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Ss34 Establishing The Evidence Base: Quality Requirements For Monitoring Networks

Congress: 2015
Author(s): E Marian Scott

E Marian Scott
School of Mathematics and Statistics

With Adrian Bowman, Claire Miller, Kelly Gallacher, Ruth O’Donnell, Mengyi Gong, Craig Wilkie, Alistair Rushworth


Oral:
Abstract
Networks in space and through time
 
A set of monitoring sites- which may be physically connected Sampling through time and over space, often sparse in space and not always representative. Water-Quality Watch displays real-time water quality data collected remotely by sensors installed in rivers, and lakes. Readings taken every 5 to 60 minutes are transmitted via satellite to the USGS National Water Information System (NWIS). Data include water temperature, pH, specific conductance, turbidity, dissolved oxygen, and (or) nitrate depending on the site.

Data challenges

Dealing with the quantity of data in terms of the number of pixels, combined with the sparsity of the data, in terms of the time series observed will be a huge challenge.
Modern functional data approaches are suitable for large numbers of time series of potentially noisy data and enable clusters of curves to be identified which are coherent in terms of temporal dynamics.
 
Opportunities and challenges
 
From a network we can learn:
  • whether there are seasonal patterns and trend
  • Whether the patterns are different at different locations
  • How to make predictions at any point on the network, regardless of whether it is near a monitoring site
 
Challenges
  • Data characteristics- quantity and quality and relatedness
  • Non stationary, complex nature of the relationships
  • For networks, how to build fast and efficient spatio-temporal models,
  • Designing the network and the resulting power to detect change
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