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Agricultural Practices to Improve Irrigation Sustainability, 2nd Edition
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Agricultural Practices to Improve Irrigation Sustainability, 2nd Edition

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

Deadline for manuscript submissions: 20 July 2025 | Viewed by 6049

Special Issue Editors

Prof. Dr. Patrícia Palma

E-Mail Website
Guest Editor
Institute of Earth Sciences (ICT-Evora)/Polytechnic Institute of Beja, 7800-295 Beja, Portugal
Interests: environmental risk assessment; water quality; ecotoxicology bioassays; pesticides
Special Issues, Collections and Topics in MDPI journals
Dr. Alexandra Tomaz

E-Mail Website
Guest Editor
Polytechnic Institute of Beja/GeoBioTec, NOVA School of Science and Technology, 7800-295 Beja, Portugal
Interests: soil and water conservation; water use efficiency; soil salinity; irrigation water quality; irrigation management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Water is the main limiting factor in agricultural production in regions affected by water scarcity, where annual or seasonal rainfall is insufficient to satisfy the water requirements of crops. In fact, food production and water use are inextricably linked. Globally, agriculture accounts for 72% of water withdrawals, mainly for irrigation. Irrigated agriculture plays a key role in feeding the world’s population, and is responsible for 40% of the global food production in only 20% of cultivated land.

An increase in irrigated land productivity in recent years has been achieved thanks to the technological development of agriculture; however, pressures on the world’s land, soil, and water resources have also emerged. An increase in the use of plant protection products and fertilizers, the uptake of farm mechanization, or inadequate irrigation management may lead to the loss of soil health by salinization, erosion, or contamination, as well as an increase in pollution processes in surface or groundwater resources. Therefore, the misuse of irrigation through inadequate practices can affect ecosystems and the services they provide.

To ensure food security and to mitigate the effects of water scarcity resulting from climate change, it is essential to improve the efficiency and productivity of water use for crop production, while preserving natural resources from the negative environmental impact that can be associated with irrigation.

Rather than focusing on these problems, this Special Issue focuses on the available agroecological practices, deciphers which options are better, explores which soil indicators are the most sensitive to irrigation practices, and assesses the advances in related technology in order to improve the sustainability of irrigation agriculture with the most effective management actions.

Therefore, we invite researchers to contribute to this Special Issue on “Agricultural Practices to Improve Irrigation Sustainability, 2nd Edition” and to develop a set of reference publications on this subject in order to promote the resilience and the efficiency of irrigated agroecosystems.

Prof. Dr. Patrícia Palma
Dr. Alexandra Tomaz
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. 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

  • irrigation efficiency
  • agroecology in irrigated agriculture
  • irrigation management practices
  • advances in irrigation technologies
  • soil health indicators

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Related Special Issue

Published Papers (8 papers)

