Use Of Uncertainty Research Articles

Extent of Equivalence of Results for Urine Albumin among 3 Candidate Mass Spectrometry Reference Measurement Procedures.

Urine albumin (UA) is an important biomarker of chronic kidney disease. Current in vitro diagnostic medical devices (IVD-MDs) for measuring UA are not standardized, and median results among IVD-MDs differ by approximately 45%. Since fixed decision values are used to interpret UA, higher-order reference measurement procedures (RMPs) are needed for metrological traceability. Three candidate liquid chromatography-tandem mass spectrometry RMPs have been developed for UA. Eight single-donation human urine samples were measured by 3 candidate RMPs. Results were compared using t-test and variance component analysis. The mean results for each urine sample from each RMP laboratory were not statistically different from the overall mean value by t-test. The median total CV including contributions from bias and imprecision among the 3 RMP laboratories was 6.23% using variance component analysis for each sample. The allowable bias to the RMP for an end-user IVD-MD was ≦9.0% or ≦3.0% based on the desirable or optimal total allowable error of 30% or 24%, respectively. A maximum allowable standard uncertainty for an RMP result was determined to be 4.3% or 3.3% for desirable or optimal performance, respectively. The standard uncertainties for all of the RMP laboratories meet the desirable and optimal standard uncertainty specifications. The candidate RMPs for UA in these 3 laboratories have suitable agreement of results and uncertainties for use as higher-order RMPs in the metrological traceability of end-user IVD-MDs for measuring UA.

Desirable uncertainty in science teaching: Exploring teachers’ perceptions and practice of using student scientific uncertainty as a pedagogical resource

Science practice introduces inevitable uncertainties that are desirable for learning. Yet, navigating student scientific uncertainties can be a challenge for teachers. This qualitative study explored how teachers perceive and utilize uncertainty during science instruction. Analysis of interviews and classroom observations collected from 14 middle school teachers in the United States indicated limited awareness of uncertainty's use as a resource in science. Teachers perceived uncertainty as a way to induce curiosity and persist through struggle; however, they were quick to reduce students' scientific uncertainty throughout lessons. Findings suggest that teachers need support to understand how uncertainty navigation can benefit student learning.

Dose estimates and their uncertainties for use in epidemiological studies of radiation-exposed populations in the Russian Southern Urals.

Many residents of the Russian Southern Urals were exposed to radioactive environmental pollution created by the operations of the Mayak Production Association in the mid- 20th century. There were two major releases: the discharge of about 1x1017 Bq of liquid waste into the Techa River between 1949 and 1959; and the atmospheric release of 7.4 * 1016 Bq as a result an explosion in the radioactive waste-storage facility in 1957. The releases into the Techa River resulted in the exposure of more than 30,000 people who lived in riverside villages between 1950 and 1961. The 1957 accident contaminated a larger area with the highest exposure levels in an area that is called the East Urals Radioactive Trace (EURT). Current epidemiologic studies of the exposed populations are based on dose estimates obtained using a Monte-Carlo dosimetry system (TRDS-2016MC) that provides multiple realizations of the annual doses for each cohort member. These dose realizations provide a central estimate of the individual dose and information on the uncertainty of these dose estimates. In addition, the correlation of individual annual doses over realizations provides important information on shared uncertainties that can be used to assess the impact of shared dose uncertainties on risk estimate uncertainty.This paper considers dose uncertainties in the TRDS-2016MC. Individual doses from external and internal radiation sources were reconstructed for 48,036 people based on environmental contamination patterns, residential histories, individual 90Sr body-burden measurements and dietary intakes. Dietary intake of 90Sr resulted in doses accumulated in active bone marrow (or simply, marrow) that were an order of magnitude greater than those in soft tissues. About 84% of the marrow dose and 50% of the stomach dose was associated with internal exposures. The lognormal distribution is well-fitted to the individual dose realizations, which, therefore, could be expressed and easily operated in terms of geometric mean (GM) and geometric standard deviation (GSD). Cohort average GM for marrow and stomach cumulative doses are 0.21 and 0.03 Gy, respectively. Cohort average dose uncertainties in terms of GSD are as follows: for marrow it is 2.93 (90%CI: 2.02-4.34); for stomach and the other non-calcified tissues it is 2.32 (90% CI: 1.78-2.9).

