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Modeling as a Tool to Explore Sustainable Irrigation Practices in...
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Modeling as a Tool to Explore Sustainable Irrigation Practices in Agriculture

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

Deadline for manuscript submissions: 31 January 2026 | Viewed by 1039

Special Issue Editors

Dr. Tao Ma

E-Mail Website
Guest Editor
College of Agricultural Science and Engineering, Hohai University, Nanjing 211100, China
Interests: agricultural high water efficiency management; smart irrigation; crop growth modeling; UAV remote sensing; 3D phenotype extraction
Prof. Dr. Xiangping Guo

E-Mail Website
Guest Editor
College of Agricultural Science and Engineering, Hohai University, Nanjing 210098, China
Interests: water-saving irrigation; irrigation and drainage optimization; saline–alkali soil remediation; land consolidation; soil–water–environment interaction
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Agriculture is one of the largest consumers of freshwater resources globally, and the pressure to optimize irrigation practices while ensuring sustainability has never been greater. Climate change, population growth, and water scarcity require innovative solutions to enhance water-use efficiency, reduce environmental impacts, and maintain crop productivity. Modeling emerges as a powerful tool to navigate this complexity, enabling the simulation of diverse irrigation scenarios, the optimization of water use efficiency, and the prediction of long-term environmental impacts. It bridges data gaps, integrates biophysical and socioeconomic factors, and supports evidence-based decisions to balance agricultural productivity with ecological sustainability. Therefore, this Special Issue focuses on the critical role of modeling as a tool to advance sustainable irrigation practices, integrating cutting-edge methodologies, interdisciplinary approaches, and real-world applications.

This Special Issue invites authors to contribute interdisciplinary studies leveraging modeling to advance sustainable irrigation. Topics include (but are not limited to) the development of hydrological crop systems or integrated models; the assessment of precision irrigation technologies; scenario analysis for climate-adaptive irrigation; and the optimization of water allocation in complex agroecosystems. We welcome the submission of original research and reviews from agronomy, hydrology, computer science, and related fields.

Dr. Tao Ma
Prof. Dr. Xiangping Guo
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. Agriculture 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

  • precision irrigation systems
  • smart irrigation
  • agricultural modeling
  • soil water movement
  • drought
  • soil salinity
  • evapotranspiration
  • remote sensing
  • artificial intelligence
  • climate-resilient agriculture

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Published Papers (2 papers)

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Research

21 pages, 3274 KB  
Article
Enhanced SWAP Model for Simulating Evapotranspiration and Cotton Growth Under Mulched Drip Irrigation in the Manas River Basin
by Shuo Zhang, Tian Gao, Rui Sun, Muhammad Arsalan Farid, Chunxia Wang, Ping Gong, Yongli Gao, Xinlin He, Fadong Li, Yi Li, Lianqing Xue and Guang Yang
Agriculture 2025, 15(20), 2178; https://doi.org/10.3390/agriculture15202178 - 21 Oct 2025
Viewed by 286
Abstract
Model-based simulation of farmland evapotranspiration and crop growth facilitates precise monitoring of crop and farmland dynamics with high efficiency, real-time responsiveness, and continuity. However, there are still significant limitations in using crop models to simulate the dynamic process of evapotranspiration and cotton growth [...] Read more.
Model-based simulation of farmland evapotranspiration and crop growth facilitates precise monitoring of crop and farmland dynamics with high efficiency, real-time responsiveness, and continuity. However, there are still significant limitations in using crop models to simulate the dynamic process of evapotranspiration and cotton growth in mulched drip-irrigated cotton fields under different irrigation gradients. The SWAP crop growth model effectively simulates crop growth. However, the original SWAP model lacks a dedicated module to consider the impact of mulching on cotton field evapotranspiration and cotton dry matter mass. Therefore, in this study, the source codes of the soil moisture, evapotranspiration, and crop growth modules of the SWAP model were improved. The evapotranspiration and cotton growth data of the mulched drip-irrigated cotton fields under three irrigation treatments (W1 = 3360 m3·hm−2, W2 = 4200 m3·hm−2, and W3 = 5040 m3·hm−2) in 2023 and 2024 at the Xinjiang Modern Water-saving Irrigation Key Experimental Station of the Corps were used to verify the simulation accuracy of the improved SWAP model. Research shows the following: (1) The average relative errors of the simulated evapotranspiration, leaf area index, and dry matter weight of cotton in the improved SWAP crop growth model are all <20% compared with the measured values. The root means square errors of the three treatments (W1, W2, and W3) ranged from 0.85 to 1.38 mm, from 0.03 to 0.18 kg·hm−2, and 55.01 to 69 kg·hm−2, respectively. The accuracy of the improved model in simulating evapotranspiration and cotton growth in the mulched cotton field increased by 37.49% and 68.25%, respectively. (2) The evapotranspiration rate of cotton fields is positively correlated with the irrigation water volume and is most influenced by meteorological factors such as temperature and solar radiation. During the flowering stage, evapotranspiration accounted for 62.83%, 62.09%, 61.21%, 26.46%, 40.01%, and 38.8% of the total evapotranspiration. Therefore, the improved SWAP model can effectively simulate the evaporation and transpiration of the mulched drip-irrigated cotton fields in the Manas River Basin. This study provides a scientific basis for the digital simulation of mulched farmland in the arid regions of Northwest China. Full article
(This article belongs to the Special Issue Modeling as a Tool to Explore Sustainable Irrigation Practices in Agriculture)
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22 pages, 2452 KB  
Article
A Farm-Scale Water Balance Assessment of Various Rice Irrigation Strategies Using a Bucket-Model Approach in Spain
by Sílvia Cufí, Gerard Arbat, Jaume Pinsach, Blanca Cuadrado-Alarcón, Arianna Facchi, Josep M. Villar, Farida Dechmi and Francisco Ramírez de Cartagena
Agriculture 2025, 15(19), 2089; https://doi.org/10.3390/agriculture15192089 - 7 Oct 2025
Viewed by 500
Abstract
Making effective decisions about scaling up on-farm irrigation practices to the district level requires a comprehensive assessment of irrigation management at the farm level. In this context, a bucket-type water mass balance model was developed, calibrated, and validated over five irrigation seasons on [...] Read more.
Making effective decisions about scaling up on-farm irrigation practices to the district level requires a comprehensive assessment of irrigation management at the farm level. In this context, a bucket-type water mass balance model was developed, calibrated, and validated over five irrigation seasons on a 121-hectare rice farm located in the lower Ter River valley (north-east Spain), to assess the water use efficiency and the impact of different irrigation practices on water savings. The model was implemented considering the spatial variability of the soils within the farm. It showed a satisfactory performance in both the calibration (2020, 2021, 2022) and validation (2023, 2024) cropping seasons, with NSE values greater than 0.50, PBIAS lower than ±20%, and RSR lower than 0.70. After model validation, the simulation of alternative water management practices revealed that the 10-day fixed-turn irrigation reduced irrigation water use by 30% compared to the traditional water management, although it may negatively impact rice yield. Simulations of an early irrigation cut-off at the end of the season and dry seeding with delayed flooding accounted for 17% and 15% irrigation water savings, respectively. The implementation of the no-runoff practice only accounted for a 6% reduction in water use. The water-saving potential of the simulated strategies was mainly driven by shortening the flooded period of rice paddies, thus demonstrating that managing the ponding water level is critical to diminishing water use in rice irrigation. Full article
(This article belongs to the Special Issue Modeling as a Tool to Explore Sustainable Irrigation Practices in Agriculture)
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