title: An analysis of the surface water resources of the upper Taieri River, Otago

authors: Simmers, I.

abstract: To plan a water resource survey data collection programme, it is vital to first establish the purpose for which the gathered data are to be used, and the degree of precision of the information at a particular confidence level that will be adequate. Purpose will determine the required data precision. Precision requirements will in turn dictate minimum record lengths of each variable necessary to estimate population parameters at a point, and the network density needed for parameter estimation over an area. 
This study is concerned with the data requirements and analyses for the planning of an irrigation scheme in the Maniototo Plains and Styx Basin, Central Otago. The 95 percent confidence level is adopted for required data precision. Allowable standard errors of population parameter estimates are stated to be 10 percent for streamflow and precipitation and five percent for temperature. 
Measured monthly, seasonal, and annual parameter values of these variables are summarised and discussed. Although the data collection networks are shown to be theoretically acceptable for most purposes, the measured data do not allow estimation of all the needed total - and sub-catchment population parameters at the required precision level. Record synthesis is necessary in order to increase the amount of information contained at this stage in the precipitation and streamflow data series. 
Techniques chosen for time series extension and spatial extrapolation are linear7 curvilinear and multiple regression analyses, water balance, conceptual and stochastic models. Each model is described, and limitations or advantages outlined. Also discussed are the theoretical aspects which concern precision of population parameter estimates from blended data, standard errors of prediction for synthetic records, and the relative simulation and prediction abilities of the models chosen. Split-record techniques are used to evaluate within and between model efficiencies. 
Addition of synthesised records to the precipitation and streamflow data series still does not permit estimates of all required population parameters at the levels of precision stated as needed. In some instances, record extension results in a decrease in statistical information. For design of any irrigation scheme to proceed now, therefore, the chosen error criteria must be judged too stringent for the Upper Taieri data. If the calculated standard errors cannot be accepted, all precipitation and streamflow records from the study area will require extension by additional observations.
 The study is also used as an opportunity to check the validity of commonly. accepted concepts of 'regional hydrology', at least within the East Otago Region. It is concluded that for low flows, hydrological homogeneity cannot be assumed to equate with uniformity of basin characteristics. Regions are better defined in terms of allowable areal variation for stated hydrological parameters. The study area is not hydrologically homogeneous by the defined criteria. Further, the boundaries of hydrologically similar regions vary dependent on which streamflow parameter is considered. 
Results are presented in British units throughout this study, since these are the units in which the basic data were measured and analysed.

text: An analysis of the surface water resources of the upper Taieri River, Otago To plan a water resource survey data collection programme, it is vital to first establish the purpose for which the gathered data are to be used, and the degree of precision of the information at a particular confidence level that will be adequate. Purpose will determine the required data precision. Precision requirements will in turn dictate minimum record lengths of each variable necessary to estimate population parameters at a point, and the network density needed for parameter estimation over an area. 
This study is concerned with the data requirements and analyses for the planning of an irrigation scheme in the Maniototo Plains and Styx Basin, Central Otago. The 95 percent confidence level is adopted for required data precision. Allowable standard errors of population parameter estimates are stated to be 10 percent for streamflow and precipitation and five percent for temperature. 
Measured monthly, seasonal, and annual parameter values of these variables are summarised and discussed. Although the data collection networks are shown to be theoretically acceptable for most purposes, the measured data do not allow estimation of all the needed total - and sub-catchment population parameters at the required precision level. Record synthesis is necessary in order to increase the amount of information contained at this stage in the precipitation and streamflow data series. 
Techniques chosen for time series extension and spatial extrapolation are linear7 curvilinear and multiple regression analyses, water balance, conceptual and stochastic models. Each model is described, and limitations or advantages outlined. Also discussed are the theoretical aspects which concern precision of population parameter estimates from blended data, standard errors of prediction for synthetic records, and the relative simulation and prediction abilities of the models chosen. Split-record techniques are used to evaluate within and between model efficiencies. 
Addition of synthesised records to the precipitation and streamflow data series still does not permit estimates of all required population parameters at the levels of precision stated as needed. In some instances, record extension results in a decrease in statistical information. For design of any irrigation scheme to proceed now, therefore, the chosen error criteria must be judged too stringent for the Upper Taieri data. If the calculated standard errors cannot be accepted, all precipitation and streamflow records from the study area will require extension by additional observations.
 The study is also used as an opportunity to check the validity of commonly. accepted concepts of 'regional hydrology', at least within the East Otago Region. It is concluded that for low flows, hydrological homogeneity cannot be assumed to equate with uniformity of basin characteristics. Regions are better defined in terms of allowable areal variation for stated hydrological parameters. The study area is not hydrologically homogeneous by the defined criteria. Further, the boundaries of hydrologically similar regions vary dependent on which streamflow parameter is considered. 
Results are presented in British units throughout this study, since these are the units in which the basic data were measured and analysed.

year: 1975

title: Sensitivity of GIS-derived terrain variables at multiple scales for modelling stoat (Mustela erminea) activity

authors: Martin, R.D.

