Sustainable Water-Resource Strategies in Agriculture for Climate Change Adaptation

A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Agricultural Water Management".

Deadline for manuscript submissions: closed (15 October 2024) | Viewed by 8457

Special Issue Editors


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Guest Editor
Council for Agricultural Research and Economics, Research Center for Agriculture and Environment (CREA-AA), Via della Navicella 2-4, 00184 Rome, Italy
Interests: water and resource use efficiency; innovative agricultural formulations (adjuvants, biostimulants) and fertilizers; eco-physiology of agro/forestry systems and quality indicators; biotic/abiotic interactions and interspecific communication in agroecosystems; participatory approaches for sustainable agriculture

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Guest Editor
Council for Agricultural Research and Economics, Research Center for Agriculture and Environment (CREA-AA), Via della Navicella 2-4, 00184 Rome, Italy
Interests: climate change adaptation and mitigation; cropping systems diversification, simulation modelling; water use efficiency
Special Issues, Collections and Topics in MDPI journals

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Guest Editor Assistant
Council for Agricultural Research and Economics, Research Center for Agriculture and Environment (CREA-AA), Via della Navicella 2-4, 00184 Rome, Italy
Interests: agricultural water management; sustainable agriculture indicators; soil quality; geomatics

Special Issue Information

Dear Colleagues,

As the climate crisis poses a threat to water supplies worldwide, agriculture accounts for a significant portion of freshwater withdrawals, primarily for irrigation and especially in arid and semi-arid regions where water scarcity is prevalent. By the end of this decade, water demand is expected to exceed freshwater supply by 40%, increasing twice as fast as population growth. Rising food demand will further exacerbate the need to increase agricultural water productivity, and for the sustainable use of water to be achieved, it will be critical to design and implement innovative resource management strategies and practices in agriculture to mitigate climate variability and preserve water resources.

To improve the resilience and adaptation of irrigated agriculture to climate change, it is of the utmost importance to better understand the driving processes and identify the most suitable crop management strategies to improve water use efficiency and economic benefits while maintaining or hopefully increasing crop yields. 

In this Special Issue, high-quality research articles will address sustainable water-resource strategies in agriculture and their current state of the art, focusing on the latest developments in practices and approach at different scales, including crops, farms, and agricultural systems.

Topics that will be considered in this Special Issue include, among others:

  • effects of crop and soil management strategies on water use efficiency (e.g., crop diversification, crop rotation, agroforestry, cover crops, crop residue management, minimum or no tillage, and physiological plant regulation of water productivity) and/or soil water conservation (e.g., mycorrhizal inoculation, use of superabsorbent polymers, amendments, and anti-transpirants);
  • improved irrigation water management and effects on water productivity (e.g., drip irrigation, deficit irrigation, subsurface irrigation, water-fertilizer coupling, and use of irrigation adjuvants);
  • innovative measuring and modeling approaches.

We also encourage particular attention to be paid to stakeholders' and policymakers' engagement in implementing innovative and integrated strategies in agriculture for sustainable water management, especially in agricultural areas that will be significantly affected by rising temperatures, more frequent droughts, and altered/reduced precipitation regimes in the coming decades. 

Dr. Valentina Baratella
Dr. Claudia Di Bene
Guest Editors

Silvia Vanino
Guest Editor Assistant

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Published Papers (5 papers)

