Co-designing Indus Water-Energy-Land Futures

Wada, Yoshihide; Vinca, Adriano; Parkinson, Simon; Willaarts, Bárbara; Magnuszewski, Piotr; Mochizuki, Junko; Mayor, Beatriz; Wang, Yaoping; Burek, P.; Byers, Edward; Riahi, Keywan; Krey, Volker; Langan, Simon; Dijk, Michiel van; Grey, D. R.; Hillers, Astrid; Novak, Robert J.; Mukherjee, Abhijit; Bhattacharya, Anindya; Bhardwaj, Saurabh; Romshoo, Shakil Ahmad; Thambi, Simi; Muhammad, Abubakr; Ilyas, Ansir; Khan, Asif; Lashari, B.; Mahar, Rasool Bux; Rasul, Ghulam; Siddiqi, Afreen; Wescoat, James L.; Yogeswara, Nithiyanandam; Ashraf, Ather; Sidhu, Buta Singh; Jiang, Tong

doi:10.1016/j.oneear.2019.10.006

Cited by 62 publications

(30 citation statements)

References 75 publications

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“…(Maier et al, 2016). A number of water resources studies have generated explorative scenarios by considering the impact of plausible changes in atmospheric carbon concentrations (Anghileri et al, 2018; Beh et al, 2014, 2015a, 2015b; Giuliani & Castelletti, 2016; Giuliani et al, 2016; Haasnoot et al, 2012, 2013; Herman & Giuliani, 2018; Huskova et al, 2016; McPhail et al, 2018), as well as plausible changes in regional socioeconomic conditions (Haasnoot et al, 2013; Wada et al, 2019). In contrast, normative scenarios consider conditions that represent interesting outcomes, as is the case with scenario discovery (e.g., Bryant & Lempert, 2010; Groves & Lempert, 2007; Hadka et al, 2015; Kasprzyk et al, 2013; Kwakkel, 2017; Kwakkel, Walker, et al, 2016; Matrosov et al, 2013; Trindade et al, 2017); conditions that result in one decision alternative being preferable to another, as is the case with MORE (Ravalico et al, 2010), POMORE (Ravalico et al, 2009) and decision scaling (e.g., Brown et al, 2012); or conditions under which certain decision alternatives no longer perform adequately, as is the case with adaptive tipping point approaches (e.g., Haasnoot et al, 2013; Kwadijk et al, 2010; Kwakkel et al, 2015; Kwakkel, Haasnoot, et al, 2016; Vervoort et al, 2014; Walker, Haasnoot, et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…How many scenarios are generated is generally linked to the philosophy that underpins scenario generation. When scenarios correspond to coherent descriptions of alternative hypothetical futures (e.g., van Notten et al, 2005), the number of scenarios considered is generally small (~3–9, see Table S1 in the supporting information), and scenarios are generally identified using some type of human input, such as the use of participatory approaches involving a variety of stakeholders (e.g., Wada et al, 2019). In contrast, when scenarios are designed to represent a broad range of combined changes in future conditions, the number of scenarios considered is generally large (~100–15,000, see Table S1 in the supporting information), and scenarios are generated using numerical modeling and/or sampling‐ or optimization‐based approaches, with minimal stakeholder input (e.g., Culley et al, 2016, 2019; Hadka et al, 2015; Hall et al, 2012; Herman et al, 2014, 2015; Kasprzyk et al, 2013; Kwakkel et al, 2015; Kwakkel, 2017; Kwakkel, Walker, et al, 2016; McPhail et al, 2018; Quinn et al, 2017, 2018; Singh et al, 2015; Trindade et al, 2017; Watson & Kasprzyk, 2017; Weaver et al, 2013; Zeff et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

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Impact of Scenario Selection on Robustness

McPhail

Maier

Westra

et al. 2020

Water Resources Research

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Multiple plausible future scenarios are being used increasingly in preference to a single deterministic or probabilistic prediction of the future in the long-term planning of water resources systems. These scenarios enable the determination of the robustness of a system-the consideration of performance across a range of plausible futures-and allow an assessment of which possible future system configurations result in a greater level of robustness. There are many approaches to selecting scenarios, and previous studies have observed that the choice of scenarios might affect the estimated robustness of the system. However, these observations have been anecdotal and qualitative. This paper develops a systematic, quantitative methodology for exploring the influence of scenario selection on the robustness and the ranking of decision alternatives. The methodology is illustrated on the Lake Problem. The quantitative results obtained confirm the qualitative observations of previous works, showing that the selection of scenarios is important, as it has a large influence on the robustness value calculated for each decision alternative. However, we show that it has a relatively small influence on how those decision alternatives are ranked. This implies that despite the difference in robustness values, similar decision outcomes will be reached in this case study, regardless of the basis on which the scenarios are obtained. It is also revealed that the impact of the scenarios on the robustness values is due to complex interactions with the system model and robustness metrics.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Impact of Scenario Selection on Robustness

