Cui et al. (2025) Optimizing deficit mulched drip irrigation improves grain crop yield and water productivity in global cropland

Identification

• Journal: Agricultural Water Management
• Year: 2025
• Date: 2025-11-21
• Authors: Ningbo Cui, Runtong Li, Shenglin Wen, Zongjun Wu, Daozhi Gong, Yaosheng Wang, Chunwei Liu, Qingyan He, Liwen Xing, Yixuan Zhang, Zhihui Wang
• DOI: 10.1016/j.agwat.2025.109994

Research Groups

• State Key Laboratory of Hydraulics and Mountain River Engineering & College of Water Resource and Hydropower, Sichuan University, Chengdu, China
• Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing, China
• Jiangsu Key Laboratory of Agricultural and Ecological Meteorology, Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration (ECSS-CMA), School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, China
• Sichuan Academy of Agricultural Machinery Sciences, Chengdu, China

Short Summary

This global meta-analysis of 1071 field observations reveals that optimizing deficit mulched drip irrigation (DMDI) can reduce grain crop yield reduction risk and significantly increase water productivity by 8.5% compared to full mulched drip irrigation, with specific management practices and environmental conditions identified as key drivers for improved performance.

Objective

• Evaluate the effects of Deficit Mulched Drip Irrigation (DMDI) on grain crop yield and water productivity (WP).
• Investigate and quantify how management practices, climatic conditions, and soil properties influence grain crop yield and WP under DMDI.
• Identify key driving factors for improving grain crop yield and WP under DMDI and determine optimal DMDI management strategies.

Study Configuration

• Spatial Scale: Global cropland, synthesizing data from 66 published studies with sampling sites worldwide, predominantly from Asia.
• Temporal Scale: Synthesis of 1071 field observations from various published studies, covering diverse experimental durations.

Methodology and Data

• Models used: Meta-analysis (random effects model), Random Forest (RF) modeling, Structural Equation Modeling (SEM).
• Data sources: 1071 paired field observations collected from 66 peer-reviewed publications (English and Chinese) from databases including Science Direct, Google Scholar, Baidu Scholar, and China National Knowledge Internet (CNKI). Data included grain crop yield, actual crop evapotranspiration (ET), and water productivity (WP).

Main Results

• Deficit Mulched Drip Irrigation (DMDI) significantly increased water productivity (WP) by 8.5% (95% CI: 5.6%–11.5%) and decreased evapotranspiration (ET) by 24.2% (95% CI: −27.2% to −21.2%) compared to full mulched drip irrigation (FMDI), while reducing the risk of grain crop yield reduction.
• Mean Annual Precipitation (MAP), water deficit degree, and emitter flow rate were identified as the main drivers for grain crop yield under DMDI.
• Mulch method, MAP, and deficit timing were the key driving factors for WP.
• Structural Equation Modeling (SEM) revealed that management practices had direct effects on grain crop yield (standard path coefficient = 0.22, p < 0.001) and WP (0.07). Climatic conditions showed direct effects on yield (0.15, p < 0.001) and WP (0.42, p < 0.001), while soil properties had direct effects on yield (0.24, p < 0.001) and WP (0.21, p < 0.001).
• Optimal DMDI management strategies include:
  • Low deficit degree (80–100% of FMDI irrigation amount) to mitigate yield reduction and improve WP by 5.3%.
  • Applying DMDI during specific growth stages rather than the whole season.
  • Adopting plastic flat mulching, which increased WP by 14.1% and 15.7% respectively, with minimal yield reduction.
  • Nitrogen fertilizer rates ≥200 kg ha−1, plant density >10 plants m−2, and emitter flow rates <2.5 L h−1 were more beneficial.
• DMDI is most appropriate for regions with MAP > 250 mm and loamy soils with soil bulk density (SBD) ≤1.4 g cm−3 and soil organic carbon content (SOC) > 10 g kg−1.

Contributions

• First comprehensive global meta-analysis to systematically investigate the effects of deficit mulched drip irrigation (DMDI) on grain crop yield and water productivity (WP) under various management practices, climatic conditions, and soil properties.
• Quantifies the relative importance of different factors influencing DMDI effectiveness and identifies key driving factors.
• Provides theoretical and technical support for optimizing DMDI strategies to collaboratively improve grain crop yield and WP.
• Highlights the need for crop-specific deficit irrigation strategies and raises awareness about the long-term environmental sustainability of plastic mulching.

Funding

• National Key Research and Development Program of China (2022YFD1900805)
• National Natural Science Foundation of China (52279041, 51922072)
• Innovations in Technology Research and Development Project of Chengdu Science and Technology Bureau (2022-YF05–01008-SN)
• Sichuan Science and Technology Program (2023NZZJ0015, 2022YFN0021, 2022YF00066)
• The Fundamental Research Funds for the Central Universities (2023SCU12121, 2020CDDZ-19)

Citation

@article{Cui2025Optimizing,
  author = {Cui, Ningbo and Li, Runtong and Wen, Shenglin and Wu, Zongjun and Gong, Daozhi and Wang, Yaosheng and Liu, Chunwei and He, Qingyan and Xing, Liwen and Zhang, Yixuan and Wang, Zhihui},
  title = {Optimizing deficit mulched drip irrigation improves grain crop yield and water productivity in global cropland},
  journal = {Agricultural Water Management},
  year = {2025},
  doi = {10.1016/j.agwat.2025.109994},
  url = {https://doi.org/10.1016/j.agwat.2025.109994}
}