Modeling Comprehensive Deficit Irrigation Strategies for Drip-Irrigated Cotton Using AquaCrop

Yalong Du, Qiuping Fu, Pengrui Ai, Yingjie Ma () and Yang Pan
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Yalong Du: College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, China
Qiuping Fu: College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, China
Pengrui Ai: College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, China
Yingjie Ma: College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, China
Yang Pan: College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, China

Agriculture, 2024, vol. 14, issue 8, 1-24

Abstract: The development of a crop production strategy through the use of a crop model represents a crucial method for the assurance of a stable agricultural yield and the subsequent enhancement thereof. There are currently no studies evaluating the suitability of the AquaCrop model for the drip irrigation of Gossypium barbadense in Southern Xinjiang, which is the primary planting region for Gossypium barbadense in China. In order to investigate the performance of the AquaCrop model in simulating the growth of cotton under mulched drip irrigation, the model was locally calibrated and validated according to different irrigation thresholds during a key growth period of two years. The results of the simulation for total soil water (TSW), crop evapotranspiration (ET c ), canopy coverage (CC), aboveground biomass (Bio), and seed cotton yield demonstrated a high degree of correlation with the observed data, with a root mean square error (RMSE) of <11.58%. The Bio and yield simulations demonstrated a high degree of concordance with the corresponding measured values, with root mean square error (RMSE) values of 1.23 t ha −1 and 0.15 t ha −1 , respectively. However, the predicted yield declined in the verification year, though the prediction error remained below 15%. Furthermore, the estimated evapotranspiration (ET c ) value demonstrated a slight degree of overestimation. Generally, the middle and late stages of cotton growth led to an overestimation of the TSW content. However, the prediction error was less than 13.99%. Through the calculation of each performance index of the AquaCrop model, it is found that they are in the acceptable range. In conclusion, the AquaCrop model can be employed as a viable tool for predicting the water response of cotton to drip irrigation under mulched film in Southern Xinjiang. Based on 64 years of historical meteorological data, three years were selected as scenarios for simulation. Principal component analysis (PCA) showed that, in a local wet year in Southern Xinjiang, the irrigation quota was 520 mm, and the irrigation cycle was 6 days/time. In normal years, the irrigation quota was 520 mm, with an irrigation cycle of 6 days/time. In dry years, the irrigation quota was 595 mm, with an irrigation cycle of 10 days/time. This allowed for higher seed cotton yields and irrigation water productivity, as well as the maximization of cotton yields and net revenue in the arid oasis area of Southern Xinjiang.

Keywords: soil moisture stress; cotton; AquaCrop; scenario year; PCA (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: 2024
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