Advances in Water and Soil Management Towards Climate Change Adaptation

Topic Information

Dear Colleagues,

The journals Sustainability, Water, Agriculture, Resources and Climate have launched a multi-disciplinary Research Topic on “Advances in Water & Soil Management towards Climate Change Adaptation” and invite researchers, experts and professionals from Universities, Research Institutions, National and International Organizations, Local and Regional Authorities and Enterprises to contribute their research achievements in this field. The main aim of this Topic is to increase the scientific knowledge and understanding of the interactions between water/soil resources management and climate change impacts at local, regional, and global scales, which is a fundamental factor for reaching the goal of a sustainable society.

Over the last few years, we have been observing and monitoring the impacts of climate on the hydrological cycle and soil quality and the increasing pressure on environmental resources. As a result, many regions worldwide suffer from diminishing water resources, water pollution and soil degradation. We can already see how the ongoing climate crisis combined with continuous urbanization and the global population increase affects the water–energy–food nexus and threatens the health of both humans and the ecosystems. In this context, it is of great importance to increase water productivity and water security, identify optimum strategies and technologies to restore water quality, effectively reduce pollution and prevent crop damage under extreme climate conditions and different anthropogenic interventions. Various measures have been proposed, such as climatic water/soil adaptive agronomic practices and geoinformatics tools (advanced modelling, GIS and remote sensing applications), ecological engineering approaches to water and wastewater management and innovative technologies for water production from non-conventional sources, among others.

Thus, in this Topic, studies that focus on new developments in managing and modelling water and soil dynamics, including sustainable solutions for water supply and water/wastewater management, are of great importance. Also, new methods to assess and mitigate hydrological extremes (floods, droughts and soil/water erosion), especially in rural areas, will be primarily considered. Due to the increased water scarcity in arid and even mild climates, the efficiency of wastewater treatment and reuse is gaining attention, and new advanced and nature-based technologies are also becoming increasingly recognized. In this context, the efficient use of brackish and saline waters is becoming a priority as climate change accelerates. Therefore, new findings in wastewater management and the reuse of treated effluents for irrigation or recycling in industrial processes are a pillar of this Topic.

Dr. Nektarios N. Kourgialas
Dr. Ioannis Anastopoulos
Dr. Alexandros I. Stefanakis
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Agriculture agriculture	3.3	4.9	2011	19.2 Days	CHF 2600	Submit
Climate climate	3.0	5.5	2013	19.7 Days	CHF 1800	Submit
Sustainability sustainability	3.3	6.8	2009	19.7 Days	CHF 2400	Submit
Water water	3.0	5.8	2009	17.5 Days	CHF 2600	Submit
Resources resources	3.6	7.2	2012	26.1 Days	CHF 1600	Submit

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Published Papers (5 papers)

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All Agriculture Climate Sustainability Water Resources

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15 pages, 4298 KiB  

Open AccessArticle

Response of Different Perennial Ryegrass Varieties to Water Stress

by Mladen Prijović, Dejan Sokolović, Jelena Dragišić Maksimović, Vuk Maksimović, Dragica Milosavljević, Snežana Babić, Marija Stepić and Aneta Sabovljević

Agriculture 2025, 15(9), 917; https://doi.org/10.3390/agriculture15090917 - 22 Apr 2025

Viewed by 229

Abstract

Perennial ryegrass represents the most important forage grass, yet its generally low drought tolerance leads to reduced yields under water scarcity. Nevertheless, large intra- and inter-population variability could be a pool for selecting new drought-tolerant varieties. In this study we evaluated three populations [...] Read more.

Perennial ryegrass represents the most important forage grass, yet its generally low drought tolerance leads to reduced yields under water scarcity. Nevertheless, large intra- and inter-population variability could be a pool for selecting new drought-tolerant varieties. In this study we evaluated three populations (K-11, Exp population and Shandon) under semi-controlled conditions across four watering levels (100%, 70%, 50% and 30% of field water capacity), focusing on yield and key morphological and biochemical traits. Dry matter yield and root dry mass decreased in all populations under limited watering conditions. The highest biomass production in such conditions was observed in the Exp population, likely due to better root performance in the deeper soil layer. On the other hand, oxidative stress markers (MDA and H₂O₂) and water-soluble sugars, which indicated the best physiological status in cultivar K-11 under severe drought, did not lead to the highest DMY. These results show the importance of including multiple physiological and biochemical traits in breeding processes, with the aim of developing perennial ryegrass cultivars capable of withstanding prolonged and intense summer drought as a consequence of climate change. Full article

