A web-based interface to visualize and model spatio-temporal variability of stream water quality — ASN Events

A web-based interface to visualize and model spatio-temporal variability of stream water quality (#70)

Danlu Guo 1 , Anna Lintern 1 2 , James A. Webb 1 , Dongryeol Ryu 1 , Shuci Liu 1 , Ulrike Bende-Michl 3 , Paul Leahy 4 , David Waters 5 , Malcolm Watson 3 , Paul Wilson 6 , Andrew W. Western 1
  1. Infrastructure Engineering, University of Melbourne, Parkville, VIC, Australia
  2. Civil Engineering, Monash University, Clayton, VIC, Australia
  3. Bureau of Meteorology, Canberra, ACT, Australia
  4. Environment Protection Authority Victoria, Melbourne, VIC, Australia
  5. Queensland Department of Natural Resources, Mines and Energy, Toowoomba, QLD, Australia
  6. Department of Environment, Land, Water & Planning, East Melbourne, VIC, Australia

Understanding the spatio-temporal variability in stream water quality is critical for designing effective water quality management strategies. To facilitate this, we developed a web-based interface to visualize and model the spatio-temporal variability of stream water quality in Victoria. We used a dataset of long-term monthly water quality measurements from 102 monitoring sites in Victoria, focusing on six water quality constituents: total suspended solids (TSS), total phosphorus (TP), filterable reactive phosphorus (FRP), total Kjedahl nitrogen (TKN), nitrate-nitrite (NOx), and electrical conductivity (EC). The interface models spatio-temporal variability in water quality via a Bayesian hierarchical modelling framework, and produces summaries of (1) the key driving factors of spatio-temporal variability and (2) model performance assessed by multiple metrics. Additional features include predicting the time-averaged mean concentration at an un-sampled site, and testing the impact of land-use changes on the mean concentration at existing sites. This tool can be very useful in supporting the decision-making processes of catchment managers in (1) understanding the key drivers of changes in water quality and (2) designing water quality mitigation and restoration strategies.

#9ASM
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