Magnitude and Slip Scaling Relations for Fault-Based Seismic Hazard

ABSTRACTScaling relations play an important role in fault-based seismic hazard estimates. Scaling relations impact estimates of the sizes and rate for a given fault area. Here, we examine which relations are the most useful for these estimates and issues that arise. These include the depth of large event ruptures, transient deepening of seismicity following large events, difficulties in using classical continuum exponent fits, and the importance of large event asymptotics. A new analysis of land-based data calls into question nonspecific exponent fitting, which is a standard practice. We show a dependence on the lower and upper cut-off magnitudes in the data in the best-fitting slope parameter relating magnitude to log area with this approach. We show as well a dependence on assumed data uncertainties. These sensitivities make using this quite standard approach very problematic. Based on this evidence and other factors, we propose recommendations for the minimal branch sets, which preserve epistemic uncertainty for use in fault-based seismic hazard estimates.

Incorporation of Real-Time Earthquake Magnitudes Estimated via Peak Ground Displacement Scaling in the ShakeAlert Earthquake Early Warning System

ABSTRACTThe United States earthquake early warning (EEW) system, ShakeAlert®, currently employs two algorithms based on seismic data alone to characterize the earthquake source, reporting the weighted average of their magnitude estimates. Nonsaturating magnitude estimates derived in real time from Global Navigation Satellite System (GNSS) data using peak ground displacement (PGD) scaling relationships offer complementary information with the potential to improve EEW reliability for large earthquakes. We have adapted a method that estimates magnitude from PGD (Crowell et al., 2016) for possible production use by ShakeAlert. To evaluate the potential contribution of the modified algorithm, we installed it on the ShakeAlert development system for real-time operation and for retrospective analyses using a suite of GNSS data that we compiled. Because of the colored noise structure of typical real-time GNSS positions, observed PGD values drift over time periods relevant to EEW. To mitigate this effect, we implemented logic within the modified algorithm to control when it issues initial and updated PGD-derived magnitude estimates (MPGD), and to quantify MPGD uncertainty for use in combining it with estimates from other ShakeAlert algorithms running in parallel. Our analysis suggests that, with these strategies, spuriously large MPGD will seldom be incorporated in ShakeAlert’s magnitude estimate. Retrospective analysis of data from moderate-to-great earthquakes demonstrates that the modified algorithm can contribute to better magnitude estimates for Mw>7.0 events. GNSS station distribution throughout the ShakeAlert region limits how soon the modified algorithm can begin estimating magnitude in some locations. Furthermore, both the station density and the GNSS noise levels limit the minimum magnitude for which the modified algorithm is likely to contribute to the weighted average. This might be addressed by alternative GNSS processing strategies that reduce noise.

Incidence of Secondary Malignancies in Patients with Chronic Myeloid Leukemia in Chronic Phase (CML-CP) in the Era of Tyrosine Kinase Inhibitors (TKI)

