operate as dispersed localised treatment systems within urban areas. There are conventionally three main constructed wetland
systems in use around the world: Surface Flow, Subsurface Flow, and Vertical Flow, each bringing with them advantages and disadvantages for treating water. Through evaluating each system, it is clear that Subsurface Flow Constructed Wetlands is the most appropriate for a location such as Qatar. It provides quick and efficient treatment, through a closed system that limits odours and reduces evaporation, and is easily integrated into urban contexts.
Figure(2.18: Systems for constructed wetlands in relation to the space needed, considering the Qatari water consumption per day (430 litres)
Surface flow Constructed Wetlands
Subsurface flow Constructed Wetlands
Vertical flow Constructed Wetlands
14m2 40m
2
90m2
Surface Flow Constructed Wetlands - Land requirement to purify water per person – 90m2 - Flow occurs on the surface, increasing odours and evaporation - Quickly treats incoming water, but less efficient - More difficult integration into urban systems, larger architectural impact - Open water beds increase wildlife diversity - Initial capital and operation costs are relatively low Subsurface Flow Constructed Wetlands - Land requirement to purify water per person – 40m2 - Flow occurs below the surface, resulting in less odours and reduced evaporation - Quickly and efficiently treats incoming water - Easy integration into urban systems, least amount of architectural impact - Covered water beds allow for less wildlife diversity - Initial capital and operation costs are relatively high Vertical Flow Constructed Wetlands - Land requirement to purify water per person – 14m2 - Flow is percolated from above the surface, increasing odours and evaporation - Slowly but efficiently treats incoming water
- Most difficult to integrate into urban systems, largest architectural impact - Open water beds increase wildlife diversity - Initial capital and operation costs are relatively high
Figure(2.19: Cross section of subsurface flow constructed wetland. soil or gravel slotted pipe water inlet Wetland Plants
0.6m inlet stone distributor
slope of 0.5%
rhizome network
effluent outlet
watertight membrane
Cross-Section of Subsurface Flow Constructed Wetland
!Domain!35
Research Proposal In a severely water stressed country such as Qatar, it is becoming ever more difficult to ensure a constant and reliable supply of water, requiring re-examination of how its urban systems are developed to meet increasing demands of a growing population. This proposal advocates a cohesive rather than independent development of how morphologies and infrastructures are organised and interact in order to cope with the needs of future urban systems. With nearly 98% of the water demand within Qatar capable of utilizing non-potable water, the vast majority of fresh water supplied from desalination plants could be provided from integration of localised grey water treatment. The clearest direction to address Qatarâ&#x20AC;&#x2122;s water security is the development of water reintegration systems and networks to utilise water to its full potential while already within the system. The integration of constructed wetland infrastructures within urban and architectural morphologies allows for relationships to develop among neighbouring typologies to support the water needs of one another depending on their population densities and ratios of integrated wetlands. This localised reintegration of grey water drastically minimises fresh water consumption demands, resulting in an improvement of the overall urban metabolic rate.
36!Collective Ecologies
!Domain!37
Domain References 52. Bettencourt L. et. al. (2006) ‘Growth, Innovation, Scaling, and the Pace of Life in Cities’ PNAS, Vol.104, No.17 53. Ibid. 54. Ibid. 55. West G., et. al. (2001) ‘A General Model for Ontogenetic Growth’ Nature, Vol. 413 56. Bettencourt L., et. al. (2010) ‘A Unified Theory of Urban Living’ Nature, Vol. 467 57. Ibid. 58. Bettencourt L. et. al. (2006) ‘Growth, Innovation, Scaling, and the Pace of Life in Cities’ PNAS, Vol.104, No.17 59. Bettencourt L., et. al. (2010) ‘Urban Scaling and Its Deviations’ PLoS ONE, Vol. 5, Iss. 11 60. Bettencourt L. et. al. (2006) ‘Growth, Innovation, Scaling, and the Pace of Life in Cities’ PNAS, Vol.104, No.17 61. Bettencourt L., et. al. (2010) ‘Urban Scaling and Its Deviations’ PLoS ONE, Vol. 5, Iss. 11 62. Ibid.
63. Bettencourt L., et. al. (2010) ‘A Unified Theory of Urban Living’ Nature, Vol. 467 67. UN-HABITAT, 2008. "Constructed Wetlands Manual". UN-HABITAT Water for Asian Cities Programme Nepal, Kathmandu. 64. Luise Davis, 1998. "A Handbook of Constructed Wetlands, Volume 1", USDA-Natural Resources Conservation Service 65. Luise Davis, 1998. "A Handbook of Constructed Wetlands, Volume 1", USDA-Natural Resources Conservation Service 66. Melbourne Water, 2005. Water Sensitive Urban Design - Engineering Procedures: Storm water
Methods City Samples p.44 Case Studies p.48 Computational Techniques p.54
Methods Overview The climate, culture, and history of Doha, Qatar that informed the development of its vernacular architectures, led to their destruction, and influenced the current morphology were analysed. Current conditions are compared with case studies around the world to analyse relationships between population density, public space and road networks, among other factors. Computational methods were then researched and evaluated to find the best strategies for analysing and informing decisions within our urban system.
City Samples Extracting data and ratios from different cities Photograph(3.9: Aerial view, sample Frankfurt, Germany Source: Google Earth
Figure(3.20: Built area, sample Frankfurt, Germany Figure(3.21: Roads area, sample Frankfurt, Germany
Frankfurt
Frankfurt, Germany Sample Patch analysis (500x500m)
44!Collective Ecologies
Number of Buildings
492
buildings
Amenities
6183.64
m2
Built Area
88306.4
m2
Streets Area
75107.35
m2
Unbuild Area
161,693.60
m2
Streets Intersections
41
nodes
Percentage Build
35.32%
%
Streets Max. Width
25
m
Minimum Blocksize
287.65
m2
Streets Min. Width
7.2
m
Maximum Blocksize
20132.88
m2
Residential Building Area
49488
m2
Block Area
174011.45
m2
Residential Building
56.00%
%
Percentage Block Are Build
0.51%
%
Office Building Area
3580
m2
Average Blocksize
5,800.38
m2
Office Building
4.00%
%
Minimum Building Footprint
3.12
m2
Mixed Use Office Area
5320
m2
Maximum Building Footprint
3715.66
m2
Mixed Use Office Building
6.00%
%
Average Area
179.48
m2
Retail Building Area
18373
m2
Minimum Stories
1
Floors
Retail Building Percentage
21.00%
%
Maximum Stories
9
Floors
Other Use Building Area
11308
m2
Avearage Stories
4.67
Floors
Other Use Building
13.00%
%
Floor Area
412201.17
m2
Population
2500
persons
Building Density
1.65
floor area/ patch size
Density
100
people / hectare
Public Water spaces
0
m2
People per Cell
2160
persons
Public Green Space
881.2
m2
Wetland needed
86400
m2
Courtyards
85705.05
m2
Photograph(3.10: Aerial view, sample Manhattan, New York, US Source: Google Earth
Figure(3.22: Built area, sample Manhattan, New York, US Figure(3.23: Roads area, sample Manhattan, New York, US
New york, Manhattan
Manhattan, New York, USA Sample Patch analysis (500x500m) Number of Buildings
345
buildings
Amenities
0
m2
Built Area
137487.33
m2
Streets Area
46073.18
m2
Unbuild Area
112512.67
m2
Streets Intersections
12
nodes
Percentage Build
54.99%
%
Streets Max. Width
37
m
Minimum Blocksize
23472.5
m2
Streets Min. Width
20.4
m
Maximum Blocksize
26462.66
m2
Residential Building Area
40962
m2
Block Area
203926.82
m2
Residential Building
31.00%
%
Percentage Block Are Build
0.67%
%
Office Building Area
26317
m2
Average Blocksize
24462.8
m2
Office Building
20.00%
%
Minimum Building Footprint
27.89
m2
Mixed Use Office Area
29899
m2
Maximum Building Footprint
2492.09
m2
Mixed Use Office Building
23.00%
%
Average Area
398.51
m2
Retail Building Area
13737
m2
Minimum Stories
1
Floors
Retail Building Percentage
11.00%
%
Maximum Stories
20
Floors
Other Use Building Area
19733
m2
Avearage Stories
6.86
Floors
Other Use Building
15.00%
%
Floor Area
943,093.64
m2
Population
4050
persons
Building Density
3.77
floor area/ patch size
Density
162
people / hectare
Public Water spaces
0
m2
People per Cell
3500
persons
Public Green Space
0
m2
Wetland needed
140000
m2
Courtyards
30804.33
m2
!Methods!45
Photograph(3.11: Aerial view, sample Amsterdam, Netherlands Source: Google Earth
Figure(3.24: Built area, sample Amsterdam, Netherlands
Figure(3.25: Roads area, sample Amsterdam, Netherlands
Amsterdam
Amsterdam, Netherlands Sample Patch analysis (500x500m)
46!Collective Ecologies
Number of Buildings
1125
buildings
Amenities
6501.47
m2
Built Area
76974.34
m2
Streets Area
11814.3
m2
Unbuild Area
173,025.66
m2
Streets Intersections
65
nodes
Percentage Build
30.79%
%
Streets Max. Width
71
m
Minimum Blocksize
252.35
m2
Streets Min. Width
3
m
Maximum Blocksize
8699.1
m2
Residential Building Area
18442
m2
Block Area
119506.48
m2
Residential Building
29.00%
%
Percentage Block Are Build
0.64%
%
Office Building Area
6903
m2
Average Blocksize
2987.662
m2
Office Building
11.00%
%
Minimum Building Footprint
5.56
m2
Mixed Use Office Area
18147
m2
Maximum Building Footprint
3499.59
m2
Mixed Use Office Building
28.00%
%
Average Area
68.42
m2
Retail Building Area
8484
m2
Minimum Stories
2
Floors
Retail Building Percentage
13.00%
%
Maximum Stories
7
Floors
Other Use Building Area
12206
m2
Avearage Stories
3.68
Floors
Other Use Building
19.00%
%
Floor Area
283557.26
m2
Population
1250
persons
Building Density
1.13
floor area/ patch size
Density
55
people / hectare
Public Water spaces
54758.42
m2
People per Cell
1188
persons
Public Green Space
14489.61
m2
Wetland needed
47520
m2
Courtyards
28,042.53
m2
Photograph(3.12: Aerial view, sample Doha, Qatar Source: Google Earth
Figure(3.26: Built area, sample Doha, Qatar Figure(3.27: Roads area, sample Doha, Qatar
Doha, Qatar Sample Patch analysis (500x500m) Number of Buildings
535
buildings
Streets Max. Width
25
m
Built Area
95353.43
m2
Streets Min. Width
3
m
Unbuild Area
154,646.57
m2
Population
2745
persons
Percentage Build
38.14%
%
Density
109.8
people / hectare
Minimum Blocksize
351.84
m2
People per Cell
0
persons
Maximum Blocksize
10996.33
m2
Wetland needed
0
m2
Block Area
165823.19
m2
Percentage Block Are Build
0.58%
%
Average Blocksize
3616.78
m2
Minimum Building Footprint
3.376
m2
Maximum Building Footprint
1657.21
m2
Average Area
193.24
m2
Minimum Stories
1
Floors
Maximum Stories
5
Floors
Avearage Stories
3.60
Floors
Public Green Space
3122.78
m2
Courtyards
10,048.99
m2
Amenities
0
m2
Streets Area
84176.81
m2
Streets Intersections
39
nodes
!Methods!47
Case Studies References and approaches considered for the development of the project Photograph(3.13: Doha current skyline. Source: Shutterstock: 84373246
Doha, Qatar
idmann, F. ‘The Urban on of Doha’ METU.JFA CWA (2012) emographic file of Qatar idmann, F. ‘The Urban on of Doha’ METU.JFA ah, I., et.al. e History of Architecture uainain, F. rbanisation idmann, F. A Study of ‘The Urban dential and on of Doha’ ercial Land METU.JFA ent in Doha idmann, F. City ‘The Urban on of Doha’ METU.JFA 48!Collective Ecologies
Doha has a surprisingly short history. Established in the early 19th century as a small fishing village, it became a British protectorate in 1916, before achieving independence in 1971. Despite foreign involvement, Doha maintained its vernacular architectural methodologies and held consistent population levels up until the discovery of its oil and gas reserves in the middle of the 20th century.68 It has since emerged as a modern urban centre with more than 1 million inhabitants.69 Doha originally developed and dispersed in a bottom up manor through the settlement and clustering of tribes along the coast. Climate and culture shaped its urban morphology, reflecting not only how its spaces were used in functionality, but also in how these spaces expressed the societal norms and tribal affiliations.70 Designs followed Islamic tradition, with high degrees of privacy, and complex systems of winding streets and alleys throughout neighbourhoods. Buildings were constructed with local materials and varied from simple one room homes, to two story courtyard houses.71 These were clustered in close proximity with one another, in a highly dense fashion, often built wall to wall, encouraging and resembling the close social relationships within communities. These adjacent building schemes helped to develop shading strategies for walkways and exposed walls from the harsh desert conditions. Oil revenues brought investment and development of infrastructure to Doha, quickly changing the conditions of the city from a bottom up organisational approach to a series of fragmented master plans and architectures imported by foreign developers.72 Nearly all of Doha’s
original urban morphology and vernacular approaches have since been replaced by fractured zone planning, orthogonal gird blocks, wide roads, and conventional cement architecture.73 This approach during the oil boom led to urban sprawl dispersed throughout the landscape. It transformed Doha into a large area of low density suburban typologies and glass high rises, connected by far spanning road networks, which developed a reliance on automobiles.74 Analysis of design principles and consideration of cultural traditions will define strategies to achieve conditions similar Doha’s pre-oil urban morphology and social connectivity. The relationships between building adjacencies, shading strategies and street layouts will inform the development of dense, well connected architectures and networks within our urban system.
