Innovative synergistic optimization of drip irrigation and subsurface drainage for alleviating salinization and improving crop productivity in arid irrigation district

Drip irrigation, as a core water-saving technology in arid regions, holds great potential for improving agricultural water productivity, but its effectiveness is often constrained by soil salinization and improper coordination with drainage systems. This study introduces a synergistic framework combining drip irrigation and subsurface drainage to enhance water productivity and reduce root-zone salinity in the Kaidu River Irrigation District, China. The SWAT-Salt model, calibrated and validated with hydrological, salinity, and crop data, was used to simulate water-salt dynamics under drip irrigation. A projection pursuit model coupled with an accelerated genetic algorithm was applied to assess 252 scenarios, focusing on drip irrigation intervals (5–14 d), winter leaching depths (150–450 mm), and subsurface drainage parameters (depth: 1.0–2.0 m; spacing: 10–100 m). Results highlighted significant spatial variability in optimal drip irrigation frequencies, increasing from upstream to downstream: 9 d intervals for wheat, 7 d intervals for maize, and 7–10 d intervals for tomato and pepper in southern regions with higher percolation rates. Optimized drip irrigation, when synergized with tailored drainage, enhanced crop yields by 8.7 %-10.1 % for wheat, 12.6 %-16.8 % for maize, 6.7 %-11.6 % for tomato, and 11.4 %-14.5 % for pepper. Drip irrigation optimization reduced deep percolation losses, improved water productivity by 4.0 %-11.7 %, and, combined with drainage, decreased soil electrical conductivity by 13.3 %-19.3 %. Economic benefits increased by 1530–6450 yuan ha⁻¹ , driven by improved drip irrigation efficiency and salt leaching effectiveness. This study demonstrates that precision drip irrigation tailored to crop type, soil texture, and salinity conditions, when integrated with subsurface drainage, is critical for sustainable agriculture in arid saline regions. The proposed framework provides actionable strategies for optimizing drip irrigation management to balance water conservation, salinization mitigation, and productivity gains. • Optimized drip irrigation and drainage reduces soil salinity by 19.3 %. • Optimized drip irrigation intervals lead to 6.7–16.8 % yield increase across crops. • Cost-effective irrigation yield up to 6450 yuan ha⁻¹ in economic returns. • A model-based framework for multi-objective irrigation optimization was developed.

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Publication Details

Journal
Agricultural Water Management
Published
2025-12-19
DOI
https://doi.org/10.1016/j.agwat.2025.110089
Primary Topic
Irrigation Practices and Water Management
Type
article
Field-Weighted Citation Impact
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article

Innovative synergistic optimization of drip irrigation and subsurface drainage for alleviating salinization and improving crop productivity in arid irrigation district

Donglin Jiang, Javlonbek Ishchanov, Wenzhi Zeng, Chang Ao et al.
Agricultural Water Management
Irrigation Practices and Water Management
article

Innovative synergistic optimization of drip irrigation and subsurface drainage for alleviating salinization and improving crop productivity in arid irrigation district

Donglin Jiang, Javlonbek Ishchanov, Wenzhi Zeng, Chang Ao, Zhen Li, Yi Liu
article en

Abstract

Drip irrigation, as a core water-saving technology in arid regions, holds great potential for improving agricultural water productivity, but its effectiveness is often constrained by soil salinization and improper coordination with drainage systems. This study introduces a synergistic framework combining drip irrigation and subsurface drainage to enhance water productivity and reduce root-zone salinity in the Kaidu River Irrigation District, China. The SWAT-Salt model, calibrated and validated with hydrological, salinity, and crop data, was used to simulate water-salt dynamics under drip irrigation. A projection pursuit model coupled with an accelerated genetic algorithm was applied to assess 252 scenarios, focusing on drip irrigation intervals (5–14 d), winter leaching depths (150–450 mm), and subsurface drainage parameters (depth: 1.0–2.0 m; spacing: 10–100 m). Results highlighted significant spatial variability in optimal drip irrigation frequencies, increasing from upstream to downstream: 9 d intervals for wheat, 7 d intervals for maize, and 7–10 d intervals for tomato and pepper in southern regions with higher percolation rates. Optimized drip irrigation, when synergized with tailored drainage, enhanced crop yields by 8.7 %-10.1 % for wheat, 12.6 %-16.8 % for maize, 6.7 %-11.6 % for tomato, and 11.4 %-14.5 % for pepper. Drip irrigation optimization reduced deep percolation losses, improved water productivity by 4.0 %-11.7 %, and, combined with drainage, decreased soil electrical conductivity by 13.3 %-19.3 %. Economic benefits increased by 1530–6450 yuan ha⁻¹ , driven by improved drip irrigation efficiency and salt leaching effectiveness. This study demonstrates that precision drip irrigation tailored to crop type, soil texture, and salinity conditions, when integrated with subsurface drainage, is critical for sustainable agriculture in arid saline regions. The proposed framework provides actionable strategies for optimizing drip irrigation management to balance water conservation, salinization mitigation, and productivity gains. • Optimized drip irrigation and drainage reduces soil salinity by 19.3 %. • Optimized drip irrigation intervals lead to 6.7–16.8 % yield increase across crops. • Cost-effective irrigation yield up to 6450 yuan ha⁻¹ in economic returns. • A model-based framework for multi-objective irrigation optimization was developed.

Agricultural Water ManagementVol. 323
Hohai University (CN), Wuhan University (CN), Tashkent Institute of Irrigation and Agricultural Mechanization Engineers (UZ), Yangzhou University (CN)
Openalex Percentile: Top 51%
Irrigation Practices and Water Management
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