Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.3
3.6
Journals
Agriculture
Special Issues
Modeling as a Tool to Explore Sustainable Irrigation Practices in...
share announcement

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: 5 July 2026 | Viewed by 5509

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 250 words) can be sent to the Editorial Office for assessment.

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

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (6 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

41 pages, 12036 KB  
Article
Return Flow Compensation Reshapes Water Savings and Carbon–Water Synergy in Cold-Region Paddy Systems
by Jing Wang, Ennan Zheng, Tao Liu, Zhe Xing and Zhenjiang Si
Agriculture 2026, 16(9), 1002; https://doi.org/10.3390/agriculture16091002 - 2 May 2026
Viewed by 1044
Abstract
Non-flooding irrigation is widely promoted as a carbon–water co-benefit strategy in paddy rice, but field-scale trials overlook return flow compensation within irrigation districts and therefore overstate water-saving potential. To reconcile this scale mismatch, we developed a semi-distributed multi-scale water balance model coupled with [...] Read more.
Non-flooding irrigation is widely promoted as a carbon–water co-benefit strategy in paddy rice, but field-scale trials overlook return flow compensation within irrigation districts and therefore overstate water-saving potential. To reconcile this scale mismatch, we developed a semi-distributed multi-scale water balance model coupled with a carbon footprint and full-component blue–green–grey water footprint framework and applied it across field, district, and provincial scales in Heilongjiang Province—a leading cold-region japonica rice region in Northeast China—using the Qinglongshan Irrigation District on the Sanjiang Plain as the focal case, supported by two growing seasons of field observations and 35 years of provincial records. Under alternate wetting and drying, apparent field-level water savings of 50–60% converge to 33% after return flow correction, implying that field-based indicators overestimate savings by 40–50%. Carbon mitigation is decoupled from water volume: CH4 suppression dominates total abatement and is governed by drying frequency rather than water saved. At the provincial scale, the water footprint has shifted from grey- to blue-water dominance, suggesting that blue-water efficiency now represents a principal remaining lever for further cold-region carbon–water co-benefits. Two-season coverage and fixed parameter assumptions affect magnitudes but not directions. Water-saving irrigation in cold-region paddy systems should therefore be evaluated at the district scale where data permit, rather than relying solely on field-scale indicators. Full article
(This article belongs to the Special Issue Modeling as a Tool to Explore Sustainable Irrigation Practices in Agriculture)
►▼ Show Figures

Figure 1

20 pages, 7310 KB  
Article
Effects of Fenlong-Ridging Deep Tillage on Soil Water and Salt Transport Under Brackish Water Irrigation
by Ningyi Fang, Genxiang Feng, Chengli Zhu, Baoping Feng, Peng Li, Hongyu Ren and Hualei Yang
Agriculture 2026, 16(7), 745; https://doi.org/10.3390/agriculture16070745 - 27 Mar 2026
Viewed by 457
Abstract
Soil salinization and water scarcity pose critical threats to agricultural sustainability. Therefore, investigating the impacts of tillage practices and brackish water irrigation on the dynamic changes in soil water and salt is of great significance. To investigate the effects of fenlong-ridging deep tillage [...] Read more.
Soil salinization and water scarcity pose critical threats to agricultural sustainability. Therefore, investigating the impacts of tillage practices and brackish water irrigation on the dynamic changes in soil water and salt is of great significance. To investigate the effects of fenlong-ridging deep tillage (FL) on soil water and salt distribution under brackish water irrigation, indoor soil column experiments were conducted comparing FL and conventional tillage (CT) across three irrigation water salinity conditions (0, 3, and 5 g·L−1). The dynamic changes in soil moisture content and electrical conductivity (EC) were measured. The HYDRUS-2D model was used to simulate transport processes under varying FL depths (40/60/80/100 cm). Results indicated that compared with CT, FL can promote water infiltration. Furthermore, FL obviously reduced EC in the 0–50 cm layer compared to CT. Simulations confirmed that increasing FL depth enhanced desalination. Notably, irrigation with 3 g·L−1 brackish water yielded higher EC reduction rates (26.04–30.12%) than 5 g·L−1 water. The combination of 3 g·L−1 salinity and 60 cm FL depth proved most effective; the soil electrical conductivity decreased by 28.28%. This study offers a feasible technical solution for the sustainable utilization of brackish water resources and the amelioration of saline soils. Full article
(This article belongs to the Special Issue Modeling as a Tool to Explore Sustainable Irrigation Practices in Agriculture)
►▼ Show Figures