Figure(3.28: Image showing the proportion of roads in East-West orientation. Source: <http://www10. aeccafe.com> Figure(3.29: Aerial Image showing the projected patch, density and proportions. Source: <http://www. adjaye.com/projects/ civic-buildings/ msheireb-downtown-doha/> Figure(3.30: Nolli Plan showing the building density and proportions of roads. The East-West roads shows a narrowed condition trying to reduce the sun exposure. Source: <http://www10. aeccafe.com>
Msheireb Downtown Doha Project Many Middle Eastern cities have developed and grown at staggering speeds, leading to potential long-term difficulties brought on by short sighted modernisation, disregarding extreme climate, urban centralisation and economic diversification. Trust in continued global demand for oil exports has led to unsustainable building typologies, migration to suburbs, and the fragmentation of urban centres, leading to inevitable loss of community and cultural traditions. Doha has been a prime example of this kind of development for the last half century. However, the government of Doha has recently pursued an alternative model for the continued future growth of their city. Their first initiative is a comprehensive revitalisation of central Doha, funded entirely by the Qatari Royal family to the tune of $5.5 billion USD. The decade long project will transform a 31 hectare area into a dense, mixed-use development, based on vernacular Qatari architecture and utilising regional urban design strategies. Comprised of more than 100 new buildings, the development will combine retail, commercial and leisure programmes with housing to service 25,000 people, while also creating public spaces that are usable in Dohaâ&#x20AC;&#x2122;s intense climate. The aim is to restore a sense of community through a sequence of densely planned urban neighbourhoods with walkable access to services and amenities within the new urban centre. At an urban scale the plan takes into account several factors to better encourage pedestrian street activity. To minimise heat and maximise solar shading, the streets are as narrow as possible in relation to the heights of buildings, and are oriented to capture the cool sea breezes from the northsouth wind. The resulting grid has also been manipulated in
response to sounding site conditions, keeping the curvature of the main thoroughfare to the south, retaining the Meccaorientation of the main market street, and bypassing several vernacular houses utilised as museums. Additionally, all car parks and service roads have been hidden underground to enhance the public pedestrian realm. These urban scale considerations are dramatically different then current conditions in Qatar, where even the shortest distances require the need for vehicles. Architecturally, several small, but important considerations have been made for building strategies. Semi-private courtyards have been reintroduced in an initiative to return Doha back to its cultural traditions. These allow for social environments to develop through interactions in a shared space by clusters of related families. In addition, features such as covered colonnades, shading canopies, and evaporative water strategies have all been incorporated to develop a habitable environment for pedestrians from intense the sunlight and heat. These approaches to environmental, cultural and social issues within Doha are critical steps to revitalising the city's cultural centre and reversing the trend of residential migration to surrounding suburbs. It is a difficult task to develop an interest for this form of urban morphology which is currently in small demand by Qatari citizens, but Msheireb Downtown Doha has the potential to change these opinions once completed in 2020. This new district gives hope to radically shift expectations of planned urban design if it can prove a commercial and cultural success; with the potential to change the face of many cities across the Middle East and other urbanising regions around the world.
!Methods!49
Photograph(3.14: Aereal view of Abu Nakhla Wetland, Qatar Source: Google Earth
Photograph(3.15: Abu Nakhla Wetland, Qatar Source: <http:// sahilonline.blogspot. co.uk/2008/12/birdingin-al-khor-qatar.html> Source : Jdylan - Green Zone bordering Water Reservoir
Wetlands: Abu Nakhla, Qatar The Abu Nakhla Reserve is unique given that it is not used for the purification of water or as an overflow containment wetland, but as an experimental reserve operated by the Department of Biological and Environmental Sciences at Qatar University. Located on the outer edge of Qatarâ&#x20AC;&#x2122;s largest city, Doha, it receives a fluctuating supply of treated municipal water discharged from local sewage treatment stations which continually adjusts the wetlandâ&#x20AC;&#x2122;s depth and the reserves topography.75 Given that Qatar is one of the few countries in the world that contains no natural surface bodies of fresh water, 76 researchers initially lacked local wetland precedents for examples as they developed the reserve. As a result, they introduced species of wetland plants from other areas around the Persian Gulf that have adapted to similar soil conditions, animal communities and climate in order to survive within the Abu Nakhla Reserve. The research conducted by Qatar University has demonstrated high levels of plant diversity within the reserve, and has successful introduced a number of submerged, littoral, and above-ground plant species for establishing future wetlands in Qatar. 77
ardousha, M. Dr., 2009. Biodiversity ardousha, M. Dr., 2009. Biodiversity ardousha, M. Dr., 2009. Biodiversity 50!Collective Ecologies
Photograph(3.16: Aerial view of Shibam, Yemen Source: <http:// webodysseum.com/art/ shibam-the-city-madeout-of-mud-bricks/>
Photograph(3.17: Shibam’s density. Source: <http:// webodysseum.com/art/ shibam-the-city-madeout-of-mud-bricks/> Photograph(3.18: Shibam’s density. Source: <http://annadingding.blogspot. co.uk/2011/08/ travellers-wishlist.html>
Shibam, Yemen Climatic conditions are one of the key parameters in the development of urban morphology, defining the vernacular approaches of local built environments. Analysis of how these methods affect performance in extreme heat and sun exposure is essential when developing design proposals within the Middle East. Shibam, located in Yemen, is an excellent case of vernacular adaptability within the region. First established during the pre-Islamic period, it developed its current urban morphology as a walled city in the 16th century.78 This cluster of tall, mud brick, tower houses has been described as the 'Manhattan of the desert' composed of dwellings five to eleven stories high, developed on a fortified, rectangular grid plan.79 Shibam’s compactness allows for a walkable city throughout its narrow streets and public squares. These passages and openings provide the 7000 inhabitant’s with sufficient shading throughout a majority of the day through strategies developed over many centuries in the layout of its urban morphology and building relationships. Analysis of design principles within Shibam will define strategies to achieve similar urban conditions in other arid, desert climates. The relationships between building heights and street widths, orientation of roads and buildings, and the dispersal of public spaces can all inform how a city can develop and maintain a balanced relationship between the building morphology, layout and the climate.
78. International Council on Monuments and Sites (1981) UNESCO World Heritage Centre Justification 79. International Council on Monuments and Sites (1981) UNESCO World Heritage Centre Justification !Methods!51
Photograph(3.19: Student Rooms, Hooke Park, Architectural Association School of Architecture Educational Facilities, Dorset, UK. Source: Nicolas Cabargas Photograph(3.20: California Academy of Sciences by Renzo Piano Source: Tim Griffith <http://seedmagazine. com/slideshow/ california_academy_ of_sciences/>
Photograph(3.21: Vertical Farming project by SOA Architects. Source: <http:// www.verticalfarm. com/designs?folder=510aa317-7750-417692b0-99f7e98cddb1>
Integrating Vegetation Within Buildings The integration of vegetation into building morphology has primarily been assimilated through green roofs on existing structures and as unbuilt proposals of vertical farming within skyscrapers. These approaches have shown to be environmentally and economically beneficial, and technically possible to engineer, demonstrating strategies that can be utilised for successfully integrate wetlands into buildings. Green Roofs Green roofs have several proven benefits at a building and urban scale. They can provide great thermal performance to moderate temperature levels inside of buildings, subsequently requiring 50-90% less continuous artificial heating and cooling.80 Collectively, a concentration of green roofs in an urban area can also improve air quality and reduce the city's average temperatures through evapotranspiration.81 Buildings with integrated green roofs however, must be able to accommodate the additional static loading of soil substrate and retained water, requiring additional structural support within the building morphology.
ll, S. et.el. pting Cities ate Change: f the Green cture.â&#x20AC;? Built ment Vol 33 No. 1 iu, K. et.el. 03) Thermal ce of Green rough Field Evaluation 52!Collective Ecologies
Vertical Farming Proposals of vertical farming have been increasingly developed within the last decade, but there has yet to be a built example of a large scale vertical farm. Proponents of vertical farming argue they allow for localised production and increased yields within a controlled setting, but environmental scientists and engineers strongly criticise these proposals as being unrealistically feasible and question their necessity. These proposals demonstrate
that although architectural engineering and agricultural technology are capable of integrating vegetation and allowing growth within buildings, the economic and productive yield feasibility of vertical farms within skyscrapers is currently not a viable option.
!Methods!53
Computational Techniques Digital strategies used for the development of the project Photograph(3.22: Seashell Organism with CA-like pattern. Source: Richard Ling : http://eldar.cz/ cognition/complex/
Figure(3.31: Complex pattern created with Cellular Automaton starting with a single black cell and following â&#x20AC;&#x2DC;Rule 30â&#x20AC;&#x2122; Source: Wolfram; S. (2002) A New Kind of Science
Cellular Automaton
Wolfram, S. New Kind of Science Holland, J. Emergence: os to Order Holland, J. Emergence: os to Order Wolfram, S. ) "Statistical s of Cellular  Reviews of ysics Vol. 55 54!Collective Ecologies
Cellular automaton (CA) is a method for modelling or developing complex systems, where patterns of selforganisation arise from the independent execution of simple rules among its components. They are revealed in phenomena that exist across a wide array of subjects, including mathematics, physics, biology, social sciences, and economics.82 These dynamic systems are based on distributed rather than centralised control, allowing for complex behaviour to emerge from local interactions of many simple components acting in parallel with one another. 83 A simple example of a CA is a one dimensional array, with two possible states per cell, updating in cycles at a specified rate. The CA is given a transition rule, determining a cells state in each cycle though the evaluation of its present condition in relation to the state of its adjacent neighbours.84 These three cells form a neighbourhood, allowing for 28 = 256 possible patterns.85 The concurrent application of this rule to each of the cells determines their states for each cycle simultaneously, establishing the global state of the CA based on the previous cycle. The utilisation of cellular automata in the development of building morphology allows for a systematic approach of integrating constructed wetlands at specified ratios to meet numerical parameters required for a given number of inhabitants.
Photograph(3.23: Sunlight in the streets of London
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Source: By Stefan Powell from Toronto; Canada (golden energy) Figure(3.32: Sunlight hours analysis of a public space using Ladybug for Grasshopper.
Solar Analysis Daylight Sunlight refers to direct sunshine throughout the day, and experiences significant changes in intensity at differing latitudes and times of year.86 It is an important factor to consider in the development and layout of an urban system in order to either embrace or obscure it through design strategies. Diffused Sky Radiation however refers to the level of natural light scattering in the atmosphere to be reflected off terrestrial surfaces.87 It is a very effective light source, illuminating a given area without projecting heat to be absorbed by surfaces, a critical factor to consider for design strategies where extreme climate conditions are an issue. Luminance Emissions or reflections from surfaces are known as Luminance, which indicates how much luminous power the eye will detect while viewing the surfaces from a particular angle of view.88 Luminance is thus an indicator of how bright the surface will appear, and will never be more than equal to the input light source.89 Illuminance Illuminance is the density of photons which fall within a given surface area.90 For a given light source, the closer to a light source the illuminated area is, the higher the Illuminance value of light striking a surface. 91 Illuminance values are more critical to consider in a design than luminance, as buildings require differing amounts of intensity based on tasks undertaken in them.
Sunlight Hours Analysis of sun exposure will evaluate and visualise how many hours of sunlight will fall on a given surface. This can be particularly helpful when quantifying solar access of key spaces and surfaces to allow sufficient sun exposure for solar panels and plants, or provide adequate shading for people within a space.
86. Byran Lighting/D Analysis: A Compariso 87. Bohre ‘Atmospher TheOpticsE 88. Long, Luminous E 89. (2009) “Lumiance” Design Glo http://www com/en/kb glossary/ill html 90. Long, Luminous E 91. (2009) “Illumiance Design Glo http://www com/en/kb glossary/ill html
!Methods!55
Figure&3.33: Multimodal Shortest Path Tree of Portland, Oregon. Public transit branches are coloured red, while walking branches are coloured black. The width of a branch corresponds to the number of shortest paths that travel through that branch. Source: <http://graphserver.sourceforge.net/ gallery.html> Figure&3.34: Minimum Spanning Tree Source: <http://www. flickr.com/photos/ ethanhein/ 2306994386/>
Graph Theory
stein, Eric raph." From d - Wolfram urce <http:// rld.wolfram. Graph.html> a, S. (2007) ns of Graph urnal of the Society for nd Applied atics Vol. 11 No. be, A.; et.al 992) Spatial aunay: Sur s: Concepts ide, Izvestia plications of Nauk SSSR, oi Diagrams Matematichestvennykh 3–800, 1934 e, D. et. al. ocol Design c Delaunay iangulation stein, Eric "Minimum nning Tree." MathWorld olfram Web rce <http:// rld.wolfram. imumSpangTree.html> gewick, R. orithms, 4th Edition 56!Collective Ecologies
Introduction In mathematics and computer science, graph theory is the study of mathematical structures used to model relationships between entities.92 Many practical problems can be represented by graphs to demonstrate pairwise relations among objects and to process dynamics in physical, biological, social and information systems.93 A graph is constructed of ‘nodes’ representing objects and ‘edges’ demonstrating their connections. We utilise graph theory and its subsets in several portions of our project, for optimisation of networks, site tessellation, and to establish hierarchies within the system. Shortest path Within graph theory, Dijkstra’s or Bellman-Ford’s algorithms can be utilised to establish the shortest path between a given set of nodes so that the sum of the lengths of its constituent edges is minimised. These paths can represent physical entities such as distances on a map with intersections represented as nodes, and roads represented as edges to find the fastest route. Shortest Path can also represent abstract entities such that nodes embody states and edges describe their possible transitions, or it can be used to find an optimal sequence of choices to reach a certain goal state. Delaunay Triangulation The application of Delaunay Triangulation to a given set of nodes within a graph can be exploited to compute the most efficient paths for a Euclidean Minimum Spanning Tree through the same nodes.94 A triangulation is formed by constructing edges between pairs of nodes so that the
edges form a non-overlapping set of triangles. 95 Delaunay Triangulation ensures that the circumcircle associated with each triangle created contains no more than three nodes in its interior, maximising the minimum angle of each triangle within the triangulation96 and developing a characteristic that each connection is no longer than 2.418 times the Euclidean distance between the two nodes. Minimum Spanning Tree Given a connected set of points in graph, a minimum spanning tree of that graph is created by establishing the shortest possible length that connects all points in a set without creating any closed loops.97 A single graph can have many different spanning trees, and the minimal spanning tree is found by summing the lengths of each edge connection within each spanning tree and comparing them to one another.98
Figure&3.35: Space Syntax axial analysis using graph theory, Centrality to see the integration of different roads in London, UK Source: Modified Space Syntax <www. spacesyntax.com> Figure&3.36: InMaps graphical representation Kevin Sugrus Linkedlin social network. Showing the contact within your social clusters and how they are linked to each other, with colour coding for connections at each employer or social peergroup.
