Towards Best Practice Framing of Uncertainty in Scientific Publications: A Review of Water Resources Research Abstracts

Uncertainty is recognized as a key issue in water resources research, amongst other sciences. Discussions of uncertainty typically focus on tools and techniques applied within an analysis, e.g. uncertainty quantification and model validation. But uncertainty is also addressed outside the analysis, in writing scientific publications. The language that authors use conveys their perspective of the role of uncertainty when interpreting a claim —what we call here “framing” the uncertainty. This article promotes awareness of uncertainty framing in four ways. 1) It proposes a typology of eighteen uncertainty frames, addressing five questions about uncertainty. 2) It describes the context in which uncertainty framing occurs. This is an interdisciplinary topic, involving philosophy of science, science studies, linguistics, rhetoric, and argumentation. 3) We analyze the use of uncertainty frames in a sample of 177 abstracts from the Water Resources Research journal in 2015. This helped develop and tentatively verify the typology, and provides a snapshot of current practice. 4) Provocative recommendations promote adjustments for a more influential, dynamic science. Current practice in uncertainty framing might be described as carefully-considered incremental science. In addition to uncertainty quantification and degree of belief (present in ~5% of abstracts), uncertainty is addressed by a combination of limiting scope, deferring to further work (~25%) and indicating evidence is sufficient (~40%) – or uncertainty is completely ignored (~8%). There is a need for public debate within our discipline to decide in what context different uncertainty frames are appropriate. Uncertainty framing cannot remain a hidden practice evaluated only by lone reviewers

Propagating uncertainty from catchment experiments to estimates of streamflow reduction by invasive alien plants in southwestern South Africa

Abstract Long-term catchment experiments from South Africa have demonstrated that afforestation of grasslands and shrublands significantly reduces surface-water runoff. These results have guided the country’s forestry policy and the implementation of a national Invasive Alien Plant (IAP) control programme for the past few decades. Unfortunately, woody IAP densities continue to increase, compounding existing threats to water security from population growth and climatic change. Decision makers need defensible estimates of the impacts of afforestation or invasions on runoff to weigh up alternative land use options, or guide investment of limited resources into ecosystem restoration through IAP clearing versus engineering-based water-augmentation schemes. Existing attempts to extrapolate the impacts observed in catchment afforestation experiments to broad-scale IAP impacts give no indication of uncertainty. Globally, the uncertainty inherent in the results from paired-catchment experiments is seldom propagated into subsequent analyses making use of these data. We present a fully reproducible Bayesian model that propagates uncertainty from input data to final estimates of changes in streamflow when extrapolating from catchment experiments to broader landscapes. We apply our model to South Africa’s catchment experiment data, estimating streamflow losses to plantations and analogous plant invasions in the catchments of southwestern South Africa, including uncertainty. We estimate that regional streamflow is reduced by 304 million m3 or 4.14% annually as a result of IAPs, with an upper estimate of 408 million m3 (5.54%) and a lower estimate of 267 million m3 (3.63%). Our model quantifies uncertainty associated with all parameters and their contribution to overall uncertainty, helping guide future research needs. Acknowledging and quantifying inherent uncertainty enables more defensible decisions regarding water resource management. This article is protected by copyright. All rights reserved

INTEGRATED ASSESSMENT MODELLING

integrated assessment

Toward best practice framing of uncertainty in scientific publications: A review of Water Resources Research abstracts

Uncertainty is recognized as a key issue in water resources research, among other sciences. Discussions of uncertainty typically focus on tools and techniques applied within an analysis, e.g., uncertainty quantification and model validation. But uncertainty is also addressed outside the analysis, in writing scientific publications. The language that authors use conveys their perspective of the role of uncertainty when interpreting a claim—what we call here “framing” the uncertainty. This article promotes awareness of uncertainty framing in four ways. (1) It proposes a typology of eighteen uncertainty frames, addressing five questions about uncertainty. (2) It describes the context in which uncertainty framing occurs. This is an interdisciplinary topic, involving philosophy of science, science studies, linguistics, rhetoric, and argumentation. (3) We analyze the use of uncertainty frames in a sample of 177 abstracts from the Water Resources Research journal in 2015. This helped develop and tentatively verify the typology, and provides a snapshot of current practice. (4) We make provocative recommendations to achieve a more influential, dynamic science. Current practice in uncertainty framing might be described as carefully considered incremental science. In addition to uncertainty quantification and degree of belief (present in ∼5% of abstracts), uncertainty is addressed by a combination of limiting scope, deferring to further work (∼25%) and indicating evidence is sufficient (∼40%)—or uncertainty is completely ignored (∼8%). There is a need for public debate within our discipline to decide in what context different uncertainty frames are appropriate. Uncertainty framing cannot remain a hidden practice evaluated only by lone reviewers.J. H. A. Guillaume was funded by the Academy of Finland project WASCO (grant 305471) and Emil Aaltonen Foundation funded project eat-lesswater. C. Helgeson received funding from the Arts and Humanities Research Council (AHRC) project Managing Severe Uncertainty (AH/ J006033/1) and L’Agence Nationale de la Recherche (ANR) project DUSUCA (ANR-14-CE29–0003-01)

