title: Henry V in 1972: Learning from Ngaio Marsh.

authors: Houlahan, Mark

abstract: Mark Houlahan University of Waikato Henry the Fifth in 1972: learning from Ngaio Marsh In the evening of October 1, 1972, the James Hay Theatre in the Christchurch Town Hall was officially launched with an impressively mounted production of Shakespeare’s Henry V, directed by Ngaio Marsh, internationally famous as one of the Queens of Crime fiction, and who had directed high quality Shakespeare productions in Ōtautahi/Christchuch since 1943. The production, using over 100 actors and featuring professional actors Marsh had trained who returned from England to perform, was a pinnacle of her production style, and each of the ten performances sold out. Marsh’s meticulously prepared promptbooks for the show, housed in the Turnbull Library, show every cut and move sketched by Marsh in advance. The Marsh archives also document reviewers’ reactions and recollections from the company, and contain a rich array of visual evidence: posters, production stills, and the official programme. In my paper I will use this data to evoke this lavish event. In 2019 the Town Hall re-opened after extensive restoration following the 2011 earthquakes, a process documented in The Christchurch Town Hall 1965-2019: a Dream Renewed (Canterbury UP, 2020); and the venue has begun presenting post-Covid entertainments. It is timely then to pivot back to 1972 and ask what we can learn from this production about the place of Marsh’s theatre in the development of performance culture in Aotearoa; and open out to the wider, ongoing questions as to the place of Shakespeare in our cultural fabric. Mark Houlahan is Associate Professor of English in Te Kura Toi (School of Arts), University of Waikato. He has published widely in Shakespeare Studies with a special focus on the afterlife of Shakespeare’s works in Aotearoa/New Zealand, as seen, for example, in his chapter: “From the Shakespeare Hut to the Pop-up Globe: Shakespeare, memory and New Zealand, 1916-2016”, in G. McMullan, P. Mead, A. G. Ferguson, M. Houlahan, & K. Flaherty (Eds.), Antipodal Shakespeare Remembering and Forgetting in Britain, Australia and New Zealand, 1916 - 2016 (pp. 117-144).

text: Henry V in 1972: Learning from Ngaio Marsh. Mark Houlahan University of Waikato Henry the Fifth in 1972: learning from Ngaio Marsh In the evening of October 1, 1972, the James Hay Theatre in the Christchurch Town Hall was officially launched with an impressively mounted production of Shakespeare’s Henry V, directed by Ngaio Marsh, internationally famous as one of the Queens of Crime fiction, and who had directed high quality Shakespeare productions in Ōtautahi/Christchuch since 1943. The production, using over 100 actors and featuring professional actors Marsh had trained who returned from England to perform, was a pinnacle of her production style, and each of the ten performances sold out. Marsh’s meticulously prepared promptbooks for the show, housed in the Turnbull Library, show every cut and move sketched by Marsh in advance. The Marsh archives also document reviewers’ reactions and recollections from the company, and contain a rich array of visual evidence: posters, production stills, and the official programme. In my paper I will use this data to evoke this lavish event. In 2019 the Town Hall re-opened after extensive restoration following the 2011 earthquakes, a process documented in The Christchurch Town Hall 1965-2019: a Dream Renewed (Canterbury UP, 2020); and the venue has begun presenting post-Covid entertainments. It is timely then to pivot back to 1972 and ask what we can learn from this production about the place of Marsh’s theatre in the development of performance culture in Aotearoa; and open out to the wider, ongoing questions as to the place of Shakespeare in our cultural fabric. Mark Houlahan is Associate Professor of English in Te Kura Toi (School of Arts), University of Waikato. He has published widely in Shakespeare Studies with a special focus on the afterlife of Shakespeare’s works in Aotearoa/New Zealand, as seen, for example, in his chapter: “From the Shakespeare Hut to the Pop-up Globe: Shakespeare, memory and New Zealand, 1916-2016”, in G. McMullan, P. Mead, A. G. Ferguson, M. Houlahan, & K. Flaherty (Eds.), Antipodal Shakespeare Remembering and Forgetting in Britain, Australia and New Zealand, 1916 - 2016 (pp. 117-144).