Centrality There are several methods for measuring the centrality of a node within a connected graph to determine its relative importance.99 This research was initially developed for social analysis to quantify the influence a person has within a social network, and has since been adapted to calculate road connectivity within urban networks. Degree Centrality The first method developed is conceptually the simplest for measuring importance within a graph, which is defined by the number of links incident upon a node in relation to others. If seen in terms of flow throughout the network, nodes with increased connectivity have higher levels of Degree Centrality, facilitating flow to them more often than others. Closeness Centrality In every connected graph there is a distance between all pair of nodes, this distance can be defined by the shortest path. The farness of a node is defined as the sum of its distances to all other nodes, and its closeness is defined as the inverse of the farness.100 With this you can define how central a node is in respect to all others. The lower this value is, the closer it is in average to the rest of the nodes.101 Our research will utilise this method for locating instances of key functions within the urban system. Betweenness Centrality The quantification of the number of times a node acts as a bridge along the shortest path between two other nodes
is known as Betweenness Centrality. The count of the node acting as a bridge is fractional, which means that if there is more than one possible shortest path this will get distributed between the different solutions. Nodes that have a high probability to occur on a path between two random nodes being evaluated will have a higher level of betweenness. Within our research this method measures the probability of a road being used in the network helping identify intersections that could be utilised as locations for points of interest in the system.
Source: Brand Tao <http://brandtao. wordpress. com/2011/04/18/ inmaps-social-network-connections-visualised/>
99. Newm (2010) Netw Introductio 100. Sabid (1966) ‘The Index of a G Psychometr Iss. 4 101. Newm (2005), "A m betweennes based on ra walks" Socia Vol. 27 No. !Methods!57
68. Weidmann, F. (2012) ‘The Urban Evolution of Doha’ METU.JFA 69. ESCWA (2012) The Demographic Profile of Qatar 70. Weidmann, F. (2012) ‘The Urban Evolution of Doha’ METU.JFA 71. Jaidah, I., et.al. (2009) The History of Qatari Architecture 72. Al Buainain, F. (1999) Urbanisation in Qatar: A Study of the Residential and Commercial Land Development in Doha City 73. Weidmann, F. (2012) ‘The Urban Evolution of Doha’ METU.JFA 74. Weidmann, F. (2012) ‘The Urban Evolution of Doha’ METU.JFA 75. Kardousha, Mahmoud M. Dr., 2009. Qatar Biodiversity 76. Kardousha, Mahmoud M. Dr., 2009. Qatar Biodiversity 77. Kardousha, Mahmoud M. Dr., 2009. Qatar Biodiversity 78. International Council on Monuments and Sites (1981) UNESCO World Heritage Centre - Justification 79. International Council on Monuments and Sites (1981) UNESCO World Heritage Centre - Justification 80. Gill, S. et.el. (2007) “Adapting Cities for climate Change: The Role of the Green Infrastructure.” Built Environment Vol 33 No. 1
81. Liu, K. et.el. (2003) Thermal Performance of Green Roofs Through Field Evaluation
Methods References 82. Wolfram, S. (2002) A New Kind of Science 83. Holland, J. (1998) Emergence: From Chaos to Order 84. Holland, J. (1998) Emergence: From Chaos to Order 85. Wolfram, S. (1983) "Statistical Mechanics of Cellular Automata" Reviews of Modern Physics Vol. 55 86. Byran, H. (2012) Lighting/Daylighting Analysis: A Comparison 87. Bohren, C. (1997) ‘Atmospheric Optics’ The Optics Encyclopedia 88. Long, W.F. (1994) Luminous Exitance 89. (2009) “Lumiance” Lighting Design Glossary, http://www.schorsch. com/en/kbase/glossary/illuminance.html 90. Long, W.F. (1994) Luminous Exitance 91. (2009) “Illumiance” Lighting Design Glossary, http://www.schorsch. com/en/kbase/glossary/illuminance.html 92. Weisstein, Eric W. "Graph." From MathWorld - Wolfram Web Resource <http://mathworld.wolfram.com/Graph.html> 93. Pirzada, S. (2007) 'Applications of Graph Theory' Journal of the Korean Society for Industrial and Applied Mathematics Vol. 11 No. 94. Okabe, A.; et.al (1992) Spatial Tessellations: Concepts and Applications of Voronoi Diagrams
95. B. Delaunay: Sur la sphère vide, Izvestia Akademii Nauk SSSR, Otdelenie Matematicheskikh i Estestvennykh Nauk, 7:793–800, 1934 96. Lee, D. et. al. (2007) Protocol Design for Dynamic Delaunay Triangulation 97. Weisstein, Eric W. "Minimum Spanning Tree." From MathWorld - A Wolfram Web Resource <http:// mathworld.wolfram.com/ MinimumSpanningTree.html> 98. Sedgewick, R. (2013) Algorithms, 4th Edition 99. Newman, M .E.J. (2010) Networks: An Introduction 100. Sabidussi, G. (1966) ‘The Centrality Index of a Graph’ Psychometrika Vol. 31, Iss. 4 101. Newman, M .E.J. (2005), "A measure of betweenness centrality based on random walks" Social Networks Vol. 27 No. 1
Experiments Wetlands p.64 Analysis of Streets and Public Spaces p.76 Subdivision and Integration p.80
Experiments Overview The possibility of moving away from reliance on desalination plants and towards localized water treatment in constructed wetlands is examined through analysing their spatial requirements within the urban context and possible integration within architecture. These approaches, coupled with analysis of Shibam, Yemen, demonstrate strategies for urban organisation and building morphologies which enable better performance in the harsh climatic conditions similar to those seen in Doha, Qatar. It further informs strategies for developing relationships between locations of interest in a network and their level of connectivity within an urban system, leading to experiments in patch development focusing on the affects patterns of subdivisions have on levels of connectivity within networks.
Wetlands A driver for a new urban morphology Photograph(4.24: Aerial view of Jebel Ali, Power and Desalination Plant, UAE Source:< http://images. cfa-uat.com/gallery/ index.php/Grace/ Energy-and-Industrial/Jebel-Ali-Power-and-Desalination-Plant_UAE
Photograph(4.25: Constructed wetlands in Houtan Park, Shangai, China Source:< http://www. phaidon.com>
Impact at City Scale
Oirschot, Certificering nwaterzuivgssystemen. 64!Collective Ecologies
Overview Qatari daily water consumption per capita can be decomposed into several categories. (Fig. 4.37) The first distinction made from this breakdown is the vast difference between consumption that necessitates potable water (8.6L) with those capable of utilising non-potable water (421.4L). Of the average 430L used in Qatar, per capita, per day, 77% (331L) of the waste water output can be treated and used for supplying services that can use non-potable water. This supply of treatable water is high in comparison to the United Kingdom and Australia, which only would be able to reintegrate 42% of their waste water. (Fig. 4.38) Focusing on recycling water through the use of constructed wetlands, it is critical to analyse its potential integration within building and urban morphology. Urban tissue samples varying in densities are tested to examine the spatial requirements necessary to purify grey water output at the levels found in Qatar. They are represented as a percentage of area needed for constructed wetlands to meet the needs of population densities within tissue samples taken from Manhattan, Frankfurt, Masdar, Islington (London), Amsterdam and Doha. (Fig. 4.39)
Parameters Given that 1m2 of subsurface constructed wetlands can purify 10L of water per day,102 wetlands within Doha would therefore require 33.1m2 of wetland per capita to treat their daily wastewater output of 331L. In order to account of worst case scenarios this area is increased to 40m2. Qualities Measured To compare the amount of wetland required for each 500x500m patch, the amount of area required for wastewater treatment is kept constant at 40m2 per capita, with each city sample alternating their density values accordingly. Conclusions Analysis of each sample shows that wetland requirements range from 30% to 40% of the entire patch, a relatively high amount compared to the available build area. Integrating wetlands at only ground level is viable, but would have a large impact on the urban context. In order to minimise this result, constructed wetlands can be integrated within the buildings to minimise their footprint on the overall site.
Fresh Water (potable)
2% - 8.6L
8.6L - 2%
Cooking & Drinking
12.9L - 3%
Floor Cleaning
21.5L - 5%
Garden Watering
98% - 421.4L
Clothes Washing
12.9L - 3%
Dish Washing
43L - 10%
Personal Washing Bathing Toilet
12%
51.6L
8.6L - 2%
Car Washing Treated Water (non-potable)
Lost
90.3L - 21
%
Grey Water Treatment (Wetlands)
331.1L
Figure(4.37: Analysis of the Water breakdown per person in Qatar. The diagram shows that only 2% of the water income needs to be fresh water and that 77% of the water outcome is grey water, therefore can be reintegrated into the system using wetlands.
77%
184.9L - 43% 47.3L - 11%
Black Water Treatment (External)
47.3L
11%
430L 161L
77%
101L
Grey Water
42% Qatar
United Kingdom
Australia
53%
47% Wetlands Impact
18%
Islington Density(p/ha) 143
Amsterdam Density(p/ha) 55
33%
36%
Frankfurt Density(p/ha) 100
42%
Doha Density(p/ha) 109
Figure(4.38: Comparison between cities with the amount of water that can be re-integrated into the system per day, considering the grey water produced. Each of the cities with different water use per capita.
Figure(4.39: Impact of wetlands considering the Qatar water consumption (430L per person/ per day) in cities with different densities.
Manhattan Density(p/ha) 162
28% Masdar Density(p/ha) 83
!Experiments!65
Photograph&4.26: Typha Domingensis selected plant specie for the project. Source: <www. ecohusky.uconn.edu> Photograph&4.27: Phragmites Australis, selected plant specie for the project. Source: Alan Cressler http://www.flickr. com/photos/alan_ cressler/479137579/ lightbox/ Photograph&4.28: Juncus Rigidus selected plant specie for the project. Source: <www. ecohusky.uconn.edu>
Ecology
Figure&4.40: Simplified Pollutant Removal Mechanism in wetlands. Source: UN-HABITAT, 2008. Constructed Wetlands Manual. UN-HABITAT Water for Asian Cities Programme Nepal, Kathmandu.
s, J.B. et.el. ) Guidance Manual for d Wetlands s, J.B. et.el. Constructed s and Links Sustainable ge Systems 66!Collective Ecologies
Strategies for developing wetlands within Qatar must address several issues to ensure viability within such a harsh climate. Extreme sun exposure, dryness, and heat can limit options for plant selection and types of constructed wetland systems. Focus is placed on integrating native and regional vegetation, to ensure robustness within the severe arid climate. Wetlands consist of a multitude of plant species with capabilities of breaking down pollutants through biological, chemical and physical processes which interact in a complex fashion to filter waste water. Vegetation absorbs dissolved inorganic nutrients such as ammonia, nitrates, and phosphates, incorporating them into their tissue and digested further by bacteria and fungi which utilise their carbon compounds and nutrients.103 These processes occur most rapidly in high temperatures, as it stimulates microbial activity,104 idea for an area with continual elevated heat such at Qatar. Of these most abundant species found in the within the region, three are commonly used in constructed wetland filtering: Phragmites Australis, Typha Domingensis and Juncus Rigidus (Fig. 4.41). They range in characteristics from full sun exposure to full shade, enabling coverage within the heterogeneous typologies found in urban systems.
Volatisation Water Inlet
Plant Metabolism
Roots Filtration & Absortion Water Outlet
Sediment
P
Bacterial Degradation
Sedimentation, precipitation & absortion
Simplified Pollutant (P) Removal Mechanism
Wastewater Constituents Removal Mechanism Suspended Solids
Soluble organics
Phosphorous
Sedimentation
Adsorption and cation exchange
Filtration
Complexation Metals
Aerobic microbial degradation Anaerobic microbial degradation
Plant uptake
Matrix sorption
Microbial Oxidation /reduction
Plant uptake
Sedimentation
Ammonification followed by microbial nitrification
Filtration
Denitrification Nitrogen
Precipitation
Source: UN-HABITAT, 2008. Constructed Wetlands Manual. UN-HABITAT Water for Asian Cities Programme Nepal, Kathmandu.
Natural die – off Pathogens
Plant uptake
Table&4.3: Pollutant removal mechanism in constructed wetlands
Predation UV irradiation (SF system)
Matrix adsorption
Excretion of antibiotics from roots of macrophytes
Ammonia volatilization (mostly in SF system)
Scientific Name
Vernacular Name
Exist in Abu Nakhla
Schoenoplectus spp.
Clumbrush species
No
Iris pseudacorus
Yellow iris
No
Typha latifolia
Common reedmace
Yes
Carex spp.
Sedge species
No
Sagittarius spp.
Arrowhead species
No
Juncus spp.
Rush species
Yes
Phragmites australis
Common reed
Yes
Butomus umbellatus
Flowering rush
No
Phalaris arundinacea
Reed canary grass
No
Acorus calamus
Sweet - flag
No
Table&4.4: Common species used in constructed wetlands, highlighting the ones with vernacular presence in Abu Nakhla Wetland, Qatar Sources: J. B. Ellis, et. al., “Constructed Wetlands and Links with Sustainable Drainage Systems” / Kardousha, Mahmoud M. Dr., 2009. Qatar Biodiversity
80%
66%
100%
3-4m 2-3m
Figure&4.41: Selected plant species for the development of constructed sub-surface wetlands in the project, and its main characteristics.
1m
Phragmites Australis Exposure Tolerance: Average Height: Flowers: Characteristics:
Nearly Full Sun 2m Yes Highly Invasive
Typha Domingensis Exposure Tolerance: Average Height: Flowers: Characteristics:
Full Sun 3m Yes Dense & Dominant
Juncus Rigidus Exposure Tolerance: Average Height: Flowers: Characteristics:
Full or Partial Sun 0.5 - 1 m No Aridity Tolerance
!Experiments!67
One Household
Figure&4.42: Initial state of wetland impact considered for the experiments
10m
10m
12m
3 Persons Household size: 100m2 Wetland per person: 40m2 Wetland per household: 120m2
Building Morphology Overview Integration of constructed wetlands within buildings explores the potentials to minimise impact on the ground level and allow for increased overall density within the urban system. Additionally, it can offer local treatment of grey water, minimising the amount of continual flow throughout the hydrological system. Parameters In consideration of Dohaâ&#x20AC;&#x2122;s projected decrease in average household size from eight to three people by 2030,105 the 40m2 of constructed wetland required per capita amounts to 120m2 per household and will be utilised throughout our subsequent experiments.