A bricolage-style exploratory scenario analysis to manage uncertainty in socio-environmental systems modeling: investigating integrated water management options

Exploratory analysis, while useful in assessing the implications of model assumptions under large uncertainty, is considered at best a semi-structured activity. There is no algorithmic way for performing exploratory analysis and the existing canonical techniques have their own limitations. To overcome this, we advocate a bricolage-style exploratory scenario analysis, which can be crafted by pragmatically and strategically combining different methods and practices. Our argument is illustrated using a case study in integrated water management in the Murray-Darling Basin, Australia. Scenario ensembles are generated to investigate potential policy innovations, climate and crop market conditions, as well as the effects of uncertainties in model components and parameters. Visualizations, regression trees and marginal effect analyses are exploited to make sense of the ensemble of scenarios. The analysis includes identifying patterns within a scenario ensemble, by visualizing initial hypotheses that are informed by prior knowledge, as well as by visualizing new hypotheses based on identified influential variables. Context-specific relationships are explored by analyzing which values of drivers and management options influence outcomes. Synthesis is achieved by identifying context-specific solutions to consider as part of policy design. The process of analysis is cast as a process of finding patterns and formulating questions within the ensemble of scenarios that merit further examination, allowing end-users to make the decision as to what underlying assumptions should be accepted, and whether uncertainties have been sufficiently explored. This approach is especially advantageous when the precise intentions of management are still subject to deliberations. By describing the reasoning and steps behind a bricolage-style exploratory analysis, we hope to raise awareness of the value of sharing this kind of (common but not often documented) analysis process, and motivate further work to improve sharing of know-how about bricolage in practice.This work was funded by the Australian National Centre for Groundwater Research and Training (NCGRT), and the MDBA-NCGRT Partnership. Joseph Guillaume was supported by the Academy of Finland WASCO water scarcity atlas project (grant number 305471

A socio-environmental model for exploring sustainable water management futures: Participatory and collaborative modelling in the Lower Campaspe catchment

Study region: Lower Campaspe, North Central Victoria, Australia Study focus: This paper presents a component-based integrated environmental model developed through participatory processes to explore sustainable water management options. Possible futures with improved farm profitability and ecological outcomes relative to modelled baselines were identified through exploratory modelling. The integrated model and the results produced are intended to raise awareness and facilitate discussion with and amongst stakeholders. New hydrological insights: The modelling illustrates that improved farm level knowledge and management with regard to crop water requirements, soil water capacity, and irrigations are the most significant factors towards achieving outcomes that are robust to a range of climate and water policy futures. Assuming farmer management with regard to these factors are at their most optimal, increasing irrigation efficiency alone did not lead to improved farm profitability and ecological outcomes under drier climate conditions. Likelihood of achieving robust outcomes were further improved through the conjunctive use of surface and groundwater, with increased consideration of groundwater use a key factor. Further discussion on the viability and impact of increased groundwater use and conjunctive use policies should be further considered

Data and Tools to Operationalize Ridge-to-Reef Management and Build Island Resilience in Oceanic Island Environments.

Ph.D. Thesis. University of Hawaiʻi at Mānoa 2017

Assessing oil spill risks in the northern Baltic Sea with Bayesian network applications

