Predicting water availability in the Antarctic dry valleys using GIS and remote sensing

Water is one of the most important ingredients for life on Earth. The presence or absence of biologically available water determines whether or not life will exist. In Antarctica most water exists as ice and is not available for sustaining life. It is usually only during December and January that temperatures will rise above zero and melt water becomes available (Kennedy, 1993). For this reason Antarctica is regarded as the driest desert in the world (Peck et al., 2006, McKnight et al., 1999)

Predicting Water Availability in the Antarctic Dry Valleys using Geographic Information Systems and Remote Sensing

Water is one of the most important ingredients for life on Earth. The presence or absence of biologically available water determines whether or not life will exist. Antarctica is an environment where abiotic constraints, particularly water, strongly influence the distribution and diversity of biota. As Antarctic biology is relatively simple when compared to more temperate climates, it is a prime location for researching constraints on biodiversity, and what may be the impacts of changes to these constraints resulting from climate change and human disturbance. This research uses Geographic Information Systems (GIS) and remote sensing to develop a relative water availability index of three Dry Valleys in Southern Victoria Land, Antarctica. This study area is being used for the IPY Terrestrial Biocomplexity project, an international collaboration researching the distribution, diversity and complexity of biology in the Dry Valleys. The development of a predictive water availability model will contribute greatly to their research goals. This thesis describes the sources of biologically available water in the Dry Valleys and its interaction with biota. Remotely sensed data of these sources is gathered and various methods of analysing the data are explored. This includes creating a mean snow cover distribution model from MODIS data over 4 summer seasons, and Landsat7 ETM+ surface temperature data. These data sets, combined with a high resolution LIDAR Digital Elevation Model and glacier and lake locations, are then analysed with GIS to produce a Compound Topographic Index (CTI), a model showing the likely accumulation and dispersal of liquid water given the spatial distribution of water sources and the flow of water over the terrain according to the influence of gravity. Visualisation techniques are used to validate the resulting model, including the use of 3D visualisation and comparison of drainage patterns using overlays of a high resolution ALOS image. This research concludes that GIS and remote sensing are valuable tools for predicting water distribution in Antarctica. Although cloud cover, varied illumination and differing spatial resolutions can create limitations, remote sensing's cost effective and environmentally sound method of data capture and the computational and spatial modelling capabilities of GIS make their use well suited to the Antarctic environment

Spatial modelling of wetness for the Antarctic Dry Valleys

This paper describes a method used to model relative wetness for part of the Antarctic Dry Valleys using Geographic Information Systems (GIS) and remote sensing. The model produces a relative index of liquid water availability using variables that influence the volume and distribution of water. Remote sensing using Moderate Resolution Imaging Spectroradiometer (MODIS) images collected over four years is used to calculate an average index of snow cover and this is combined with other water sources such as glaciers and lakes. This water source model is then used to weight a hydrological flow accumulation model that uses slope derived from Light Detection and Ranging (LIDAR) elevation data. The resulting wetness index is validated using three-dimensional visualization and a comparison with a high-resolution Advanced Land Observing Satellite image that shows drainage channels. This research demonstrates that it is possible to produce a wetness model of Antarctica using data that are becoming widely available

Calculating the surface melt rate of Antarctic glaciers using satellite-derived temperatures and stream flows

Melt rate models are fundamental for understanding the impacts of climate change on glaciers and the subsequent effects on habitats and sea level rise. Ice melt models have mostly been derived from energy balance or air temperature index calculations. This research demonstrates that satellite-derived land surface temperature (LST) measurements provide a simpler method for estimating surface melt rate that substitutes for energy balance models. Since these satellite images are continuous (distributed) across space, they do not need calibration for topography. Antarctic glacier melt discharge data from nearby stream gauges were used to calibrate an LST-derived melt model. The model calculations are simplified by the fact that groundwater flow is assumed to be minimal due to permafrost, and the glaciers are assumed to only melt on the surface. A new method called the Temperature Area Sum model is developed, which builds on an existing Temperature Area Index model. A daily melt rate model is developed using 77 Landsat 8 images and calculates the volume of meltwater produced per hectare for any given LST between − 7 and 0 °C. A seasonal average daily melt rate model is also developed that uses 1660 MODIS images. The utility of the seasonal MODIS model is demonstrated by calculating melt rates, water flows and wetness across the entire Ross Sea Region. An unexpected large wet area to the southwest of the Ross Ice Shelf requires further investigation and demonstrates the usefulness of these models for large remote areas. Surface melt rate and wetness can now be calculated for different climate change scenarios