IntroductionWith TKI therapy the survival of patients with CML-CP is approaching to that of general population. Data on the incidence of secondary malignancies in CML is conflicting given the rarity of CML and the low incidence of secondary malignancies. The aim of this study is to evaluate the incidence of secondary malignancies in patients with CML-CP in a large US-based database.MethodsThe Surveillance, Epidemiology, and End Results (SEER) database identified 13,276 patients with newly diagnosed CML-CP during the period from 2001 to 2014. Patients who had prior history of cancer, concurrent diagnosis of other malignancies at the same diagnostic year, and patients who developed secondary leukemia after the diagnosis of CML were excluded. Cumulative incidence of secondary malignancies were estimated with the presence of competing risk of death. Standard incidence ratio (SIR) was calculated from person-years at risk divided by expected cases based on the age-adjusted incidence ratio of the 2000 U.S. standard population.ResultsOf 13,276 patients, secondary malignancies were observed in 597 patients (4%) with a median follow-up of 69 months (Table 1). The three most common secondary malignancies were male genital system 130 (22%), digestive system 124 (21%) and respiratory system, 92 (15%). The 5-year and 10-year cumulative incidence of death for all patients was 30.5% (95% confidence interval [CI], 29.6-31.4), and 41.8% (95% CI, 40.7-43.0). The 5-year and 10-year cumulative incidence of secondary malignancies were 4.4% (95% CI, 4.0-4.8), and 7.2% (95% CI, 6.6-7.9), respectively (Figure 1). Overall SIR was 1.204 (95% CI, 1.108-1.301). The increased SIRs were observed in male genital system of 1.593 (95% CI, 1.319-1.866); digestive system, 1.291 (95% CI, 1.064-1.519); skin, 1.588 (95% CI, 1.083-2.093); urinary system, 1.366 (95% CI, 1.008-1.724); and miscellaneous, 1.877 (1.033-2.721) (Figure 2). The decreased SIR was observed in breast cancer of 0.665 (95% CI, 0.479-0.852). Overall excess absolute risk was 1.714 per 1,000 person years at risk (95% CI, 0.622-2.805).ConclusionRelative incidence of overall secondary malignancies in CML-CP is slightly higher than that of general population with minimal increase in the excess absolute risk. Given the limitation of registry data, the uncertainty of use and type of TKI, and response status at the diagnosis of secondary malignancies, conclusions regarding actual risk should be cautiously interpreted. It is also at this stage not possible to determine whether any possible increased risk is associated with the diagnosis of CML-CP per se or the use of TKIs. Further analysis is needed. [Display omitted] DisclosuresKantarjian:Bristol-Meyers Squibb: Research Funding; Novartis: Research Funding; ARIAD: Research Funding; Amgen: Research Funding; Pfizer: Research Funding; Delta-Fly Pharma: Research Funding. O'Brien:Amgen: Consultancy; Alexion: Consultancy; Celgene: Consultancy; Astellas: Consultancy; Janssen: Consultancy; Vaniam Group LLC: Consultancy; AbbVie: Consultancy; TG Therapeutics: Consultancy, Other: Research Support: Honorarium, Research Funding; GSK: Consultancy; Acerta: Other: Research Support: Honorarium, Research Funding; Gilead Sciences, Inc.: Consultancy, Other: Research Support: Honorarium, Research Funding; Regeneron: Other: Research Support: Honorarium, Research Funding; Aptose Biosciences, Inc.: Consultancy; ProNAI: Other: Research Support: Honorarium, Research Funding; Pharmacyclics: Consultancy, Other: Research Support: Honorarium, Research Funding; CLL Global Research Foundation: Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Research Funding; Sunesis: Consultancy. Wierda:Emergent: Consultancy, Honoraria, Research Funding; Janssen: Research Funding; Karyopharm: Research Funding; The University of Texas MD Anderson Cancer Center: Employment; Acerta: Research Funding; Kite: Research Funding; GSK/Novartis: Consultancy, Honoraria, Research Funding; Genzyme: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria, Research Funding; Juno: Research Funding; Genentech/Roche: Consultancy, Honoraria, Research Funding; Sanofi: Consultancy, Honoraria; Merck: Consultancy, Honoraria; Pharmacyclics: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Research Funding. Daver:Daiichi-Sankyo: Research Funding; Kiromic: Research Funding; Incyte Corporation: Honoraria, Research Funding; Jazz: Consultancy; Bristol-Myers Squibb Company: Consultancy, Research Funding; Otsuka America Pharmaceutical, Inc.: Consultancy; Karyopharm: Consultancy, Research Funding; Novartis Pharmaceuticals Corporation: Consultancy; Immunogen: Research Funding; Pfizer Inc.: Consultancy, Research Funding; Sunesis Pharmaceuticals, Inc.: Consultancy, Research Funding. Takahashi:Symbio Pharmaceuticals: Consultancy. Jabbour:Bristol-Myers Squibb: Consultancy. Cortes:Novartis Pharmaceuticals Corporation: Consultancy, Research Funding; Sun Pharma: Research Funding; BMS: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Teva: Research Funding; ImmunoGen: Consultancy, Research Funding; ARIAD: Consultancy, Research Funding.

