Low impact development technologies for mitigating climate change: Summary and prospects
Many cities are adopting low impact development (LID) technologies (a type of nature-based solution) to sustainably manage urban stormwater in future climates. LIDs, such as bioretention cells, green roofs, and permeable pavements, are developed and applied at small-scales in urban and peri-urban se...
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| Format: | Article |
| Language: | English |
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Science Press
2024-01-01
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| Series: | National Science Open |
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| Online Access: | https://www.sciengine.com/doi/10.1360/nso/20230025 |
| _version_ | 1797348660520943616 |
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| author | Zhang Zhonghao Valeo Caterina |
| author_facet | Zhang Zhonghao Valeo Caterina |
| author_sort | Zhang Zhonghao |
| collection | DOAJ |
| description | Many cities are adopting low impact development (LID) technologies (a type of nature-based solution) to sustainably manage urban stormwater in future climates. LIDs, such as bioretention cells, green roofs, and permeable pavements, are developed and applied at small-scales in urban and peri-urban settings. There is an interest in the large-scale implementation of these technologies, and therefore assessing their performance in future climates, or conversely, their potential for mitigating the impacts of climate change, can be valuable evidence in support of stormwater management planning. This paper provides a literature review of the studies conducted that examine LID function in future climates. The review found that most studies focus on LID performance at over <sc>5 km<sup>2</sup></sc> scales, which is quite a bit larger than traditional LID sizes. Most paper used statistical downscaling methods to simulate precipitation at the scale of the modelled LID. The computer model used to model LIDs was predominantly SWMM or some hybrid version of SWMM. The literature contains examples of both vegetated and un-vegetated LIDs being assessed and numerous studies show mitigation of peak flows and total volumes to high levels in even the most extreme climates (characterized by increasing rainfall intensity, higher temperatures, and greater number of dry days in the inter-event period). However, all the studies recognized the uncertainty in the projections with greatest uncertainty in the LID’s ability to mitigate storm water quality. Interestingly, many of the studies did not recognize the impact of applying a model intended for small-scale processes at a much larger scale for which it is not intended. To explore the ramifications of scale when modelling LIDs in future climates, this paper provides a simple case study of a large catchment on Vancouver Island in British Columbia, Canada, using the Shannon Diversity Index. PCSWMM is used in conjunction with providing regional climates for impacts studies (PRECIS) regional climate model data to determine the relationship between catchment hydrology (with and without LIDs) and the information loss due to PCSWMM’s representation of spatial heterogeneity. The model is applied to five nested catchments ranging from 3 to <sc>51 km<sup>2</sup></sc> and with an RCP4.5 future climate to generate peak flows and total volumes in 2022, and for the period of 2020–2029. The case study demonstrates that the science behind the LID model within PC stormwater management model (PCSWMM) is too simple to capture appropriate levels of heterogeneity needed at larger-scale implementations. The model actually manufactures artificial levels of diversity due to its landuse representation, which is constant for every scale. The modelling exercise demonstrated that a simple linear expression for projected precipitation vs. catchment area would provide comparable estimates to PCSWMM. The study found that due to the spatial representation in PCSWMM for landuse, soil data and slope, slope (an important factor in determining peak flowrates) had the highest level of information loss followed by soil type and then landuse. As the research scale increased, the normalized information loss index (NILI) value for landuse exhibited the greatest information loss as the catchments scaled up. The NILI values before and after LID implementation in the model showed an inverse trend with the predicted LID mitigating performance. |
| first_indexed | 2024-03-08T12:09:06Z |
| format | Article |
| id | doaj.art-cfe0979ce3a7459d8ce37fdd07ce93e0 |
| institution | Directory Open Access Journal |
| issn | 2097-1168 |
| language | English |
| last_indexed | 2024-03-08T12:09:06Z |
| publishDate | 2024-01-01 |
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| series | National Science Open |