Visualising and communicating population diversity through web maps

An online New Zealand Atlas of Population Change (NZAPC) is being developed (http://socialatlas.waikato.ac.nz/) to communicate the interaction and associated diversity resulting from three important components of population change: migration, natural change (births minus deaths), and population ageing. A comparative evaluation is made between five prominent international population web maps that utilise automated map server technology and the NZAPC, which uses static maps designed collaboratively by a demographer and a cartographer. This evaluation combined the needs of demography, cartographic communication and human computer interaction, as well as consideration of software. Interactive online maps and graphics are a powerful medium for communicating population distribution and associated diversity, but care needs to be taken in the choice of data and their interpretation. The NZAPC differs from the other web map sites evaluated in that it is accompanied by supporting research and narrative. The design of the NZAPC has had extensive demographic and cartographic input so that users are provided with relevant and easy-to-understand maps and graphs. This is a different approach to mainstream population web mapping sites that provide access to large data sets and allow the user to dynamically construct their own maps. We argue that the provision of research-supported maps and graphs by experienced researchers has a rising place in online mapping. We provide examples from the NZAPC with a focus on assisting New Zealanders to better understand population change and thus prepare for, respond to and celebrate the increasingly diverse population of Aotearoa New Zealand

Spatial modelling of wetness for the Antarctic Dry Valleys

This paper describes a method used to model relative wetness for part of the Antarctic Dry Valleys using Geographic Information Systems (GIS) and remote sensing. The model produces a relative index of liquid water availability using variables that influence the volume and distribution of water. Remote sensing using Moderate Resolution Imaging Spectroradiometer (MODIS) images collected over four years is used to calculate an average index of snow cover and this is combined with other water sources such as glaciers and lakes. This water source model is then used to weight a hydrological flow accumulation model that uses slope derived from Light Detection and Ranging (LIDAR) elevation data. The resulting wetness index is validated using three-dimensional visualization and a comparison with a high-resolution Advanced Land Observing Satellite image that shows drainage channels. This research demonstrates that it is possible to produce a wetness model of Antarctica using data that are becoming widely available. Keywords: GIS; water; Antarctica; remote sensing Citation: Polar Research 2011, 30, 6330, DOI: 10.3402/polar.v30i0.633

Fishing activity in the Waikato and Waipa rivers

The purpose of this research project is to collate information regarding the recent use of fisheries resources in the Waikato River and Waipa River catchment areas. In particular, the project sought to summarise the commercial, customary, and recreational fishing activity in the catchments of the Waikato and Waipa rivers in the spatial context of recently introduced co-governance areas. These fisheries include, but are not exclusive to, the broad range of aquatic life managed under the Fisheries Act 1996. Such information is required to support management which includes a co-management framework. The research describes the commercial, customary and recreational fisheries including species and quantities taken, fishing methods, and seasonal influences

Hindcasting water clarity from Landsat satellite images of unmonitored shallow lakes in the Waikato region, New Zealand

Cost-effective monitoring is necessary for all investigations of lake ecosystem responses to perturbations and long-term change. Satellite imagery offers the opportunity to extend low-cost monitoring and to examine spatial and temporal variability in water clarity data. We have developed automated procedures using Landsat imagery to estimate total suspended sediments (TSS), turbidity (TURB) in nephlometric turbidity units (NTU) and Secchi disc transparency (SDT) in 34 shallow lakes in the Waikato region, New Zealand, over a 10-year time span. Fifty-three Landsat 7 Enhanced Thematic Mapper Plus images captured between January 2000 and March 2009 were used for the analysis, six of which were captured within 24 h of physical in situ measurements for each of 10 shallow lakes. This gave 32-36 usable data points for the regressions between surface reflectance signatures and in situ measurements, which yielded r (2) values ranging from 0.67 to 0.94 for the three water clarity variables. Using these regressions, a series of Arc Macro Language scripts were developed to automate image preparation and water clarity analysis. Minimum and maximum in situ measurements corresponding to the six images were 2 and 344 mg/L for TSS, 75 and 275 NTU for TURB, and 0.05 and 3.04 m for SDT. Remotely sensed water clarity estimates showed good agreement with temporal patterns and trends in monitored lakes and we have extended water clarity datasets to previously unmonitored lakes. High spatial variability of TSS and water clarity within some lakes was apparent, highlighting the importance of localised inputs and processes affecting lake clarity. Moreover, remote sensing can give a whole lake view of water quality, which is very difficult to achieve by in situ point measurements

Accuracy assessment of land surface temperature retrievals from Landsat 7 ETM + in the Dry Valleys of Antarctica using iButton temperature loggers and weather station data

The McMurdo Dry Valleys of Antarctica are the largest snow/ice-free regions on this vast continent, comprising 1 % of the land mass. Due to harsh environmental conditions, the valleys are bereft of any vegetation. Land surface temperature is a key determinate of microclimate and a driver for sensible and latent heat fluxes of the surface. The Dry Valleys have been the focus of ecological studies as they arguably provide the simplest trophic structure suitable for modelling. In this paper, we employ a validation method for land surface temperatures obtained from Landsat 7 ETM + imagery and compared with in situ land surface temperature data collected from four transects totalling 45 iButtons. A single meteorological station was used to obtain a better understanding of daily and seasonal cycles in land surface temperatures. Results show a good agreement between the iButton and the Landsat 7 ETM + product for clear sky cases. We conclude that Landsat 7 ETM + derived land surface temperatures can be used at broad spatial scales for ecological and meteorological research