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Research

19 pages, 2188 KiB  
Article
Patterns, Risks, and Forecasting of Irrigation Water Quality Under Drought Conditions in Mediterranean Regions
by Alexandra Tomaz, Adriana Catarino, Pedro Tomaz, Marta Fabião and Patrícia Palma
Water 2025, 17(12), 1783; https://doi.org/10.3390/w17121783 - 14 Jun 2025
Abstract
The seasonal and interannual irregularity of temperature and precipitation is a feature of the Mediterranean climate that is intensified by climate change and constitutes a relevant driver of water and soil degradation. This study was developed during three years in a hydro-agricultural area [...] Read more.
The seasonal and interannual irregularity of temperature and precipitation is a feature of the Mediterranean climate that is intensified by climate change and constitutes a relevant driver of water and soil degradation. This study was developed during three years in a hydro-agricultural area of the Alqueva irrigation system (Portugal) with Mediterranean climate conditions. The sampling campaigns included collecting water samples from eight irrigation hydrants, analyzed four times yearly. The analysis incorporated meteorological data and indices (precipitation, temperature, and drought conditions) alongside chemical parameters, using multivariate statistics (factor analysis and cluster analysis) to identify key water quality drivers. Additionally, machine learning models (Random Forest regression and Gradient Boosting machine) were employed to predict electrical conductivity (ECw), sodium adsorption ratio (SAR), and pH based on chemical and climatic variables. Water quality evaluation showed a prevalence of a slight to moderate soil sodification risk. The factor analysis outcome was a three-factor model related to salinity, sodicity, and climate. The cluster analysis revealed a grouping pattern led by year and followed by stage, pointing to the influence of inter-annual climate irregularity. Variations in water quality from the reservoirs to the distribution network were not substantial. The Random Forest algorithm showed superior predictive accuracy, particularly for ECw and SAR, confirming its potential for the reliable forecasting of irrigation water quality. This research emphasizes the importance of integrating time-sensitive monitoring with data-driven predictions of water quality to support sustainable water resources management in agriculture. This integrated approach offers a promising framework for early warning and informed decision-making in the context of increasing drought vulnerability across Mediterranean agro-environments. Full article
(This article belongs to the Special Issue Agricultural Practices to Improve Irrigation Sustainability, 2nd Edition)
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23 pages, 36340 KiB  
Article
Understanding Unsustainable Irrigation Practices in a Regionally Contested Large River Basin in Peninsular India Through the Lens of the Water–Energy–Food–Environment (WEFE) Nexus
by Bhawana Gupta and John S. Rowan
Water 2025, 17(11), 1644; https://doi.org/10.3390/w17111644 - 29 May 2025
Viewed by 430
Abstract
Water management is a long-standing source of dispute between the riparian states of Karnataka and Tamil Nadu. Recently, these disputes have intensified due to impacts from climate change and Bangalore’s rapid growth to megacity status. Despite well-defined national water governance instruments, competition between [...] Read more.
Water management is a long-standing source of dispute between the riparian states of Karnataka and Tamil Nadu. Recently, these disputes have intensified due to impacts from climate change and Bangalore’s rapid growth to megacity status. Despite well-defined national water governance instruments, competition between state actors and limited access to reliable hydrometric data have led to a fragmented regulatory regime, allowing unchecked exploitation of surface and groundwater resources. Meanwhile, subsidised energy for groundwater pumping incentivises the unsustainable irrigation of high-value, water-intensive crops, resulting in overextraction and harm to aquatic ecosystems. Here, we employ a water–energy–food–environment (WEFE) nexus approach to examine the socio-political, economic, and environmental factors driving unsustainable irrigation practices in the Cauvery River Basin (CRB) of Southern India. Our methodology integrates spatially explicit analysis using digitised irrigation census data, theoretical energy modelling, and crop water demand simulations to assess groundwater use patterns and energy consumption for irrigation and their links with governance and economic growth. We analyse spatio-temporal irrigation patterns across the whole basin (about 85,000 km2) and reveal the correlation between energy access and groundwater extraction. Our study highlights four key findings. First, groundwater pumping during the Rabi (short-rain) season consumes 24 times more energy than during the Kharif (long-rain) season, despite irrigating 40% less land. Second, the increasing depth of borewells, driven by falling water table levels, is a major factor in rising energy consumption. Third, energy input is highest in regions dominated by paddy cultivation. Fourth, water pumping in the Cauvery region accounts for about 16% of India’s agricultural energy use, despite covering only 4% of the country’s net irrigated area. Our study reinforces the existing literature advocating for holistic, catchment-wide planning, aligned with all UN Sustainable Development Goals. Full article
