A virtual hydrological framework for evaluation of stochastic rainfall models

Stochastic rainfall modelling is a commonly used technique for evaluating the impact of flooding, drought, or climate change in a catchment. While considerable attention has been given to the development of stochastic rainfall models (SRMs), significantly less attention has been paid to developing methods to evaluate their performance. Typical evaluation methods employ a wide range of rainfall statistics. However, they give limited understanding about which rainfall statistical characteristics are most important for reliable streamflow prediction. To address this issue a formal evaluation framework is introduced, with three key features: (i) streamflow-based, to give a direct evaluation of modelled streamflow performance, (ii) virtual, to avoid the issue of confounding errors in hydrological models or data, and (iii) targeted, to isolate the source of errors according to specific sites and seasons. The virtual hydrological evaluation framework uses two types of tests, integrated tests and unit tests, to attribute deficiencies that impact on streamflow to their original source in the SRM according to site and season. The framework is applied to a case study of 22 sites in South Australia with a strong seasonal cycle. In this case study, the framework demonstrated the surprising result that apparently “good” modelled rainfall can produce “poor” streamflow predictions, whilst “poor” modelled rainfall may lead to “good” streamflow predictions. This is due to the representation of highly seasonal catchment processes within the hydrological model that can dampen or amplify rainfall errors when converted to streamflow. The framework identified the importance of rainfall in the “wetting-up” months (months where the rainfall is high but streamflow low) of the annual hydrologic cycle (May and June in this case study) for providing reliable predictions of streamflow over the entire year despite their low monthly flow volume. This insight would not have been found using existing methods and highlights the importance of the virtual hydrological evaluation framework for SRM evaluation.Bree Bennett, Mark Thyer, Michael Leonard, Martin Lambert and Bryson Bate

A comprehensive and systematic evaluation framework for a parsimonious daily rainfall field model

The spatial distribution of rainfall has a significant influence on catchment dynamics and the generation of streamflow time series. However, there are few stochastic models that can simulate long sequences of stochastic rainfall fields continuously in time and space. To address this issue, the first goal of this study was to present a new parsimonious stochastic model that produces daily rainfall fields across the catchment. To achieve parsimony, the model used the latent-variable approach (because this parsimoniously simulates rainfall occurrences as well as amounts) and several other assumptions (including contemporaneous and separable spatiotemporal covariance structures). The second goal was to develop a comprehensive and systematic evaluation (CASE) framework to identify model strengths and weaknesses. This included quantitative performance categorisation that provided a systematic, succinct and transparent method to assess and summarise model performance over a range of statistics, sites, scales and seasons. The model is demonstrated using a case study from the Onkaparinga catchment in South Australia. The model showed many strengths in reproducing the observed rainfall characteristics with the majority of statistics classified as either statistically indistinguishable from the observed or within 5% of the observed across the majority of sites and seasons. These included rainfall occurrences/amounts, wet/dry spell distributions, annual volumes/extremes and spatial patterns, which are important from a hydrological perspective. One of the few weaknesses of the model was that the total annual rainfall in dry years (lower 5%) was overestimated by 15% on average over all sites. An advantage of the CASE framework was that it was able to identify the source of this overestimation was poor representation of the annual variability of rainfall occurrences. Given the strengths of this continuous daily rainfall field model it has a range of potential hydrological applications, including drought and flood risk.Bree Bennett, Mark Thyer, Michael Leonard, Martin Lambert, Bryson Bate

Estimating extreme spatial rainfall intensities

Determining the impact of catchment flooding requires an estimate of extreme spatial rainfall intensity. Current flood design practice typically converts a point estimate of rainfall intensity into a spatial rainfall intensity using an areal reduction factor, assumed constant across an entire region. Areal reduction factors do not explicitly consider regional variations in extreme rainfall. Here, a new approach for spatial estimates of extreme rainfall is introduced that directly incorporates the spatial area (A) into an intensity-frequency-duration relationship (IFD). This IFDA approach uses spatial rainfall fields to overcome shortcomings of the areal reduction factor by explicitly incorporating spatial variations in the extreme rainfall intensity. The IFDA approach is evaluated for 11 case study regions in Australia, across climates (tropical to Mediterranean), areas (25–7,225  km2), durations (1–4 days), and average recurrence intervals (ARI 2–100 years). The change in extreme spatial rainfall with respect to area varies markedly within each region suggesting that constant areal reduction factors for a region are inappropriate. Constant areal reduction factors are shown to underestimate extreme spatial rainfall intensities by 5–15%. The IFDA approach avoids these biases and is a promising new technique for use in design flood estimation.Bree Bennett, Martin Lambert, Mark Thyer, Bryson C. Bates, and Michael Leonar

