Enhanced SWAP Model for Simulating Evapotranspiration and Cotton Growth Under Mulched Drip Irrigation in the Manas River Basin

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 ()
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Shuo Zhang: College of Water and Architectural Engineering, Shihezi University, Shihezi 832003, China
Tian Gao: College of Water and Architectural Engineering, Shihezi University, Shihezi 832003, China
Rui Sun: Key Laboratory of Cold and Arid Regions Eco-Hydraulic Engineering of Xinjiang Production & Construction Corps, Shihezi 832000, China
Muhammad Arsalan Farid: College of Water and Architectural Engineering, Shihezi University, Shihezi 832003, China
Chunxia Wang: College of Water and Architectural Engineering, Shihezi University, Shihezi 832003, China
Ping Gong: College of Water and Architectural Engineering, Shihezi University, Shihezi 832003, China
Yongli Gao: Department of Earth and Planetary Sciences, University of Texas, San Antonio, TX 78249, USA
Xinlin He: College of Water and Architectural Engineering, Shihezi University, Shihezi 832003, China
Fadong Li: Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Yi Li: College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China
Lianqing Xue: College of Hydrology and Water Resources, Hohai University, Nanjing 210024, China
Guang Yang: College of Water and Architectural Engineering, Shihezi University, Shihezi 832003, China

Agriculture, 2025, vol. 15, issue 20, 1-21

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 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 m 3 ·hm −2 , W2 = 4200 m 3 ·hm −2 , and W3 = 5040 m 3 ·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.

Keywords: evapotranspiration in cotton fields; drip irrigation with plastic; improved SWAP models; cotton (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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