year: 2021

title: Lake level forecasting for hydro power operation in the Clutha catchment

authors: Waters, Amy

abstract: The Clutha River is New Zealand’s largest river, located within New Zealand’s largest catchment. The river runs through two hydro-power stations, the Clyde Dam and downstream the Roxburgh Dam, together providing around 10% of New Zealand’s electrical energy. Over 80% of the river flow at Clyde Dam is sourced from the outflow of three large lakes further up in the catchment, Lake Wanaka, Lake Wakatipu and Lake Hāwea. To efficiently operate the hydro-scheme the operator, Contact Energy, requires hourly forecast of the inflows into the head-pond lake of the Clyde Dam, Lake Dunstan. The current model is subject to some degree of predictive error and it has been identified that improving the accuracy of the forecast levels of Lakes Wanaka and Wakatipu may reduce the error of the inflow model.
This project develops an empirical model for estimating the lake level changes, with a lead-time from 1 hour out to 48 hours, in Lakes Wanaka and Wakatipu, using only a few independent variables. The empirical model was developed, calibrated, and first evaluated using recorded rainfall and temperature data (hindcast validation). The model was then revaluated using forecast rainfall and temperature data to gain an understanding of how the model will perform during operation (forecast validation). 
The empirical model has two main components, the first component estimates the lake level recession rates as a function of current lake level. The second component estimates the lake rise resulting from recent rainfall in the catchment, the model uses an inverse Gaussian distribution to represent the lake level rise hydrograph form resulting from recent effective rainfall in the catchment. Average catchment temperature is used as a proxy for estimating the proportion of rainfall contributing to lake level rise. 
During the hindcast validation the model performed reasonably well, closely estimating the time distribution of positive lake level changes and lake level recessions. For Lakes Wanaka and Wakatipu, the Nash-Sutcliffe efficiency index values for each season, at lead-time of 48 hours, had minimal change from the calibration index values, apart from in spring where the values notably dropped. 

To perform the forecast validation, the forecast rainfall was first correlated to recorded rainfall, for which the model was calibrated. The use of weather-based forecasts of rainfall and temperature introduced a significant amount of error. While most of the time the forecast rainfall accurately predicted the presence of rainfall, the forecast rainfall depth was subject to a large error. This transferred through to the model output, with the model largely accurately predicting if the lake level will rise or fall but lost accuracy predicting the magnitude of lake level rises. 
For the forecast validation the Nash-Sutcliffe efficiency index values for each season, at a lead-time of 48 hours, all dropped, apart from winter, when compared to the hindcast calibration fits. Again, spring performed the worst for both lakes. The model tended to underpredict most lake levels rises, with the extent of underprediction increasing with increasing predicted lake level rise magnitudes. The quality of the forecast validation of the model is subject to a level of uncertainty itself. This is because the time period of the validation had low rainfall, with relatively few lake level rise events. 
The model was shown to be limited by the assumption being made by the model that rain gauge rainfall is representative of the spatially average catchment rainfall. This is most often not the case and leads to errors in the model outputs. It may be possible to improve the predictive ability of the model by sourcing rainfall data more representative of the spatially average catchment rainfall. The model will also likely be improved by performing a recalibration using forecast data, this is highly recommended once more data becomes available.
While not perfect, as with any hydrological model, the model has shown to be able to reasonably forecast lake level changes in an operational situation, when considering the uncertainties associated with forecast rainfall and rain gauge data.

text: Lake level forecasting for hydro power operation in the Clutha catchment The Clutha River is New Zealand’s largest river, located within New Zealand’s largest catchment. The river runs through two hydro-power stations, the Clyde Dam and downstream the Roxburgh Dam, together providing around 10% of New Zealand’s electrical energy. Over 80% of the river flow at Clyde Dam is sourced from the outflow of three large lakes further up in the catchment, Lake Wanaka, Lake Wakatipu and Lake Hāwea. To efficiently operate the hydro-scheme the operator, Contact Energy, requires hourly forecast of the inflows into the head-pond lake of the Clyde Dam, Lake Dunstan. The current model is subject to some degree of predictive error and it has been identified that improving the accuracy of the forecast levels of Lakes Wanaka and Wakatipu may reduce the error of the inflow model.
This project develops an empirical model for estimating the lake level changes, with a lead-time from 1 hour out to 48 hours, in Lakes Wanaka and Wakatipu, using only a few independent variables. The empirical model was developed, calibrated, and first evaluated using recorded rainfall and temperature data (hindcast validation). The model was then revaluated using forecast rainfall and temperature data to gain an understanding of how the model will perform during operation (forecast validation). 
The empirical model has two main components, the first component estimates the lake level recession rates as a function of current lake level. The second component estimates the lake rise resulting from recent rainfall in the catchment, the model uses an inverse Gaussian distribution to represent the lake level rise hydrograph form resulting from recent effective rainfall in the catchment. Average catchment temperature is used as a proxy for estimating the proportion of rainfall contributing to lake level rise. 
During the hindcast validation the model performed reasonably well, closely estimating the time distribution of positive lake level changes and lake level recessions. For Lakes Wanaka and Wakatipu, the Nash-Sutcliffe efficiency index values for each season, at lead-time of 48 hours, had minimal change from the calibration index values, apart from in spring where the values notably dropped. 

