title: Blind testing of shoreline evolution models.

authors: Montaño, Jennifer

abstract: Beaches around the world continuously adjust to daily and seasonal changes in wave and tide conditions, which are themselves changing over longer time-scales. Different approaches to predict multi-year shoreline evolution have been implemented; however, robust and reliable predictions of shoreline evolution are still problematic even in short-term scenarios (shorter than decadal). Here we show results of a modelling competition, where 19 numerical models (a mix of established shoreline models and machine learning techniques) were tested using data collected for Tairua beach, New Zealand with 18 years of daily averaged alongshore shoreline position and beach rotation (orientation) data obtained from a camera system. In general, traditional shoreline models and machine learning techniques were able to reproduce shoreline changes during the calibration period (1999-2014) for normal conditions but some of the model struggled to predict extreme and fast oscillations. During the forecast period (unseen data, 2014-2017), both approaches showed a decrease in models' capability to predict the shoreline position. This was more evident for some of the machine learning algorithms. A model ensemble performed better than individual models and enables assessment of uncertainties in model architecture. Research-coordinated approaches (e.g., modelling competitions) can fuel advances in predictive capabilities and provide a forum for the discussion about the advantages/disadvantages of available models.

text: Blind testing of shoreline evolution models. Beaches around the world continuously adjust to daily and seasonal changes in wave and tide conditions, which are themselves changing over longer time-scales. Different approaches to predict multi-year shoreline evolution have been implemented; however, robust and reliable predictions of shoreline evolution are still problematic even in short-term scenarios (shorter than decadal). Here we show results of a modelling competition, where 19 numerical models (a mix of established shoreline models and machine learning techniques) were tested using data collected for Tairua beach, New Zealand with 18 years of daily averaged alongshore shoreline position and beach rotation (orientation) data obtained from a camera system. In general, traditional shoreline models and machine learning techniques were able to reproduce shoreline changes during the calibration period (1999-2014) for normal conditions but some of the model struggled to predict extreme and fast oscillations. During the forecast period (unseen data, 2014-2017), both approaches showed a decrease in models' capability to predict the shoreline position. This was more evident for some of the machine learning algorithms. A model ensemble performed better than individual models and enables assessment of uncertainties in model architecture. Research-coordinated approaches (e.g., modelling competitions) can fuel advances in predictive capabilities and provide a forum for the discussion about the advantages/disadvantages of available models.

year: 2020

title: Growth in densely populated Asia: implications for primary product exporters

authors: Anderson, Kym

subjects: Asian economic growth

abstract: Economic growth and integration in Asia is rapidly increasing the global economic importance of the region. To the extent that this growth continues and is strongest in natural resource-poor Asian economies, it will add to global demand for imports of primary products, to the benefit of (especially nearby) resource-abundant countries. How will global production, consumption and trade patterns change by 2030 in the course of such economic developments and structural changes? We address this question using the GTAP model and Version 8.1 of the 2007 GTAP database, together with supplementary data from a range of sources, to support projections of the global economy from 2007 to 2030 under various scenarios. Factor endowments and real gross domestic product are assumed to grow at exogenous rates, and trade-related policies are kept unchanged to generate a core baseline, which is compared with an alternative slower growth scenario. We also consider the impact of several policy changes aimed at increasing China's agricultural self-sufficiency relative to the 2030 baseline. Policy implications for countries of the Asia-Pacific region are drawn out in the final section.

text: Growth in densely populated Asia: implications for primary product exporters Economic growth and integration in Asia is rapidly increasing the global economic importance of the region. To the extent that this growth continues and is strongest in natural resource-poor Asian economies, it will add to global demand for imports of primary products, to the benefit of (especially nearby) resource-abundant countries. How will global production, consumption and trade patterns change by 2030 in the course of such economic developments and structural changes? We address this question using the GTAP model and Version 8.1 of the 2007 GTAP database, together with supplementary data from a range of sources, to support projections of the global economy from 2007 to 2030 under various scenarios. Factor endowments and real gross domestic product are assumed to grow at exogenous rates, and trade-related policies are kept unchanged to generate a core baseline, which is compared with an alternative slower growth scenario. We also consider the impact of several policy changes aimed at increasing China's agricultural self-sufficiency relative to the 2030 baseline. Policy implications for countries of the Asia-Pacific region are drawn out in the final section.

year: 2013

title: Understanding the context of hospital transfers and away-from-home hospitalisations for Māori

authors: Cormack, Donna

subjects: Humans

abstract: In Aotearoa New Zealand, people regularly travel away from their home to receive hospital care. While the role of whānau support for patients in hospital is critical for Māori, there is little information about away-from-home hospitalisations. This paper describes the frequency and patterning of away-from-home hospitalisations and inter-hospital transfers for Māori. Data from the National Minimum Dataset (NMDS), for the 6-year period of 1 January 2009-31 December 2014, were analysed. Basic frequencies, means and descriptive statistics were produced using SAS software. We found that more than 10% of all routine hospitalisations constituted an away-from-home hospitalisation for Māori; that is, a hospitalisation that was in a district health board (DHB) other than the DHB of usual residence for the patient. One quarter (25.19%) of transfer hospitalisations were to a DHB other than the patient's DHB of domicile. Away-from-home hospital admissions increase for Māori as deprivation increases for both routine and transfer admissions, with over half of Māori hospital admissions among people who live in areas of high deprivation. This analysis aids in understanding away-from-home hospitalisations for Māori whānau, the characteristics associated with these types of hospitalisations and supports the development and implementation of policies which better meet whānau Māori needs. The cumulative impact of the need to travel to hospital for care, levels of poverty and a primarily reimbursement-based travel assistance system all perpetuate an unequal cost burden placed upon Māori whānau.

text: Understanding the context of hospital transfers and away-from-home hospitalisations for Māori In Aotearoa New Zealand, people regularly travel away from their home to receive hospital care. While the role of whānau support for patients in hospital is critical for Māori, there is little information about away-from-home hospitalisations. This paper describes the frequency and patterning of away-from-home hospitalisations and inter-hospital transfers for Māori. Data from the National Minimum Dataset (NMDS), for the 6-year period of 1 January 2009-31 December 2014, were analysed. Basic frequencies, means and descriptive statistics were produced using SAS software. We found that more than 10% of all routine hospitalisations constituted an away-from-home hospitalisation for Māori; that is, a hospitalisation that was in a district health board (DHB) other than the DHB of usual residence for the patient. One quarter (25.19%) of transfer hospitalisations were to a DHB other than the patient's DHB of domicile. Away-from-home hospital admissions increase for Māori as deprivation increases for both routine and transfer admissions, with over half of Māori hospital admissions among people who live in areas of high deprivation. This analysis aids in understanding away-from-home hospitalisations for Māori whānau, the characteristics associated with these types of hospitalisations and supports the development and implementation of policies which better meet whānau Māori needs. The cumulative impact of the need to travel to hospital for care, levels of poverty and a primarily reimbursement-based travel assistance system all perpetuate an unequal cost burden placed upon Māori whānau.

year: 2022-11-11