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Informing the SWAT model with remote sensing detected vegetation phenology for improved modeling of ecohydrological processes

Chen, Shouzhi (författare)
Beijing Normal University
Fu, Yongshuo H. (författare)
Beijing Normal University,University of Antwerp
Wu, Zhaofei (författare)
Beijing Normal University
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Hao, Fanghua (författare)
Beijing Normal University
Hao, Zengchao (författare)
Beijing Normal University
Guo, Yahui (författare)
Beijing Normal University
Geng, Xiaojun (författare)
Beijing Normal University
Li, Xiaoyan (författare)
Beijing Normal University
Zhang, Xuan (författare)
Beijing Normal University
Tang, Jing (författare)
Lund University,Lunds universitet,MERGE: ModElling the Regional and Global Earth system,Centrum för miljö- och klimatvetenskap (CEC),Naturvetenskapliga fakulteten,Institutionen för naturgeografi och ekosystemvetenskap,LTH profilområde: Aerosoler,LTH profilområden,Lunds Tekniska Högskola,Centre for Environmental and Climate Science (CEC),Faculty of Science,Dept of Physical Geography and Ecosystem Science,LTH Profile Area: Aerosols,LTH Profile areas,Faculty of Engineering, LTH,University of Copenhagen
Singh, Vijay P. (författare)
Texas A and M University
Zhang, Xuesong (författare)
USDA Hydrology and Remote Sensing Laboratory
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 (creator_code:org_t)
Elsevier BV, 2023
2023
Engelska.
Ingår i: Journal of Hydrology. - : Elsevier BV. - 0022-1694. ; 616
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • The Soil and Water Assessment Tool (SWAT) model has been widely applied for simulating the water cycle and quantifying the influence of climate change and anthropogenic activities on hydrological processes. A major uncertainty of SWAT stems from the poor representation of vegetation dynamics due to the use of a simplistic vegetation growth and development module. Using long-term remote sensing-based phenological data, the SWAT model's vegetation module was improved by adding a dynamic growth start date and the dynamic heat requirement for vegetation growth rather than using constant values. The new SWAT model was verified in the Han River basin, China, and found its performance was much improved in comparison with that of the original SWAT model. Specifically, the accuracy of the leaf area index (LAI) simulation improved notably (coefficient of determination (R2) increased by 0.193, Nash–Sutcliffe Efficiency (NSE) increased by 0.846, and percent bias decreased by 42.18 %), and that of runoff simulation improved modestly (R2 increased by 0.05 and NSE was similar). Additionally, it is found that the original SWAT model substantially underestimated evapotranspiration (Penman-Monteith method) in comparison with the new SWAT model (65.09 mm (or 22.17 %) for forests, 92.27 mm (or 32 %) for orchards, and 96.16 mm (or 36.4 %) for farmland), primarily due to the inaccurate representation of LAI dynamics. Our results suggest that an accurate representation of phenological dates in the vegetation growth module is important for improving the SWAT model performance in terms of estimating terrestrial water and energy balance.

Ämnesord

NATURVETENSKAP  -- Geovetenskap och miljövetenskap -- Oceanografi, hydrologi och vattenresurser (hsv//swe)
NATURAL SCIENCES  -- Earth and Related Environmental Sciences -- Oceanography, Hydrology and Water Resources (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Naturresursteknik -- Fjärranalysteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Environmental Engineering -- Remote Sensing (hsv//eng)

Nyckelord

LAI simulation
Runoff
SWAT modification
Vegetation phenology

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art (ämneskategori)
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