(This article belongs to the Special Issue Agricultural Practices to Improve Irrigation Sustainability, 2nd Edition)
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18 pages, 266 KiB  
Article
Evaluation of Hydraulic and Irrigation Performances of Drip Systems in Nectarine Orchards (Prunus persica var. nucipersica) in The Mediterranean Region
by Alper Baydar, Yeşim Bozkurt Çolak, Cenk Küçükyumuk and Burak Dalkılıç
Water 2025, 17(5), 758; https://doi.org/10.3390/w17050758 - 5 Mar 2025
Viewed by 754
Abstract
This study focused on evaluating the performance of the drip irrigation systems installed in 18 different nectarines (Prunus persica var. nucipersica) orchards in the Tarsus Plain in the Mediterranean region from 2017 through 2018. The performance of the drip systems was [...] Read more.
This study focused on evaluating the performance of the drip irrigation systems installed in 18 different nectarines (Prunus persica var. nucipersica) orchards in the Tarsus Plain in the Mediterranean region from 2017 through 2018. The performance of the drip systems was evaluated based on parameters like average emitter discharge (Qavg), Christiansen uniformity coefficient (CU), distribution uniformity (DU), emission uniformity (EU), and system application efficiency (Ea). The results indicated that the CU varied between 81 and 98%; DU changed from 82 to 97%; EU 61–92%; absolute emission uniformity (EUa) ranged between 93 and 98%; statistical uniformity (Us) changed from 85 to 97%; application efficiency of low-quarter (AELQ) varied between 45 and 97%; potential application efficiency of low-quarter (PELQ) ranged between 55 and 83%; system application efficiency (Ea) changed from 56 to 96%; storage efficiency (Es) fluctuated between 45 and 97%; and pressure variation (Pv) 17–81% and emitter flow variations (qv) of 2–36% were determined. Although the CU, DU, and EU values were acceptable, the variations in emitter flow rates and pressures were not acceptable. The results revealed that the lower performances might be attributed to physical clogging and/or lack of system design and application practices by the farmers. It is recommended that the farmers receive appropriate training on the operation and management of drip irrigation systems. Full article
(This article belongs to the Special Issue Agricultural Practices to Improve Irrigation Sustainability, 2nd Edition)
19 pages, 3630 KiB  
Article
Transformation of Terraces with Irrigation Systems: Profitability and Water Savings in Potato Crop (Solanum tuberosum L.)
by Russell Poma-Chamana, Ricardo Flores-Marquez, Joel Cordova-Tadeo, Antony Quello, José Arapa-Quispe and Richard Solórzano-Acosta
Water 2025, 17(5), 668; https://doi.org/10.3390/w17050668 - 25 Feb 2025
Cited by 1 | Viewed by 736
Abstract
In recent decades, climate change has intensified the challenges in agriculture, increasing the incidence of water and heat stress during critical stages of the crop cycle. It includes the exacerbation of the seasonality of rainfall and temperature. This significantly affects their development and [...] Read more.
In recent decades, climate change has intensified the challenges in agriculture, increasing the incidence of water and heat stress during critical stages of the crop cycle. It includes the exacerbation of the seasonality of rainfall and temperature. This significantly affects their development and yield. In addition, climate change has reduced irrigation water availability, highlighting the need to evaluate joint strategies to increase water productivity. These strategies include the implementation of irrigation systems, the use of terraces, and the application of deficit irrigation (DI). In this context, the present research aims to evaluate the irrigation water productivity (WPirri) and the economic water productivity (EWP) of the combined use of DI through a pressurized irrigation system in terraces of the southern highlands of Peru for a potato crop. The treatments included L0: traditional surface irrigation with irrigation depth equivalent to 100% ETc, L1: drip irrigation with irrigation depth equivalent to 100% ETc, L2: drip irrigation with DI at 75% ETc, and L3: drip irrigation with DI at 50% ETc. The DI treatments (L2 and L3) were implemented by forming stolons (60 DAS). As a result, L2 allows saving irrigation water of 3930 m3 ha−1 compared to L0 and 1164 m3 ha−1 compared to L1. It means a WPirri of 6.15 ± 0.35 kg m−3 allowing a commercial yield (CY: 27.15 ± 1.47 t ha−1) statistically similar to L1 (WPirri: 5.45 ± 0.34 kg m−3; CY: 30.14 ± 1.83 t ha−1) and higher than the traditional surface irrigation (WPirri: 2.63 ± 0.23 kg m−3; CY: 21.62 ± 1.99 t ha−1). This water saving meant a net income of 3097.04 ± 435.52 USD ha−1 for L2, close to L1 (4421.12 ± 724.24 USD ha−1), and much higher than L0 (1664.50 ± 834.24 USD ha−1). The results suggest that using drip irrigation systems in terraced crops optimizes water savings, maintains yields and profitability, and could promote the modernization of terraces in rural environments. Full article