To perform the forecast validation, the forecast rainfall was first correlated to recorded rainfall, for which the model was calibrated. The use of weather-based forecasts of rainfall and temperature introduced a significant amount of error. While most of the time the forecast rainfall accurately predicted the presence of rainfall, the forecast rainfall depth was subject to a large error. This transferred through to the model output, with the model largely accurately predicting if the lake level will rise or fall but lost accuracy predicting the magnitude of lake level rises. 
For the forecast validation the Nash-Sutcliffe efficiency index values for each season, at a lead-time of 48 hours, all dropped, apart from winter, when compared to the hindcast calibration fits. Again, spring performed the worst for both lakes. The model tended to underpredict most lake levels rises, with the extent of underprediction increasing with increasing predicted lake level rise magnitudes. The quality of the forecast validation of the model is subject to a level of uncertainty itself. This is because the time period of the validation had low rainfall, with relatively few lake level rise events. 
The model was shown to be limited by the assumption being made by the model that rain gauge rainfall is representative of the spatially average catchment rainfall. This is most often not the case and leads to errors in the model outputs. It may be possible to improve the predictive ability of the model by sourcing rainfall data more representative of the spatially average catchment rainfall. The model will also likely be improved by performing a recalibration using forecast data, this is highly recommended once more data becomes available.
While not perfect, as with any hydrological model, the model has shown to be able to reasonably forecast lake level changes in an operational situation, when considering the uncertainties associated with forecast rainfall and rain gauge data.

year: 2019

title: Engaging Māori in Biobanking and Genetic Research: Legal, Ethical and Policy Challenges

authors: Beaton, Angela

subjects: Indigenous

abstract: Publically funded biobanking initiatives and genetic research should contribute towards reducing inequalities in health by reducing the prevalence and burden of disease. It is essential that Maori and other Indigenous populations share in health gains derived from these activities. The Health Research Council of New Zealand has funded a research project (2012-2015) to identify Maori perspectives on biobanking and genetic research, and to develop cultural guidelines for ethical biobanking and genetic research involving biospecimens. This review describes relevant values and ethics embedded in Maori indigenous knowledge, and how they may be applied to culturally safe interactions between biobanks, researchers, individual participants, and communities. Key issues of ownership, privacy, and consent are also considered within the legal and policy context that guides biobanking and genetic research practices within New Zealand. Areas of concern are highlighted and recommendations of international relevance are provided. To develop a productive environment for "next-generation" biobanking and genomic research,"‘next-generation" regulatory solutions will be required.

text: Engaging Māori in Biobanking and Genetic Research: Legal, Ethical and Policy Challenges Publically funded biobanking initiatives and genetic research should contribute towards reducing inequalities in health by reducing the prevalence and burden of disease. It is essential that Maori and other Indigenous populations share in health gains derived from these activities. The Health Research Council of New Zealand has funded a research project (2012-2015) to identify Maori perspectives on biobanking and genetic research, and to develop cultural guidelines for ethical biobanking and genetic research involving biospecimens. This review describes relevant values and ethics embedded in Maori indigenous knowledge, and how they may be applied to culturally safe interactions between biobanks, researchers, individual participants, and communities. Key issues of ownership, privacy, and consent are also considered within the legal and policy context that guides biobanking and genetic research practices within New Zealand. Areas of concern are highlighted and recommendations of international relevance are provided. To develop a productive environment for "next-generation" biobanking and genomic research,"‘next-generation" regulatory solutions will be required.

year: 2015