Abstract
Background: Green Infrastructure (GI) is widely being promoted as an adaptation strategy for urban flooding. Like urban flooding, tree species could be impacted by future climatic conditions. However, there have been limited studies on the implications of future climate on GI planning, mostly due to the lack of climate data at higher spatial resolutions.
Objective: In this paper, we analyze the implications of climate projections on heat hardiness zones since this could impact the GI landscape in the coming years. This is an extension of our earlier work on evaluating impacts of climate projections on plant hardiness zones.
Method: Using downscaled daily temperature data from ten Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models for the historical (1980 - 2005) and projected (2025 - 2050) periods, we analyzed future heat hardiness zones in the watershed bounding Knox County, TN. We analyzed the implications of these outputs for the current list of suggested native and non-native tree species selected for GI in the study area.
Results: All the models suggest that a considerable part of the study area will move into the next warmer heat zone. While most trees remain suitable for GI, several are at the limit of their ideal heat zones.
Conclusion: The insights from this study will help guide the selection and placement of GI across the study area. Specifically, it should help green infrastructure planners design better mitigation and adaptation strategies to achieve higher returns on investments as more cities are now investing in GI projects.
Keywords: Green infrastructure, climate projection, adaptation, plant hardiness zones, urban planning, urban flooding.
Graphical Abstract
[1]
Carmin J, Nadkarni N, Rhie C. Progress and challenges in urban climate adaptation planning Results of a global survey Cambridge, MA,. 2012.
[2]
French J, Ing R, Von Allmen S, Wood R. Mortality from flash floods: A review of national weather service reports, 1969-81. Public Health Rep 1983; 98(6): 584-8.
[3]
Doocy S, Daniels A, Packer C, Dick A, Kirsch TD. The human impact of earthquakes: A historical review of events 1980-2009 and systematic literature review. PLoS Curr 2013; 5. PMID: 23857161.
[4]
Zhou Q, Leng G, Huang M. Impacts of future climate change on urban flood volumes in Hohhot in northern China: Benefits of climate change mitigation and adaptations. Hydrol Earth Syst Sci 2018; 22(1): 305-16.
[5]
Hettiarachchi S, Wasko C, Sharma A. Increase in flood risk resulting from climate change in a developed urban watershed the role of storm temporal patterns. Hydrol Earth Syst Sci 2018; 22(3): 2041-56.
[6]
Trenberth KE. The impact of climate change and variability on heavy precipitation, floods, and droughts. Encycl Hydrol Sci 2005; 1
[http://dx.doi.org/10.1002/0470848944.hsa211]
[http://dx.doi.org/10.1002/0470848944.hsa211]
[7]
Neal GJ. The physical and economic impacts of urban
flooding on critical infrastructure & surrounding
communities: A decision-support framework. A
Thesis Submitted to the Faculty of the University of
Tennessee at Chattanooga in Partial Fulfillment of the
Requirements of the Degree of Master of Science,
2014.
[8]
Chang H, Lafrenz M, Jung IW, et al. Future flooding impacts on transportation infrastructure and traffic patterns resulting from climate change Final Report OTREC RR-11-24 for Oregon Transportation Research and Education Consortium. OTREC 2011.
[9]
Mitsakis E, Stamos I, Diakakis M, Grau JS. Impacts of high-intensity storms on urban transportation: Applying traffic flow control methodologies for quantifying the effects. Int J Environ Sci Technol 2014; 11(8): 2145-54.
[10]
Chithra SV, Nair MH, Amarnath A, Anjana NS. Impacts of impervious surfaces on the environment. Int J Eng Sci Invent 2015; 4(5): 27-31.
[11]
Yao L, Chen L, Wei W. Exploring the linkage between urban flood risk and spatial patterns in small urbanized catchments of Beijing, China. Int J Environ Res Public Health 2017; 14(3): 239.
