Multi-scale planning model for robust urban drought response
Increasingly severe droughts are straining municipal water resources and jeopardizing urban water security, but uncertainty in their duration, frequency, and intensity challenges drought planning and response. We develop the Drought Resilient Interscale Portfolio Planning model (DRIPP) to generate o...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2023-01-01
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| Series: | Environmental Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1748-9326/acceb5 |
| _version_ | 1797747301381308416 |
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| author | Marta Zaniolo Sarah Fletcher Meagan S Mauter |
| author_facet | Marta Zaniolo Sarah Fletcher Meagan S Mauter |
| author_sort | Marta Zaniolo |
| collection | DOAJ |
| description | Increasingly severe droughts are straining municipal water resources and jeopardizing urban water security, but uncertainty in their duration, frequency, and intensity challenges drought planning and response. We develop the Drought Resilient Interscale Portfolio Planning model (DRIPP) to generate optimal planning responses to urban drought. DRIPP is a generalizable multi-scale framework for optimizing dynamic planning strategies of long-term infrastructure deployment and short-term drought response. It integrates climate and hydrological variability with high-fidelity representations of urban water distribution, available technology options, and demand reduction measures to yield robust and cost-effective water supply portfolios that are location-specific. We apply DRIPP in Santa Barbara, California to assess how least cost water supply portfolios vary under different drought scenarios and identify portfolios that are robust across drought scenarios. In Santa Barbara, we find that drought intensity, not duration or frequency, drives cost increases, reliability risk, and regret of overbuilding infrastructure. Under uncertain drought conditions, a diversified technology portfolio that includes both rapidly deployable, decentralized technologies alongside larger centralized technologies minimizes water supply cost while maintaining high robustness to climate uncertainty. |
| first_indexed | 2024-03-12T15:49:47Z |
| format | Article |
| id | doaj.art-509ec6624fd54dc9994a095f52291f42 |
| institution | Directory Open Access Journal |
| issn | 1748-9326 |
| language | English |
| last_indexed | 2024-03-12T15:49:47Z |
| publishDate | 2023-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research Letters |
| spelling | doaj.art-509ec6624fd54dc9994a095f52291f422023-08-09T15:16:46ZengIOP PublishingEnvironmental Research Letters1748-93262023-01-0118505401410.1088/1748-9326/acceb5Multi-scale planning model for robust urban drought responseMarta Zaniolo0https://orcid.org/0000-0001-9466-7102Sarah Fletcher1https://orcid.org/0000-0003-3289-2237Meagan S Mauter2https://orcid.org/0000-0002-4932-890XDepartment of Civil and Environmental Engineering, Stanford University , Stanford, CA 94305, United States of AmericaDepartment of Civil and Environmental Engineering, Stanford University , Stanford, CA 94305, United States of America; Woods Institute for the Environment, Stanford University , Stanford, CA 94305, United States of AmericaDepartment of Civil and Environmental Engineering, Stanford University , Stanford, CA 94305, United States of America; Global Environmental Policy, Stanford University , Stanford, CA 94305, United States of America; Precourt Institute for Energy, Stanford University , Stanford, CA 94305, United States of America; Woods Institute for the Environment, Stanford University , Stanford, CA 94305, United States of AmericaIncreasingly severe droughts are straining municipal water resources and jeopardizing urban water security, but uncertainty in their duration, frequency, and intensity challenges drought planning and response. We develop the Drought Resilient Interscale Portfolio Planning model (DRIPP) to generate optimal planning responses to urban drought. DRIPP is a generalizable multi-scale framework for optimizing dynamic planning strategies of long-term infrastructure deployment and short-term drought response. It integrates climate and hydrological variability with high-fidelity representations of urban water distribution, available technology options, and demand reduction measures to yield robust and cost-effective water supply portfolios that are location-specific. We apply DRIPP in Santa Barbara, California to assess how least cost water supply portfolios vary under different drought scenarios and identify portfolios that are robust across drought scenarios. In Santa Barbara, we find that drought intensity, not duration or frequency, drives cost increases, reliability risk, and regret of overbuilding infrastructure. Under uncertain drought conditions, a diversified technology portfolio that includes both rapidly deployable, decentralized technologies alongside larger centralized technologies minimizes water supply cost while maintaining high robustness to climate uncertainty.https://doi.org/10.1088/1748-9326/acceb5urban drought securitywater reusewater desalinationwater infrastructure adaptationreinforcement learning |
| spellingShingle | Marta Zaniolo Sarah Fletcher Meagan S Mauter Multi-scale planning model for robust urban drought response Environmental Research Letters urban drought security water reuse water desalination water infrastructure adaptation reinforcement learning |
| title | Multi-scale planning model for robust urban drought response |
| title_full | Multi-scale planning model for robust urban drought response |
| title_fullStr | Multi-scale planning model for robust urban drought response |
| title_full_unstemmed | Multi-scale planning model for robust urban drought response |
| title_short | Multi-scale planning model for robust urban drought response |
| title_sort | multi scale planning model for robust urban drought response |
| topic | urban drought security water reuse water desalination water infrastructure adaptation reinforcement learning |
| url | https://doi.org/10.1088/1748-9326/acceb5 |
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