SDP (2009) onal Vision 2030 68!Collective Ecologies
Experiment 1 Exploring the relationships between constructed wetlands and built area is important when developing an understanding of the impact vertical growth has at ground level. Initial explorations serve as a guideline for the further development of an algorithm that can couple individual households with constructed wetlands needed to sustain them. Impact of Wetland on Ground The experiment begins with one household and the accompanying constructed wetland area required. As households begin to be added in the z-axis, the wetland area increases on the x and y axes at ground level (Fig. 4.43). Impact of Wetland on Roof A small script was developed which scales the roof uniformly to fit the area required for the constructed
wetland. As the number of households increase in the z-axis, the roof scales horizontally to accommodate the needs for the entire building (Fig. 4.43). Experiment 2 By relying solely on ground level or roof constructed wetlands, Experiment 1 demonstrated that vertical stacking is constrained to handle only five households, keeping densities fairly low at only 15 people per 700m2. To enable additional increases in density, this experiment aims to study the integration of constructed wetlands within a building footprint through vertical stacking and patterning of three by three households. Starting with eight households and a centre core, additional floors are added, and households start to be removed and replaced by constructed wetlands as required to sustain the density of the building. (Fig. 4.44) Qualities Measured Ratios of required wetland area/built area Conclusions The geometry developed in the previous experiment proved to not be architecturally viable for a dense urban system. However, it helped establish a correlation between the building morphology and constraints brought by constructed wetlands. Experiment 2 introduces new geometrical relationships between the building and pockets of constructed wetland to sustain higher densities. The porosity of the building therefore is driven by necessities brought by the constructed wetlands, representing the water consumption that each building has.
Experiment 01 Impact of Wetlands On the Ground
Impact of Wetlands On the Roof
15 Persons Number of households: 5 Number of Floors: 5 Wetland required: 600m2 z x
15 Persons Number of households: 5 Number of Floors: 5 Wetland required: 600m2 z
y
x
Figure&4.43: Wetlands impact on ground and roof.
y
Experiment 02 Initial State
One Floor
24 Persons Number of households: 8 Wetland required: 960m2 Actual Wetland: 900m2 Spare Wetland: -60m2
Two Floors
21 Persons Number of households: 7 Wetland required: 840m2 Actual Wetland: 1000m2 Spare Wetland: 160m2
Figure&4.44: Integration of wetlands within a building
Three Floors
33 Persons Number of households: 11 Wetland required: 1320m2 Actual Wetland: 1400m2 Spare Wetland: 80m2
Four Floors
48 Persons Number of households: 15 Wetland required: 1800m2 Actual Wetland: 1800m2 Spare Wetland: 0m2
Five Floors
57 Persons Number of households: 19 Wetland required: 2280m2 Actual Wetland: 2200m2 Spare Wetland: -80m2
69 Persons Number of households: 23 Wetland required: 2640m2 Actual Wetland: 2700m2 Spare Wetland: 60m2
!Experiments!69
Experiment 03 Integration of wetlands within the building
Initial State Case 016
Figure&4.45: Resulting buildings considering the integration of wetlands within buildings using computational methods (Cellular Automaton). Experiment 03
Second Generation Case 016_Rule 011
Figure&4.46: Example of an Initial state and next 2 generation applied in the experiment 03
Build Volume: 29700.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 79 People: 237 Wetland surface area needed: 9480 m2 Actual wetland in the building: 8100.0 m2 Wetland difference: 1380.0 m2
Third Generation Case 016_Rule 011
Rule 011
Experiment 3 Continued from Experiment 2, the logic of constructed wetland integration within the building is further explored through a systematic approach to computation. Cellular automaton allows for ratios to be established between states of built (households) and unbuilt (wetlands) through the introduction of rules for patterning the development of the building. The rule set to drive a cellular automaton can be read from the bottom three cells, comprising the configuration of states for the centre cell, and its two immediate neighbour cells. There are 23 = 8 possible configurations a cell can take in relation to its neighbours. The fourth cell above this configuration specifies the state the centre cell will take in the next generation resulting in 28 = 256 possible elementary cellular automata rules. (Fig. Rule 11) Each time the experiment is ran it starts in one of a possible 28 = 256 initial case states, with each subsequent generation stacked on top of the previous. (Fig. 4.47) Each of these 256 initial case states were tested with each set of 256 cellular automata rules. The resulting 65,536 building possible outcomes were evaluated and graphed, and a small percentage (0.037%) of which are represented from the results of Case 16 on the following pages. (Fig. 4.53) 70!Collective Ecologies
Qualities Measured Ratios of wetland area/built area Production of water Density
Twentieth Generation
Flat Cellular Automata Figure&4.47: Twentieth Generation:
Figure&4.48: Flat Cellular Automaton:
Throughout the experiments generations were kept constant at 20 generations to represent a mid-high rise building.
Building Core
Seen as a sequence of generations from top to bottom, CA’s can begin to develop patterns based on their CA rule
The Facade Wraps Around the Core. Figure&4.49: Building Core:
Figure&4.50: The facades wrap around the core:
To ensure viability of the design, each tower includes a consistent ‘Building Core’ allowing for basic elements such as stairwells and utilities to be included which are necessary for a functional tower.
The Facade Wraps Around the Core.
Transitioning from the 2D structure of wetlands and households into a 3D tower is achieved by wrapping its morphology around the building core until both ends connect together.
The Facade Wraps Around the Core. Figure&4.51: The facades wrap around the core.
Figure&4.52: The facades wrap around the core.
!Experiments!71
Figure&4.53: Some of the resulting buildings considering the integration of wetlands. Experiment 03
Rule 000 Build Volume: 6300.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 1 People: 3 Wetland surface area needed: 120 m2 Actual wetland in the building: 15900.0 m2 Wetland difference: -15780.0 m2
Rule 007 Build Volume: 30000.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 80 People: 240 Wetland surface area needed: 9600 m2 Actual wetland in the building: 8000.0 m2 Wetland difference: 1600.0 m2
Rule 013 Build Volume: 29100.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 77 People: 231 Wetland surface area needed: 9240 m2 Actual wetland in the building: 8300.0 m2 Wetland difference: 940.0 m2
Rule 037 Build Volume: 24300.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 61 People: 183 Wetland surface area needed: 7320 m2 Actual wetland in the building: 9900.0 m2 Wetland difference: -2580.0 m2
72!Collective Ecologies
Rule 006 Build Volume: 15000.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 30 People: 90 Wetland surface area needed: 3600 m2 Actual wetland in the building: 13000.0 m2 Wetland difference: -9400.0 m2
Rule 011 Build Volume: 29700.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 79 People: 237 Wetland surface area needed: 9480 m2 Actual wetland in the building: 8100.0 m2 Wetland difference: 1380.0 m2
Rule 014 Build Volume: 17700.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 39 People: 117 Wetland surface area needed: 4680 m2 Actual wetland in the building: 12100.0 m2 Wetland difference: -7420.0 m2
Rule 058 Build Volume: 28200.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 74 People: 222 Wetland surface area needed: 8880 m2 Actual wetland in the building: 8600.0 m2 Wetland difference: 280.0 m2
Rule 062 Build Volume: 33600.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 92 People: 276 Wetland surface area needed: 11040 m2 Actual wetland in the building: 6800.0 m2 Wetland difference: 4240.0 m2
Rule 087 Build Volume: 30300.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 81 People: 243 Wetland surface area needed: 9720 m2 Actual wetland in the building: 7900.0 m2 Wetland difference: 1820.0 m2
Rule 101 Build Volume: 30000.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 80 People: 240 Wetland surface area needed: 9600 m2 Actual wetland in the building: 8000.0 m2 Wetland difference: 1600.0 m2
Rule 155 Build Volume: 43500.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 125 People: 375 Wetland surface area needed: 15000 m2 Actual wetland in the building: 3500.0 m2 Wetland difference: 11500.0 m2
Rule 075 Build Volume: 29100.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 77 People: 231 Wetland surface area needed: 9240 m2 Actual wetland in the building: 8300.0 m2 Wetland difference: 940.0 m2
Rule 094 Build Volume: 29400.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 78 People: 234 Wetland surface area needed: 9360 m2 Actual wetland in the building: 8200.0 m2 Wetland difference: 1160.0 m2
Rule 124 Build Volume: 31500.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 85 People: 255 Wetland surface area needed: 10200 m2 Actual wetland in the building: 7500.0 m2 Wetland difference: 2700.0 m2
Rule 161 Build Volume: 25800.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 66 People: 198 Wetland surface area needed: 7920 m2 Actual wetland in the building: 9400.0 m2 Wetland difference: -1480.0 m2
!Experiments!73
Case 44 150 135
Case 170
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64
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74!Collective Ecologies
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Figure&4.54: Graphs, analysis of the resulting buildings versus the number of buildings with different initial states.
Case 43
Percentage of Wetland Area (m2)
Percentage of Wetland Area (m2)
Conclusion: Through this experiment, an evaluation of the results can establish the most successful cases based on chosen criteria. From the 65,536 buildings created and analysed through cellular automaton, we noticed several distinct groupings based on their ratios of wetland to built area. One of the distinct typologies found were those that can treat more wastewater than what it actually produces. These buildings have the disadvantage of being extremely low in density, but on the other hand they can be integrated into areas where the other typologies need assistance of additional water treatment. On the opposite spectrum of building typologies analysed were those that resemble urban residential blocks in typical urban systems. These typologies are high in density, but lack the constructed wetlands needed to support the treatment of its own waste water. The remaining building typologies are capable of producing just above or below the amount of wastewater that they are capable to recycle.
Analysis of the 256 initial states within each of the 256 cases studies presented the percentage ratios of wetland integration within building morphology, resulting in four common types of graph dispersals. Case 44 represents graphs with a dispersed bell curve, indicating the ratios were distributed fairly even through the building typology. Case 43 demonstrates graphs which had a tighter distribution, representing a higher level of building ratios within the midrange of wetland dispersal. Case 170 illustrates graphs with clustered dispersals primarily in mid-range ratios and the two extremes of the graph. Lastly, Case 255 exhibits graph types with distribution predominantly in the low level of integration within buildings. Evaluations of these building to wetland performance ratios and their accompanying graphs allowed for the targeting of building typologies appropriate for sustaining their water treatment requirements.
!Experiments!75
Analysis of Streets and Public Spaces The case study of Shibam, Yemen Photograph)4.29: Aerial view of Shibam, Yemen Source: <http:// webodysseum.com/art/ shibam-the-city-madeout-of-mud-bricks/>
Overview Shibamâ&#x20AC;&#x2122;s unique layout and morphology enables it be well connected and able to handle sun exposure and high temperatures within an extreme arid region. Through analysing these characteristics, geometric ratios are abstracted, and quantifiable data is collected, which can be utilised to drive network layout and building morphologies within similar climatic conditions, such as Doha, Qatar. Study 1: Network Analysis Methods for analysing degree, closeness and betweenness centrality within networks measure the relative level of connectivity and importance of a node within a graph. Utilising these techniques creates an understanding of the network topology within Shibam and the impact or correlation it might have on the location of public squares or important buildings. Degree Centrality The diagram analysis demonstrates clearly that there are four highly connected vertices, all of which are nodes representing public squares. (Fig 4.55) The bar chart demonstrates that many nodes are connected to only one additional neighbour, meaning there is a high level of impasse streets. Additionally, a majority of the nodes connect to three other neighbours, signifying that many intersections connect only three roads in the network. (Fig 4.56) Closeness Centrality The central public square in Shibam contains two highly integrated nodes, with additional surrounding nodes decreasing in value as they move away from this central 76!Collective Ecologies
point. (Fig 4.57) Analysis of the bar chart reveals the integration values of the nodes follow a bell curve, with very few nodes being highly integrated and very little nodes being hardly integrated. (Fig 4.58) This signifies that a majority of Shibam is fairly evenly connected with a few main points of interest and just several areas that are isolated. Betweenness Centrality The importance a node has within the network can be measured by the probability it has of being used to pass from one node to any other. The bar chart reveals that there are a few nodes which have an extremely high likelihood of being used within Shibamâ&#x20AC;&#x2122;s network. (Fig 4.60) Analysis of the diagram reveals that these nodes are located within the public squares and receive a high level of traffic through them. (Fig.4.59) Qualities Measured: Betweenness Centrality Closeness Centrality Degree Centrality Observations and Conclusions All of the centrality analysis clearly demonstrates two primary locations within Shibamâ&#x20AC;&#x2122;s network. These two public squares contain a majority of the activity within the city and demonstrate a correlation between the network topology and the location of its architecture, primarily important points of interest such as mosques and areas where markets congregate.
Degree Centrality Figure)4.55: Diagram of most integrated nodes in Shibam using Degree Centrality analysis (Graph Theory)
Degree Centrality Number of Nodes
100 80 60
Figure)4.56: Graph, Number of nodes versus degree values, resulting from Degree Centrality analysis (Graph Theory)
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Closeness Centrality Figure)4.57: Diagram of most integrated nodes in Shibam using Closeness Centrality analysis (Graph Theory)
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Figure)4.58: Graph, Number of nodes versus centrality values resulting from Closeness Centrality analysis (Graph Theory)
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Betweenness Centrality Figure)4.59: Diagram of most integrated nodes in Shibam using Betweenness Centrality analysis (Graph Theory)
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Figure)4.60: Graph, Number of nodes versus centrality values resulting from Closeness Centrality analysis (Graph Theory)
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!Experiments!77
Shibam Figure&4.61: Top view plan of Shibam .
i.
Figure&4.62: Analysis of Shibam streets width
A
ii.
iii.