[12]
Du S, Shi P, Van Rompaey A, Wen J. Quantifying the impact of impervious surface location on flood peak discharge in urban areas. Nat Hazards 2015; 76(3): 1457-71.
[13]
Freeborn J. Decreasing runoff and increasing stormwater infiltration. In: Virginia Cooperative Extension 2015.
[14]
Markovi G, Zele M, Káposztásová D, Hudáková G. Rainwater infiltration in the urban areas. WIT Trans Ecol Environ 2014; 181: 313-20.
[15]
Soz SA, Kryspin-Watson J, Stanton-Geddes Z. The role of green infrastructure solutions in urban flood risk management The World Bank 2016; 1: 108291.
[16]
Kim H, Lee DK, Sung S. Effect of urban green spaces and flooded area type on flooding probability. Sustainability 2016; 8(2): 134.
[17]
Sörensen J, Persson A, Sternudd C, et al. Re-thinking urban flood management time for a regime shift. Water 2016; 8(8): 332.
[18]
Zimmermann E, Bracalenti L, Piacentini R, Inostroza L. Urban flood risk reduction by increasing green areas for adaptation to climate change. Proc Eng 2016; 161: 2241-6.
[19]
Luo P, He B, Takara K, et al. Historical assessment of Chinese and Japanese flood management policies and implications for managing future floods. Environ Sci Policy 2015; 48: 265-77.
[20]
Scherrer S, Naef F, Faeh AO, Cordery I. Formation of runoff at the hillslope scale during intense precipitation. Hydrol Earth Syst Sci 2007; 11(2): 907-22.
[21]
Eisenbies MH, Aust WM, Burger JA, Adams MB. Forest operations, extreme flooding events, and considerations for hydrologic modeling in the Appalachians. A review. For Ecol Manage 2007; 242(2-3): 77-98.
[22]
Bonell M, Purandara BK, Venkatesh B, et al. The impact of forest use and reforestation on soil hydraulic conductivity in the Western Ghats of India: Implications for surface and sub-surface hydrology. J Hydrol 2010; 391(1-2): 47-62.
[23]
Luo P, Zhou M, Deng H, et al. Impact of forest maintenance on water shortages: Hydrologic modeling and effects of climate change. Sci Total Environ 2018; 615: 1355-63.
[24]
De Roo A, Odijk M, Schmuck G, Koster E, Lucieer A. Assessing the effects of land use changes on floods in the Meuse and Oder catchment. Phys Chem Earth B: Hydrol Ocean Atmos 2001; 26(7-8): 593-9.
[25]
Brath A, Montanari A, Moretti G. Assessing the effect on flood frequency of land use change via hydrological simulation (with uncertainty). J Hydrol 2006; 324(1-4): 141-53.
[26]
Wang G, Zhang Y, Liu G, Chen L. Impact of land-use change on hydrological processes in the Maying River basin, China. Sci China Ser D Earth Sci 2006; 49(10): 1098-110.
[27]
Luo P, He B, Duan W, Takara K, Nover D. Impact assessment of rainfall scenarios and land‐use change on hydrologic response using synthetic Area IDF curves. J Flood Risk Manag 2018; 11: S84-97.
[28]
Huong HT, Pathirana A. Urbanization and climate change impacts on future urban flooding in Can Tho city, Vietnam. Hydrol Earth Syst Sci 2013; 17(1): 379-94.
[29]
Arnbjerg-Nielsen K, Leonardsen L, Madsen H. Evaluating adaptation options for urban flooding based on new high-end emission scenario regional climate model simulations. Clim Res 2015; 64(1): 73-84.
[30]
Alfieri L, Burek P, Feyen L, Forzieri G. Global warming increases the frequency of river floods in Europe. Hydrol Earth Syst Sci 2015; 19(5): 2247-60.
[31]
Arheimer B, Lindström G. Climate impact on floods: Changes in high flows in Sweden in the past and the future (1911-2100). Hydrol Earth Syst Sci 2015; 19(2): 771-84.
