eprintid: 10057472 rev_number: 23 eprint_status: archive userid: 608 dir: disk0/10/05/74/72 datestamp: 2018-10-03 11:41:19 lastmod: 2021-09-20 00:25:19 status_changed: 2018-10-03 11:41:19 type: article metadata_visibility: show creators_name: Erfani, T creators_name: Pachos, K creators_name: Harou, JJ title: Real‐Options Water Supply Planning: Multistage Scenario Trees for Adaptive and Flexible Capacity Expansion Under Probabilistic Climate Change Uncertainty ispublished: pub divisions: UCL divisions: B04 divisions: C05 divisions: F44 keywords: flexibility, adaptive planning, decision tree, uncertainty, optimization, capacity expansion note: © 2018. The Authors. This is an open access article under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). abstract: Planning water supply infrastructure includes identifying interventions that cost‐effectively secure an acceptably reliable water supply. Climate change is a source of uncertainty for water supply developments as its impact on source yields is uncertain. Adaptability to changing future conditions is increasingly viewed as a valuable design principle of strategic water planning. Because present decisions impact a system's ability to adapt to future needs, flexibility in activating, delaying, and replacing engineering projects should be considered in least‐cost water supply intervention scheduling. This is a principle of Real Options Analysis, which this paper applies to least‐cost capacity expansion scheduling via multistage stochastic mathematical programming. We apply the proposed model to a real‐world utility with many investment decision stages using a generalized scenario tree construction algorithm to efficiently approximate the probabilistic uncertainty. To evaluate the implementation of Real Options Analysis, the use of two metrics is proposed: the value of the stochastic solution and the expected value of perfect information that quantify the value of adopting adaptive and flexible plans, respectively. An application to London's water system demonstrates the generalized approach. The investment decisions results are a mixture of long‐term and contingency schemes that are optimally chosen considering different futures. The value of the stochastic solution shows that by considering uncertainty, adaptive investment decisions avoid £100 million net present value (NPV) cost, 15% of the total NPV. The expected value of perfect information demonstrates that optimal delay and early decisions have £50 million NPV, 6% of total NPV. Sensitivity of results to the characteristics of the scenario tree and uncertainty set is assessed. date: 2018-07 date_type: published publisher: AMER GEOPHYSICAL UNION official_url: https://doi.org/10.1029/2017WR021803 oa_status: green full_text_type: pub language: eng primo: open primo_central: open_green article_type_text: Journal Article verified: verified_manual elements_id: 1576418 doi: 10.1029/2017WR021803 language_elements: English lyricists_name: Erfani, Tohid lyricists_name: Pachos, Kevis lyricists_id: TERFA00 lyricists_id: KPACH87 actors_name: Erfani, Tohid actors_name: Laslett, David actors_id: TERFA00 actors_id: DLASL34 actors_role: owner actors_role: impersonator full_text_status: public publication: Water Resources Research volume: 54 number: 7 pagerange: 5069-5087 pages: 19 issn: 0043-1397 citation: Erfani, T; Pachos, K; Harou, JJ; (2018) Real‐Options Water Supply Planning: Multistage Scenario Trees for Adaptive and Flexible Capacity Expansion Under Probabilistic Climate Change Uncertainty. Water Resources Research , 54 (7) pp. 5069-5087. 10.1029/2017WR021803 <https://doi.org/10.1029/2017WR021803>. Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/10057472/1/Erfani_Real-Options%20Water%20Supply%20Planning.%20Multistage%20Scenario%20Trees%20for%20Adaptive%20and%20Flexible%20Capacity%20Expansion%20Under%20Probabilistic%20Climate%20Change%20Uncertainty_VoR.pdf