(This article belongs to the Special Issue Agricultural Practices to Improve Irrigation Sustainability, 2nd Edition)
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18 pages, 3127 KiB  
Article
How Much Is Enough? Data Requirements for Practical Irrigation Decision-Making in Vietnamese Coffee Production
by Michael Scobie, David Freebairn, Shahbaz Mushtaq and Darrell Donahue
Water 2025, 17(5), 646; https://doi.org/10.3390/w17050646 - 23 Feb 2025
Viewed by 858
Abstract
In making irrigation decisions, farmers typically rely on local observation and experience, such as observing crops and neighbors’ actions. Research has mainly focused on understanding crop water requirements to improve farming practices, but it is important to acknowledge that farmers have unique perspectives, [...] Read more.
In making irrigation decisions, farmers typically rely on local observation and experience, such as observing crops and neighbors’ actions. Research has mainly focused on understanding crop water requirements to improve farming practices, but it is important to acknowledge that farmers have unique perspectives, access to diverse local “signals”, and experience. The challenge is to strike a balance between complex technical assessments of field conditions (the science) and harnessing farmers’ skills to manage their irrigation in ways that maximize yield and quality. This study established a basis for specifying minimum data requirements for pragmatic, but not necessarily perfect, irrigation decision-making for small-scale Vietnamese coffee farmers. This study focuses on three areas in Dak Lak province in the Central Highlands of Vietnam. To explore the role of monitoring in irrigation management, two contrasting monitoring systems were set up to collect soil, weather, and irrigation data. We also compared a variety of water balance models with different data requirements, with a focus on processes that used “passive data collection”, i.e., farmers do not manually collect data, rather data can be accessed readily from external sources. In Vietnam, traditional hosepipe irrigation is applied where it is impractical to know the volume of applied water. The proposed Low Data Model (LDM) is suited to more informed irrigation scheduling decisions, which have potential to improve the likelihood of coffee growers adopting measurement-based decision-making. While researchers may seek a detailed daily sub-millimeter understanding of soil water dynamics, farmers require practical decision support if there is to be any adoption of improved methods. This study offers a simple and practical approach for irrigation scheduling rather than a model using numerically perfect data that is unachievable in the field. The work demonstrates that on-site rainfall data is essential. However, other data can be collected passively to reduce the burden of data collection on users. This approach may enhance the likelihood of model-based irrigation scheduling being adopted by coffee farmers in Vietnam. Full article
(This article belongs to the Special Issue Agricultural Practices to Improve Irrigation Sustainability, 2nd Edition)
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20 pages, 3264 KiB  
Article
Energy of Sorghum Biomass Under Deficit Irrigation Strategies in the Mediterranean Area
by Simone Pietro Garofalo, Anna Francesca Modugno, Gabriele de Carolis and Pasquale Campi
Water 2025, 17(4), 578; https://doi.org/10.3390/w17040578 - 17 Feb 2025
Viewed by 459
Abstract
The growing demand for renewable energy sources and the need to optimize water use in agriculture, particularly in water-scarce regions, highlights the importance of growing species suitable for semi-arid areas, such as sorghum (Sorghum bicolor L. Moench). Deficit irrigation strategies allow water [...] Read more.
The growing demand for renewable energy sources and the need to optimize water use in agriculture, particularly in water-scarce regions, highlights the importance of growing species suitable for semi-arid areas, such as sorghum (Sorghum bicolor L. Moench). Deficit irrigation strategies allow water savings by optimizing water use efficiency. However, the potential of sorghum for bioethanol production with deficit irrigation strategies is still not well studied. This work investigates the impact of three irrigation strategies (full, deficit, and regulated deficit) on the biomass yield, ethanol production, and water use efficiency of sorghum (‘KWS Bulldozer’) in a semi-arid Mediterranean area (the Apulia region, Southeastern Italy) over three growing seasons (2013, 2014, and 2017); irrigation needs were calculated from crop evapotranspiration using standard crop coefficients and soil water content measurements. Harvested biomass was analyzed for cellulose and hemicellulose content, and ethanol production was estimated using conversion models. The full irrigation treatment resulted in the highest biomass and ethanol production in all seasons (22,633 kg × ha−1, 28,367 kg × ha−1, and 23,835 kg × ha−1, in 2013, 2014, and 2017, respectively), highlighting the relationship between a full water supply and yield optimization. However, deficit irrigation showed a higher biomass and ethanol water productivity (10.93 kg × m−3 and 3.23 L × m−3, respectively) than other treatments, suggesting that moderate irrigation strategies can effectively balance production and sustainable water use. The results suggest the importance of adjusting irrigation practices to specific environmental conditions to improve the efficiency and productivity of sorghum. Full article