[32]
Kim S, Chung U, Lawler JJ, Anderson RE. Assessing the impacts of climate change on urban forests in the Puget Sound region: Climate suitability analysis for tree species. Final Report, University of Washington, Seattle, WA, 2012.
[33]
McKenney DW, Pedlar JH, Lawrence K, Campbell K, Hutchinson MF. Potential impacts of climate change on the distribution of North American trees. AIBS Bull 2007; 57(11): 939-48.
[34]
Lanza K, Stone Jr B.. Climate adaptation in cities: What trees are suitable for urban heat management? Landsc Urban Plan 2016; 153: 74-82.
[35]
Iverson LR, Prasad AM, Matthews SN, Peters M. Estimating potential habitat for 134 eastern US tree species under six climate scenarios. For Ecol Manage 2008; 254(3): 390-406.
[36]
USDA, USDA Plant Hardiness Zone Map, 2012. [Online]. Available from: https://planthardiness. ars.usda.gov/PHZMWeb/ (Accessed on Oct 9th, 2018).
[37]
Denman EC, May PB, Moore GM. The use of trees in urban stormwater management. In: Trees, people and the built environment: Proceedings of the Urban Trees Research Conference 2011: pp. 13-14.
[38]
Bartens J, Day SD, Harris JR, Dove JE, Wynn TM. Can urban tree roots improve infiltration through compacted subsoils for stormwater management? J Environ Qual 2008; 37(6): 2048-57.
[39]
Iacob O, Rowan JS, Brown I, Ellis C. Evaluating wider benefits of natural flood management strategies: An ecosystem-based adaptation perspective. Hydrol Res 2014; 45(6): 774-87.
[40]
Hansen AJ, Neilson RP, Dale VH, et al. Global change in forests: Responses of species, communities, and biomes: Interactions between climate change and land use are projected to cause large shifts in biodiversity. AIBS Bull 2001; 51(9): 765-79.
[41]
Aitken SN, Yeaman S, Holliday JA, Wang T, Curtis‐McLane S. Adaptation, migration or extirpation: Climate change outcomes for tree populations. Evol Appl 2008; 1(1): 95-111.
[42]
Allen CD, Macalady AK, Chenchouni H, et al. A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. For Ecol Manage 2010; 259(4): 660-84.
[43]
Somero GN. The physiology of climate change: How potentials for acclimatization and genetic adaptation will determine ‘winners’ and ‘losers’. J Exp Biol 2010; 213(6): 912-20.
[44]
Iverson LR, Prasad AM. Predicting abundance of 80 tree species following climate change in the eastern United States. Ecol Monogr 1998; 68(4): 465-85.
[45]
Sylvester L, Omitaomu O, Parish E. Analyzing the implications of climate data on plant hardiness zones for green infrastructure planning: Case Study of Knoxville, Tennessee and Surrounding Region Oak Ridge National Laboratory. ORNL: Oak Ridge, TN, United States 2016.
[46]
Real Climate, Do regional climate models add value compared to global models?, Climate science from climate models, 2016. [Online]. Available from: http://www.realclimate.org/index.php/archives/2016/05/do-regional-climate-models-add-value-compared-to-global-models/ (Accessed on May 22, 2016)
[47]
Kotlarski S, Block A, Böhm U, et al. Regional climate model simulations as input for hydrological applications: Evaluation of uncertainties. Adv Geosci 2005; 5: 119-25.
[48]
Foughali A, Tramblay Y, Bargaoui Z, Carreau J, Ruelland D. Hydrological modeling in Northern Tunisia with regional climate model outputs: Performance evaluation and bias-correction in present climate conditions. Climate 2015; 3(3): 459-73.
[49]
Foley AM. Uncertainty in regional climate modelling: A review. Prog Phys Geogr 2010; 34(5): 647-70.