Coastal and marine ecosystems across the globe are heavily impacted by various anthropogenic stressors, which has led to a significant loss of biodiversity and ecosystem services in recent decades. In order to find means to counteract this trend, there is a need to develop methods for assessing the environmental impacts of human activities and the effectiveness of management practices to mitigate the harmful effects. However, this is a challenging task due to the complex interactions within and between the ecosystems and human components, and various uncertainties related to them. Bayesian networks (BNs) are graphical models for reasoning under uncertainty. A BN consists of a set of probabilistic variables connected with links describing causalities within the system. As the states of the variables are described with probability distributions, uncertainty can be described in an explicit manner. BNs also enable integration of qualitative and quantitative knowledge from various sources such as observational data sets, models and expert knowledge. In this thesis I have developed BN models to study environmental risks related to anthropogenic stressors in the Gulf of Finland and the Finnish Archipelago Sea. The main aim is to quantify human impacts on the environment, and to assess the ability of different management measures to lessen these impacts. I focus especially on oil spills resulting from potential tanker accidents and I set out to fill various information gaps related to this recently emerged threat. The thesis includes five papers. In paper I, the main aim is to assess the spatial risk posed by oil spills in the Gulf of Finland and the Finnish Archipelago Sea, and identify species and habitat types with the highest risk. In paper II, I focus on the effectiveness of different oil combating methods to mitigate the negative impacts of oil spills on the ecosystem, and paper III widens the approach to a probabilistic cost-benefit analysis of preventive and post-spill measures. Paper IV deals with multiple risks as, in addition to oil spills, eutrophication and harvesting of species are studied. Paper V reviews and discusses various methods that can be applied to evaluate the uncertainty related to deterministic models, which could increase their usefulness in decision-making. The results suggest that risks related to tanker accidents are distributed unevenly between areas, habitats and species. Furthermore, the results support the current Finnish strategy to base oil combating primarily on offshore recovery vessels instead of chemical dispersants. However, as the efficiency of mechanical recovery is dependent on several factors, there is also a need to develop preventive measures. Although major oil accidents are estimated to be rare events, the costs can be very high, if a spill occurs. The work offers new insights to the oil spill risks in the study area and provides examples how Bayesian networks can be applied in environmental risk assessment. The thesis is a part of the work needed in order to develop comprehensive decision support tools related to environmental risk management in the northern Baltic Sea.Ihmistoiminta vaikuttaa monin haitallisin tavoin merien ja rannikkoalueiden ekosysteemeihin, mikä on johtanut luonnon monimuotoisuuden vähenemiseen ja monien ekosysteemipalveluiden heikkenemiseen. Mikäli tämä kehityskulku halutaan pysäyttää, tarvitaan työkaluja, joilla voidaan tarkastella ihmistoiminnan vahingollisia vaikutuksia ympäristöön ja eri toimenpidevaihtoehtojen kykyä vähentää haittoja. Tämä ei ole kuitenkaan yksinkertaista johtuen ekosysteemien ja ihmisvaikutusten monimutkaisista vuorovaikutussuhteista ja niihin liittyvistä suurista epävarmuuksista. Väitöskirjatyössä on kehitetty malleja Suomenlahden ja Saaristomeren ympäristöriskien arviointiin. Työssä sovelletaan Bayes-verkkoja eli graafisia malleja, joissa kuvataan tutkimusongelmalle keskeiset muuttujat ja niiden väliset syy-seuraussuhteet todennäköisyysjakaumien avulla. Todennäköisyyspohjaisten mallien avulla voidaan ilmentää myös epävarmuutta luontevasti. Bayes-verkot mahdollistavat niin määrällisen kuin laadullisen tiedon käytön samassa mallissa, ja tietoja voidaan yhdistellä monista eri lähteistä kuten tilastoista, muista malleista ja asiantuntija-arvioista. Väitöskirjassa keskitytään erityisesti alusöljyonnettomuuksien ympäristöriskeihin. Työssä arvioidaan öljyonnettomuuksien seurauksia tutkimusalueella esiintyvien lajien ja elinympäristöjen kannalta sekä eri toimenpiteiden tehokkuutta vähentää mahdollisia haittoja. Lisäksi työssä tarkastellaan todennäköisyyspohjaisen kustannus-hyötyanalyysin avulla onnettomuuksien ennaltaehkäisyä ja jälkitorjuntaa sekä esitellään malli, jossa riskitekijöinä ovat öljyonnettomuuksien lisäksi rehevöityminen ja kalastus. Tulosten mukaan öljyonnettomuusriski vaihtelee niin alueiden, lajien kuin elinympäristöjenkin välillä. Tietyt alueet rannikolla ovat suuremmassa vaarassa öljyyntyä kuin toiset, ja alueiden välillä on eroja myös öljylle alttiiden luontoarvojen suhteen. Tulokset myös tukevat Suomen nykyistä öljyntorjuntastrategiaa, joka perustuu mekaaniseen öljynkeruuseen kemiallisten torjunta-aineiden sijaan. Mekaanisen öljyntorjunnan tehokkuus riippuu kuitenkin monesta tekijästä, minkä takia olisi tärkeää kehittää edelleen myös onnettomuuksia ennaltaehkäiseviä toimenpiteitä. Suuret öljyonnettomuudet ovat harvinaisia, mutta tapahtuessaan onnettomuus voi aiheuttaa hyvinkin mittavat kustannukset. Työssä kehiteltyjä malleja ja tuloksia voidaan käyttää päätöksenteon tukena ja kehitettäessä kokonaisvaltaisia työkaluja ympäristöriskien arviointiin ja hallintaan