High-Resolution Monitoring and Assessment of Evapotranspiration and Gross Primary Production Using Remote Sensing in a Typical Arid Region

Junxia Yan, Yanfei Ma, Dongyun Zhang, Zechen Li, Weike Zhang, Zhenhua Wu, Hui Wang and Lihua Wen
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Junxia Yan: College of Resource and Environment Sciences/Hebei Technology Innovation Center for Remote Sensing Identification of Environmental Change, Hebei Normal University, Shijiazhuang 050024, Hebei, China
Yanfei Ma: Department of Geography, Handan College, Handan 056005, Hebei, China
Dongyun Zhang: Department of Geography, Handan College, Handan 056005, Hebei, China
Zechen Li: College of Sciences, Harbin University of Science and Technology, Harbin 150080, Heilongjiang, China
Weike Zhang: Department of Geography, Handan College, Handan 056005, Hebei, China
Zhenhua Wu: Department of Geography, Handan College, Handan 056005, Hebei, China
Hui Wang: Department of Geography, Handan College, Handan 056005, Hebei, China
Lihua Wen: Department of Geography, Handan College, Handan 056005, Hebei, China

Land, 2021, vol. 10, issue 4, 1-27

Abstract: Land surface evapotranspiration (ET) and gross primary productivity (GPP) are critical components in terrestrial ecosystems with water and carbon cycles. Large-scale, high-resolution, and accurately quantified ET and GPP values are important fundamental data for freshwater resource management and help in understanding terrestrial carbon and water cycles in an arid region. In this study, the revised surface energy balance system (SEBS) model and MOD17 GPP algorithm were used to estimate daily ET and GPP at 100 m resolution based on multi-source satellite remote sensing data to obtain surface biophysical parameters and meteorological forcing data as input variables for the model in the midstream oasis area of the Heihe River Basin (HRB) from 2010 to 2016. Then, we further calculated the ecosystem water-use efficiency (WUE). We validated the daily ET, GPP, and WUE from ground observations at a crop oasis station and conducted spatial intercomparisons of monthly and annual ET, GPP, and WUE at the irrigation district and cropland oasis scales. The site-level evaluation results show that ET and GPP had better performance than WUE at the daily time scale. Specifically, the deviations in the daily ET, GPP, and WUE data compared with ground observations were small, with a root mean square error (RMSE) and mean absolute percent error (MAPE) of 0.75 mm/day and 26.59%, 1.13 gC/m 2 and 36.62%, and 0.50 gC/kgH 2 O and 39.83%, respectively. The regional annual ET, GPP, and WUE varied from 300 to 700 mm, 200 to 650 gC/m 2 , and 0.5 to 1.0 gC/kgH 2 O, respectively, over the entire irrigation oasis area. It was found that annual ET and GPP were greater than 550 mm and 500 gC/m 2 , and annual oasis cropland WUE had strong invariability and was maintained at approximately 0.85 gC/kgH 2 O. The spatial intercomparisons from 2010 to 2016 revealed that ET had similar spatial patterns to GPP due to tightly coupled carbon and water fluxes. However, the WUE spatiotemporal patterns were slightly different from both ET and GPP, particularly in the early and late growing seasons for the oasis area. Our results demonstrate that spatial full coverage and reasonably fine spatiotemporal variation and variability could significantly improve our understanding of water-saving irrigation strategies and oasis agricultural water management practices in the face of water shortage issues.

Keywords: evapotranspiration (ET); gross primary productivity (GPP); cropland WUE; remote sensing model; irrigation water management; data fusion; agriculture monitoring; arid region (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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