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3.46m
Entrance
N
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Figure&4.63: Space A: orientation North-South. Analysis of the main public spaces in Shibam,
Figure&4.64: Space B: orientation East-West. Analysis of the main public spaces in Shibam,
A 3542m2
Study 2: Solar Exposure Studies Analysis of solar exposure levels throughout the year within Shibamâ&#x20AC;&#x2122;s public squares and streets will establish strategies for developing usable outdoor public spaces and promote pedestrian street use. Investigations into the two main public squares demonstrate the impacts of how orientation and geometry influence the use of the spaces throughout the seasons. Examinations of the street network will provide insight into how its organization can influence shading conditions. Located in the centre of Shibam, the first public space analysed is located near the centre of the city, its orientation is along the north-south axis and is located adjacent to the largest mosque in Shibam. (Fig. 4.63) To the south east of this space another public square is located which is the largest open space within the city, and has approximately a 2:1 width to length ratio, with its geometry primarily facing towards the east-west axis. (Fig. 4.64)
78!Collective Ecologies
B 4331m2
Qualities Measured: Average number of sunlight access hours. Observations and Conclusions Solar analysis studies reveal that the orientation of the central public square provides sun protection year round through shading provided from adjacent buildings along the East and West edges. (Fig. 4.65) This strategy limits exposure to only 4 hours of direct sunlight throughout the day, with the majority of this exposure confined to areas closest to the street intersections. The southeast public square however is allowed access to sunlight year round, with daily exposures ranging from 7-13 hours during the summer and only 4-8 hours during the winter. Extreme solar exposure is not desirable during the summer months, but is welcomed within the public square during the winter as temperatures fall to a 10-15 °C average. Further analysis into the solar exposure maps reveals additional strategies within the street networks of Shibam. The grid has been massaged into a wavy set of non-linear
Figure&4.65: Sun exposure analysis for different seasons in Shibam. Software used: Ladybug for Grasshopper
roads which is the key to its successful shading qualities. The buildings have orchestrated their positions to avoid similarly aligned facades and street widths, ensuring sun exposure for only minimal periods of time throughout the day. This arrangement, coupled with building heights, provides a nearly completely shaded pedestrian street environment throughout the entire year. The few streets that demonstrate higher levels of exposure tend to be along extended stretches of the east-west axis, creating seasonal network systems which provide pathways of preferable climatic conditions throughout extremes of both hot and cool weather.
Photograph&4.30: Shibamâ&#x20AC;&#x2122;s streets. Source: UNESCO / Maria Gropa
!Experiments!79
Subdivision and Integration Recursive subdivision based on attractors and betweenness centrality analysis Influence of the attractor Figure'4.66: Example of subdivision experiment and analysis using Betweenness Centrality in a 500 x 500m patch, with attractors
Level 3 Level 2
Level 1
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Resulting Subdivision
Overview A systematic approach for developing a heterogeneous set of block types and network organisations is established through evaluation of block proximity to elements on the site. The initial experiment explores how subdivisions are controlled and manipulated through gradual, recursive iterations based on location in relation to a set attractor. The smaller the distance between a parcel and attractor, the further each parcel subdivides into subsequently smaller parcels. (Fig 4.67) The resulting network is evaluated with betweenness centrality to assess how integrated each of the nodes are within the overall network, mapping out the most connected nodes. Parameters Level of subdivision Amount of attractor lines Location of attractor lines Experiment A series of patches measuring 500x500 meters were evaluated to test the placement of attractor lines and their resulting subdivided quadrilateral parcels. This reveals how many levels of subdivision are required to reach the size of a 80!Collective Ecologies
block (150x70m), high-rise building footprints (90x90m) and low-rise building footprints (10x10m). Six studies were conducted with varying attractor positions, and two different starting conditions: a. The initial patch as one complete square b. The initial patch as a square separated into two triangles The resulting parcel distributions are analysed with Betweenness Centrality to measure the connectivity of each node. Observations Case 1 The analysis indicates that with a single linear attractor placed at the top of the patch, the most integrated nodes are in very similar locations for both case starting conditions. The topologies of the nodes differ however, with the recursive subdivision within the triangle being more integrated and more dispersed within the patch. (Fig. 4.68) Case 2 Placement of a single linear attractor through the middle of the patch demonstrates much different results in the level of connectivity between nodes. Within the patch subdividing a square, the most integrated nodes are located closer to the attractor, gradually minimising the level of connectivity as the distance from the centre of the attractor increases.
Recursive Subdivision of Square
Recursive Subdivision of Triangles Figure'4.67: Recursive subdivision logic for squares and triangles
Case 01_a
Case 01_b Figure'4.68: Betweenness centrality analysis of recursive subdivision experiments using squares and triangles.
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!Experiments!81
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Figure'4.69: Betweenness centrality analysis of recursive subdivision experiments using squares and triangles.
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However, the recursive subdivisions within the triangle patch establishes nodes that have connectivity levels dispersed in a non-uniform manor located both near and away from the attractor curve. (Fig. 4.68) Case 3 The location of a single linear attractor running diagonally through the patch results in most integrated node dispersal throughout any of the cases tested. Although the patch is highly connected, the most integrated nodes are all relatively close to each other in a uniform manor rather than distinct moments of dispersal across the site. This success however is not seen in the patch subdividing the triangles, which demonstrates almost the opposite behaviour, with very low connectivity in two opposite corners of the patch. Case 4 An additional attractor curve is incorporated to explore methods of achieving higher levels of distribution for integrated nodes. The placement of attractors at opposite 82!Collective Ecologies
Case 04_b
Double Attractor - Linear
ends of the patch demonstrates very similar results in both types of patches. They concentrate the most integrated nodes in the centre of the patch, with gradual dispersal out toward the edges. The subdivision of the triangle however disperses the subdivisions in a less homogeneous way while maintaining a high level of integration. Case 5 A third attractor is added, which decreases the amount of the most integrated nodes, but increases the overall connectivity levels. The dispersal is similar to the previous case, but with increased sub-divisions throughout the patch. The subdivision of the triangle patch disperses the more integrated areas throughout a larger portion of the site, establishing four zones of high connectivity. Case 6 The introduction of a non-linear attractor gives some insight into how parcel size behaves along curves and its affects the subsequent connectivity of the resulting nodes.
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The patches subdividing a square result in a clustering of nodes along the most planar portion of the attractor line. The opposite is true however for the patch subdividing triangles, in which the resulting sub divisions contain areas of highest integration where the angles of curvature along the attractor line are most intense. Conclusions These case studies, demonstrate that recursive subdivisions within the square and triangle patches lead to a series of unique network topologies with increased connectivity. Attractor curves, regardless of their placement, will establish further subdivided parcels and will return increased levels node connectivity within the network. Understanding and cataloguing these results will help inform strategies to influence and control areas of high connectivity in the development an integrated network.
!Experiments!83
Experiments References 102. van Oirschot, D. (2002) Certificering van plantenwaterzuiveringssystemen. 103. Ellis, J.B. et.el. (2003) Guidance Manual for Constructed Wetlands 104. Ellis, J.B. et.el. (2003) Constructed Wetlands and Links with Sustainable Drainage Systems 105. GSDP (2009) Qatar National Vision 2030
Design Proposal Site p.90 Cells p.92 Public Spaces p.100 Network Development p.106 Test Patch p.108 Building Typologies p.120 Urban Wetland Integration p.140 Conclusions p.145 Seasonal Adaptive Behaviour p.148
Design Proposal Overview The culmination of the previously explored methods and experiments leads to the development of a design proposal to address the issues presented within Doha, Qatar. Through implantation of these strategies on a chosen site, population densities are dispersed, networks are developed and optimised, and building typologies are positioned to create a system aimed at demonstrating the viability of the urban system.
Site Doha, Qatar Photograph(5.31: Doha skyline Source: <http://www. qia-qatar.com/content/ doha-city-tour>
Photograph(5.32: Contrast between the West-End building morphology (High rises) and the rest of the city. Source: Deep Ghosh <https://www.flickr. com/groups/1599245@ N24/>
The chosen site to test the urban system is located along the Qatari coastline of the Arabian Gulf, allowing for access to seaside winds and a relatively flat and empty patch of desert. Covering an area of 13.62km2, this patch will be designed to support 150,000 people at an average density of 109.8 per hectare, similar to rates found within central Doha. Located midway between two major Qatari cities, Doha and Al Khor, the site is subject to their continued outward expansion, leading to its increasing and density development in the near future.
90!Collective Ecologies
Figure(5.70: Aerial view of the site in relation to Doha Source: Google Earth
Site
Photograph(5.33: Aerial view of the site Source: A. Ahmed <http://static. panoramio.com
Figure(5.71: Site with measurements
2.96km
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!Design Proposal!91
Cells Cells as containers of information Figure&5.72: 3 different cell types with different ratios and wetland required.
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Cell density Population: Water usage per capita: Total water consumption: Wetlands surface area:
100 p/ha 2160 430 L/day 928800 L/day 86400 m2
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Cell density Population: Water usage per capita: Total water consumption: Wetlands surface area:
Cell Types With the site chosen and an overall desired density established, a systematic approach for dispersing population levels is developed, informing the resulting amount of wetland required to sustain them. Within a series of cells types, each cell represents a collection of information in regards to density, ratios of function type, and their consequential water consumption levels. (Fig 5.72) Analysis of tissue samples from Frankfurt, Manhattan and Amsterdam informed the characteristics of each of the cell types. Leading ‘Cell A’ to be primarily residential based, ‘Cell B’ to be mostly office based, and ‘Cell C’ to be comprised of evenly split function types. The distribution of cells on the site will allow for a variation of density levels and wetland dispersal within the urban system.
92!Collective Ecologies
162 p/ha 3500 430 L/day 1505000 L/day 140000 m2
Wetland Required
Cell density Population: Water usage per capita: Total water consumption: Wetlands surface area:
55 p/ha 1188 430 L/day 510840 L/day 47520 m2
Growth Strategy The growth strategy begins with the placement of a cell on the site from which to start from. Its cell type is randomly chosen and additional cells begin to connect based on preferential attachment rules. This procedure disperses population densities based levels found in surrounding neighbours, allowing for a gradual transition between areas of low and high density. The probability of the selection of a cell type for placement on the site is controlled through a weighted probability algorithm, adjusting the ratios between cell types on the site in order to achieve an overall desired population level.
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Figure&5.73: Rules defining preferential attachment
Preferrential Attachment Rules
Figure&5.74: Steps for cells aggregation process.
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!Design Proposal!93
Figure&5.75: Three different starting points for the cell aggregation process.
Study 00
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Population : 150,916 Number of Cell types Cell A : 28 Cell B : 16 Cell C : 29
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)1 Table&5.5: Possible cells distributions, highlighting the three selected ones to run the experiments using different starting points
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Cell Ratios Each cell covers an area of 21 hectares, permitting a total 73 cells to fit on the site. This allows for a population range from 86,724 up to 255,500 depending on the ratios of the differing cells. All combinations of cell types were calculated and their resulting population levels were assessed to find all arrangements that come within 1% of the target population range. (Table 5.5) Of these, three combinations are further evaluated, two that are closest to the targeted population goal, and one which had the lowest standard deviation between the ratios of cell types throughout the site.
94!Collective Ecologies
Study 03 Population : 150,916 Number of Cell types Cell A : 28 Cell B : 16 Cell C : 29
)1
Study 06
Population : 150,916 Number of Cell types Cell A : 28 Cell B : 16 Cell C : 29
)2
Aggregation and Starting Points Three starting points were established to test the behaviour of the aggregation of cells throughout the site. Locating points in the centre, Northwest and Southeast corners, these points examine how the relationship between the starting point and the border condition has an effect in the organisation of cell types. (Fig 5.75) Each of starting positions develops a unique pattern of dispersal, either flowing along the border condition or through the middle of the site. Variations in the ratios of cell types allow for some patters to emerge, with some studies having more defined clustering of types, and others developing a more mixed distribution. (Fig 5.76)
Population : 150,569 Number of Cell types Cell A : 11 Cell B : 23 Cell C : 39
Study 01
Study 02
)0
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Population : 150,053 Number of Cell types Cell A : 39 Cell B : 11 Cell C : 29
Study 04
Figure&5.76: Experiments based on the three selected distribution running from three different starting points
Study 05
Population : 150,569 Number of Cell types Cell A : 11 Cell B : 23 Cell C : 39
Population : 150,053 Number of Cell types Cell A : 39 Cell B : 11 Cell C : 29
)1
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Study 07
Population : 150,569 Number of Cell types Cell A : 11 Cell B : 23 Cell C : 39
Study 08
)2
Population : 150,053 Number of Cell types Cell A : 39 Cell B : 11 Cell C : 29
)2
!Design Proposal!95
Example 1 Figure&5.77: Three different examples for clustering
Example 2
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Figure&5.78: Clustering studies
96!Collective Ecologies
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Clustering Cells are coupled together to develop regional clusters that can collectively sustain themselves, permitting autonomy from other clusters in the treatment, storage and reintegration of water. Each cluster allows for the urban systems within them to collectively accommodate fluctuations in population or function within the cells of the cluster. Cells cluster with their neighbours in the order they were placed on the site until they reach a collective population of 7000-9000 people. (Fig. 5.77) In most studies, a range of 3-8 cells are required to meet this population level within a cluster.(Fig 5.78) Clusters with the most similar amounts of cells within them also have comparable surface areas. (Fig.5.79) Analysis of the clustering studies shows that Study 05 demonstrates the most similarity in cluster types, which will maintain density variations, allowing it to develop a heterogeneous urban landscape.
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Figure&5.79: Analysis of clustering studies.
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Number of clustered cells !Design Proposal!97
Clustered Site Through this systematic distribution of population across the site, the information that is coupled with the resulting clusters informs parameters which will drive the manner in which the site will develop. Factors such as population, density, surface area, buildable area and wetland impact will continually be referenced from these studies throughout the development of the urban system.
Study _ 05
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!7 )9
)7
!5 !0 )4 )8 )6 )2 !4 !1 )3 )5 )1 )0
125 Population 9008
75
Water Consumption 3873440 L
50 25 0
Available Wetland Area Needed
Cell A : 2 Cell B : 1 Cell C : 1
125 100
Population 9828 Water Consumption 4226040 L
25 0
Available Wetland Area Needed
Cell A : 4 Cell B : 0 Cell C : 1
Surface Area (hectares)
Surface Area (hectares) 98!Collective Ecologies
125
50
Population 8640
75
Water Consumption 3715200 L
50 25 0
Available Wetland Area Needed
Cell A : 4 Cell B : 0 Cell C : 0
125 Population 8036
75
Water Consumption 3455480 L
50 25 0
Available Wetland Area Needed
Water Consumption 4226040 L
50 25 0
Available Wetland Area Needed
Cell A : 4 Cell B : 0 Cell C : 1
150 125 100
Population 8036
75
Water Consumption 3455480 L
50 25 0
Available Wetland Area Needed
Cell A : 1 Cell B : 1 Cell C : 2
Cluster 6
150
100
Population 7668
75
Cluster 5
150
75
Surface Area (hectares)
150
Cluster 4
100
125 100
Cluster 03 Surface Area (hectares)
150
100
150
Cluster 02 Surface Area (hectares)
Cluster 01 Surface Area (hectares)
Figure&5.81: Analysis of clustered cells informs future development of the parcels on the site.
