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Abstract

Agriculture faces growing pressure to optimize water use, particularly in woody perennial crops where irrigation systems are installed once and seldom redesigned despite changes in canopy structure, soil conditions, or plant mortality. Such static layouts may accumulate inefficiencies over time. This study introduces a decision support system (DSS) that evaluates the hydraulic adequacy of existing irrigation systems using two new concepts: the Resource Overutilization Ratio (ROR) and the Irrigation Ecolabel. The ROR quantifies the deviation between the actual discharge of an installed irrigation network and the theoretical discharge required from crop water needs and user-defined scheduling assumptions, while the ecolabel translates this value into an intuitive A+++–D scale inspired by EU energy labels. Crop water demand was estimated using the FAO-56 Penman–Monteith method and adjusted using canopy cover derived from UAV-based canopy height models. A vineyard case study in Galicia (Spain) serves an example to illustrate the potential of the DSS. Firstly, using a fixed canopy cover, the FAO-based workflow indicated moderate oversizing, whereas secondly, UAV-derived canopy measurements revealed substantially higher oversizing, highlighting the limitations of non-spatial or user-estimated canopy inputs. This contrast (A+ vs. D rating) illustrates the diagnostic value of integrating high-resolution geospatial information when canopy variability is present. The DSS, released as open-source software, provides a transparent and reproducible framework to help farmers, irrigation managers, and policymakers assess whether existing drip systems are hydraulically oversized and to benchmark system performance across fields or management scenarios. Rather than serving as an irrigation scheduler, the DSS functions as a standardized diagnostic tool for identifying oversizing and supporting more efficient use of water, energy, and materials in perennial cropping systems.

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1009240
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Title
A Decision Support System (DSS) for Irrigation Oversizing Diagnosis Using Geospatial Canopy Data and Irrigation Ecolabels
Author
Vélez, Sergio 1   VIAFID ORCID Logo  ; Martínez-Peña, Raquel 2 ; Valente João 3   VIAFID ORCID Logo  ; Ariza-Sentís Mar 4   VIAFID ORCID Logo  ; Sirnik Igor 5   VIAFID ORCID Logo  ; Pardo, Miguel Ángel 6   VIAFID ORCID Logo 

 JRU Drone Technology, Department of Architectural Constructions and I.C.T., University of Burgos, 09001 Burgos, Spain, INF Department, Wageningen University & Research, 6708 PB Wageningen, The Netherlands; [email protected] 
 Regional Institute of Agri-Food and Forestry Research and Development of Castilla-La Mancha (IRIAF), CIAG “EL CHAPARRILLO”, Ctra. de Porzuna s/n, 13071 Ciudad Real, Spain; [email protected] 
 Centre for Automation and Robotics (CAR), Spanish National Research Council (CSIC), 28006 Madrid, Spain; [email protected] 
 INF Department, Wageningen University & Research, 6708 PB Wageningen, The Netherlands; [email protected] 
 Faculty of Civil and Geodetic Engineering, University of Ljubljana, Jamova Cesta 2, 1000 Ljubljana, Slovenia; [email protected] 
 Department of Civil Engineering, University of Alicante, 03690 Alicante, Spain; [email protected] 
Publication title
Volume
7
Issue
12
First page
429
Number of pages
23
Publication year
2025
Publication date
2025
Publisher
MDPI AG
Place of publication
Basel
Country of publication
Switzerland
Publication subject
e-ISSN
26247402
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-12-12
Milestone dates
2025-09-27 (Received); 2025-12-04 (Accepted)
Publication history
 
 
   First posting date
12 Dec 2025
ProQuest document ID
3286238583
Document URL
https://www.proquest.com/scholarly-journals/decision-support-system-dss-irrigation-oversizing/docview/3286238583/se-2?accountid=208611
Copyright
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-12-24
Database
ProQuest One Academic