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Research

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24 pages, 5068 KiB  
Article
Modeling Comprehensive Deficit Irrigation Strategies for Drip-Irrigated Cotton Using AquaCrop
by Yalong Du, Qiuping Fu, Pengrui Ai, Yingjie Ma and Yang Pan
Agriculture 2024, 14(8), 1269; https://doi.org/10.3390/agriculture14081269 - 2 Aug 2024
Viewed by 1035
Abstract
The development of a crop production strategy through the use of a crop model represents a crucial method for the assurance of a stable agricultural yield and the subsequent enhancement thereof. There are currently no studies evaluating the suitability of the AquaCrop model [...] Read more.
The development of a crop production strategy through the use of a crop model represents a crucial method for the assurance of a stable agricultural yield and the subsequent enhancement thereof. There are currently no studies evaluating the suitability of the AquaCrop model for the drip irrigation of Gossypium barbadense in Southern Xinjiang, which is the primary planting region for Gossypium barbadense in China. In order to investigate the performance of the AquaCrop model in simulating the growth of cotton under mulched drip irrigation, the model was locally calibrated and validated according to different irrigation thresholds during a key growth period of two years. The results of the simulation for total soil water (TSW), crop evapotranspiration (ETc), canopy coverage (CC), aboveground biomass (Bio), and seed cotton yield demonstrated a high degree of correlation with the observed data, with a root mean square error (RMSE) of <11.58%. The Bio and yield simulations demonstrated a high degree of concordance with the corresponding measured values, with root mean square error (RMSE) values of 1.23 t ha−1 and 0.15 t ha−1, respectively. However, the predicted yield declined in the verification year, though the prediction error remained below 15%. Furthermore, the estimated evapotranspiration (ETc) value demonstrated a slight degree of overestimation. Generally, the middle and late stages of cotton growth led to an overestimation of the TSW content. However, the prediction error was less than 13.99%. Through the calculation of each performance index of the AquaCrop model, it is found that they are in the acceptable range. In conclusion, the AquaCrop model can be employed as a viable tool for predicting the water response of cotton to drip irrigation under mulched film in Southern Xinjiang. Based on 64 years of historical meteorological data, three years were selected as scenarios for simulation. Principal component analysis (PCA) showed that, in a local wet year in Southern Xinjiang, the irrigation quota was 520 mm, and the irrigation cycle was 6 days/time. In normal years, the irrigation quota was 520 mm, with an irrigation cycle of 6 days/time. In dry years, the irrigation quota was 595 mm, with an irrigation cycle of 10 days/time. This allowed for higher seed cotton yields and irrigation water productivity, as well as the maximization of cotton yields and net revenue in the arid oasis area of Southern Xinjiang. Full article
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19 pages, 5719 KiB  
Article
A Standardized Treatment Model for Head Loss of Farmland Filters Based on Interaction Factors
by Zhenji Liu, Chenyu Lei, Jie Li, Yangjuan Long and Chen Lu
Agriculture 2024, 14(5), 788; https://doi.org/10.3390/agriculture14050788 - 20 May 2024
Viewed by 906
Abstract
A head loss model for pressureless mesh filters used in farmland irrigation was developed by integrating the four basic test factors: irrigation flow, filter cartridge speed, self-cleaning flow, and initial sand content. The model’s coefficient of determination was found to be 98.61%. Among [...] Read more.
A head loss model for pressureless mesh filters used in farmland irrigation was developed by integrating the four basic test factors: irrigation flow, filter cartridge speed, self-cleaning flow, and initial sand content. The model’s coefficient of determination was found to be 98.61%. Among the basic factors, the total irrigation flow accounted for only 17.20% of the relatively small self-cleaning flow. The contribution of initial sand content was found to be the smallest, with a coefficient of only 0.0166. Furthermore, the contribution rate of the flow term was significantly higher than that of the initial sand content, with a value of 159.73%. In terms of quadratic interaction, the difference between the interaction term of flushing flow and filter cartridge speed, and the interaction term of filter cartridge speed and self-cleaning flow was 38.42%. On the other hand, the difference within this level for the interaction term between initial sand content and filter cartridge speed, as well as the interaction term between irrigation flow and self-cleaning flow, was 2.82%. Finally, through joint optimization of the response surface and model, the optimal values for the irrigation flow rate, filter cartridge speed, self-cleaning flow rate, and initial sand content were determined to be 121.687 m3·h−1, 1.331 r·min−1, 19.980 m3·h−1, and 0.261 g·L−1; the measured minimum head loss was found to be 21.671 kPa. These research findings can serve as a reference for enhancing the design of farmland filters and optimizing irrigation systems. Full article
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15 pages, 18883 KiB  
Article
Meteorological and Agricultural Drought Risk Assessment via Kaplan–Meier Survivability Estimator
by Cem Polat Cetinkaya and Mert Can Gunacti
Agriculture 2024, 14(3), 503; https://doi.org/10.3390/agriculture14030503 - 20 Mar 2024
Cited by 2 | Viewed by 1477
Abstract
Dry periods and drought are inherent natural occurrences. However, due to the increasing pressures of global warming and climate change, these events have become more frequent and severe on a global scale. These phenomena can be traced with various indicators and related indices [...] Read more.
Dry periods and drought are inherent natural occurrences. However, due to the increasing pressures of global warming and climate change, these events have become more frequent and severe on a global scale. These phenomena can be traced with various indicators and related indices proposed by various scholars. In general, drought risk assessment is done by modeling these indicators and determining the drought occurrence probabilities. The proposed adaptation introduces the “Kaplan–Meier estimator”, a non-parametric statistic traditionally used in medical contexts to estimate survival functions from lifetime data. The study aims to apply this methodology to assess drought risk by treating past droughts as “events” and using drought indicators such as the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI). Mapping these results for a better understanding of the drought risks on larger spatial scales such as a river basin is also within the expected outcomes. The adapted method provides the probability of non-occurrence, with inverted results indicating the likelihood of drought occurrence. As a case study, the method is applied to SPI and SPEI values at different time steps (3, 6, and 12 months) across 27 meteorological stations in the Gediz River Basin, located in Western Turkey—a region anticipated to be profoundly affected by global climate change. The results are represented as the generated drought risk maps and curves, which indicate that (i) drought risks increase as the considered period extends, (ii) drought risks decrease as the utilized indicator timescales increase, (iii) locally plotted drought curves indicate higher drought risks as their initial slope gets steeper. The method used enables the generation of historical evidence based spatially distributed drought risk maps, which expose more vulnerable areas within the river basin. Full article
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26 pages, 8530 KiB  
Article
Optimal Pumping Flow Algorithm to Improve Pumping Station Operations in Irrigation Systems
by Enrique Bonet and María Teresa Yubero
Agriculture 2024, 14(3), 463; https://doi.org/10.3390/agriculture14030463 - 12 Mar 2024
Cited by 1 | Viewed by 1534
Abstract
In Spain, irrigated agriculture is the most water-intensive sector, consuming around of 80% of water resources. Moreover, irrigation water distribution systems are the infrastructure by which one-third of water resource losses take place. Monitoring and controlling operations in irrigation canals are essential for [...] Read more.
In Spain, irrigated agriculture is the most water-intensive sector, consuming around of 80% of water resources. Moreover, irrigation water distribution systems are the infrastructure by which one-third of water resource losses take place. Monitoring and controlling operations in irrigation canals are essential for mitigating leakages and water waste in operational actions. On the other hand, energy consumption by agriculture is around 5% of usage in developed countries and even higher in undeveloped countries. Although it is a small part of the total energy supply for a country, energy waste reduces the competitiveness of the agriculture sector, which continually reduces profit margins in an economic sector with very low profit margins already. The tool developed in this paper aims to increase the efficiency of water and energy management in the agricultural sector and is included in an overall control diagram for scheduled irrigation management. This tool, the optimal pumping flow (OPF algorithm), optimizes the pumping flow from the irrigation canal to the irrigation reservoir in terms of water level at the canal and reservoir, crop flow demand, system constraints, and energy prices. Regarding the results, the OPF algorithm can calculate the optimum pumping operations, being able to optimize water resource usage and energy expenses by ensuring that the water level at reservoirs remains within a specified range and that pump flow never exceeds a threshold. Further, it allows for the management of pump operations outside of peak hours. On the other hand, the OPF algorithm is also integrated into the overall control diagram in a second test. Here, the OPF algorithm collaborates with a control canal algorithm such as the GoRoSo algorithm to optimize canal gates and pump operations, respectively. In this scenario, OPF reduces cumulative energy expenses by 58% compared to the scenario where the pump station operates only when the reservoir water level is below a certain threshold. Full article
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Review