Cluster 00
Cell A : 1 Cell B : 1 Cell C : 2
Surface Area (hectares)
Figure&5.80: Selected clustering Cluster Analysis 73 individual cells grouped together into 19 clusters.
150 125 100
Population 9008
75
Water Consumption 3873440 L
50 25 0
Available Wetland Area Needed
Cell A : 2 Cell B : 1 Cell C : 1
150 125 Population 8640 Water Consumption 3715200 L
25 0
Available Wetland Area Needed
Cell A : 4 Cell B : 0 Cell C : 0
25 0
Population 9828 Water Consumption 4226040 L
25 0
Available Wetland Area Needed
Cell A : 4 Cell B : 0 Cell C : 1
Surface Area (hectares)
Surface Area (hectares)
125
50
Population 7668 Water Consumption 3297240 L
25 0
Available Wetland Area Needed
Cell A : 3 Cell B : 0 Cell C : 1
Surface Area (hectares)
Surface Area (hectares)
125
50
Population 3348 Water Consumption 1439640 L
25 0
Available Wetland Area Needed
Cell A : 1 Cell B : 0 Cell C : 1
Surface Area (hectares)
Surface Area (hectares)
125
50
Water Consumption 4449640 L
50 25 0
Available Wetland Area Needed
Cell A : 1 Cell B : 2 Cell C : 1
25 0
125 Population 1188
75
Water Consumption 510840 L
50 25 0
Available Wetland Area Needed
Cell A : 0 Cell B : 0 Cell C : 1
125 Population 9008
75
Water Consumption 3873440 L
50 25 0
Available Wetland Area Needed
Cell A : 1 Cell B : 2 Cell C : 2
150 125 100
Population 7668
75
Water Consumption 3297240 L
50 25 0
Available Wetland Area Needed
Cell A : 3 Cell B : 0 Cell C : 1
150 125 100
Population 8036
75
Water Consumption 3455480 L
50 25 0
Available Wetland Area Needed
Cell A : 1 Cell B : 1 Cell C : 2
Cluster 18
150
100
Available Wetland Area Needed
Cluster 15
150
100
Water Consumption 4960480 L
50
Cluster 17
150
75
Population 10348
75
Population 11536
75
Cluster 12
125 100
Cluster 16
100
125 100
Cluster 14
150
75
Cell A : 1 Cell B : 1 Cell C : 2
150
Cluster 13
100
Available Wetland Area Needed
Figure&5.82: Cluster analysis of selected clustering.
150
Cluster 11
150
75
Water Consumption 3455480 L
50
Cluster 10
100
Population 8036
75
Surface Area (hectares)
50
125 100
Surface Area (hectares)
75
150
Cell A : 2 Cell B : 1 Cell C : 1
Surface Area (hectares)
100
Cluster 09 Surface Area (hectares)
Cluster 08 Surface Area (hectares)
Surface Area (hectares)
Cluster 07
150 125 100
Population 2376
75
Water Consumption 1021680 L
50 25 0
Available Wetland Area Needed
Cell A : 0 Cell B : 0 Cell C : 2
!Design Proposal!99
Public Spaces Figure&5.83: Wetlands as a public park based on the most integrated nodes. The park is defining the subdivision as an attractor and density distribution
Low - Mid Rise
High Rise
Courtyards
Public Wetlands
Locating Public Wetlands Figure&5.84: Wetlands required for the site according to density.
Figure&5.85: Public wetlands percentage defining the public park.
100!Collective Ecologies
Overview Given that 40m2 of constructed wetland is required to treat the average daily grey water output per person, the amount of surface area to sustain 150,000 people would necessitate 36% of the entire site. Of this amount of required wetland, 60% will be integrated within buildings and courtyards, and the remaining 40% will be located at ground level as public wetlands. These public wetlands are usable parks that also act as water purification systems for neighbouring built morphologies. Therefore, their incorporation within the urban system should be within the most integrated parts of the site to minimise water flow distances throughout the system. Initial Parcellation Through the clustering of cells throughout the site, each cluster has individual water storage. In order to allow for shifts in density distribution and fluctuation of water demand, these storage points need to be interconnected to help each other overcome these variations. Storage points are connected through the application of Delaunay Triangulation which returns a triangular subdivision on the site through all of the points. (Fig.XX) These points are then further refined to more evenly and fully connect the site.
Surface Area of Wetland Required
36% Required
Surface Area of Public Wetland
36% Required 21% Buildings 15% Public
Water Route and Storage Points
Integration Analysis (Betweenness Centrality)
Re-adjustment of nodes to be part of the site boundary
Relocation of Storage Points
Connection of most Integrated nodes (Minimum Spaning Tree)
Wetland area required is spread along the most integrated part of the site
Figure&5.86: Work flow steps to define the public wetland and building density distribution.
15%
Height of building distribution in relation to the park
Low-Mid Rise
High Rise
Courtyard
Public Wetland
Public Wetland From this connected network, betweenness centrality is applied to identify the most integrated and traversed nodes within the site. (FigXX) These nodes, primarily located in the centre of the site and along the coastline, are then connected with a minimum spanning tree to establish the shortest possible network that connects all points in a set. (Fig XX) This connected network is what defines the location of our public wetland, ensuring high connectivity within the site. (Fig XX) Parcel Subdivision With the public wetland located within the site, a recursive subdivision algorithm was applied to diversify parcel size
Modification of building height distribution based on most integrated nodes of the site
Low-Mid Rise
High Rise
Courtyard
Public Wetland
throughout the site. Two approaches were considered and tested for determining block size. The initial approach established more connection points and resulted in smaller parcel sizes that were closer to the public wetlands. This method allowed for inhabitants of low rise typologies to more easily access the public wetlands. However, this decreased over all connection to the park, given that larger parcels which housed higher densities of inhabitants were located farther away from the public wetlands. (FigXX) The second method attempted to approach this condition by locating the high rise parcels nearest the most connected nodes within the site, with lower density parcels in less integrated areas. This provides the highest number of people to the most accessible areas of the site. !Design Proposal!101
Figure&5.87: Public squares based on Closeness Centrality,
Low - Mid Rise
High Rise
Courtyards
Public Wetland
Locating Public Squares Figure&5.88: Clustering used to analyse the integration
102!Collective Ecologies
Once the public wetland and initial subdivisions are established on the site, closeness centrality analysis of each cluster establishes the areas of highest connectivity (Fig. 5.89) for placement of public squares. With the locations of the public squares, each cluster is analysed further for additional subdivision, in a similar manner as the public wetlands. (Fig. 5.87) Parcel subdivisions within each cluster position the high rise parcels nearest the most connected nodes within the site, with lower density parcels in less integrated areas, generally further away from the public square. This allows for the highest number of people within the cluster to have access to their local public space.
Cluster Target
7000 People
Closeness Centrality Analysis per Cluster
Location of Public Squares Figure&5.89: Clustering analysis of integration with the public squares to define subdivision and density distribution.
low
high
Evaluationof public square within a cluster based on Closeness Centrality
low
high
Evaluation of the subdivided cluster based on Closeness Centrality
low
high
!Design Proposal!103
Final Subdivision, Public Squares and Park Figure&5.90: Merging public wetlands and pubic squares layer
Low - Mid Rise 5.4 km2 Courtyard 1.8 km2 High Rise 4.6 km2 Public Wetlands 1.8 km2 Total Surface Area
104!Collective Ecologies
13.6 km2
!Design Proposal!105
Network Development Differentiation of system hierarchies Photograph(5.34: Branching network of a tree Source: David Hulme <http://www.flickr. com/photos/davidhulme/5269425862/>
“
The construction and the structure of graphs or networks is the key to understanding the complex world around us.”
Figure(5.91: Betweenness centrality analysis
A hierarchy of three network typologies are established through evaluation of the parcel subdivisions across the site. The primary road network is informed through betweenness centrality analysis of the network, which finds the paths with the highest probability of being utilised when traversing from one node to another. This resulting network contains the most integrated paths, with a width of 22m. The secondary road network is based on the initial subdivision established through the Delaunay Triangulation, creating localized road connections that are 11.5m wide. Lastly a pedestrian network aims to have as many uninterrupted paths as possible while minimising intersections. These pathways are located along road networks and as dedicated pedestrian pathways 3.5m wide, to minimise sun exposure and promote use.
Albert-László Barabási, 2002
Betweenness Centrality Analysis on First Level of Subdivision
low
106!Collective Ecologies
high
Figure&5.92: Roads network based on integration analysis.
Primary
Secondary
Pedestrian
Public Wetland
Primary
Secondary
Pedestrian
2.50
3.25
building pedestrian
3.50
building
building
3.25
pedestrian
lane 1
3.25
lane 2
pedestrian
2.00 22.00
building
building 3.25
pedestrian
lane 2
3.25
lane 4
lane 1
3.50
lane 3
pedestrian
building
Figure&5.93: Sections of roads and streets based on downtown Doha
3.25
2.50
3.50
11.50
!Design Proposal!107
Test Patch System development
Figure&5.94: Outcome of network development, indicating the specific patch for further development
Public park and Public Spaces
Relationship of network integration and building height With each clusterâ&#x20AC;&#x2122;s subdivision established, information of the floor area and the wetland required for its population is utilised to develop each clusterâ&#x20AC;&#x2122;s urban morphology. (Fig 5.95) Each building typology is dispersed based on the parcel subdivisions throughout the clusters within the site. The level of integration each parcel subdivision has within the network is analysed and informs the extruded building height. This relationship between network integration and building heights allows for increased floor areas and higher densities within the most well-connected areas of the site. (Fig 5.96) 108!Collective Ecologies
Available Wetland Area In Buildings
Floor Area
Available Wetland Area In Buildings
Floor Area
450 400 350 300 250 200 150 100 50 0
Available Wetland Area In Buildings
Roads Integration Analysis low
Available Wetland Area In Buildings
high
Floor Area
450 400 350 300 250 200 150 100 50 0
Available Wetland Area In Buildings
Available Wetland Area In Buildings
Floor Area
Cluster 09
Floor Area
450 400 350 300 250 200 150 100 50 0
Cluster 12 Surface Area (hectares)
Surface Area (hectares)
Cluster 10 450 400 350 300 250 200 150 100 50 0
Floor Area
Surface Area (hectares)
450 400 350 300 250 200 150 100 50 0
Available Wetland Area In Buildings
450 400 350 300 250 200 150 100 50 0
Cluster 08 Surface Area (hectares)
Surface Area (hectares)
Cluster 07
Surface Area (hectares)
450 400 350 300 250 200 150 100 50 0
Figure&5.95: Cluster analysis
Cluster 06
Available Wetland Area In Buildings
Floor Area
Cluster 13 Surface Area (hectares)
450 400 350 300 250 200 150 100 50 0
Cluster 04 Surface Area (hectares)
Surface Area (hectares)
Cluster 02
Floor Area
Most Integrated Road Defining Height
450 400 350 300 250 200 150 100 50 0
Available Wetland Area In Buildings
Floor Area
Buildings Height Based on Roads Integration
Figure&5.96: Defining buildings height based on integration analysis of surrounding roads.
!Design Proposal!109
Figure&5.97: Heights gradients per typology
110!Collective Ecologies
Building Heights
20
Number of floors
18 16 14 12 10 8 6 4 2 0 Low Rise
Courtyards
High Rise
!Design Proposal!111
Figure&5.98: Outcome of building heights
Study A Study B
Evaluation of Pedestrian Network From the developed network and morphology, two tissue samples within the patch were evaluated to analyse the amount influence building heights and street widths have on the resulting sun exposure levels within the site. Focusing on Study A, high density typologies arenâ&#x20AC;&#x2122;t provided enough access to sun in both the summer and winter because of very narrow adjacent roads. However Study B, comprised of primarily low rise typologies, demonstrates a more balanced exposure level, allowing some solar access in the winter season, yet still providing some shadows during the summer. (Fig. 5.99)
112!Collective Ecologies
Autumn
Figure&5.99: Network sun exposure studies
Autumn 13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
!Design Proposal!113
Figure&5.100: Close-up view of the patch
Optimisation of Pedestrian Network Figure&5.101: Street analysis of Shibam in different seasons
To better optimize solar exposure levels within the road Autumn networks, a small study examines the solar conditions at ground level based on street width and orientation (Fig. 5.102) Four test patches are developed and are evaluated for both winter and summer solar exposure. These eight tests contain a set of buildings 12 stories high, with street widths ranging from 6-24m. Analysis of these studies indicates how to develop a system of varying street widths to better control solar exposure and promote pedestrian use within a network.
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Autumn 13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
114!Collective Ecologies
Study 01 Street widths that are 6m wide provide shade throughout the year, with some solar access for 4-6 hours a day during the summer months.
Figure&5.102: Pedestrian roads solar analysis in different seasons with a width variation
Study 02 Doubling the width to 12m wide, the streets develop two distinct characteristics, almost completely shading the north-south streets for the entire year, with solar access only to streets running east-west during the summer months.
Study 03 At 18m wide, the street demonstrates very similar solar access to what occurs at a width of 12m. This allows for further expansion of widths on along the north-south streets, providing shade while allowing for additional wind flow.