| spelling | doaj.art-cfe0979ce3a7459d8ce37fdd07ce93e02024-01-23T03:11:43ZengScience PressNational Science Open2097-11682024-01-01310.1360/nso/20230025eb33e642Low impact development technologies for mitigating climate change: Summary and prospectsZhang Zhonghao0Valeo Caterina1[][]Many cities are adopting low impact development (LID) technologies (a type of nature-based solution) to sustainably manage urban stormwater in future climates. LIDs, such as bioretention cells, green roofs, and permeable pavements, are developed and applied at small-scales in urban and peri-urban settings. There is an interest in the large-scale implementation of these technologies, and therefore assessing their performance in future climates, or conversely, their potential for mitigating the impacts of climate change, can be valuable evidence in support of stormwater management planning. This paper provides a literature review of the studies conducted that examine LID function in future climates. The review found that most studies focus on LID performance at over <sc>5 km<sup>2</sup></sc> scales, which is quite a bit larger than traditional LID sizes. Most paper used statistical downscaling methods to simulate precipitation at the scale of the modelled LID. The computer model used to model LIDs was predominantly SWMM or some hybrid version of SWMM. The literature contains examples of both vegetated and un-vegetated LIDs being assessed and numerous studies show mitigation of peak flows and total volumes to high levels in even the most extreme climates (characterized by increasing rainfall intensity, higher temperatures, and greater number of dry days in the inter-event period). However, all the studies recognized the uncertainty in the projections with greatest uncertainty in the LID’s ability to mitigate storm water quality. Interestingly, many of the studies did not recognize the impact of applying a model intended for small-scale processes at a much larger scale for which it is not intended. To explore the ramifications of scale when modelling LIDs in future climates, this paper provides a simple case study of a large catchment on Vancouver Island in British Columbia, Canada, using the Shannon Diversity Index. PCSWMM is used in conjunction with providing regional climates for impacts studies (PRECIS) regional climate model data to determine the relationship between catchment hydrology (with and without LIDs) and the information loss due to PCSWMM’s representation of spatial heterogeneity. The model is applied to five nested catchments ranging from 3 to <sc>51 km<sup>2</sup></sc> and with an RCP4.5 future climate to generate peak flows and total volumes in 2022, and for the period of 2020–2029. The case study demonstrates that the science behind the LID model within PC stormwater management model (PCSWMM) is too simple to capture appropriate levels of heterogeneity needed at larger-scale implementations. The model actually manufactures artificial levels of diversity due to its landuse representation, which is constant for every scale. The modelling exercise demonstrated that a simple linear expression for projected precipitation vs. catchment area would provide comparable estimates to PCSWMM. The study found that due to the spatial representation in PCSWMM for landuse, soil data and slope, slope (an important factor in determining peak flowrates) had the highest level of information loss followed by soil type and then landuse. As the research scale increased, the normalized information loss index (NILI) value for landuse exhibited the greatest information loss as the catchments scaled up. The NILI values before and after LID implementation in the model showed an inverse trend with the predicted LID mitigating performance.https://www.sciengine.com/doi/10.1360/nso/20230025low impact developmentclimate changestormwater management modelsstormwater runoff volumespeak flowratesscaling |
| spellingShingle | Zhang Zhonghao Valeo Caterina Low impact development technologies for mitigating climate change: Summary and prospects National Science Open low impact development climate change stormwater management models stormwater runoff volumes peak flowrates scaling |
| title | Low impact development technologies for mitigating climate change: Summary and prospects |
| title_full | Low impact development technologies for mitigating climate change: Summary and prospects |
| title_fullStr | Low impact development technologies for mitigating climate change: Summary and prospects |
| title_full_unstemmed | Low impact development technologies for mitigating climate change: Summary and prospects |
| title_short | Low impact development technologies for mitigating climate change: Summary and prospects |
| title_sort | low impact development technologies for mitigating climate change summary and prospects |
| topic | low impact development climate change stormwater management models stormwater runoff volumes peak flowrates scaling |
| url | https://www.sciengine.com/doi/10.1360/nso/20230025 |
| work_keys_str_mv | AT zhangzhonghao lowimpactdevelopmenttechnologiesformitigatingclimatechangesummaryandprospects AT valeocaterina lowimpactdevelopmenttechnologiesformitigatingclimatechangesummaryandprospects |