Clearly, the closer a computer model approximates what actually happens, the more valuable it is as an investigatory and management tool. We recently ran extensive validation tests on two of our models and were very pleased with the outcome.
To satisfy requests for information from the Western Australian Department of Environment (DOE), a number of clients retained us to study Cockburn Sound on Australia's southwestern coast. Like many bays fringing major cities, the sound has suffered significant deterioration in water quality from excess nutrients and industrial discharges. As a result there has been a significant loss of seagrass. A vitally important habitat in that ecosystem, seagrass is a nursery for larvae and juvenile fish, a feeding ground for larger fish and invertebrates and a stabilizing influence against shoreline erosion. Recent research and management efforts have helped improve water quality and slow seagrass loss but many threats to this important habitat remain. A number of continuous and occasional activities contribute to elevated levels of suspended sediments, which can block light seagrass needs and can also smother it. Although individual sources may be relatively small and short-lived, the DOE, as the sound's environmental manager, seeks to understand the cumulative impact.
To model Cockburn Sound, we used two of our programs, HYDROMAP for a three-dimensional simulation of water circulation and MUDMAP to investigate sedimentation. Together our models support estimation of suspended solid concentrations and sedimentation patterns at fine temporal (minutes) and spatial (sub-10 m) scales. Thus our system is well suited to the patchy plumes generated by the discharges.
Working with DAL Science & Engineering, Asia Pacific Applied Science Associates (APASA) has undertaken an extensive proving program for our combined HYDROMAP-MUDMAP system in Cockburn Sound. In every test our modeling system generated very close approximations to the observed distribution patterns of suspended solids and sedimentation. This demonstrates that our system may be confidently applied to predict the outcomes of future sediment discharges.
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