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18 pages, 1836 KiB  
Review
An Overview of Polymeric Hydrogel Applications for Sustainable Agriculture
by Priscila Vedovello, Lívia Valentim Sanches, Gabriel da Silva Teodoro, Vinícius Ferraz Majaron, Ricardo Bortoletto-Santos, Caue Ribeiro and Fernando Ferrari Putti
Agriculture 2024, 14(6), 840; https://doi.org/10.3390/agriculture14060840 - 27 May 2024
Cited by 4 | Viewed by 2514
Abstract
Agriculture, a vital element of human survival, confronts challenges of meeting rising demand due to population growth and product availability in developing nations. Reliance on pesticides and fertilizers strains natural resources, leading to soil degradation and water scarcity. Addressing these issues necessitates enhancing [...] Read more.
Agriculture, a vital element of human survival, confronts challenges of meeting rising demand due to population growth and product availability in developing nations. Reliance on pesticides and fertilizers strains natural resources, leading to soil degradation and water scarcity. Addressing these issues necessitates enhancing water efficiency in agriculture. Polymeric hydrogels, with their unique water retention and nutrient-release capabilities, offer promising solutions. These superabsorbent materials form three-dimensional networks retaining substantial amounts of water. Their physicochemical properties suit various applications, including agriculture. Production involves methods like bulk, solution, and suspension polymerization, with cross-linking, essential for hydrogels, achieved through physical or chemical means, each with different advantages. Grafting techniques incorporate functional groups into matrices, while radiation synthesis offers purity and reduced toxicity. Hydrogels provide versatile solutions to tackle water scarcity and soil degradation in agriculture. Recent research explores hydrogel formulations for optimal agricultural performance, enhancing soil water retention and plant growth. This review aims to offer a comprehensive overview of hydrogel technologies as adaptable solutions addressing water scarcity and soil degradation challenges in agriculture, with ongoing research refining hydrogel formulations for optimal agricultural use. Full article
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