ENIGMA-anxiety working group: Rationale for and organization of large-scale neuroimaging studies of anxiety disorders

Anxiety disorders are highly prevalent and disabling but seem particularly tractable to investigation with translational neuroscience methodologies. Neuroimaging has informed our understanding of the neurobiology of anxiety disorders, but research has been limited by small sample sizes and low statistical power, as well as heterogenous imaging methodology. The ENIGMA‐Anxiety Working Group has brought together researchers from around the world, in a harmonized and coordinated effort to address these challenges and generate more robust and reproducible findings. This paper elaborates on the concepts and methods informing the work of the working group to date, and describes the initial approach of the four subgroups studying generalized anxiety disorder, panic disorder, social anxiety disorder, and specific phobia. At present, the ENIGMA‐Anxiety database contains information about more than 100 unique samples, from 16 countries and 59 institutes. Future directions include examining additional imaging modalities, integrating imaging and genetic data, and collaborating with other ENIGMA working groups. The ENIGMA consortium creates synergy at the intersection of global mental health and clinical neuroscience, and the ENIGMA‐Anxiety Working Group extends the promise of this approach to neuroimaging research on anxiety disorders

The Effect of Auditory Distraction on the Useful Field of View in Hearing Impaired Individuals and its implications for driving

This study assessed whether the increased demand of listening in hearing impaired individuals exacerbates the detrimental impact of auditory distraction on a visual task (useful field of view test), relative to normally hearing listeners. Auditory distraction negatively affects this visual task, which is linked with various driving performance outcomes. Hearing impaired and normally hearing participants performed useful field of view testing with and without a simultaneous listening task. They also undertook a cognitive test battery. For all participants, performing the visual and auditory tasks together reduced performance on each respective test. For a number of subtests, hearing impaired participants showed poorer visual task performance, though not to a statistically significant extent. Hearing impaired participants were significantly poorer at a reading span task than normally hearing participants and tended to score lower on the most visually complex subtest of the visual task in the absence of auditory task engagement. Useful field of view performance is negatively affected by auditory distraction, and hearing loss may present further problems, given the reductions in visual and cognitive task performance suggested in this study. Suggestions are made for future work to extend this study, given the practical importance of the findings

Experimental evaluation of the dynamic seasonal streamflow forecasting approach

The primary focus of this experimental evaluation project is to answer the key question: is it possible to provide accurate and reliable seasonal streamflow forecasts using the dynamic hydrologic modelling approach? To address this issue, this experimental project evaluated the performance of the dynamic modelling approach to key catchments in the Murray-Darling Basin, where statistical seasonal streamflow forecasts are currently available.Tuteja NK, Shin D, Laugesen R, Khan U, Shao Q, Wang E, Li M, Zheng H, Kuczera G, Kavetski D, Evin G, Thyer M, MacDonald A, Chia T & Le

EMDR Effects on Pursuit Eye Movements

This study aimed to objectivize the quality of smooth pursuit eye movements in a standard laboratory task before and after an Eye Movement Desensitization and Reprocessing (EMDR) session run on seven healthy volunteers. EMDR was applied on autobiographic worries causing moderate distress. The EMDR session was complete in 5 out of the 7 cases; distress measured by SUDS (Subjective Units of Discomfort Scale) decreased to a near zero value. Smooth pursuit eye movements were recorded by an Eyelink II video system before and after EMDR. For the five complete sessions, pursuit eye movement improved after their EMDR session. Notably, the number of saccade intrusions—catch-up saccades (CUS)—decreased and, reciprocally, there was an increase in the smooth components of the pursuit. Such an increase in the smoothness of the pursuit presumably reflects an improvement in the use of visual attention needed to follow the target accurately. Perhaps EMDR reduces distress thereby activating a cholinergic effect known to improve ocular pursuit