Quantifying Global and Random Uncertainties in High Resolution Global Geomagnetic Field Models Used for Directional Drilling

SummaryTotal field strength, declination, and dip angle of the Earth's magnetic field, in conjunction with gravity, are used by magnetic-survey tools to determine a wellbore's location. Magnetic field values may be obtained from global models that, depending on the model, have a wide range of spatial resolution at the Earth's surface from large scale (3000 km) to small scale (28 km). The magnetic field varies continuously in both time and space, so no model can fully capture the complexity of all sources; hence, there are uncertainties associated with the values provided. The SPE Wellbore Positioning Technical Section/Industry Steering Committee on Wellbore Surveying Accuracy (ISCWSA) published their original measurement-while-drilling (MWD) error model in 2000. Such models and uncertainties define positional error ellipsoids along the wellbore, which assist the driller in achieving their geological target, in addition to aiding collision avoidance. With the recent update to Revision 5 of the ISCWSA error model, we have reassessed the uncertainties associated with our latest high-resolution global magnetic field model.We describe the derivation of location-specific global and random uncertainties for use with predicted geomagnetic values from high-resolution models within magnetic MWD survey-tool-error models. We propose a sophisticated approach to provide realistic values at different locations around the globe; for example, we determine separate errors for regions where the models have high spatial resolution from aeromagnetic data compared to regions where only satellite data are available.The combined uncertainties are freely available via a web service with which the user can also see how they vary with time. The use of the revised uncertainty values in the MWD-error model, in most cases, reduces the positional error ellipsoids and allows better use of the increased accuracy from recent improvements in geomagnetic modeling. This is demonstrated using the new uncertainty values in the MWD-error model for three standard ISCWSA well profiles. A fourth theoretical well offshore Brazil where the vertical magnetic field is weak shows that with drillstring interference correction relying on the more uncertain magnetic dip, the positional error ellipsoids can increase. This is clearly of concern for attaining geological targets and collision avoidance.

A Value of Information Analysis of Research on the 21-Gene Assay for Breast Cancer Management

ObjectivesThe 21-gene assay Oncotype DX (21-GA) shows promise as a guide in deciding when to initiate adjuvant chemotherapy in women with hormone receptor–positive early-stage breast cancer. Nevertheless, its routine use remains controversial, owing to insufficient evidence of its clinical utility and cost-effectiveness. Accordingly, we aim to quantify the value of conducting further research to reduce decision uncertainty in the use of the 21-GA. MethodsUsing value of information methods, we first generated probability distributions of survival and costs for decision making with and without the 21-GA alongside traditional risk prediction. These served as the input to a comparison of 3 alternative study designs: a retrospective observational study to update risk classification from the 21-GA, a prospective observational study to estimate prevalence of chemotherapy use, and a randomized controlled trial (RCT) of the 21-GA predictive value. ResultsWe found that current evidence strongly supports the use of the 21-GA in intermediate- and high-risk women. Further research should focus on low-risk women, among whom the cost-effectiveness findings remained equivocal. For this population, we identified a high value of reducing uncertainty in the 21-GA use for all proposed research studies. The RCT had the greatest potential to efficiently reduce the likelihood of choosing a suboptimal strategy, providing a value between $162 million and $1.1 billion at willingness-to-pay thresholds of $150 000 to $200 000/quality-adjusted life years. ConclusionFuture research to inform 21-GA decision making is of high value. The RCT of the 21-GA predictive value has the greatest potential to efficiently reduce decision uncertainty around 21-GA use in women with low-risk early-stage breast cancer.

Quantification of system uncertainties in activation experiments at nuclear research reactors

Neutron flux measurements in reactor cores are often used for code validation studies, however reported experimental flux uncertainties remain limited in scope. This work presents both a detailed assessment of several flux measurement uncertainties and a guideline for reporting these quantities. The effects of the sample position, the presence of 135Xe, the control rod positions, reactor power, and nuclear data during activation procedures were individually quantified at the McMaster Nuclear Reactor. NiCr flux wires were used to study the 51Cr (n,γ) activation reaction experimentally and through a series of MCNP6 simulations, and the SCALE-6.2.2 252-group library was used to study cross-section data uncertainty for use in translating activation measurements into neutron flux values. The placement of the sample and the reactor power measurements were found to be the most significant contributors to the overall measurement uncertainty. A procedure for reporting the results and uncertainties of an irradiation procedure is provided.