subjects: terrain

abstract: This research combines automated Geographical Information Systems (GIS) and iterative logistic regression scripting to data-mine for terrain variables that predict stoat (Mustela erminea) visitation to tracking-stations in a New Zealand indigenous forest and explore the impact of spatial analysis scale on modelling outcomes. Variables such as curvature and density of tracks are dependent on the scale of the analysis window used to compute the values. With automated GIS analysis it is possible to derive a large number of terrain parameters that vary in computational scale. It is common for analysts to make nominal choices regarding the size and type of analysis windows when calculating these derived variables, without testing the statistical validity of that choice. Stoats are a significant pest in New Zealand and threaten extinction for a number of vulnerable native species. Field data on stoat activity, based on footprint tracking tunnels, were used to develop an Akaike Information Criterion (AIC) optimised predictive model applying stepwise model selection. Once the optimal model was determined, the sensitivity of the model to different terrain parameters was tested by systematically substituting each variable and calculating the difference this made to the model equation. The most dominant terrain predictors influencing stoat visitation were proximity to tracks, altitude, northerly and easterly aspect, mean curvature, and topographical position and slope. Proximity to tracks and mean curvature were the most sensitive variables to analysis scale. This paper demonstrates the importance of considering scale in developing predictive models and the need to test many ecologically sensible analysis scales in order to find the best predictive variables. The paper concludes that GIS-based spatial data extraction, combined with automated statistical data mining methods, has an important role in developing accurate animal activity models.

text: Sensitivity of GIS-derived terrain variables at multiple scales for modelling stoat (Mustela erminea) activity This research combines automated Geographical Information Systems (GIS) and iterative logistic regression scripting to data-mine for terrain variables that predict stoat (Mustela erminea) visitation to tracking-stations in a New Zealand indigenous forest and explore the impact of spatial analysis scale on modelling outcomes. Variables such as curvature and density of tracks are dependent on the scale of the analysis window used to compute the values. With automated GIS analysis it is possible to derive a large number of terrain parameters that vary in computational scale. It is common for analysts to make nominal choices regarding the size and type of analysis windows when calculating these derived variables, without testing the statistical validity of that choice. Stoats are a significant pest in New Zealand and threaten extinction for a number of vulnerable native species. Field data on stoat activity, based on footprint tracking tunnels, were used to develop an Akaike Information Criterion (AIC) optimised predictive model applying stepwise model selection. Once the optimal model was determined, the sensitivity of the model to different terrain parameters was tested by systematically substituting each variable and calculating the difference this made to the model equation. The most dominant terrain predictors influencing stoat visitation were proximity to tracks, altitude, northerly and easterly aspect, mean curvature, and topographical position and slope. Proximity to tracks and mean curvature were the most sensitive variables to analysis scale. This paper demonstrates the importance of considering scale in developing predictive models and the need to test many ecologically sensible analysis scales in order to find the best predictive variables. The paper concludes that GIS-based spatial data extraction, combined with automated statistical data mining methods, has an important role in developing accurate animal activity models.

year: 2010

title: Teachers' perceptions of the effectiveness of the Whānau Rūmaki teacher education programme, 1990-1992

authors: Kana, Fred

subjects: Maori Language

abstract: In 1990 the School of Education, the University of Waikato, initiated a special option within its regular pre-service teacher training programmes, an option designed to prepare teachers to deliver the New Zealand curriculum in bilingual and total immersion schools through the medium of te reo Māori. This alternative programmed, designated Whānau Rūmaki, was experimental and evolutionary. Inevitably particular elements of it had to be varied with each year's operation as its architects attempted 'to get the mix right'. It is difficult, however, when engaged in the day to day running of a programme, to stand back and review with any degree of objectivity its strengths and weaknesses. This study, therefore, in retrospect attempts to do three things: one, to follow the initial Whānau Rūmaki student cohort through its three or four year training cycle noting especially the difficulties confronting individual students some of whom dropped out of the programme; two, to gather information from as many as possible of the graduates who graduated about how well they felt they had been prepared for the rigours of classroom teaching; three, to be able, after analysing the data gathered, to recommend ways of improving the on-going Whānau Rūmaki programme.

text: Teachers' perceptions of the effectiveness of the Whānau Rūmaki teacher education programme, 1990-1992 In 1990 the School of Education, the University of Waikato, initiated a special option within its regular pre-service teacher training programmes, an option designed to prepare teachers to deliver the New Zealand curriculum in bilingual and total immersion schools through the medium of te reo Māori. This alternative programmed, designated Whānau Rūmaki, was experimental and evolutionary. Inevitably particular elements of it had to be varied with each year's operation as its architects attempted 'to get the mix right'. It is difficult, however, when engaged in the day to day running of a programme, to stand back and review with any degree of objectivity its strengths and weaknesses. This study, therefore, in retrospect attempts to do three things: one, to follow the initial Whānau Rūmaki student cohort through its three or four year training cycle noting especially the difficulties confronting individual students some of whom dropped out of the programme; two, to gather information from as many as possible of the graduates who graduated about how well they felt they had been prepared for the rigours of classroom teaching; three, to be able, after analysing the data gathered, to recommend ways of improving the on-going Whānau Rūmaki programme.

year: 1997