Understanding Circular Economy Complexities and the Climate–Water–Food–Energy Nexus in an SDG Framework: Interactions and Alternatives for Decision Making

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water-Energy Nexus".

Deadline for manuscript submissions: closed (15 August 2023) | Viewed by 9576

Special Issue Editors


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Guest Editor
Facultad de Ingeniería, Universidad del Desarrollo, Santiago, Chile
Interests: sustainability science; environmental sciences; environmental policy; materials and energy recovery; material flow analysis; circular economy
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Guest Editor
Kenitra Higher School of Chemistry, Ibn Tofail University, Kenitra, Morocco
Interests: sustainable agriculture; food security; water management; irrigation technologies; water–food–energy nexus

Special Issue Information

Dear Colleagues,

Currently, the world is in the middle of a very critical socio-economic, political and environmental crisis. This context is marked by the increasing pressure on natural resources, and a big demand for energy, food and water. Climate variations make the situation more complicated at different levels. In fact, the situation puts more pressure on scientists and decision makers to find alternatives and tools for more visibility and to respond adequately and urgently with feasible, innovative solutions in order to tackle the current and future demands on natural resources and to reduce the impact of climate change, especially on water, food and energy sectors, while seeking to protect ecosystems. The proposed alternatives concern the important interactions between climate, water, food and energy and the potential tools (models) and approaches for making decisions. This Special Issue is focused on how different approaches can be applied to understand circular economy challenges and the complexities of a nexus in an SDG framework. Articles based on modeling, empirical and experimental evidence are welcome. Additionally, articles focused on how the industrial sectors interact between themselves are welcome too. The purpose of this Special Issue is to provide evidence and useful tools that can be applied in different contexts and regions.

Prof. Dr. Alex Godoy-Faundez
Dr. Lahcen El Youssfi
Guest Editors

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Keywords

  • nexus
  • climate
  • water–energy–food nexus
  • wastes
  • ecosystem
  • circular economy
  • SDGs

Published Papers (3 papers)

