Data-mining models for water resource applications

Abstract

Advancements in the field of instrumentation has led to the development of sophisticated apparatus with inbuilt data storage mechanism for measuring water quantity and quality. In water resources, the database has been measured and recorded both in the temporal and spatial scale for many watersheds. Dealing with a large database increases the associated complexity in modelling. The complexity existing in a large database is well represented as simple and understandable expressions by data-mining models/processes. This review paper elaborates the theoretical background of data-mining models and highlights the applications in knowledge data discovery from a water resources database. Based on the understanding/learning from the reported research works, research gaps have been identified and potential directions towards minimising the gap are identified and discussed.

Keywords:

• data mining
• knowledge discovery
• temporal and spatial modelling
• water resources

Acknowledgement

This article belongs to the papers presented at the Hydro-2012 conference held at IIT Bombay on December 7-8, 2012, that were short-listed by the Editor for publication in this Journal after re-review and revisions where necessary.