Electricity rates for electric vehicle direct current fast charging in the United States

While several efforts are promoting a widespread and convenient network of direct current fast charging (DCFC) stations to support electric vehicles, there is limited understanding of the magnitude and variability of the cost of electricity for these applications. This information gap may hinder optimal investing and planning for charging station placement and in turn affect electric vehicle adoption and usage. Here, we assess the electricity cost for different scenarios of DCFC station size and use based on over 7500 commercial and industrial electricity rates available for 2017 across the United States. Results show that the cost of electricity for DCFC varies dramatically, ranging from less than $0.10 to over $2 per kilowatt-hour, depending on station design and high uncertainty in use. The main driver of cost is low utilization, which results from a combination of few charging events and limited energy recharged during each event. Low utilization leads to significantly higher electricity cost, particularly for rates with demand charges; however, cost decreases rapidly as utilization increases. For high-utilization stations, selecting rates with demand charges can actually reduce electricity costs compared to non-demand-charge rates. Moreover, significant opportunities for cost savings based on existing rates include preferential charging during off-peak hours and limiting multi-plug station power so that not all plugs can be used simultaneously at maximum power.

Evaluation of Ge-doped silica fibre TLDs for in vivo dosimetry during intraoperative radiotherapy

Ge-doped silica fibre (GDSF) thermoluminescence dosimeters (TLD) are non-hygroscopic spatially high-resolution radiation sensors with demonstrated potential for radiotherapy dosimetry applications. The INTRABEAM® system with spherical applicators, one of a number of recent electronic brachytherapy sources designed for intraoperative radiotherapy (IORT), presents a representative challenging dosimetry situation, with a low keV photon beam and a desired rapid dose-rate fall-off close-up to the applicator surface. In this study, using the INTRABEAM® system, investigations were made into the potential application of GDSF TLDs for in vivo IORT dosimetry. The GDSFs were calibrated over the respective dose- and depth-range 1 to 20 Gy and 3 to 45 mm from the x-ray probe. The effect of different sizes of spherical applicator on TL response of the fibres was also investigated. The results show the GDSF TLDs to be applicable for IORT dose assessment, with the important incorporated correction for beam quality effects using different spherical applicator sizes. The total uncertainty in use of this type of GDSF for dosimetry has been found to range between 9.5% to 12.4%. Subsequent in vivo measurement of skin dose for three breast patients undergoing IORT were performed, the measured doses being below the tolerance level for acute radiation toxicity.

Development of a Ukrainian- speaking questionnaire on tolerance to uncertainty for use by the National Police of Ukraine

Development of a Ukrainian- speaking questionnaire on tolerance to uncertainty for use by the National Police of Ukraine

Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems

Abstract. The global carbon cycle is an important component of the Earth system and it interacts with the hydrology, energy and nutrient cycles as well as ecosystem dynamics. A better understanding of the global carbon cycle is required for improved projections of climate change including corresponding changes in water and food resources and for the verification of measures to reduce anthropogenic greenhouse gas emissions. An improved understanding of the carbon cycle can be achieved by data assimilation systems, which integrate observations relevant to the carbon cycle into coupled carbon, water, energy and nutrient models. Hence, the ingredients for such systems are a carbon cycle model, an algorithm for the assimilation and systematic and well error-characterised observations relevant to the carbon cycle. Relevant observations for assimilation include various in situ measurements in the atmosphere (e.g. concentrations of CO2 and other gases) and on land (e.g. fluxes of carbon water and energy, carbon stocks) as well as remote sensing observations (e.g. atmospheric composition, vegetation and surface properties).We briefly review the different existing data assimilation techniques and contrast them to model benchmarking and evaluation efforts (which also rely on observations). A common requirement for all assimilation techniques is a full description of the observational data properties. Uncertainty estimates of the observations are as important as the observations themselves because they similarly determine the outcome of such assimilation systems. Hence, this article reviews the requirements of data assimilation systems on observations and provides a non-exhaustive overview of current observations and their uncertainties for use in terrestrial carbon cycle data assimilation. We report on progress since the review of model-data synthesis in terrestrial carbon observations by Raupach et al.(2005), emphasising the rapid advance in relevant space-based observations.

