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Agronomy
Volume 16
Issue 6
10.3390/agronomy16060639
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Article

Integrating GLASS LAI into the SWAT Model for Improved Hydrological Simulation in Semi-Arid Regions

by
Xun Zhang
1,
Yanan Jiang
1,2,3,4,*,
Ting Yan
1,
Kun Xie
1,
Ping Li
1,2,*,
Jiping Niu
1,2,*,
Kexin Li
1 and
Xiaojun Wang
5,6
1
College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China
2
Key Laboratory of Arid Agricultural Soil and Water Engineering of Ministry of Education, Northwest A&F University, Yangling 712100, China
3
Xinjiang Research Institute of Agriculture in Arid Areas, Urumqi 830091, China
4
Shaanxi Belt and Road Joint Laboratory of Dryland Biological Resources and Green Smart Agriculture, Northwest A&F University, Yangling 712100, China
5
National Key Laboratory of Water Disaster Prevention, Nanjing Hydraulic Research Institute, Nanjing 210029, China
6
Research Center for Climate Change, Ministry of Water Resources, Nanjing 210029, China
*
Authors to whom correspondence should be addressed.
Agronomy 2026, 16(6), 639; https://doi.org/10.3390/agronomy16060639
Submission received: 31 January 2026 / Revised: 27 February 2026 / Accepted: 16 March 2026 / Published: 18 March 2026
(This article belongs to the Topic Remote Sensing Research and Application of Agricultural Drought and Water Management)
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Abstract

The Soil and Water Assessment Tool (SWAT) model has been widely used to simulate ecohydrological processes in watersheds. However, the SWAT model uses a simplified Environmental Policy Impact Climate (EPIC) model to simulate the leaf area index (LAI), creating a critical gap in accurately simulating evapotranspiration (ET) and runoff in semi-arid regions. This work aims to fill this gap by modifying the SWAT source code to integrate high-resolution Global Land Surface Satellite (GLASS) leaf area index (LAI) data. The modified version was applied to the semi-arid Wuding River Basin and calibrated using a Fortran-based dynamic dimension search (DDS) algorithm. The results show a relatively significant improvement in the accuracy of the daily-scale runoff simulation (R2 from 0.52 to 0.71 and NSE from 0.52 to 0.7 for the calibration period, and R2 from 0.21 to 0.58 and NSE from 0.2 to 0.51 for the validation period). The improved version also corrects the unrealistic default LAI peak (from >5.0 to 1.5–3.0), correcting the multi-year average ET from 251.7 mm to 341.8 mm. The improved vegetation growth module of the SWAT model effectively improved the accuracy of hydrologic simulation in the semi-arid region and enhanced the structural robustness of SWAT for water management.
Keywords: runoff; SWAT; GLASS LAI; vegetation dynamics runoff; SWAT; GLASS LAI; vegetation dynamics

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MDPI and ACS Style

Zhang, X.; Jiang, Y.; Yan, T.; Xie, K.; Li, P.; Niu, J.; Li, K.; Wang, X. Integrating GLASS LAI into the SWAT Model for Improved Hydrological Simulation in Semi-Arid Regions. Agronomy 2026, 16, 639. https://doi.org/10.3390/agronomy16060639

AMA Style

Zhang X, Jiang Y, Yan T, Xie K, Li P, Niu J, Li K, Wang X. Integrating GLASS LAI into the SWAT Model for Improved Hydrological Simulation in Semi-Arid Regions. Agronomy. 2026; 16(6):639. https://doi.org/10.3390/agronomy16060639

Chicago/Turabian Style

Zhang, Xun, Yanan Jiang, Ting Yan, Kun Xie, Ping Li, Jiping Niu, Kexin Li, and Xiaojun Wang. 2026. "Integrating GLASS LAI into the SWAT Model for Improved Hydrological Simulation in Semi-Arid Regions" Agronomy 16, no. 6: 639. https://doi.org/10.3390/agronomy16060639

APA Style

Zhang, X., Jiang, Y., Yan, T., Xie, K., Li, P., Niu, J., Li, K., & Wang, X. (2026). Integrating GLASS LAI into the SWAT Model for Improved Hydrological Simulation in Semi-Arid Regions. Agronomy, 16(6), 639. https://doi.org/10.3390/agronomy16060639

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