Figure 1

26 pages, 9000 KB  
Article
Dynamic Quantification and Prediction of Salt Tolerance Threshold in Summer Maize Under Different Regimes of Brackish Water Irrigation
by Suhan Peng, Tao Ma, Jiao Liu, Zang Zhong, Hetong Wang, Qiwei Jiang, Sackelia Fayiah Willie and Wanli Xu
Agriculture 2026, 16(5), 495; https://doi.org/10.3390/agriculture16050495 - 24 Feb 2026
Viewed by 460
Abstract
To investigate how different training modes of salt stress priming affect the dynamic variation of the salt tolerance threshold (STT) in summer maize, a micro-plot experiment with staged brackish water irrigation was conducted. Based on physiological and biochemical parameters, along with shoot and [...] Read more.
To investigate how different training modes of salt stress priming affect the dynamic variation of the salt tolerance threshold (STT) in summer maize, a micro-plot experiment with staged brackish water irrigation was conducted. Based on physiological and biochemical parameters, along with shoot and root traits, a dynamic salt tolerance coefficient (αSTT) was defined to quantify STT across growth stages. The results revealed a clear two-stage adaptive response to salt stress, consisting of an initial physiological adaptation phase followed by a phenotypic adaptation phase. Different training modes induced distinct salt stress memory effects by regulating the coordination between these two stages. Among treatments, the S1-2-3 regime—corresponding to mild (2.0 g·L−1), moderate (4.0 g·L−1), and severe (6.0 g·L−1) salinity applied sequentially at the six-leaf, ten-leaf, and tasseling stages—exhibited the most favorable adaptive outcome, with αSTT gradually recovering to 1.0 at later stages and a concomitantly higher STT. Furthermore, a unified predictive framework was established to estimate STT dynamics, within which the process-constrained PCR-STP pathway outperformed purely data-driven pathways. Overall, our study elucidates the dynamic nature of salt tolerance in summer maize and provides a scientific basis for optimizing brackish water irrigation regimes and refining salt stress modules in crop models. Full article
(This article belongs to the Special Issue Modeling as a Tool to Explore Sustainable Irrigation Practices in Agriculture)
►▼ Show Figures

Figure 1

17 pages, 2735 KB  
Article
Modeling Soil Salinity Dynamics in Paddy Fields Under Long-Term Return Flow Irrigation in the Yinbei Irrigation District
by Hangyu Guo, Chao Shi, Alimu Abulaiti, Hongde Wang and Xiaoqin Sun
Agriculture 2026, 16(2), 222; https://doi.org/10.3390/agriculture16020222 - 15 Jan 2026
Viewed by 441
Abstract
The imbalance between water supply and demand in the arid and semi-arid regions of northwest China has become increasingly severe, highlighting the urgent need to develop and utilize unconventional water resources. Return flow, originating from canal leakage and field drainage, is widely distributed [...] Read more.
The imbalance between water supply and demand in the arid and semi-arid regions of northwest China has become increasingly severe, highlighting the urgent need to develop and utilize unconventional water resources. Return flow, originating from canal leakage and field drainage, is widely distributed in these regions. However, as it contains a certain amount of salts, long-term use of return flow can lead to soil salinization and degradation of soil structure. Therefore, the scientific utilization of return flow has become a key issue for achieving sustainable agricultural development and efficient water use in arid areas. This study was conducted in the Yinbei Irrigation District, Ningxia, northwest China. Water samples were collected from the main and branch drainage ditches and analyzed to evaluate the feasibility of using return flow irrigation in the area. In addition, based on two years of continuous field monitoring and HYDRUS model simulations, the long-term dynamics of soil salinity under moderate return flow irrigation over the next 20 years were predicted. The results show that the total salinity of the main return ditches consistently remained below the agricultural irrigation water quality standard of 2000 mg/L, with Na+ and SO42− as the predominant ions. Seasonal variations in return flow salinity were notable, with higher levels observed in spring compared to summer. Simulation results based on field trial data indicated that soil salinity displayed regular seasonal fluctuations. During the rice-growing season, strong leaching kept the salinity in the plough layer (0–40 cm) low. However, after irrigation ceased, evaporation in autumn and winter led to an increase in surface soil salinity, creating annual peaks. Long-term simulations showed that soil salinity throughout the entire profile (0–100 cm) followed a pattern of “slight increase—gradual decrease—dynamic stability.” Specifically, winter salinity peaks slightly increased during the first two years but then gradually declined, stabilizing after approximately 15 years. This indicates that long-term return-flow irrigation does not result in the accumulation of soil salinity in the plough layer. Full article
(This article belongs to the Special Issue Modeling as a Tool to Explore Sustainable Irrigation Practices in Agriculture)
►▼ Show Figures

Figure 1

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
Cited by 1 | Viewed by 1113
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)
►▼ Show Figures

Figure 1

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
Cited by 1 | Viewed by 1300
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)
►▼ Show Figures

Graphical abstract

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-6
Back to TopTop