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Applied Sciences
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Novel Smart Technologies in Water Resource Management
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Novel Smart Technologies in Water Resource Management

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Environmental Sciences".

Deadline for manuscript submissions: closed (21 July 2024) | Viewed by 3553

Special Issue Editors

Dr. Alexandre Maniçoba da Rosa Ferraz Jardim

E-Mail Website
Guest Editor
Department of Biodiversity, Institute of Biosciences, São Paulo State University-UNESP, Av. 24A, 1515, Rio Claro 13506-900, São Paulo, Brazil
Interests: abiotic stresses; salinity; physiological and biochemical changes in plants; salt stress tolerance; reactive oxygen species (ROS); ion homeostasis; ion toxicity; agricultural challenges in arid and semi-arid regions
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Thieres George Freire da Silva

E-Mail Website
Guest Editor
Federal Rural University of Pernambuco Academic Unit of Serra Talhada
Interests: hydrology; climate change

Special Issue Information

Dear Colleagues,

In recent years, several innovations in the field of the application of sensors for water management have been gaining increasing strength and practicality. In this context, embedded systems, smart sensors, and other technologies can be fundamental in irrigation management, for example. We invite the submission of unpublished, innovative and high-quality contributions on any topics focused on applied sciences using concepts in the areas of water resources, among others.

Dr. Alexandre Maniçoba da Rosa Ferraz Jardim
Prof. Dr. Thieres George Freire da Silva
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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Applied Sciences 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 2400 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

  • climate change and water
  • water resource management
  • water balance
  • evapotranspiration

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Published Papers (2 papers)

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Research

14 pages, 2374 KiB  
Article
Can Unmanned Aerial Vehicle Images Be Used to Estimate Forage Production Parameters in Agroforestry Systems in the Caatinga?
by Wagner Martins dos Santos, Claudenilde de Jesus Pinheiro Costa, Maria Luana da Silva Medeiros, Alexandre Maniçoba da Rosa Ferraz Jardim, Márcio Vieira da Cunha, José Carlos Batista Dubeux Junior, David Mirabedini Jaramillo, Alan Cezar Bezerra and Evaristo Jorge Oliveira de Souza
Appl. Sci. 2024, 14(11), 4896; https://doi.org/10.3390/app14114896 - 5 Jun 2024
Cited by 2 | Viewed by 1343
Abstract
The environmental changes in the Caatinga biome have already resulted in it reaching levels of approximately 50% of its original vegetation, making it the third most degraded biome in Brazil, due to inadequate grazing practices that are driven by the difficulty of monitoring [...] Read more.
The environmental changes in the Caatinga biome have already resulted in it reaching levels of approximately 50% of its original vegetation, making it the third most degraded biome in Brazil, due to inadequate grazing practices that are driven by the difficulty of monitoring and estimating the yield parameters of forage plants, especially in agroforestry systems (AFS) in this biome. This study aimed to compare the predictive ability of different indexes with regard to the biomass and leaf area index of forage crops (bushveld signal grass and buffel grass) in AFS in the Caatinga biome and to evaluate the influence of removing system components on model performance. The normalized green red difference index (NGRDI) and the visible atmospherically resistant index (VARI) showed higher correlations (p < 0.05) with the variables. In addition, removing trees from the orthomosaics was the approach that most favored the correlation values. The models based on classification and regression trees (CARTs) showed lower RMSE values, presenting values of 3020.86, 1201.75, and 0.20 for FB, DB, and LAI, respectively, as well as higher CCC values (0.94). Using NGRDI and VARI, removing trees from the images, and using CART are recommended in estimating biomass and leaf area index in agroforestry systems in the Caatinga biome. Full article
(This article belongs to the Special Issue Novel Smart Technologies in Water Resource Management)
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15 pages, 1315 KiB  
Article
Spectral and Energy Efficiency Trade-Off in UAV-Based Olive Irrigation Systems
by Ayman Massaoudi, Abdelwahed Berguiga, Ahlem Harchay, Mossaad Ben Ayed and Hafedh Belmabrouk
Appl. Sci. 2023, 13(19), 10739; https://doi.org/10.3390/app131910739 - 27 Sep 2023
Cited by 5 | Viewed by 1614
Abstract
Precision agriculture, also referred to as smart farming, is one of the main pillars of modern society to achieve the Sustainable Development Goals (SDGs). Precision agriculture aims to improve the quality and quantity of production while conserving scarce natural resources. Smart farming has [...] Read more.
Precision agriculture, also referred to as smart farming, is one of the main pillars of modern society to achieve the Sustainable Development Goals (SDGs). Precision agriculture aims to improve the quality and quantity of production while conserving scarce natural resources. Smart farming has grown in recent years thanks to the adoption of modern technologies, including artificial intelligence (AI) and the Internet of Things (IoT). In this work, we consider an irrigation system for olive orchards based on unmanned aerial vehicles (UAVs). Specifically, UAVs ensure remote sensing (RS), which offers the advantage of collecting vital information on a large temporal and spatial scale (which cannot be achieved with traditional technologies). However, UAV-based irrigation systems face tremendous challenges due to the various requirements of a powerful computing ability, battery capacity, energy efficiency, and spectral efficiency for different connected devices. This paper addresses the energy efficiency and spectral efficiency trade-off problem of UAV-based irrigation systems. We propose to adopt massive multiple input, multiple output (M-MIMO) technology to ensure wireless communication. In fact, this technology plays a significant role in future sixth-generation (6G) wireless mobile networks and has the potential to enhance the energy efficiency as well as the spectral efficiency. We design a network model with a three-layered architecture and analytically compute the achievable spectral efficiency and the energy efficiency of the studied system. Then, we numerically determine the optimal number of ground base station antennas as well as the optimal number of IoT devices that should be used to ensure the maximum energy efficiency while guaranteeing a high spectral efficiency. The numerical results prove that the proposed UAV-based irrigation system outperforms conventional systems and demonstrate that the best spectral and energy efficiency trade-off is obtained by using the M-MMSE combiner. Full article
(This article belongs to the Special Issue Novel Smart Technologies in Water Resource Management)
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