Constraining the GENIE model of neutrino-induced single pion production using reanalyzed bubble chamber data

The longstanding discrepancy between bubble chamber measurements of $\nu_\mu$-induced single pion production channels has led to large uncertainties in pion production cross section parameters for many years. We extend the reanalysis of pion production data in deuterium bubble chambers where this discrepancy is solved (Wilkinson et al., PRD 90 (2014) 112017) to include the $\nu_{\mu}n\rightarrow \mu^{-}p\pi^{0}$ and $\nu_{\mu}n\rightarrow \mu^{-}n\pi^{+}$ channels, and use the resulting data to fit the parameters of the GENIE (Rein-Sehgal) pion production model. We find a set of parameters that can describe the bubble chamber data better than the GENIE default parameters, and provide updated central values and reduced uncertainties for use in neutrino oscillation and cross section analyses which use the GENIE model. We find that GENIE's non-resonant background prediction has to be significantly reduced to fit the data, which may help to explain the recent discrepancies between simulation and data observed by the MINERvA coherent pion and NOvA oscillation analyses.

K-shell fluorescence yields and their uncertainties for use in hybrid K-edge densitometry

Hybrid K-edge densitometry (HKED) is a non-destructive analytical assay technique used to provide rapid determination of actinide concentration in tank solutions. Of special interest for HKED is the estimation, along with associated uncertainties, of the ratio of the flouresence yeilds, ωK, of uranium and plutonium. Limited experimental data for ωK(Z) as a function of atomic number, Z, exist and the data are subject to experimental uncertainty. Previous studies have provided values for ωK(Z) with uncertainty estimates but have not included covariance information. We use a phenomenological model with a bootstrapping method to generate the ratio ωK(94)/ωK(92) and associated uncertainty.

Volumetric and dynamic uncertainty modelling in Block 22, offshore Trinidad and Tobago

Block 22, located offshore in the North Coast Marine Area (NCMA) of Trinidad and Tobago, contains the Cassra gas accumulation discovered by the Cassra-1 and Cassra-2 wells. Both wells encountered dry, biogenic gas in early Pliocene, shoreface–shelfal sandstone reservoirs. A best-practice modelling methodology is documented to capture a range of subsurface uncertainties for use in reservoir simulation to generate production profiles in support of pre-development project planning. Calibration of a sequence stratigraphic interpretation from seismic with core data was instrumental in generating a depositional model, within which sedimentary facies could be stochastically distributed and used to constrain the population of petrophysical properties. Static geological uncertainties were modelled using an uncertainty workflow methodology in commercial three-dimensional (3D) geomodelling software, resulting in multiple, static model realizations and probabilistic GIIP (Gas Initially In Place) distributions for Cassra and some nearby prospects. The multi-regional model required careful selection of realizations for reservoir simulation, based on a ranking scheme that combined GIIP, GRV (gross rock volume) and net:gross (net to gross ratio), and not simply P90–P50–P10 percentiles from the global distribution. The reservoir simulation phase included a dynamic uncertainty workflow using commercial experimental design modelling software. By including dynamic uncertainties such as horizontal/vertical permeability and well productivity in the workflow, a more objectively defined suite of production profile predictions was achieved.

Content and Relational Implications of Children-In-Law's Relational Uncertainty Within the In-Law Dyad During the Transition to Extended Family

Two studies were conducted to examine children-in-law's experiences of relational uncertainty and satisfaction during the transition to marriage. In Study 1, responses revealed children-in-law's (N = 154) myriad concerns revolving around three, broad themes of relational uncertainty: dyadic uncertainty, family system uncertainty, and individual uncertainty. Based on these results, we constructed scales of children-in-law's uncertainty for use in Study 2 (N = 204). Bivariate correlations revealed negative associations between children-in-law's uncertainty and relationship satisfaction within both the in-law and marital dyads. Collectively, these findings extend theoretical understanding of the role of relational uncertainty and social network influence during a crucial family transition.

