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Empirical modeling and simulation for discharge dynamics enabling catchment-scale water quality management

Empirical modeling and simulation for discharge dynamics enabling catchment-scale water quality management
Empirical modeling and simulation for discharge dynamics enabling catchment-scale water quality management
Excessive or poorly timed application of irrigation and fertilizers, coupled with inherent inefficiency of nutrient uptake by crops result in nutrient fluxes into the water system. Due to the recent adoption of WSNs in precision agriculture, it is proposed that existing networked agricultural activities can be leveraged into an integrated mechanism by sharing information about discharges and predicting their impact, allowing dynamic decision making for irrigation strategies. Since resource constraints on network nodes (e.g. battery life, computing power etc.) require a simplified predictive model, low-dimensional model parameters are derived from the existing National Resource Conservation Method (NRCS). An M5 decision tree algorithm is then used to develop predictive models for depth (Q), response-time (t1) and duration (td) of the discharge. 10-fold cross-validation of these models demonstrates RRSE of 10.2%, 30% and 9.6% for Q, t1 and td respectively. Furthermore, performance of these models is validated using multiple linear regression method
Zia, Huma
74118b4c-35ab-44e8-a44f-daa4cc6f83e8
Harris, Nick
237cfdbd-86e4-4025-869c-c85136f14dfd
Merrett, Geoff V.
89b3a696-41de-44c3-89aa-b0aa29f54020
Zia, Huma
74118b4c-35ab-44e8-a44f-daa4cc6f83e8
Harris, Nick
237cfdbd-86e4-4025-869c-c85136f14dfd
Merrett, Geoff V.
89b3a696-41de-44c3-89aa-b0aa29f54020

Zia, Huma, Harris, Nick and Merrett, Geoff V. (2014) Empirical modeling and simulation for discharge dynamics enabling catchment-scale water quality management At The 26th European Modeling & Simulation Symposium. 10 - 12 Sep 2014.

Record type: Conference or Workshop Item (Paper)

Abstract

Excessive or poorly timed application of irrigation and fertilizers, coupled with inherent inefficiency of nutrient uptake by crops result in nutrient fluxes into the water system. Due to the recent adoption of WSNs in precision agriculture, it is proposed that existing networked agricultural activities can be leveraged into an integrated mechanism by sharing information about discharges and predicting their impact, allowing dynamic decision making for irrigation strategies. Since resource constraints on network nodes (e.g. battery life, computing power etc.) require a simplified predictive model, low-dimensional model parameters are derived from the existing National Resource Conservation Method (NRCS). An M5 decision tree algorithm is then used to develop predictive models for depth (Q), response-time (t1) and duration (td) of the discharge. 10-fold cross-validation of these models demonstrates RRSE of 10.2%, 30% and 9.6% for Q, t1 and td respectively. Furthermore, performance of these models is validated using multiple linear regression method

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Submitted date: 2014
Venue - Dates: The 26th European Modeling & Simulation Symposium, 2014-09-10 - 2014-09-12
Organisations: EEE

Identifiers

Local EPrints ID: 365853
URI: http://eprints.soton.ac.uk/id/eprint/365853
PURE UUID: bab26bc9-df7b-4b89-b003-f95e0c0db16f
ORCID for Nick 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: 19 Jun 2014 11:28
Last modified: 18 Jul 2017 02:17

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Contributors

Author: Huma Zia
Author: Nick Harris ORCID iD
Author: Geoff V. Merrett ORCID iD

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