Satellite data-driven modeling of field scale evapotranspiration in croplands using the MOD16 algorithm framework

Mingzhu He; John S. Kimball; Yonghong Yi; Steven W. Running; Kaiyu Guan; Alvaro Moreno; Xiaocui Wu; Marco Maneta

doi:10.1016/j.rse.2019.05.020

Satellite data-driven modeling of field scale evapotranspiration in croplands using the MOD16 algorithm framework

Mingzhu He
, John S. Kimball
, Yonghong Yi
, Steven W. Running
, Kaiyu Guan
, Alvaro Moreno
, Xiaocui Wu
, Marco Maneta

Research output: Contribution to journal › Article › peer-review

71 Scopus citations

Abstract

Evapotranspiration (ET) is a key variable linking the global water, carbon and energy cycles, while accurate ET estimates are crucial for understanding cropland water use in context with agricultural management. Satellite remote sensing provides spatially and temporally continuous information that can be used for global ET estimation. The NASA MODIS MOD16A2 operational product provides 500-m 8-day global ET estimates extending from 2001 to present. However, reliable estimates for delineating field level cropland ET patterns are lacking. In this investigation, we modified the MOD16 global algorithm to better represent cropland ET by calibrating model parameters according to C3 and C4 crop types, and incorporating finer scale satellite vegetation inputs to derive 30-m cropland ET estimates over the continental USA (CONUS). Similar overlapping enhanced vegetation index (EVI) records from Landsat and MODIS were used to generate a continuous 30-m 8-day fused EVI and ET record extending from 2008 to 2017 over CONUS croplands. The satellite-based ET estimates were compared with tower based ET observations over different crop types, and more traditional cropland actual ET (AET) estimates derived from reference ET and crop-specific coefficients. The new satellite based 30-m cropland ET estimates (ET_30m) corresponded favorably with both tower ET observations (ET_flux; R² = 0.69, RMSE = 0.70 mm d⁻¹, bias = 0.04 mm d⁻¹) and the baseline global MOD16A2 ET product (ET_MOD16). The ET_30m results also showed better performance against the ET_flux observations than ET_MOD16 (R² = 0.54, RMSE = 0.82 mm d⁻¹) or AET (R² = 0.52, RMSE = 2.47 mm d⁻¹) for monitoring CONUS croplands. The spatial and temporal patterns of the ET_30m results show enhanced delineation of agricultural water use, including impacts from variable climate, cropland area and diversity. The resulting ET_30m record is suitable for operational applications promoting more effective agricultural water management and food security.

Original language	English
Article number	111201
Journal	Remote Sensing of Environment
Volume	230
DOIs	https://doi.org/10.1016/j.rse.2019.05.020
State	Published - Sep 1 2019

Funding

This study was funded by USDA NIFA-AFRI and NASA programs ( 658 2016-67026-25067 , NNX14AI50G , NNX14A169G , 80NSSC18K0738 , NNX08AG87A ). This work used eddy covariance data acquired and shared by the FLUXNET community, including the AmeriFlux network. The MODIS Collection 6 MOD16A2, MCD43A3 and MCD12Q1 products were retrieved from the online Data Pool, courtesy of the NASA Land Processes Distributed Active Archive Center (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota, https://lpdaac.usgs.gov/data_access/data_pool . A portion of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA. © 2019. All rights reserved. This study was funded by USDA NIFA-AFRI and NASA programs (658 2016-67026-25067, NNX14AI50G, NNX14A169G, 80NSSC18K0738, NNX08AG87A). This work used eddy covariance data acquired and shared by the FLUXNET community, including the AmeriFlux network. The MODIS Collection 6 MOD16A2, MCD43A3 and MCD12Q1 products were retrieved from the online Data Pool, courtesy of the NASA Land Processes Distributed Active Archive Center (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota, https://lpdaac.usgs.gov/data_access/data_pool. A portion of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA. © 2019. All rights reserved.

Funders	Funder number
1633831
National Aeronautics and Space Administration	NNX14A169G, 658 2016-67026-25067, NNX14AI50G, NNX08AG87A, 80NSSC18K0738

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 2 Zero Hunger
SDG 13 Climate Action

Keywords

30-m
Cropland
Evapotranspiration
Landsat
MODIS

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10.1016/j.rse.2019.05.020

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title = "Satellite data-driven modeling of field scale evapotranspiration in croplands using the MOD16 algorithm framework",

abstract = "Evapotranspiration (ET) is a key variable linking the global water, carbon and energy cycles, while accurate ET estimates are crucial for understanding cropland water use in context with agricultural management. Satellite remote sensing provides spatially and temporally continuous information that can be used for global ET estimation. The NASA MODIS MOD16A2 operational product provides 500-m 8-day global ET estimates extending from 2001 to present. However, reliable estimates for delineating field level cropland ET patterns are lacking. In this investigation, we modified the MOD16 global algorithm to better represent cropland ET by calibrating model parameters according to C3 and C4 crop types, and incorporating finer scale satellite vegetation inputs to derive 30-m cropland ET estimates over the continental USA (CONUS). Similar overlapping enhanced vegetation index (EVI) records from Landsat and MODIS were used to generate a continuous 30-m 8-day fused EVI and ET record extending from 2008 to 2017 over CONUS croplands. The satellite-based ET estimates were compared with tower based ET observations over different crop types, and more traditional cropland actual ET (AET) estimates derived from reference ET and crop-specific coefficients. The new satellite based 30-m cropland ET estimates (ET30m) corresponded favorably with both tower ET observations (ETflux; R2 = 0.69, RMSE = 0.70 mm d−1, bias = 0.04 mm d−1) and the baseline global MOD16A2 ET product (ETMOD16). The ET30m results also showed better performance against the ETflux observations than ETMOD16 (R2 = 0.54, RMSE = 0.82 mm d−1) or AET (R2 = 0.52, RMSE = 2.47 mm d−1) for monitoring CONUS croplands. The spatial and temporal patterns of the ET30m results show enhanced delineation of agricultural water use, including impacts from variable climate, cropland area and diversity. The resulting ET30m record is suitable for operational applications promoting more effective agricultural water management and food security.",