McPhail

Maier

Westra

et al. 2020

Water Resources Research

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show abstract

“…A common method to link different scales in scenarios is to incorporate themes from global scenario archetypes into local scenario development exercises or using higher level scenarios for regional or local assessments (Ash et al, 2010;Biggs et al, 2007). There is an increasing amount of "multiscale" scenario studies, which are a set of linked scenarios constructed at two or more scales (Biggs et al, 2007;Wardropper et al, 2016;Kok et al, 2019;Wada et al, 2019).…”

Section: Scenario Processmentioning

confidence: 99%

Bringing the sharing-sparing debate down to the ground—Lessons learnt for participatory scenario development

et al. 2020

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The concepts of Land Sharing (LSH) and Land Sparing (LSP) shall help to manage trade-offs between land use and biodiversity conservation but applications in real world contexts are scarce. We review the literature on scenario and stakeholder processes and present a participatory approach to translate the LSH/LSP concept into practice. It is based on a scenario definition process harmonized across five case studies in Europe and resulted in semi-quantitative participative LSH and LSP scenarios. Harmonization eases comparability among case studies despite fundamentally different scenarios due to heterogeneous conditions across the regions. A key challenge was the right level of standardization for the scenario process to reach a common understanding across case study regions while acknowledging regional peculiarities. The resulting scenarios support for regional specific planning recommendations and can be input to quantitative ecosystem service and biodiversity models.

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“…When the NEST framework was applied to the Indus River basin in Asia it showed that the interlinkages between water and energy have significant policy implications [8]. Both the CLEWs and NEST frameworks are optimization models that choose the optimal development path within the constraints and trade-offs defined in the model structure, and both focus solely on the climate, land, water and energy nexus.…”

Section: Recent Modelling Advancesmentioning

confidence: 99%

Embedding the United Nations Sustainable Development Goals into Systems Analysis – Expanding the Food-Energy-Water Nexus

Niet

Arianpoo

Kuling

et al. 2020

Preprint

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Background: There have been many studies that consider the nexus interactions between energy systems, land use, water use and climate adaptation and impacts. These studies have filled a gap in the literature to allow for more effective policymaking by considering the trade-offs between land use, energy infrastructure as well as the use of water for agriculture and providing energy services. Though these studies fill a significant gap in the modelling literature, we argue that more work is needed to effectively consider policy trade-offs between the 17 United Nations Sustainable Development Goals (SDGs) to avoid missing important interactions.Results: We examine the 17 SDGs to determine if it should be included in a modelling framework and the challenges of doing so. We show that the nexus of climate, land, energy and water needs to be expanded to consider economic well-being of both individuals and the greater economy, health benefits and impacts, as well as land use in terms of both food production and in terms of sustaining ecological diversity and natural capital. Such an expansion will allow systems models to better address the trade-offs and synergies inherent in the SDGs. Luckily, although there are some challenges with expanding the nexus in this way, we feel the challenges are generally modest and that many model structures can already incorporate many of these factors without significant modification.Finally, we argue that SDGs 16 and 17 cannot be met without open-source models and open data to allow for transparent analysis that can be used and reused with a low cost of entry for modellers from less well off nations.Conclusions: To effectively address the SDGs there is a need to expand the common definition of the nexus of climate, land, energy, and water to include the synergies and trade-offs of health impacts, ecological diversity and the system requirements for human and environmental well-being. In most cases, expanding models to be able to incorporate these factors will be relatively straight forward, but open models and analysis are needed to fully support the SDGs.

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Co-designing Indus Water-Energy-Land Futures

Cited by 62 publications

References 75 publications

Impact of Scenario Selection on Robustness

Impact of Scenario Selection on Robustness

Bringing the sharing-sparing debate down to the ground—Lessons learnt for participatory scenario development

Embedding the United Nations Sustainable Development Goals into Systems Analysis – Expanding the Food-Energy-Water Nexus

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