(This article belongs to the Topic Advances in Water and Soil Management Towards Climate Change Adaptation)

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41 pages, 11437 KiB  

Open AccessArticle

A Decision Support System for Managed Aquifer Recharge Through Non-Conventional Waters in the South of the Mediterranean

by Rym Hadded, Mongi Ben Zaied, Fatma Elkmali, Giulio Castelli, Fethi Abdelli, Zouhaier Khabir, Khaled Ben Zaied, Elena Bresci and Mohamed Ouessar

Resources 2025, 14(4), 63; https://doi.org/10.3390/resources14040063 - 11 Apr 2025

Viewed by 875

Abstract

Water management in arid regions faces significant challenges due to limited water resources and increasing competition among sectors. Climate change (CC) exacerbates these issues, highlighting the need for advanced modeling tools to predict trends and guide sustainable resource management. This study employs Water [...] Read more.

Water management in arid regions faces significant challenges due to limited water resources and increasing competition among sectors. Climate change (CC) exacerbates these issues, highlighting the need for advanced modeling tools to predict trends and guide sustainable resource management. This study employs Water Evaluation And Planning (WEAP) software to develop a Decision Support System (DSS) to evaluate the impact of climate change and water management strategies on the Triassic aquifer of “Sahel El Ababsa” in southeast Tunisia up to 2050. The reference scenario (SC0) assumes constant climatic and socio-economic conditions as of 2020. CC is modeled under RCP4.5 (SC1.0) and RCP8.5 (SC2.0). Additional scenarios include Seawater Desalination Plants (SDPs) (SC3.0 and SC4.0), water harvesting techniques (SC5.0) to highlight their impact on the recharge, and irrigation management strategies (SC6.0). All these scenarios were further developed under the “SC1.0” scenario to assess the impact of moderate CC. The initial aquifer storage is estimated at 100 Million cubic meters (Mm³). Under (SC0), storage would decrease by 76%, leaving only 23.7 Mm³ by 2050. CC scenarios (SC1.0, SC2.0) predict about a 98% reduction. The implementation of the Zarat SDP (SC3.0) would lead to a 45% improvement compared to reference conditions by the end of the simulation period, while its extension (SC4.0) would result in a 69.5% improvement. Under moderate CC, these improvements would be reduced, with SC3.1 showing a 59% decline and SC4.1 a 35% decline compared to the reference scenario. The WHT scenario (SC5.0) demonstrated a 104% improvement in Triassic aquifer storage by 2050 compared to the reference scenario. However, under CC (SC5.1), this improvement would be partially offset, leading to a 29% decline in aquifer storage. The scenario maintaining stable agricultural demand from the Triassic aquifer under CC (SC6.1) projected an 83% decrease in storage. Conversely, the total “Irrigation Cancellation” scenario (SC7.1) under CC showed a significant increase in aquifer storage, reaching 59.3 Mm³ by 2050—an improvement of 250% compared to the reference scenario. The study underscores the critical need for alternative water sources for irrigation and integrated management strategies to mitigate future water scarcity. Full article

(This article belongs to the Topic Advances in Water and Soil Management Towards Climate Change Adaptation)

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23 pages, 5210 KiB  

Open AccessArticle

Dynamic Water and Fertilizer Management Strategy for Greenhouse Tomato Based on Morphological Characteristics

by Zhiyu Zuo, Tianyuan Lü, Jicheng Sun, Haitao Peng, Deyong Yang, Jinxiu Song, Guoxin Ma and Hanping Mao

Agriculture 2025, 15(3), 304; https://doi.org/10.3390/agriculture15030304 - 30 Jan 2025

Viewed by 585

Abstract

A dynamic management strategy for water and fertilizer application based on morphological characteristics was developed to enhance water use efficiency (WUE) and fruit yield in greenhouse-cultivated tomato (Solanum lycopersicum L.). Multivariate regression analysis was employed to determine the baseline water and fertilizer [...] Read more.

