Accounting for uncertainty and flexibility in flood risk management: comparing R eal‐ I n‐ O ptions optimisation and A daptation T ipping P oints
Abstract This paper provides practical experience with two climate impact and adaptation assessment methods: R eal‐ I n‐ O ptions ( RIO ) optimisation and A daptation T ipping P oints ( ATP ). These methods were selected because they both provide insight into and promote the ability of the system to...
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Published in | Journal of flood risk management Vol. 8; no. 2; pp. 135 - 144 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
01.06.2015
|
Online Access | Get full text |
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Abstract | Abstract
This paper provides practical experience with two climate impact and adaptation assessment methods:
R
eal‐
I
n‐
O
ptions (
RIO
) optimisation and
A
daptation
T
ipping
P
oints (
ATP
). These methods were selected because they both provide insight into and promote the ability of the system to deal with future change and thus can be used within a resilience approach. The resilience approach takes a dynamic perspective on adaptive processes and the effects of these processes at/across different spatio‐temporal scales. Although the two methods share a similar aim, they have considerable differences in orientation and application.
RIO
optimisation aims to minimise the expected costs of acquiring climate change resilience. To achieve this aim, it uses probabilistic climate data to identify the optimal set of adaptive strategies in response to advances in knowledge about future climate change. The
ATP
method is virtually independent of climate change scenarios, and in particular of probabilities of climate change. Rather, it requires input from decision makers and other stakeholders to select the preferred adaptive strategy. This paper discusses the concept, procedures, case examples and benefits/limitations of each method, examining its usefulness for informing adaptation‐related decision making. Based on this, it gives specific recommendations on which method to use under what circumstances. |
---|---|
AbstractList | Abstract
This paper provides practical experience with two climate impact and adaptation assessment methods:
R
eal‐
I
n‐
O
ptions (
RIO
) optimisation and
A
daptation
T
ipping
P
oints (
ATP
). These methods were selected because they both provide insight into and promote the ability of the system to deal with future change and thus can be used within a resilience approach. The resilience approach takes a dynamic perspective on adaptive processes and the effects of these processes at/across different spatio‐temporal scales. Although the two methods share a similar aim, they have considerable differences in orientation and application.
RIO
optimisation aims to minimise the expected costs of acquiring climate change resilience. To achieve this aim, it uses probabilistic climate data to identify the optimal set of adaptive strategies in response to advances in knowledge about future climate change. The
ATP
method is virtually independent of climate change scenarios, and in particular of probabilities of climate change. Rather, it requires input from decision makers and other stakeholders to select the preferred adaptive strategy. This paper discusses the concept, procedures, case examples and benefits/limitations of each method, examining its usefulness for informing adaptation‐related decision making. Based on this, it gives specific recommendations on which method to use under what circumstances. |
Author | Zevenbergen, C. Jeuken, A. Pathinara, A. Gersonius, B. Ashley, R. |
Author_xml | – sequence: 1 givenname: B. surname: Gersonius fullname: Gersonius, B. organization: Water Science and Engineering UNESCO‐IHE Institute for Water Education Delft The Netherlands – sequence: 2 givenname: R. surname: Ashley fullname: Ashley, R. organization: Water Science and Engineering UNESCO‐IHE Institute for Water Education Delft The Netherlands – sequence: 3 givenname: A. surname: Jeuken fullname: Jeuken, A. organization: Scenarios and Policy Analysis Deltares Utrecht The Netherlands – sequence: 4 givenname: A. surname: Pathinara fullname: Pathinara, A. organization: Water Science and Engineering UNESCO‐IHE Institute for Water Education Delft The Netherlands – sequence: 5 givenname: C. surname: Zevenbergen fullname: Zevenbergen, C. organization: Water Science and Engineering UNESCO‐IHE Institute for Water Education Delft The Netherlands |