Study 04 Widening the streets even further, to 24m, we find that the shading condition still remains along the north-south axis for a majority of the day, only being exposed for four hours a day
!Design Proposal!115
Figure'5.103: Patch network and tissue samples
Figure'5.104: Pedestrian roads optimisation logic according to orientation
Re-evaluated Network
Pedestrian Street Widths based on orientation
From the previous tests and analysis, east-west pedestrian streets demonstrate high levels of solar exposure, limiting their widths to expand to a maximum of 6m. North-south pedestrian streets however are able to increase up to 18m wide, while still providing sufficient shading conditions. Given the non-linearity of the streets throughout the site, their orientation varies to a great degree, alternating shading conditions throughout the lengths of many streets. (Fig. 5.104) An algorithm evaluates street orientation within the network and adjusts their widths accordingly to better accommodate or discourage solar access. These changes allow for both increased public space and better environmental conditions throughout the entire urban system. (Fig. 5.105)
3m 6.75 m
10.5 m
14.25 m
18 m
N 116!Collective Ecologies
Tissue Sample A Before
Tissue Sample A After
Figure'5.105: Pedestrian street tissue sample before and after optimisation
Tissue Sample B Before
Tissue Sample B After
!Design Proposal!117
Building Typologies Wetlands driving the building morphology
Figure'5.106: Distribution of building typologies
Overview Of the constructed wetland required to support the total population on the site, 40% has been integrated as public wetlands, leaving 60% to be integrated within buildings and courtyards. Figure'5.107: Percentages of required public wetland
Three building typologies are utilised on the site, each allowing for differing densities and capabilities of wetland integration within the building morphology. As seen in the previous Experiments chapter, cellular automaton is an appropriate tool for the quick development and analysis of the ratio between built area and required wetlands within a building. This strategy will be explored within additional typologies to test their viability of supporting populations within them.
Surface Area of Wetland
36% Required
15% Public
120!Collective Ecologies
Low Rise
Courtyard
High Rise Figure'5.108: Building typologies
Surface Area of Wetland
Private Wetlands / Buildings
Figure'5.109: Percentage of wetland integrated within buildings.
36% Required 21% Buildings
21%
!Design Proposal!121
100%
25-40%
9%
Fully Productive
Fitness Criteria
Least productive
Figure'5.110: Fitness criteria for selection of building morphologies.
Rule 000
Rule 255
Building Integration
Figure'5.111: Wetland impact per household
122!Collective Ecologies
Utilising cellular automaton, a catalogue of 256 possible building types were created and evaluated. The resulting building morphologies varied their capabilities of water treatment, from extremely productive, with 100% constructed wetland, to very unproductive, with only 9% constructed wetland integration. From the analysis of cluster water requirements, it was calculated that at least 30% of the building should contain constructed wetland in order to sustain its population. A fitness criteria requiring 25-40% of constructed wetland integration was established, refining the catalogue to 25 possible examples. These demonstrate various kinds of organizations within the building. Solar exposure studies are essential to establish whether these organizational layouts are viable for wetland growth. The following pages analyse these exposure levels but account for only the direct sunlight hours, Diffused Sky Radiation is not analysed but is also capable of being utilised for plant growth. Although the analysis indicates low access to light, this does not signify that growth is not viable, since diffused light also enters into the space.
One household
10m 10m 3 Persons Household size: 100m2 Wetland per person: 40m2 Wetland per household: 120m2
12m
Rule 121 Build Volume: 30000.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 80 People: 240 Wetland surface area needed: 9600 m2 Actual wetland in the building: 8000.0 m2 Wetland difference: 1600.0 m2
Rule 188 Build Volume: 30000.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 80 People: 240 Wetland surface area needed: 9600 m2 Actual wetland in the building: 8000.0 m2 Wetland difference: 1600.0 m2
Rule 222 Build Volume: 39000.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 110 People: 330 Wetland surface area needed: 13200 m2 Actual wetland in the building: 5000.0 m2 Wetland difference: 8200.0 m2
Rule 15 Build Volume: 44100.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 127 People: 381 Wetland surface area needed: 15240 m2 Actual wetland in the building: 3300.0 m2 Wetland difference: 11940.0 m2
Rule 139 Build Volume: 29700.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 79 People: 237 Wetland surface area needed: 9480 m2 Actual wetland in the building: 8100.0 m2 Wetland difference: 1380.0 m2
Figure'5.112: Building morphologies selection
Rule 195 Build Volume: 30000.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 80 People: 240 Wetland surface area needed: 9600 m2 Actual wetland in the building: 8000.0 m2 Wetland difference: 1600.0 m2
Rule 246 Build Volume: 44400.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 128 People: 384 Wetland surface area needed: 15360 m2 Actual wetland in the building: 3200.0 m2 Wetland difference: 12160.0 m2
Rule 109 Build Volume: 39600.0 m3 Volume Envolope: 18000 m3 Number of floors: 20 Houses: 112 People: 336 Wetland surface area needed: 13440 m2 Actual wetland in the building: 4800.0 m2 Wetland difference: 8640.0 m2
!Design Proposal!123
Sun Exposure Studies for Pockets Morphology Corner Pockets
Autumn
Winter 13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Spring
Summer 13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Autumn and winter demonstrate high levels of solar access, with the remainder of the year supplying sufficient levels of light into the space.
Interior Pockets
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Autumn
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Winter 13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Spring Interior Pockets drastically reduce the solar levels that penetrate into the building. There is almost no direct sunlight into the north openings. This is the worst position for wetlands out of the tested cases.
124!Collective Ecologies
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Summer 13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
East-West Strips
Winter
Autumn 13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Spring
Summer 13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
East-west strips provide the best scenario for solar access, especially during the winter months, with more than 10 hours of direct sunlight.
North-South Strips
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Autumn
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Winter 13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Spring Similar to the east-west strips, there is an overall high solar gain that is fairly constant throughout the year, with direct sun exposure between 4 and 8 hours a day.
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Summer 13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
!Design Proposal!125
Corner Pockets (2 Stories)
Winter
Autumn 13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Spring
Summer 13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
An increase in ceiling height allows for a substantial elevation in solar gain throughout all four seasons.
Interior Pockets (2 Stories)
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Autumn
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Winter 13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Spring Even though the ceiling height has doubled, its impact is fairly minimal, as this scenario still demonstrates poor sun exposure throughout the majority of the year.
126!Collective Ecologies
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Summer 13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
East-West Strips (2 Stories)
Winter
Autumn 13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Spring
Summer 13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
With extended ceiling height, the eastwest strip continues to demonstrate the best performance out of all the cases, allowing for deep penetration into the openings.
North-South Strips (2 Stories)
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Autumn
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Winter 13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Spring
Similar to the east-west strips, doubling the ceiling heights allows for increased solar exposure, with near continual exposure levels throughout the year.
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
Summer 13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
!Design Proposal!127
High Rise The high rise typology aims at allowing for high density populations within a parcel footprint. Due to variations in footprint sizes throughout the site, the basic 30x30m tower footprint developed may not be applied directly. In some cases buildings are combined and transformed in order to fit within the target footprint. Through the solar analysis of the constructed wetland locations, it was concluded that the doubling of ceiling heights would increase direct solar exposure, especially in pockets within the middle of two neighbouring walls. However, this action, although beneficial for increased sunlight, would significantly decrease the overall population within the building. Therefore, wetland plant species that are capable of living in shade or partial sunlight would flourish best in these building enclaves.
128!Collective Ecologies
!Design Proposal!129
Courtyards Through initial research into early Doha, courtyard typologies were a major factor in the cities culture and vernacular building tradition. Their ability to encourage local pedestrian interaction and host cultural events, prompted a re-introducing this typology into the urban fabric. As courtyards average similar dimensions but slightly shorter heights as high rise typologies, a similar strategy was used to generate their building morphology.
130!Collective Ecologies
!Design Proposal!131
Courtyard Typology
Courtyard Solar Analysis The CA used to establish the ratio of constructed wetland and built area is kept the same. Solar studies are conducted to establish adequate lighting conditions within the courtyards. In order to define the size of the courtyard, studies were conducted to evaluate the relationship between building heights and the width of the open space. These findings are the basis for our courtyards as they develop within the heterogeneous parcel footprints across the site.
132!Collective Ecologies
10 Floors Courtyard 100m2
Autumn 13.713.7 12.4 12.4 11.011.0 9.69.6 8.28.2 6.96.9 5.55.5 4.1 4.1 2.72.7 1.41.4 0.00.0 Hours Hours
10 Floors Courtyard 400m2
Autumn 13.713.7 12.4 12.4 11.011.0 9.69.6 8.28.2 6.96.9 5.55.5 4.1 4.1 2.72.7 1.41.4 0.00.0 Hours Hours
10 Floors Courtyard 900m2
Similarly as the first test, even with an increase in size the ground level has very minimal solar exposure.
Autumn 13.713.7 12.4 12.4 11.011.0 9.69.6 8.28.2 6.96.9 5.55.5 4.1 4.1 2.72.7 1.41.4 0.00.0 Hours Hours
10 Floors Courtyard 1600m2
A courtyard of 10x10m offers nearly no sunlight that can access the ground level throughout the day.
By further increasing the size, some solar exposure is made possible, but with only three hours a day of direct sunlight.
Autumn 13.713.7 12.4 12.4 11.011.0 9.69.6 8.28.2 6.96.9 5.55.5 4.1 4.1 2.72.7 1.41.4 0.00.0 Hours Hours
Increasing the courtyard even further, there is a drastic increase in the amount of solar hours at the ground level. This case offered 4-6 hours of direct sunlight a day.
!Design Proposal!133
Solar Analysis of Courtyards and Streets
Carving out the building
Courtyard Carving Once the courtyard typologies were placed on site, a study was conducted in order to evaluate the solar comfort conditions within the open space. From this analysis, it is established that the north-south streets are often shaded, while those orientated east-west are typically exposed. To enable the use of alternative pedestrian streets for shade during summer, secondary routes are established by carving out of courtyard typologies to allow for pedestrian flow.
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!Design Proposal!135
Low rise Strategy
Low rise Through development of the other two typologies, the 30% of constructed wetland required per buildings was able to be accommodated within their morphology. However, low rise typologies cannot as easily integrate equal ratios of constructed wetland within their limited size. Therefore, low rise typologies utilise a wetland at the ground level within a cluster of eight buildings. This both serves as water treatment for the adjacent residences and allows for semiprivate places for local interaction among inhabitants.
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!Design Proposal!137
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!Design Proposal!139
Urban Wetland Integration Strategies for the development of public wetlands
Development of the public wetland was driven through the ecological requirements of plant species coupled with the impacts of their physical characteristics on the site. Diverse plant species can handle differing solar exposure levels, and provide variations in shading abilities, density, and visibility. The public wetland running though the centre of the site meets with multiple road network types, prompting strategic placement of plant species to allow or discourage views throughout these areas. These variations in plant characteristic allows for the development of differentiated placement throughout the public wetland of varying sun exposure and shading qualities.
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4.5m Shaded
Grey water
Grey water
1m Typha Domingensis 0.6m
3.5m Juncus Rigidus Purified water output
Shaded 4.5m Grey water
Grey water 0.6m Typha Domingensis
Phragmites Australis
3.5m
Purified water output
3m
Shaded
Grey water
Grey water 0.6m
3.5m Typha Domingensis
Phragmites Australis Purified water output
!Design Proposal!141
Grey water
Pedestrian road
Phragmites Australis
Purified water output
Grey water
Pedestrian road
Purified water output
142!Collective Ecologies
Typha Domingensis
Grey water
Grey water
Juncus Rigidus
Pedestrian road
4m
20-22m Primary road
Purified water output
3m
Grey water
Grey water
Pedestrian road 6.5m Phragmites Australis Purified water output
Secondary road
Wetlands barrier to car roads
!Design Proposal!143
Conclusions The extremes to which Doha, Qatar and other nations are currently approaching their demands for water prompted the need for a fundamental shift in how to address water stress. The consideration of hydrological cycles within an urban context was therefore the primary driver in nearly all aspects of the proposal, through various hierarchies and scales. Utilization of constructed wetlands, and their distribution throughout multiple levels of the urban fabric, provided the framework for the development of urban and building morphology, and their organisation within the system. Through identifying relationships between population densities and the amount of water treatment required to sustain them, the initial approach for the integration of constructed wetlands is at the urban scale. The positioning of public wetlands throughout the most integrated areas of the site creates a hierarchy of network parcellations, placing high density typologies nearest the constructed wetlands,
and provides close access to additional water treatment for increased demand in the future. Similarly, the integration of constructed wetlands within building morphologies examines the possibilities of buildings to be self-reliant in their water treatment, and their ability to accommodate the fluctuating water needs of neighbours around it. Through formulating urban clusters throughout the site, these collective relationships between multiple buildings establish an adaptable system for the changing demands for water throughout each cluster. Through utilisation of currently existing constructed wetland technologies and processes, this innovative system of organisation and clustering relationships turns the current water crisis into an opportunity for sustaining its future growth and urban development.
