BESS-STAIR: a framework to estimate daily, 30m, and all-weather crop evapotranspiration using multi-source satellite data for the US Corn Belt

Jiang, Chongya; Guan, Kaiyu; Pan, Ming; Ryu, Youngryel; Peng, Bin; Wang, Sibo

doi:10.5194/hess-24-1251-2020

Title: BESS-STAIR: a framework to estimate daily, 30m, and all-weather crop evapotranspiration using multi-source satellite data for the US Corn Belt

Journal Article · 20 March 2020 · Hydrology and Earth System Sciences (Online)

DOI: https://doi.org/10.5194/hess-24-1251-2020 · OSTI ID:1616269

^[1]; Guan, Kaiyu ^[1]; Pan, Ming ^[2];

^[3]; Peng, Bin ^[1];

^[1]

Univ. of Illinois at Urbana-Champaign, IL (United States)
Princeton Univ., NJ (United States)
Seoul National Univ. (Korea, Republic of)

Abstract. With increasing crop water demands and drought threats, mapping andmonitoring of cropland evapotranspiration (ET) at high spatial and temporalresolutions become increasingly critical for water management andsustainability. However, estimating ET from satellites for precise waterresource management is still challenging due to the limitations in bothexisting ET models and satellite input data. Specifically, the process of ETis complex and difficult to model, and existing satellite remote-sensing datacould not fulfill high resolutions in both space and time. To address theabove two issues, this study presents a new high spatiotemporal resolution ETmapping framework, i.e., BESS-STAIR, which integrates a satellite-drivenwater–carbon–energy coupled biophysical model, BESS (Breathing Earth SystemSimulator), with a generic and fully automated fusion algorithm, STAIR(SaTallite dAta IntegRation). In this framework, STAIR provides daily 30'mmultispectral surface reflectance by fusing Landsat and MODIS satellite datato derive a fine-resolution leaf area index and visible/near-infrared albedo,all of which, along with coarse-resolution meteorological and CO₂ data, are used to drive BESS to estimate gap-free 30 m resolution daily ET.We applied BESS-STAIR from 2000 through 2017 in six areas across the US CornBelt and validated BESS-STAIR ET estimations using flux-tower measurementsover 12 sites (85 site years). Results showed that BESS-STAIR daily ETachieved an overall R2=0.75, with root mean square error RMSE=0.93 mm d^-1 and relative error RE =27.9 % when benchmarkedwith the flux measurements. In addition, BESS-STAIR ET estimations capturedthe spatial patterns, seasonal cycles, and interannual dynamics well indifferent sub-regions. The high performance of the BESS-STAIR frameworkprimarily resulted from (1) the implementation of coupled constraints onwater, carbon, and energy in BESS, (2) high-quality daily 30 m data from theSTAIR fusion algorithm, and (3) BESS's applicability under all-skyconditions. BESS-STAIR is calibration-free and has great potentials to be areliable tool for water resource management and precision agricultureapplications for the US Corn Belt and even worldwide given the globalcoverage of its input data.

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Research Organization:: Center for Advanced Bioenergy and Bioproducts Innovation (CABBI), Urbana, IL (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: SC0018420

OSTI ID:: 1616269

Journal Information:: Hydrology and Earth System Sciences (Online), Vol. 24, Issue 3; ISSN 1607-7938

Publisher:: European Geosciences Union (EGU)Copyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 18 works

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