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research-article

Perspectives on delineating management zones for variable rate irrigation

Authors:

Amir Haghverdi,

Robert A. Washington-Allen,

Michael J. BuschermohleAuthors Info & Claims

Computers and Electronics in Agriculture, Volume 117, Issue C

Pages 154 - 167

https://doi.org/10.1016/j.compag.2015.06.019

Published: 01 September 2015 Publication History

Abstract

Up to 40% of soil available water content variance was explained by pie shape zoning.Dynamic zoning strategy may be needed if soil spatial arrangement varies by depth.Soil ECa and satellite images were useful attributes for irrigation zone delineation. This study aimed at investigating the performance of multiple irrigation zoning scenarios on a 73ha irrigated field located in west Tennessee along the Mississippi river. Different clustering methods, including k-means, ISODATA and Gaussian Mixture, were selected. In addition, a new zoning method, based on integer linear programming, was designed and evaluated for center pivot irrigation systems with limited speed control capability. The soil available water content was used as the main attribute for zoning while soil apparent electrical conductivity (ECa), space-borne satellite images and yield data were required as ancillary data. A good agreement was observed among delineated zones by different clustering methods. The new zoning method explained up to 40% of available water content variance underneath center pivot irrigation systems. The ECa achieved the highest Kappa coefficient (=0.79) among ancillary attributes, hence exhibited a considerable potential for irrigation zoning.

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Cited By

Alves Souza SNeiva Rodrigues L(2022)Irrigation management zone strategies impact assessment on potential crop yield, water and energy savingsComputers and Electronics in Agriculture10.1016/j.compag.2022.107349201:COnline publication date: 1-Oct-2022
https://dl.acm.org/doi/10.1016/j.compag.2022.107349
Garg ASapkota AHaghverdi A(2022)SAMZ-DesertComputers and Electronics in Agriculture10.1016/j.compag.2022.106803194:COnline publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1016/j.compag.2022.106803
Cadenas JGarrido MMartinez-España R(2020)Development of an application to make knowledge available to the farmerJournal of Ambient Intelligence and Smart Environments10.3233/AIS-20057512:5(419-432)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.3233/AIS-200575
Show More Cited By

Perspectives on delineating management zones for variable rate irrigation
1. Applied computing
  1. Physical sciences and engineering

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Published In

cover image Computers and Electronics in Agriculture

Computers and Electronics in Agriculture Volume 117, Issue C

September 2015

277 pages

ISSN:0168-1699

Issue’s Table of Contents

Copyright © Elsevier B.V.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 September 2015

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Cited By

Alves Souza SNeiva Rodrigues L(2022)Irrigation management zone strategies impact assessment on potential crop yield, water and energy savingsComputers and Electronics in Agriculture10.1016/j.compag.2022.107349201:COnline publication date: 1-Oct-2022
https://dl.acm.org/doi/10.1016/j.compag.2022.107349
Garg ASapkota AHaghverdi A(2022)SAMZ-DesertComputers and Electronics in Agriculture10.1016/j.compag.2022.106803194:COnline publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1016/j.compag.2022.106803
Cadenas JGarrido MMartinez-España R(2020)Development of an application to make knowledge available to the farmerJournal of Ambient Intelligence and Smart Environments10.3233/AIS-20057512:5(419-432)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.3233/AIS-200575
Cid-Garcia NIbarra-Rojas O(2019)An integrated approach for the rectangular delineation of management zones and the crop planning problemsComputers and Electronics in Agriculture10.1016/j.compag.2019.104925164:COnline publication date: 1-Sep-2019
https://dl.acm.org/doi/10.1016/j.compag.2019.104925
Ohana-Levi NBahat IPeeters AShtein ANetzer YCohen YBen-Gal A(2019)A weighted multivariate spatial clustering model to determine irrigation management zonesComputers and Electronics in Agriculture10.1016/j.compag.2019.05.012162:C(719-731)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1016/j.compag.2019.05.012
Albornoz VÑanco LSáez J(2019)Delineating robust rectangular management zones based on column generation algorithmComputers and Electronics in Agriculture10.1016/j.compag.2019.01.045161:C(194-201)Online publication date: 1-Jun-2019
https://dl.acm.org/doi/10.1016/j.compag.2019.01.045
Haghverdi AWashington-Allen RLeib B(2018)Prediction of cotton lint yield from phenology of crop indices using artificial neural networksComputers and Electronics in Agriculture10.1016/j.compag.2018.07.021152:C(186-197)Online publication date: 1-Sep-2018
https://dl.acm.org/doi/10.1016/j.compag.2018.07.021
Haghverdi ALeib BWashington-Allen RBuschermohle MAyers P(2016)Studying uniform and variable rate center pivot irrigation strategies with the aid of site-specific water production functionsComputers and Electronics in Agriculture10.5555/2912581.2912647123:C(327-340)Online publication date: 1-Apr-2016
https://dl.acm.org/doi/10.5555/2912581.2912647
Mieza MCravero WKovac FBargiano P(2016)Delineation of site-specific management units for operational applications using the topographic position index in La Pampa, ArgentinaComputers and Electronics in Agriculture10.1016/j.compag.2016.06.005127:C(158-167)Online publication date: 1-Sep-2016
https://dl.acm.org/doi/10.1016/j.compag.2016.06.005

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