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!Design Proposal!147
Seasonal Adaptive Behaviour Responsive architecture to climatic conditions by Mikaella Papadopoulou Overview Seasonal behaviour of public space could be defined as the use and quality of a space that adapts or changes depending on seasonal changes throughout the year. As climatic conditions change, different requirements are needed for the design of a successful public space. Throughout my various projects within the Emergent Technologies and Design programme, including my thesis research, an interest into seasonal adaptability has grown to become a personal topic of interest. Before my entry into the Emtech programme, I considered the design and development of cities as the organisation and distribution of streets and functions within a certain area. Throughout the projects, I have gained a better understanding of how cities work and define their morphology as a whole. Through my boot-camp project, where a series of components are assembled together to generate a surface, I learned about emergent behaviour. Each of the components has its own individual condition, which affects the relationship with its neighbours and their behaviour which forms the overall surface. By changing the condition of some components within the surface, it allows for variations within the surface to be completely flat in some places and for others to have a curvature. These multi scaled relationships, at local, regional and global scales can be understood also within a city scale, where component parts of the city accumulate allowing them to work collectively as a whole. Furthermore, there are additional external factors that affect the morphology of a city, such as climate. During the Biomimetics and Core I projects we looked closely into the relationship between form and external climatic factors. A study of an organism and how it responds to pressure enabled us to develop a system that deforms based on the amount of pressure applied to it. Joints were also designed to control the direction in which the object deformed. In contrast to the adaptation of form due to pressure, the Core I project aimed to analyse how certain static forms can be arranged in such a way that they can create different microclimatic effects between them by controlling the wind flow. From the above mentioned projects it was established that the morphology of individual aspects within a city, such as buildings and streets, could be designed to collectively create certain environmental conditions or in contrast, the climate of a city can inform how the morphology of buildings and streets should be in order to create adequate spaces and qualities within the city. Within cities, it is difficult to accommodate the fast pace of population and urban growth and predict its impact at multiple scales. The ground level, which consists of public spaces and networks, receives the greatest impact from the vertical expansion of cities. The infrastructure and morphology of a city is not able to constantly adapt to respond to these changes. Seasonal adaptability can 148!Collective Ecologies
be implied as a way to allow for certain parts to be more comfortable for specific seasons through the year. One is tempted to raise the question of whether public spaces and high rise buildings could be integrated together within a cityâ&#x20AC;&#x2122;s urban fabric rather than being separated, and whether seasonal behaviour could be implemented to provide better integration of green and use of public spaces. Existing Approaches The approach towards a better design of such spaces has been seen within several urban models. However, each kind of approach has been successful within its context for specific reasons and does not mean that if applied elsewhere would achieve the same result. In the last few decades, there has been a growing interest from designers and architects to embrace the use of public spaces within cities. There have been several different attempts such as elevated public spaces and large linear parks through the city. Integrated ecological aspects have also been introduced either as a way to bring integrate nature within cities or as a way to solve problems within the urban infrastructure of the city. Chicago is one of the cities that have adapted positively to increased demographic pressures. Skyscrapers are part of the cityâ&#x20AC;&#x2122;s downtown identity, and it is difficult to move away from the growth and development of such buildings. However, the approach of integrating additional public space and natural aspects are successfully introduced within the dense cityscape through elevated parks over the abandoned railway of Bloomingdale Trail station. The park is designed to become the main link to several other ground level parks such as the Burnham Wildlife Corridor. Burnham Wildlife Corridor aims to achieve a sanctuary for more than 5 million birds through the integration of specific plant species. The adaptation of bird species will depend on the season that the plants flourish. This intervention of parks within the city will allow a shift for people from one public space to another depending on the season and the differentiation that both ecological and seasonal factors impose on each park. Another example of seasonal behaviour of public space is the river Besos in Barcelona. A river that once was the cause of severe flooding problems, has now become a generator for purifying water. It has been transformed into a constructed wetland, increasing the value of the area surrounding it. The river not only provides the improved water quality, it also helps prevent erosion and flooding, and is also developed as a park which reconnects nature back to the cityâ&#x20AC;&#x2122;s main urban infrastructure. Bike lanes establish connections to nearby green spaces, along with integrating ecology to encourage wildlife to improve the quality of the area. The river Besos allows for a seasonal variation in its use coupled with its ecological integration provides a different experience for the people in Barcelona. The beneficial effects of ecological integration within the
city is not limited to the integration of wildlife and nature, but can also be implemented through urban growth and the cityâ&#x20AC;&#x2122;s infrastructure. A key objective of such an integration is to establish a correlation between seasonal climatic change and adaptive public spaces, that will allow for the emergence of various differentiated seasonal qualities rather than a universal solution that is not tailored to the specific needs of each season. Current Thoughts My Core II project, located in the area of Isle of Dogs, London, aimed to create a differentiated quality of public spaces by avoiding overshadowed areas due to the high density buildings and climate conditions. The elevated pedestrian network became the main driver of the project, with the objective to achieve public spaces with increased sun exposure that had minimal solar gain at ground level within high density areas. The strategy that was used to optimise as much as possible the location, proportions and connections of the elevated public spaces were problematic and resulted in almost all public spaces to be similar with each other. A complete disconnection from the public spaces at ground level was established and further other issues including infrastructure had to be resolved. However, our investigation demonstrated a significant potential to the elevated network idea and particularly at city areas where we have to cope with a need for increased density. Seasonal elevated networks could be very beneficial and probably become part of the development of future cities because they maintain the existing urban fabric and quality of cities while creating new and interesting city experiences. For the development of my Thesis, a similar approach for the design of seasonal public spaces is established. Collective Ecology is a project that aims to develop an urban system that considers the integration of multiple infrastructural subsets within a single cohesive system that drives architectural and organisational principals for the treatment and reintegration of water at local, regional and global scales. The cleansing of water is achieved by the introduction of constructed wetlands at every scale, reducing significantly the amount of water that gets moved around within the city. Seasonal networks emerged in a small study we conducted on the city of Shibam. The study aimed to understand the success of the cityâ&#x20AC;&#x2122;s organisation, its public spaces and morphology. Shibam is a small high dense city that for many years has been considered successful. The main public spaces showed a differentiation in orientation, proportions which resulted in different sun exposures. Based on solar studies it was established that one public space was mainly suitable for winter and the other more suitable through summer. The analysis of the generated system on site showed a distinguished relationship between streets and public
spaces that are more sun exposed than others. Similar to Shibam, North to South orientated public spaces are more appropriate during summer as they provide nice shaded plazas in contrast to east to west oriented public spaces that are more suitable during winter as they are exposed to direct sunlight. The climate of Qatar allows for the development of seasonal networks. Furthermore the solar qualities within public spaces are not achieved only with climate and adequate proportions. Vegetation is therefore, a crucial element to be considered. As constructed wetlands are a main part of the project, their efficiency plays a major role to make the project viable. The plants selected to be accommodated within the wetlands require different conditions from each other such as amount of sun exposure and shade. Therefore, the public spaces that will accommodate the wetlands should be able to provide the environmental conditions required for them to function. Hence ecology also becomes an intricate part of the design of public spaces. The different sun conditions within each public space could accommodate different plant species that also flourish through different seasons. The contemporary development of computational tools has allowed designers, especially architects, with a library of tools to explore environmental analysis of building within any region in the world. The climatic conditions of a city reflect different needs of spatial characteristics for public spaces. Rather than focusing on the successful design of public spaces throughout the year, which limits the design and variation of what could be achieved, seasonal behaviour that is adaptive to parameters such as climatic and ecological factors, aims to provide ecological spatial qualities and differentiated public spaces throughout the city.
!Design Proposal!149
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Bibliography 1.!(2009) “Illumiance” Lighting Design Glossary, http:// www.schorsch.com/en/kbase/glossary/illuminance.html 2.!(2009) “Lumiance” Lighting Design Glossary, http:// www.schorsch.com/en/kbase/glossary/illuminance.html 3.!Al Buainain, F. (1999) Urbanisation in Qatar: A Study of the Residential and Commercial Land Development in Doha City 4.!Al Malki, A.S. (2009) Water Network Affairs 5.!Al-Mohannadi, et. al. (2003) Controlling Residential Water Demand in Qatar 6.!B. Delaunay: Sur la sphère vide, Izvestia Akademii Nauk SSSR, Otdelenie Matematicheskikh i Estestvennykh Nauk, 7:793–800, 1934 7.!Bettencourt L. et. al. (2006) ‘Growth, Innovation, Scaling, and the Pace of Life in Cities’ PNAS, Vol.104, No.17 8.!Bettencourt L., et. al. (2010) ‘A Unified Theory of Urban Living’ Nature, Vol. 467 9.!Bettencourt L., et. al. (2010) ‘Urban Scaling and Its Deviations’ PLoS ONE, Vol. 5, Iss. 11 10.!Bohren, C. (1997) ‘Atmospheric Optics’ The Optics Encyclopedia 11.!Byran, H. (2012) Lighting/Daylighting Analysis: A Comparison 12.!Decker, E., et. al. (2000) Energy and Material Flow through the Urban Ecosystem 13.!Ellis, J.B. et.el. (2003) Constructed Wetlands and Links with Sustainable Drainage Systems 14.!ESCWA (2012) The Demographic Profile of Qatar 15.!Gill, S. et.el. (2007) “Adapting Cities for climate Change: The Role of the Green Infrastructure.” Built Environment Vol 33 No. 1 16.!Global Water Market (2011) Qatar - General Indicators p.577 17.!GSDP (2009) Qatar National Vision 2030 18.!GSDP (2011) Qatar National Development Strategy 2011–2016 19.!Holland, J. (1998) Emergence: From Chaos to Order 20.!International Council on Monuments and Sites (1981) UNESCO World Heritage Centre - Justification 21.!Jaidah, I., et.al. (2009) The History of Qatari Architecture 22.!KAHRAMAA Statistics Report 2008 (2009) 23.!Kardousha, Mahmoud M. Dr., 2009. Qatar Biodiversity 24.!Kennedy, C. et.el (2007) ‘The changing metabolism of cities’ Journal of Industrial Ecology 25.!Lee, D. et. al. (2007) Protocol Design for Dynamic Delaunay Triangulation 26.!Liu, K. et.el. (2003) Thermal Performance of Green Roofs Through Field Evaluation 27.!Long, W.F. (1994) Luminous Exitance 28.!Luise Davis, 1998. “A Handbook of Constructed Wetlands, Volume 1”, USDA-Natural Resources Conservation Service 29.!Melbourne Water, 2005. Water Sensitive Urban Design - Engineering Procedures: Storm water 30.!Newman, M .E.J. (2005), "A measure of betweenness centrality based on random walks" Social Networks Vol. 27 No. 1 31.!Newman, M .E.J. (2010) Networks: An Introduction
32.!Okabe, A.; et.al (1992) Spatial Tessellations: Concepts and Applications of Voronoi Diagrams 33.!Pirzada, S. (2007) 'Applications of Graph Theory' Journal of the Korean Society for Industrial and Applied Mathematics Vol. 11 No. 34.!Qatar Electricty & Water (2013) Ras Abu Fontas Plant to Open in 2015 35.!Sabidussi, G. (1966) ‘The Centrality Index of a Graph’ Psychometrika Vol. 31, Iss. 4 36.!Sedgewick, R. (2013) Algorithms, 4th Edition 37.!The Demographic Profile of Qatar (2012) ESCWA Annual Report 38.!The United Nations World Water Development Report 3, 2009 39.!Thompson, D. (1917, 1961) On Growth and Form 40.!UN-HABITAT, 2008. "Constructed Wetlands Manual". UN-HABITAT Water for Asian Cities Programme Nepal, Kathmandu. 41.!UN-Habitat / World Health Organisation (2010) Hidden Cities 42.!United Nations (2013) World Population Prospects The 2012 Revision 43.!UN-Water Decade Programme on Advocacy and Communication 2 (UNW-DPAC) 44.!UN-Water Decade Programme on Advocacy and Communication 4 (UNW-DPAC) 45.!van Oirschot, D. (2002) Certificering van plantenwaterzuiveringssystemen. 46.!Weidmann, F. (2012) ‘The Urban Evolution of Doha’ METU.JFA 47.!Weidmann, F. (2012) ‘The Urban Evolution of Doha’ METU.JFA 48.!Weinstock, M. (2008) ‘Metabolism and Morphology’ AD Vol. 78, Iss. 2 49.!Weinstock, M. (2010) ‘Emergence and the Forms of Cities’ AD, Vol. 80, Iss. 3 50.!Weinstock, M. (2010) ‘Emergence and the Forms of Metabolism’ AD, Vol. 80, Iss. 2 51.!Weinstock, M. (2010) The Architecture of Emergence 52.!Weinstock, M (2011) ‘The Metabolism of the City’ AD, Vol. 81, Iss. 4 53.!Weinstock, M. (2011) ‘The Metabolism of the City’ AD Vol. 81, Iss. 4 54.!Weinstock, M. (2011) ‘The Metabolism of the City’ AD, Vol. 81, Iss. 4 55.!Weisstein, Eric W. "Graph." From MathWorld - Wolfram Web Resource <http://mathworld.wolfram.com/Graph.html> 56.!Weisstein, Eric W. "Minimum Spanning Tree." From MathWorld - A Wolfram Web Resource <http:// mathworld. wolfram.com/MinimumSpanningTree.html> 57.!West, G. (1997) ‘A General Model for the Origin of Allometric Scaling Laws in Biology’ Nature, Vol. 413 58.!West G., et. al. (2001) ‘A General Model for Ontogenetic Growth’ Nature, Vol. 413 59.!Wolfram, S. (1983) "Statistical Mechanics of Cellular Automata" Reviews of Modern Physics Vol. 55 60.!Wolfram, S. (2002) A New Kind of Science 61.!World Population Prospects (2013) The 2012 Revision 62.!World Population Prospects - The 2012 Revision, 2013 !Appendix!151
Appendix Algorithm p.106
Algorithms Defining Cells
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Population Cell A
Cell B
Cell C
Standard Deviation
149577
29
15
29
6.60
150420
37
12
24
10.21
149706
22
18
33
6.34
150440
18
20
35
7.59
149815
34
13
26
8.65
150549
30
15
28
6.65
149835
15
21
37
9.29
150569
11
23
39
11.47
149944
27
16
30
6.02
150678
23
18
32
5.79
150053
39
11
23
11.47
150787
35
13
25
8.99
150073
20
19
34
6.85
150807
16
21
36
8.50
150182
32
14
27
7.59
150916
28
16
29
5.91
150202
13
22
38
10.34
151025
40
11
22
11.95
150311
25
17
31
5.73
151045
21
19
33
6.18
Cell Aggregation
!Appendix!155
Building Density
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!Appendix!157
Subdivision Experiment 02
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Rules
Cellular Automata Rules
!Appendix!159
CA Buildings
High Rises Typology
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!Appendix!161
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!Appendix!163
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!Appendix!165
Betweenness Centrality
Centrality Analysis (Betweenness, Degree, Closeness)
high
low
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!Appendix!167
Experiments Cellular Automata Experiments (Samples from Case 16 - Rules 12 to 108)
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R 16
R 17
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!Appendix!169
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R 37
R 38
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!Appendix!171
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R 61
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!Appendix!175
Courtyard Study (Sunlight Hours) 4 Floors Courtyard 100m2
2 Floors Courtyard 100m2
50m
6 Floors Courtyard 100m2
50m
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
8 Floors Courtyard 100m2
10 Floors Courtyard 100m2
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
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13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
2 Floors Courtyard 400m2
60m
4 Floors Courtyard 400m2
6 Floors Courtyard 400m2
60m
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
8 Floors Courtyard 400m2
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
10 Floors Courtyard 400m2
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
!Appendix!177
2 Floors Courtyard 900m2
70m
4 Floors Courtyard 900m2
6 Floors Courtyard 900m2
70m
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
8 Floors Courtyard 900m2
10 Floors Courtyard 900m2
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
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13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
2 Floors Courtyard 1600m2
80m
4 Floors Courtyard 1600m2
6 Floors Courtyard 1600m2
80m
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
8 Floors Courtyard 1600m2
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
10 Floors Courtyard 1600m2
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
13.7 12.4 11.0 9.6 8.2 6.9 5.5 4.1 2.7 1.4 0.0 Hours
!Appendix!179
Collective Ecology
An Integrated Hydrological System for Arid Climates
180!Collective Ecologies