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Water Resource Simulation and Optimal Allocation: Theory, Methods and Applications

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water Resources Management, Policy and Governance".

Deadline for manuscript submissions: closed (20 December 2025) | Viewed by 955

Special Issue Editors


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Guest Editor
School of Energy, Geoscience, Infrastructure and Society, Heriot-Watt University, Edinburgh, UK
Interests: water resources management; reservoir planning and management; optimisation of water systems; climate change impacts & adaptation; simulation of water resource systems; modeling of environmental systems; stochastic hydrology & water resources
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
School of Energy, Geoscience, Infrastructure and Society, Heriot-Watt University, Edinburgh, UK
Interests: data handling; water resources planning and management; data mining; artificial intelligence (AI); software sensors; water and wastewater quality; water supply; hydrology; hydraulics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The development of simulation and optimisation approaches for the planning and operation of water resources systems has engaged researchers for a long time. This has led to the publication of numerous research articles, and the development of bespoke user-friendly software tools for their implementation. Despite these efforts, however, the deployment of these paradigms in practical applications has been limited. Possible reasons for this might have to do with perceived complexity of the approaches, and the unclear way they have been communicated especially to the practice community. The aim of this Special Issue is to document examples of successful applications of simulation and optimization approaches in water resource planning and management at different spatial and temporal scales. Specifically, articles addressing, but not limited to, the following topics are encouraged:

  • Procedural details of simulation and optimisation approaches.
  • Literature reviews of the state-of-the-art in simulation and optimisation approaches.
  • Traditional optimisation approaches, and emerging heuristic approaches, e.g., AI and ML.
  • Hybrid simulation–optimisation; multi-objective optimisation approaches.
  • Case study applications on water quantity (e.g. irrigation, hydropower, floods) and water quality.
  • Challenges and apathy in practical applications of simulation and optimisation.
  • Uncertainty characterisation in simulation and optimisation.
  • Accommodating climate change effects in simulation and optimisation.

Prof. Dr. Adebayo J. Adeloye
Prof. Dr. Rabee Rustum
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • simulation
  • optimization methods
  • hybrid simulation–optimisation
  • multi-objective optimisation
  • irrigation
  • hy-dropower
  • floods
  • water quality
  • artificial intelligence (AI)
  • machine learning (ML)
  • heuristics optimization
  • un-certainty characterization
  • climate change

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Published Papers (1 paper)

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Research

22 pages, 1824 KB  
Article
The Impact of Scientific Irrigation Scheduling on Water Use Efficiency, Energy Productivity and Economic Profitability: Analysis at the Farm Level in Tunisia
by Hacib El Amami, Alfonso Domínguez, Charles Muanda, Ángel Martínez-Romero, José Antonio Martínez-López, Nicolas R. Dalezios, Nicholas Dercas, Ioannis Faraslis, Marios Spiliotopoulos, Jean Robert Kompany, Mariem Ben Sâada and Radhouan Nsiri
Water 2026, 18(6), 655; https://doi.org/10.3390/w18060655 - 10 Mar 2026
Cited by 1 | Viewed by 584
Abstract
In water-limited areas, scientific irrigation scheduling is suggested as a valuable tool to optimize the amount and frequency of water required by crops. MOPECO, based on local data including soil texture, crop growth stages, climatic conditions, weather forecast and irrigation scheme characteristics, can [...] Read more.
In water-limited areas, scientific irrigation scheduling is suggested as a valuable tool to optimize the amount and frequency of water required by crops. MOPECO, based on local data including soil texture, crop growth stages, climatic conditions, weather forecast and irrigation scheme characteristics, can be employed to define the optimal irrigation strategy. This tool was implemented within the SUPROMED project and tested in real farms managed by progressive farmers (leader farmers) who had been advised by the research team to monitor irrigation for seven major water-demanding crops (wheat, oat, onion, maize, olive, almond and pistachio). The obtained results were compared with conventional irrigation management as usually practiced by farmers (average farmers), based on their local experiences and knowledge, for the same crops growing in very similar conditions. Water use and energy efficiency use as well as irrigation cost and economic profitability were compared. The results showed that the advised irrigation scheduling provided an effective way to improve water and energy efficiency and increase yields and economic profitability with respect to current farm management. On average, the scientific method (MOPECO) reduced water consumption and energy use by 25.5% and 22%, respectively, achieving a 29% increase in yield and a reduction of 18% in water irrigation cost. The gross margin per hectare was also higher, increasing by 26%. The results also showed that, under advised management, the farmers’ income became more resilient to market price variability, allowing the farmers to have better economic viability. Based on these results, our study suggested that the adaptation of scientific models such as MOPECO to farmers’ requirements and their implementation through training activities could provide end users with a significant opportunity to improve the agronomic and economic efficiency of water and energy in arid regions. Full article
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