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Water quality monitoring, control and management (WQMCM) framework using collaborative wireless sensor networks

Water quality monitoring, control and management (WQMCM) framework using collaborative wireless sensor networks
Water quality monitoring, control and management (WQMCM) framework using collaborative wireless sensor networks
Improving water quality is of global concern, with agricultural practices being the major contributors to reduced water quality. The reuse of nutrient-rich drainage water can be a valuable strategy to gain economic-environmental benefits. However, currently the tools and techniques to allow this do not exist. Therefore, we have proposed a framework, WQMCM, which utilises increasingly common local farm-scale networks across a catchment, adding provision for collaborative information sharing. Using this framework, individual sub-networks can learn their environment and predict the impact of catchment events on their locality, allowing dynamic decision making for local irrigation strategies. Since resource constraints of network nodes (e.g. power consumption, computing power etc.) require a simplified predictive model for discharges, therefore low-dimensional model parameters are derived from the existing National Resource Conservation Method (NRCS), utilising real-time field values. Evaluation of the predictive models, developed using M5 decision trees, demonstrates accuracy of 84-94% compared with the traditional NRCS curve number model. The discharge volume and response time model was tested to perform with 6% relative root mean square error (RRMSE), even for a small training set of around 100 samples; however the discharge response time model required a minimum of 300 training samples to show reasonable performance with 16% RRMSE
Zia, Huma
74118b4c-35ab-44e8-a44f-daa4cc6f83e8
Harris, N.R.
237cfdbd-86e4-4025-869c-c85136f14dfd
Merrett, Geoff V.
89b3a696-41de-44c3-89aa-b0aa29f54020
Zia, Huma
74118b4c-35ab-44e8-a44f-daa4cc6f83e8
Harris, N.R.
237cfdbd-86e4-4025-869c-c85136f14dfd
Merrett, Geoff V.
89b3a696-41de-44c3-89aa-b0aa29f54020

Zia, Huma, Harris, N.R. and Merrett, Geoff V. (2014) Water quality monitoring, control and management (WQMCM) framework using collaborative wireless sensor networks At 11th International Conference on Hydroinformatics (HIC) 2014, United States. 17 - 21 Aug 2014.

Record type: Conference or Workshop Item (Paper)

Abstract

Improving water quality is of global concern, with agricultural practices being the major contributors to reduced water quality. The reuse of nutrient-rich drainage water can be a valuable strategy to gain economic-environmental benefits. However, currently the tools and techniques to allow this do not exist. Therefore, we have proposed a framework, WQMCM, which utilises increasingly common local farm-scale networks across a catchment, adding provision for collaborative information sharing. Using this framework, individual sub-networks can learn their environment and predict the impact of catchment events on their locality, allowing dynamic decision making for local irrigation strategies. Since resource constraints of network nodes (e.g. power consumption, computing power etc.) require a simplified predictive model for discharges, therefore low-dimensional model parameters are derived from the existing National Resource Conservation Method (NRCS), utilising real-time field values. Evaluation of the predictive models, developed using M5 decision trees, demonstrates accuracy of 84-94% compared with the traditional NRCS curve number model. The discharge volume and response time model was tested to perform with 6% relative root mean square error (RRMSE), even for a small training set of around 100 samples; however the discharge response time model required a minimum of 300 training samples to show reasonable performance with 16% RRMSE

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Accepted/In Press date: 2014
Venue - Dates: 11th International Conference on Hydroinformatics (HIC) 2014, United States, 2014-08-17 - 2014-08-21
Organisations: EEE

Identifiers

Local EPrints ID: 365852
URI: http://eprints.soton.ac.uk/id/eprint/365852
PURE UUID: 95159627-d637-45c2-bd8d-2e2e9b519bbc
ORCID for N.R. Harris: ORCID iD orcid.org/0000-0003-4122-2219
ORCID for Geoff V. Merrett: ORCID iD orcid.org/0000-0003-4980-3894

Catalogue record

Date deposited: 24 Jun 2014 15:50
Last modified: 18 Jul 2017 02:17

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Contributors

Author: Huma Zia
Author: N.R. Harris ORCID iD
Author: Geoff V. Merrett ORCID iD

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