keywords = "30-m, Cropland, Evapotranspiration, Landsat, MODIS",

author = "Mingzhu He and Kimball, \{John S.\} and Yonghong Yi and Running, \{Steven W.\} and Kaiyu Guan and Alvaro Moreno and Xiaocui Wu and Marco Maneta",

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T1 - Satellite data-driven modeling of field scale evapotranspiration in croplands using the MOD16 algorithm framework

AU - He, Mingzhu

AU - Kimball, John S.

AU - Yi, Yonghong

AU - Running, Steven W.

AU - Guan, Kaiyu

AU - Moreno, Alvaro

AU - Wu, Xiaocui

AU - Maneta, Marco

PY - 2019/9/1

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N2 - Evapotranspiration (ET) is a key variable linking the global water, carbon and energy cycles, while accurate ET estimates are crucial for understanding cropland water use in context with agricultural management. Satellite remote sensing provides spatially and temporally continuous information that can be used for global ET estimation. The NASA MODIS MOD16A2 operational product provides 500-m 8-day global ET estimates extending from 2001 to present. However, reliable estimates for delineating field level cropland ET patterns are lacking. In this investigation, we modified the MOD16 global algorithm to better represent cropland ET by calibrating model parameters according to C3 and C4 crop types, and incorporating finer scale satellite vegetation inputs to derive 30-m cropland ET estimates over the continental USA (CONUS). Similar overlapping enhanced vegetation index (EVI) records from Landsat and MODIS were used to generate a continuous 30-m 8-day fused EVI and ET record extending from 2008 to 2017 over CONUS croplands. The satellite-based ET estimates were compared with tower based ET observations over different crop types, and more traditional cropland actual ET (AET) estimates derived from reference ET and crop-specific coefficients. The new satellite based 30-m cropland ET estimates (ET30m) corresponded favorably with both tower ET observations (ETflux; R2 = 0.69, RMSE = 0.70 mm d−1, bias = 0.04 mm d−1) and the baseline global MOD16A2 ET product (ETMOD16). The ET30m results also showed better performance against the ETflux observations than ETMOD16 (R2 = 0.54, RMSE = 0.82 mm d−1) or AET (R2 = 0.52, RMSE = 2.47 mm d−1) for monitoring CONUS croplands. The spatial and temporal patterns of the ET30m results show enhanced delineation of agricultural water use, including impacts from variable climate, cropland area and diversity. The resulting ET30m record is suitable for operational applications promoting more effective agricultural water management and food security.

AB - Evapotranspiration (ET) is a key variable linking the global water, carbon and energy cycles, while accurate ET estimates are crucial for understanding cropland water use in context with agricultural management. Satellite remote sensing provides spatially and temporally continuous information that can be used for global ET estimation. The NASA MODIS MOD16A2 operational product provides 500-m 8-day global ET estimates extending from 2001 to present. However, reliable estimates for delineating field level cropland ET patterns are lacking. In this investigation, we modified the MOD16 global algorithm to better represent cropland ET by calibrating model parameters according to C3 and C4 crop types, and incorporating finer scale satellite vegetation inputs to derive 30-m cropland ET estimates over the continental USA (CONUS). Similar overlapping enhanced vegetation index (EVI) records from Landsat and MODIS were used to generate a continuous 30-m 8-day fused EVI and ET record extending from 2008 to 2017 over CONUS croplands. The satellite-based ET estimates were compared with tower based ET observations over different crop types, and more traditional cropland actual ET (AET) estimates derived from reference ET and crop-specific coefficients. The new satellite based 30-m cropland ET estimates (ET30m) corresponded favorably with both tower ET observations (ETflux; R2 = 0.69, RMSE = 0.70 mm d−1, bias = 0.04 mm d−1) and the baseline global MOD16A2 ET product (ETMOD16). The ET30m results also showed better performance against the ETflux observations than ETMOD16 (R2 = 0.54, RMSE = 0.82 mm d−1) or AET (R2 = 0.52, RMSE = 2.47 mm d−1) for monitoring CONUS croplands. The spatial and temporal patterns of the ET30m results show enhanced delineation of agricultural water use, including impacts from variable climate, cropland area and diversity. The resulting ET30m record is suitable for operational applications promoting more effective agricultural water management and food security.

KW - 30-m

KW - Cropland

KW - Evapotranspiration

KW - Landsat

KW - MODIS

UR - https://www.scopus.com/pages/publications/85065868078

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DO - 10.1016/j.rse.2019.05.020

M3 - Article

AN - SCOPUS:85065868078

SN - 0034-4257

VL - 230

JO - Remote Sensing of Environment

JF - Remote Sensing of Environment

M1 - 111201

ER -

Satellite data-driven modeling of field scale evapotranspiration in croplands using the MOD16 algorithm framework

Abstract

Funding

UN SDGs

Keywords

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