(This article belongs to the Special Issue Agricultural Practices to Improve Irrigation Sustainability, 2nd Edition)
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16 pages, 15870 KiB  
Article
Optimizing Irrigation and Nitrogen Application for Greenhouse Tomato Using the DSSAT–CROPGRO–Tomato Model
by Zhijie Shan, Junwei Chen, Xiping Zhang, Zhuanyun Si, Ruochen Yi and Haiyan Fan
Water 2025, 17(3), 426; https://doi.org/10.3390/w17030426 - 3 Feb 2025
Cited by 1 | Viewed by 1026
Abstract
The aim of this study was to optimize water-saving and high-efficiency irrigation and nitrogen application scheduling for greenhouse tomato cultivation in North China. Using experimental data on water and nitrogen inputs, the DSSAT-GLUE parameter adjustment tool was employed to calibrate the genetic parameters [...] Read more.
The aim of this study was to optimize water-saving and high-efficiency irrigation and nitrogen application scheduling for greenhouse tomato cultivation in North China. Using experimental data on water and nitrogen inputs, the DSSAT-GLUE parameter adjustment tool was employed to calibrate the genetic parameters of the DSSAT–CROPGRO–Tomato model. Simulations were conducted to assess greenhouse tomato growth, water use, and yield under varying water and nitrogen conditions. After calibration, the model showed average relative errors of 3.19% for the phenological stages, 3.33% for plant height, and 4.52% for yield dry weight, meeting accuracy standards. The results from the calibrated model indicated that increasing irrigation or nitrogen levels initially enhanced yield but led to diminishing returns beyond optimal ranges. The maximum tomato yield and water–nitrogen use efficiency were achieved with irrigation quotas between 320 and 340 mm and nitrogen applications between 360 and 400 kg·ha−1. These findings provide a guideline for efficient water and nitrogen management for greenhouse tomatoes under drip irrigation conditions. Full article
(This article belongs to the Special Issue Agricultural Practices to Improve Irrigation Sustainability, 2nd Edition)
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19 pages, 6533 KiB  
Article
Robustness of Actual Evapotranspiration Predicted by Random Forest Model Integrating Remote Sensing and Meteorological Information: Case of Watermelon (Citrullus lanatus, (Thunb.) Matsum. & Nakai, 1916)
by Simone Pietro Garofalo, Francesca Ardito, Nicola Sanitate, Gabriele De Carolis, Sergio Ruggieri, Vincenzo Giannico, Gianfranco Rana and Rossana Monica Ferrara
Water 2025, 17(3), 323; https://doi.org/10.3390/w17030323 - 23 Jan 2025
Cited by 1 | Viewed by 969
Abstract
Water scarcity, exacerbated by climate change and increasing agricultural water demands, highlights the necessity for efficient irrigation management. This study focused on estimating actual evapotranspiration (ETa) in watermelons under semi-arid Mediterranean conditions by integrating high-resolution satellite imagery and agro-meteorological data. Field experiments were [...] Read more.
Water scarcity, exacerbated by climate change and increasing agricultural water demands, highlights the necessity for efficient irrigation management. This study focused on estimating actual evapotranspiration (ETa) in watermelons under semi-arid Mediterranean conditions by integrating high-resolution satellite imagery and agro-meteorological data. Field experiments were conducted in Rutigliano, southern Italy, over a 2.80 ha area. ETa was measured with the eddy covariance (EC) technique and predicted using machine learning models. Multispectral reflectance data from Planet SuperDove satellites and local meteorological records were used as predictors. Partial least squares, the generalized linear model and three machine learning algorithms (Random Forest, Elastic Net, and Support Vector Machine) were evaluated. Random Forest yielded the highest predictive accuracy with an average R2 of 0.74, RMSE of 0.577 mm, and MBE of 0.03 mm. Model interpretability was performed through permutation importance and SHAP, identifying the near-infrared and red spectral bands, average daily temperature, and relative humidity as key predictors. This integrated approach could provide a scalable, precise method for watermelon ETa estimation, supporting data-driven irrigation management and improving water use efficiency in Mediterranean horticultural systems. Full article
(This article belongs to the Special Issue Agricultural Practices to Improve Irrigation Sustainability, 2nd Edition)
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