Analyzing the Uncertainties in Use of Forest-Derived Biomass Equations for Open-Grown Trees in Agricultural Land

Quantifying carbon in agroforestry trees requires biomass equations that capture the growth differences (e.g., tree specific gravity and architecture) created in the more open canopies of agroforestry plantings compared with those generally encountered in forests. Whereas forest-derived equations are available, equations for open-grown trees are not. Data from destructively sampled open-grown trees in the Northern Great Plains were used to examine the uncertainties in the use of forest-derived equations for open-grown trees. Three species, representative of major morphological types of agroforestry trees, were studied: green ash, Austrian pine, and eastern redcedar. Forest-derived equations provided good estimates of trunk biomass at lower diameter ranges but, as diameter increased, resulted in overestimation up to 40% for individual trees. Across the full diameter ranges, individual tree branch biomass was underestimated by 29 – 82%, depending on species and equation source (regional or nonregional). Although open-grown trunk and branch biomass curves diverged down and up, respectively, from their forest-derived counterparts, those for the whole tree tended to converge, albeit significantly above the forest-derived curves. Whole-tree biomass for individual trees was underestimated by at least 18%. To correct the biases, we studied the adjustment factor of forestto open-grown tree biomass. It shows a power function with diameter. On a whole-tree basis, it was evaluated as a constant (1.2) independent of species and diameters. Application of this constant factor adjusted the biomass underestimation of three-species-mixed plantation by forest-derived equations from 21 to 4.6%, providing a cost-efficient approach to use forest-derived equations for open-grown trees in agriculture land.

A framework to quantify GCM uncertainties for use in impact assessment studies

The impacts of climate change on hydrology and water resources are commonly assessed through future projections of Global Climate Models (GCMs). However, since GCM projections are uncertain due to standard errors in the model structure, scenarios and initial conditions, the reliability of impact assessments becomes questionable. This study proposes a new framework to examine uncertainties in GCM simulations and impact assessment studies. The framework involves quantification of GCM simulation uncertainties and consideration of this uncertainty in the estimation of parameters in impact assessment models. This is done through the following steps: (1) systematic biases in GCM simulations are corrected using the nested bias correction (NBC) approach; (2) uncertainties in projections from GCMs are estimated using an uncertainty metric, the square root error variance (SREV); and (3) uncertainty is accounted during parameter estimation of impact assessment models using simulation–extrapolation (SIMEX). The utility of the proposed framework is illustrated for assessment of future droughts through estimation of improved model parameters of the standard precipitation index (SPI). Precipitation outputs from six GCMs, three scenarios and three realisations from the Coupled Model Inter-comparison Project phase 3 (CMIP3) datasets are considered for the analysis. The results reveal that model structural uncertainty is the main source of standard error in GCM simulations and that correction for biases decreases this error. The SPI model parameters as well as the future drought frequency before and after implementation of the method are found to differ widely. The proposed method allows quantifying and accounting for GCM uncertainties in climate change impact assessment more reliably.

The uncertainty cascade in model fusion

Abstract There are increasing demands in assessing the impacts of change on environmental systems to couple different model components together in a cascade, the outputs from one component providing the inputs to another with or without feedbacks in the coupling. Each model component will necessarily involve some uncertainty in its specification and simulations that can be conditioned using some observational data. Taking account of this uncertainty should result in more robust decision making and may change the nature of the decision made. The difficulty in environmental decision making is in making proper estimates of uncertainties when so many of the sources of uncertainty result from lack of knowledge (epistemic uncertainties) rather than uncertainty that can be treated as random variability (aleatory uncertainty). This is particularly the case for problems that involve cascades of model components. Examples are the use of UKCP09 climate scenarios in impact studies, flood risk assessment involving models of runoff generation and their impact on hydraulic models of flood plains, and integrated catchment management involving upstream to downstream surface and subsurface routing of water quality variables. The uncertainties are such that, even for relatively simple problems, they can result in wide ranges of potential outputs. This poses the questions that will be considered in this paper: how to take account of knowledge uncertainties in cascades of model components; and how to constrain the potential uncertainties for use in making decisions. In particular we highlight the difficulties of defining statistical likelihood functions that properly reflect the non-stationary uncertainty characteristics expected of epistemic sources of uncertainty.