[50]
Pan Z, Christensen JH, Arritt RW, Gutowski WJ, Takle ES, Otieno F. Evaluation of uncertainties in regional climate change simulations. J Geophys Res Atmos 2001; 106(D16): 17735-51.
[51]
Deidda R, Marrocu M, Caroletti G, et al. Regional climate models’ performance in representing precipitation and temperature over selected Mediterranean areas. Hydrol Earth Syst Sci 2013; 17(12): 5041-59.
[52]
Ba W, Du P, Liu T, et al. Simulating hydrological responses to climate change using dynamic and statistical downscaling methods: A case study in the Kaidu River Basin, Xinjiang, China. J Arid Land 2018; 10(6): 905-20.
[53]
Lauwaet D, Hooyberghs H, Maiheu B, et al. Detailed urban heat island projections for cities worldwide: Dynamical downscaling CMIP5 global climate models. Climate 2015; 3(2): 391-415.
[54]
Cooney CM. Downscaling climate models: Sharpening the focus on local-level changes. Environ Health Perspect 2012; 120(1): a22.
[55]
Knowlton K, Rosenthal JE, Hogrefe C, et al. Assessing ozone-related health impacts under a changing climate. Environ Health Perspect 2004; 112(15): 1557.
[56]
Knowlton K, Lynn B, Goldberg RA, et al. Projecting heat-related mortality impacts under a changing climate in the New York City region. Am J Public Health 2007; 97(11): 2028-34.
[57]
Cooney CM. Preparing a people: Climate change and public health. Environ Health Perspect 2011; 119(4): A166.
[58]
Fowler HJ, Blenkinsop S, Tebaldi C. Linking climate change modelling to impacts studies: Recent advances in downscaling techniques for hydrological modelling. Int J Climatol 2007; 27(12): 1547-78.
[59]
Hewitson BC, Crane RG. Climate downscaling: Techniques and application. Clim Res 1996; 7(2): 85-95.
[60]
Sunyer MA, Gregersen IB, Rosbjerg D, Madsen H, Luchner J, Arnbjerg‐Nielsen K. Comparison of different statistical downscaling methods to estimate changes in hourly extreme precipitation using RCM projections from ENSEMBLES. Int J Climatol 2015; 35(9): 2528-39.
[61]
Trzaska S, Schnarr E. A review of downscaling methods for climate change projections. United States Agency for International Development by Tetra Tech ARD 2014; pp. 1-42.
[62]
Ashfaq M, Bowling LC, Cherkauer K, Pal JS, Diffenbaugh NS. Influence of climate model biases and daily‐scale temperature and precipitation events on hydrological impacts assessment: A case study of the United States. J Geophys Res Atmos 2010; 115(D14): 1-15.
[63]
PRISM Climate Group, Oregon State University.
[Online]. Available from: prism.oregonstate.edu/ (Accessed on Oct 9th, 2018).
[64]
Sylvester L, Omitaomu O, Parish E, Allen M. Processing and Monthly Summaries of Downscaled
Climate Data for Knoxville, Tennessee and
Surrounding Region. Oak Ridge National Laboratory
(ORNL), Oak Ridge, TN (United States); 2016 Sep 1.
[66]
AHS Plant Heat Zone Map, American Horticultural
Society. Available from: http://ahsgardening.org/ gardening-resources/gardening-maps/heat-zone-map (Accessed on Oct 9th, 2018).
[67]
Urban Forestry - City of Knoxville. [Online].
Available from: http://www.knoxvilletn.gov/govern-ment/city_departments_offices/public_service/urban_forestry (Accessed on Oct 9th, 2018).
[68]
Li G, Xie SP, Du Y, Luo Y. Effects of excessive equatorial cold tongue bias on the projections of tropical Pacific climate change. Part I: The warming pattern in CMIP5 multi-model ensemble. Clim Dyn 2016; 47(12): 3817-31.
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