A system for collecting spatially variable terrain data
Introduction
The natural landscape exhibits spatial variability in a range of properties and state variables. This variability occurs over a wide range of spatial and temporal scales and has a variety of implications. An example of spatial variability of hydrological significance is the spatial variation of soil moisture and the occurrence of saturation excess runoff in catchments. Understanding the characteristics and implications of this spatial variation is important for understanding the behaviour of the landscape and for enlightened management of our land resources. To achieve this it is necessary to be able to map spatially variable characteristics rapidly, economically and at appropriate spatial resolutions.
This paper discusses spatial variability in the landscape. Sampling, instrumentation, logistical and economic issues associated with the measurement of spatially variable parameters are discussed briefly. A ground-based system for acquiring spatially variable data is then described and example soil moisture data sets are presented.
Section snippets
Characteristics of spatial variation
The occurrence of spatial variation in the landscape is clear. Soil moisture varies spatially in response to topographic (Dunne and Black, 1970a, Beven and Kirkby, 1979, Moore et al., 1988) and other effects. This has important implications for runoff generation by the partial area saturation excess mechanism (Dunne and Black, 1970a, Dunne and Black, 1970b, Anderson and Burt, 1978). Understanding the spatial distribution of runoff production would assist in understanding catchment behaviour (
Requirements of field measurements
When making field measurements for the purpose of studying spatial variation it is necessary to identify the resolution (both in space and time) that is required. In making this choice, sampling, instrumentation, logistical and economic issues need to be considered. Up to a point, higher resolution allows a better characterisation of the spatial variation. Often a small set of widely spaced points provides the basis for spatial analysis. As a consequence, the spatial variation often appears
A ground-based data acquisition system
A ground-based system for acquiring spatially distributed data has been developed at the University of Melbourne. It is based on a dedicated data collection vehicle (DCV) and associated equipment (Tyndale-Biscoe, 1994, Moore and Grayson, 1994). This system is being used for hydrologic and other research including the measurement of spatial patterns of soil moisture variation (Western et al., 1996).
Accuracy of the position fixing system
Field testing of the DCV involved firstly testing the accuracy and repeatability of the Accutrak System. Six points were surveyed as accurately as possible with a total station electronic survey instrument over an area of about 3 ha. The beacons were set up over three of these points and the system initialised. The DCV was then driven to the other three points in turn and the coordinates, as measured by the Accutrak, recorded. This was repeated ten times. The results are shown in Table 1.
As can
Conclusion
Data describing spatially variable parameters and state-variables is required to better understand catchment behaviour and to improve land management. Remote sensing can provide some of this data economically; however, there exists a need for cheaper methods of ground based measurement of variables which cannot be remotely sensed, for ground truth data, and for high resolution data. A system for ground based collection of spatially variable data has been developed. It is based on an all terrain
Acknowledgements
Capital funding for the data collection system described in this paper was provided by a University of Melbourne major equipment grant. The Cooperative Research Centre for Catchment Hydrology provided support for Paul Tyndale-Biscoe. Funding for work performed at the Tarrewarra site was provided by the Australian Research Council.
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