A dynamic management strategy for water and fertilizer application based on morphological characteristics was developed to enhance water use efficiency (WUE) and fruit yield in greenhouse-cultivated tomato (Solanum lycopersicum L.). Multivariate regression analysis was employed to determine the baseline water and fertilizer requirements and to evaluate the effects of varying irrigation and fertilization regimes on fruit yield and WUE. A coupled irrigation–fertilization experiment was conducted, and regression models were established to describe the changes in stem diameter and plant height under these regimes. These models were validated experimentally. The results showed that irrigation significantly influenced both tomato fruit yield and WUE, while fertilization significantly impacted yield, but not WUE. No interactive effects between irrigation and fertilization were observed for either parameter. Stem diameter and plant height were positively correlated with the irrigation and fertilization levels. The proposed dynamic management strategy improved fruit yield by 6.9% and 14.7% under the basic and well-irrigated/fertilized conditions, respectively, compared to that of the fixed regime. Furthermore, model implementation increased WUE by 6.93% and 43.17% and improved the economic benefits by 4.9% and 20.6% under the respective conditions. This provides a practical and effective tool for optimizing water and fertilizer management in greenhouse tomato production, contributing to resource-efficient and high-yield farming practices. Full article

(This article belongs to the Topic Advances in Water and Soil Management Towards Climate Change Adaptation)

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13 pages, 1983 KiB  

Open AccessArticle

Estimation of the Water Footprint of Wood Construction in Chile Using a Streamlined Input–Output-Based Model

by Ximena Vallejos, Steven Hidalgo, Belén González and Patricio Neumann

Sustainability 2025, 17(3), 1061; https://doi.org/10.3390/su17031061 - 28 Jan 2025

Cited by 1 | Viewed by 885

Abstract

Wood construction is often proposed to reduce the construction sector’s greenhouse gas emissions due to its carbon sequestration potential. However, forestry significantly impacts natural water flows and increases water use—a critical concern in Chile. This study evaluates the water footprint of wood construction [...] Read more.

Wood construction is often proposed to reduce the construction sector’s greenhouse gas emissions due to its carbon sequestration potential. However, forestry significantly impacts natural water flows and increases water use—a critical concern in Chile. This study evaluates the water footprint of wood construction in Chile, considering direct and indirect water consumption under various scenarios. An input–output model was developed to quantify economic interactions, incorporating a new wood-construction sector based on data from a model house. An environmental extension matrix was also created to account for blue water (groundwater and surface water extraction) and green water (rainwater absorbed from soil) consumption. Future scenarios for the residential building sector were defined based on different growth rates for wood-based construction and current construction methods, and the model was resolved using the scenarios as demand vectors. The results indicate that wood construction’s water footprint is 2.38–2.47 times higher than conventional construction methods, with over 64% linked to forestry’s green water demand. By 2050, increased wood construction could raise the sector’s total water footprint by 30.0–31.8%. These findings underscore the need to assess water consumption as a critical sustainability parameter for wood construction and highlight the value of tools like the water footprint to guide decision-making. Full article

(This article belongs to the Topic Advances in Water and Soil Management Towards Climate Change Adaptation)

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26 pages, 7990 KiB  

Open AccessArticle

A Novel Method to Forecast Nitrate Concentration Levels in Irrigation Areas for Sustainable Agriculture

by Halil Karahan and Müge Erkan Can

Agriculture 2025, 15(2), 161; https://doi.org/10.3390/agriculture15020161 - 13 Jan 2025

Viewed by 1123

Abstract

This study developed an ANN-based model to predict nitrate concentrations in drainage waters using parameters that are simpler and more cost-effective to measure within the Lower Seyhan Basin, a key agricultural region in Turkey. For this purpose, daily water samples were collected from [...] Read more.

This study developed an ANN-based model to predict nitrate concentrations in drainage waters using parameters that are simpler and more cost-effective to measure within the Lower Seyhan Basin, a key agricultural region in Turkey. For this purpose, daily water samples were collected from a drainage measurement station during the 2022 and 2023 water years, and nitrate concentrations were determined in the laboratory. In addition to nitrate concentrations, other parameters, such as flow rate, EC, pH, and precipitation, were also measured simultaneously. The complex relationship between measured nitrate values and other parameters, which are easier and less costly to measure, was used in two different scenarios during the training phase of the ANN-Nitrate model. After the model was trained, nitrate values were estimated for the two scenarios using only the other parameters. In Scenario I, random values from the dataset were predicted, while in Scenario II, predictions were made as a time series, and model results were compared with measured values for both scenarios. The proposed model reliably fills dataset gaps (Scenario I) and predicts nitrate values in time series (Scenario II). The proposed model, although based on an artificial neural network (ANN), also has the potential to be adapted for methods used in machine learning and artificial intelligence, such as Support Vector Machines, Decision Trees, Random Forests, and Ensemble Learning Methods. Full article

(This article belongs to the Topic Advances in Water and Soil Management Towards Climate Change Adaptation)

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