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CitedBy_id | crossref_primary_10_1016_j_envsoft_2016_09_017 crossref_primary_10_1177_0739456X18769134 crossref_primary_10_1007_s13753_022_00421_6 crossref_primary_10_3390_su11195505 crossref_primary_10_1360_TB_2021_1218 crossref_primary_10_2166_bgs_2019_199 crossref_primary_10_1007_s13280_020_01342_8 crossref_primary_10_1016_j_envsci_2024_103711 crossref_primary_10_1111_jfr3_12315 crossref_primary_10_1007_s11269_023_03429_9 crossref_primary_10_1098_rsta_2019_0204 |
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References_xml | – start-page: 265 volume-title: Proceedings of the 5th Hydroinformatics Conference year: 2002 ident: e_1_2_6_9_1 contributor: fullname: Dhondia J. – volume-title: Motivated metamodels: synthesis of cause effect reasoning and statistical metamodeling year: 2003 ident: e_1_2_6_6_1 contributor: fullname: Davis P.K. – ident: e_1_2_6_26_1 – ident: e_1_2_6_34_1 – ident: e_1_2_6_14_1 doi: 10.1016/j.watres.2012.03.060 – volume-title: UK Climate Projections Science Report: climate change projections year: 2009 ident: e_1_2_6_30_1 contributor: fullname: Murphy J. – ident: e_1_2_6_31_1 doi: 10.1287/inte.14.1.126 – volume-title: EURO 2006 year: 2006 ident: e_1_2_6_38_1 contributor: fullname: Van Grol R. – ident: e_1_2_6_10_1 doi: 10.1515/9781400830176 – ident: e_1_2_6_37_1 – ident: e_1_2_6_23_1 doi: 10.1623/hysj.53.1.3 – ident: e_1_2_6_41_1 doi: 10.1111/j.1753-318X.2011.01119.x – ident: e_1_2_6_20_1 doi: 10.2166/wst.2007.533 – ident: e_1_2_6_22_1 doi: 10.1002/wcc.97 – volume: 1 start-page: 729 issue: 5 year: 2011 ident: e_1_2_6_24_1 article-title: Using adaptation tipping points to prepare for climate change and sea level rise: a case study in the Netherlands publication-title: Wiley Interdisciplinary Reviews: Climate Change contributor: fullname: Kwadijk J.C.J. – ident: e_1_2_6_15_1 doi: 10.1680/cien.11.00053 – ident: e_1_2_6_32_1 doi: 10.1146/annurev.energy.32.051807.090348 – ident: e_1_2_6_4_1 – ident: e_1_2_6_2_1 doi: 10.1016/j.gloenvcha.2009.11.004 – volume-title: Foresight flood and coastal defence project: scientific summary year: 2004 ident: e_1_2_6_11_1 contributor: fullname: Evans E. – ident: e_1_2_6_19_1 – volume-title: Assessing current climate risks. Adaptation policy framework for climate change: developing strategies, policies and measures, Ian Burton, Elizabeth L. Malone and Saleemul Huq (lead authors) year: 2005 ident: e_1_2_6_21_1 contributor: fullname: Jones R. – volume: 143 start-page: 461 year: 2002 ident: e_1_2_6_5_1 article-title: Option pricing: a simplified approach publication-title: International Library of Critical Writings in Economics contributor: fullname: Cox J. – ident: e_1_2_6_27_1 doi: 10.1023/B:CLIM.0000037561.75281.b3 – ident: e_1_2_6_28_1 doi: 10.7249/MR1626 – ident: e_1_2_6_17_1 doi: 10.1007/s10584-012-0444-2 – ident: e_1_2_6_8_1 – volume-title: Decision support planning methods: incorporating climate change uncertainties into water planning year: 2010 ident: e_1_2_6_29_1 contributor: fullname: Means E. – volume-title: Building real options into physical systems with stochastic mixed‐integer programming year: 2004 ident: e_1_2_6_40_1 contributor: fullname: Wang T. – ident: e_1_2_6_18_1 doi: 10.1016/j.gloenvcha.2012.12.006 – ident: e_1_2_6_33_1 doi: 10.1076/iaij.4.1.26.16461 – ident: e_1_2_6_3_1 – ident: e_1_2_6_7_1 doi: 10.1109/4235.996017 – ident: e_1_2_6_16_1 doi: 10.1002/sd.438 – ident: e_1_2_6_35_1 – ident: e_1_2_6_13_1 doi: 10.1007/s10584-012-0494-5 – ident: e_1_2_6_39_1 doi: 10.1016/S0377-2217(00)00071-0 – ident: e_1_2_6_36_1 doi: 10.1680/ffacer.34495 – ident: e_1_2_6_25_1 doi: 10.2166/wst.2009.650 – ident: e_1_2_6_12_1 |
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Snippet | Abstract
This paper provides practical experience with two climate impact and adaptation assessment methods:
R
eal‐
I
n‐
O
ptions (
RIO
) optimisation and
A... |
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