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Research

15 pages, 3040 KiB  
Article
Innovative Solutions for Drought: Evaluating Hydrogel Application on Onion Cultivation (Allium cepa) in Morocco
by Omnia El Bergui, Aziz Abouabdillah, Mohamed Bourioug, Dominik Schmitz, Markus Biel, Abdellah Aboudrare, Manuel Krauss, Ahlem Jomaa, Sebastian Romuli, Joachim Mueller, Mustapha Fagroud and Rachid Bouabid
Water 2023, 15(11), 1972; https://doi.org/10.3390/w15111972 - 23 May 2023
Cited by 4 | Viewed by 2090
Abstract
Throughout the last decade, and particularly in 2022, water scarcity has become a critical concern in Morocco and other Mediterranean countries. The lack of rainfall during spring was worsened by a succession of heat waves during the summer. To address this drought, innovative [...] Read more.
Throughout the last decade, and particularly in 2022, water scarcity has become a critical concern in Morocco and other Mediterranean countries. The lack of rainfall during spring was worsened by a succession of heat waves during the summer. To address this drought, innovative solutions, including the use of new technologies such as hydrogels, will be essential to transform agriculture. This paper presents the findings of a study that evaluated the impact of hydrogel application on onion (Allium cepa) cultivation in Meknes, Morocco. The treatments investigated in this study comprised two different types of hydrogel-based soil additives (Arbovit® polyacrylate and Huminsorb® polyacrylate), applied at two rates (30 and 20 kg/ha), and irrigated at two levels of water supply (100% and 50% of daily crop evapotranspiration; ETc). Two control treatments were included, without hydrogel application and with both water amounts. The experiment was conducted in an open field using a completely randomized design. The results indicated a significant impact of both hydrogel-type dose and water dose on onion plant growth, as evidenced by various vegetation parameters. Among the hydrogels tested, Huminsorb® Polyacrylate produced the most favorable outcomes, with treatment T9 (100%, HP, 30 kg/ha) yielding 70.55 t/ha; this represented an increase of 11 t/ha as compared to the 100% ETc treatment without hydrogel application. Moreover, the combination of hydrogel application with 50% ETc water stress showed promising results, with treatment T4 (HP, 30 kg, 50%) producing almost the same yield as the 100% ETc treatment without hydrogel while saving 208 mm of water. Full article
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22 pages, 3823 KiB  
Article
Rainfall Prediction Rate in Saudi Arabia Using Improved Machine Learning Techniques
by Mohammed Baljon and Sunil Kumar Sharma
Water 2023, 15(4), 826; https://doi.org/10.3390/w15040826 - 20 Feb 2023
Cited by 7 | Viewed by 3207
Abstract
Every farmer requires access to rainfall prediction (RP) to continue their exploration of harvest yield. The proper use of water assets, the successful collection of water, and the successful pre-growth of water construction all depend on an accurate assessment of rainfall. The prediction [...] Read more.
Every farmer requires access to rainfall prediction (RP) to continue their exploration of harvest yield. The proper use of water assets, the successful collection of water, and the successful pre-growth of water construction all depend on an accurate assessment of rainfall. The prediction of heavy rain and the provision of information regarding natural catastrophes are two of the most challenging factors in this regard. In the twentieth century, RP was the most methodically and technically complicated issue worldwide. Weather prediction may be used to calculate and analyse the behaviour of weather with unique features and to determine rainfall patterns at an exact locale. To this end, a variety of methodologies have been used to determine the rainfall intensity in Saudi Arabia. The classification methods of data mining (DM) approaches that estimate rainfall both numerically and categorically can be used to achieve RP. This study, which used DM approaches, achieved greater accuracy in RP than conventional statistical methods. This study was conducted to test the efficacy of several machine learning (ML) approaches for forecasting rainfall, utilising southern Saudi Arabia’s historical weather data obtained from the live database that comprises various meteorological data variables. Accurate crop yield predictions are crucial and would undoubtedly assist farmers. While engineers have developed analysis systems whose performance relies on several connected factors, these methods are seldom used despite their potential for precise crop yield forecasts. For this reason, agricultural forecasting should make use of these methods. The impact of drought on crop yield can be difficult to forecast and there is a need for careful preparation regarding crop choice, planting window, harvest motive, and storage space. In this study, the relevant characteristics required to predict precipitation were identified and the ML approach utilised is an innovative classification method that can be used determine whether the predicted rainfall will be regular or heavy. The outcomes of several different methodologies, including accuracy, error, recall, F-measure, RMSE, and MAE, are used to evaluate the performance metrics. Based on this evaluation, it is determined that DT provides the highest level of accuracy. The accuracy of the Function Fitting Artificial Neural Network classifier (FFANN) is 96.1%, which is higher than that of any of the other classifiers currently used in the rainfall database. Full article
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18 pages, 2432 KiB  
Article
The Influence of Circular Economy and 4IR Technologies on the Climate–Water–Energy–Food Nexus and the SDGs
by Mohamed Sameer Hoosain, Babu Sena Paul, Wesley Doorsamy and Seeram Ramakrishna
Water 2023, 15(4), 787; https://doi.org/10.3390/w15040787 - 17 Feb 2023
Cited by 7 | Viewed by 3541
Abstract
The United Nations Member States created a common roadmap for sustainability and development in 2015. The UN-SDGs are included in the 2030 Plan as an immediate call to action from all nations in the form of global partnerships. To date, a handful of [...] Read more.
The United Nations Member States created a common roadmap for sustainability and development in 2015. The UN-SDGs are included in the 2030 Plan as an immediate call to action from all nations in the form of global partnerships. To date, a handful of countries have achieved substantial progress toward the targets. The climate–water–energy–food nexus is being advocated as a conceptual method for achieving sustainable development. According to research, frameworks for adopting nexus thinking have not been the best solution to clearly or sufficiently include thoughts on sustainability. Therefore, there is much room for other solutions; these are in the form of newer Fourth Industrial Revolution digital technologies, as well as transitioning from a linear economy to a circular economy. In this paper, we come to understand these two models and their linkages between climate, water, energy, and food; their application and challenges, and, finally, the effects on the UN-SDGs. It was found that both circular economy and newer Fourth Industrial Revolution digital technologies can positively support the nexus as well as directly address the UN-SDGs, specifically SDGs 7, 8, 9, 11, 12, and 13. Full article
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